[{"data":1,"prerenderedAt":22332},["ShallowReactive",2],{"content-\u002Fblog\u002Fengineering-analytics-trends-2025":3,"author-Omer Celebioglu":555,"blog-list-engineering-intelligence,software-engineering-1":570},{"id":4,"title":5,"author":6,"avatar":7,"body":8,"categories":539,"createAt":542,"date":543,"description":544,"extension":545,"meta":546,"navigation":547,"path":548,"position":542,"seo":549,"spotImage":542,"spotText":542,"stem":550,"tags":551,"__hash__":554},"blog\u002Fblog\u002Fengineering-analytics-trends-2025.md","The Future of Engineering Analytics: Trends to Watch in 2025 - Blog","Omer Celebioglu","unknown-user.png",{"type":9,"value":10,"toc":525},"minimark",[11,32,51,56,66,69,91,98,102,116,119,139,145,149,162,165,188,194,198,212,215,241,256,260,274,277,296,303,307,321,324,344,355,359,373,376,399,403,418,421,447,450,464,475,479,493,500,503,510],[12,13,14,15,19,20,23,24,27,28,31],"p",{},"In today’s fast-paced software development world, engineering analytics is becoming a fundamental part of how teams optimize performance, improve quality, and enhance efficiency. As we enter 2025, new trends are shaping the future of ",[16,17,18],"strong",{},"engineering analytics platforms",", influencing how teams collect, analyze, and act on data-driven insights. The rise of ",[16,21,22],{},"real-time data processing",", ",[16,25,26],{},"predictive analytics",", and ",[16,29,30],{},"automated reporting"," is enabling engineering managers to make better decisions faster. ",[12,33,34,35,38,39,42,43,46,47,50],{},"This blog explores the ",[16,36,37],{},"top trends in engineering analytics for 2025"," and how they will impact software development teams. From ",[16,40,41],{},"data democratization"," to ",[16,44,45],{},"cloud-native analytics",", these trends highlight how organizations can stay ahead by leveraging the most effective ",[16,48,49],{},"engineering analytics solutions",". ",[52,53,55],"h3",{"id":54},"_1-the-shift-to-real-time-data-processing-in-engineering","1. The Shift to Real-Time Data Processing in Engineering ",[12,57,58,59,62,63,65],{},"The days are gone when teams relied on ",[16,60,61],{},"batch data processing"," for engineering performance analysis. In 2025, the demand for ",[16,64,22],{}," is growing as teams need immediate insights to detect inefficiencies and act before they disrupt workflows. ",[12,67,68],{},"Why It Matters: ",[70,71,72,79,85],"ul",{},[73,74,75,78],"li",{},[16,76,77],{},"Faster troubleshooting:"," Immediate visibility into bottlenecks allows teams to act faster. ",[73,80,81,84],{},[16,82,83],{},"Improved development cycles:"," Real-time analytics reduce delays in identifying problems. ",[73,86,87,90],{},[16,88,89],{},"Continuous visibility:"," Engineering managers can see trends and patterns without waiting for manual reports. ",[12,92,93,94,97],{},"Organizations that embrace ",[16,95,96],{},"real-time engineering analytics platforms"," will have a significant advantage in accelerating their software delivery processes. ",[52,99,101],{"id":100},"_2-data-democratization-in-engineering-teams","2. Data Democratization in Engineering Teams ",[12,103,104,107,108,111,112,115],{},[16,105,106],{},"Data democratization"," means making engineering analytics accessible across teams rather than keeping data insights limited to management. In 2025, companies are shifting towards ",[16,109,110],{},"self-service analytics",", allowing engineers, QA teams, and project managers to access relevant ",[16,113,114],{},"software development performance metrics"," without relying on data specialists. ",[12,117,118],{},"Key Benefits: ",[70,120,121,127,133],{},[73,122,123,126],{},[16,124,125],{},"Enhanced transparency:"," Everyone in the team understands performance metrics. ",[73,128,129,132],{},[16,130,131],{},"Faster decision-making:"," Teams can address inefficiencies in real-time without waiting for top-down analysis. ",[73,134,135,138],{},[16,136,137],{},"More accountability:"," Developers and managers can take proactive ownership of issues. ",[12,140,141,142,144],{},"To successfully implement data democratization, ",[16,143,18],{}," must provide easy-to-use dashboards and ensure secure access control to prevent data overload. ",[52,146,148],{"id":147},"_3-predictive-maintenance-analytics-proactive-engineering-insights","3. Predictive Maintenance Analytics & Proactive Engineering Insights ",[12,150,151,152,155,156,158,159,50],{},"Engineering teams are shifting from reactive troubleshooting to ",[16,153,154],{},"proactive issue detection"," using ",[16,157,26],{},". Instead of discovering problems after they cause major setbacks, teams can now anticipate challenges and resolve them ",[16,160,161],{},"before they impact performance",[12,163,164],{},"How Predictive Analytics Helps: ",[70,166,167,174,181],{},[73,168,169,170,173],{},"Identifies ",[16,171,172],{},"recurring issues"," that could cause deployment failures. ",[73,175,176,177,180],{},"Detects bottlenecks in ",[16,178,179],{},"CI\u002FCD pipelines"," before they slow down releases. ",[73,182,183,184,187],{},"Highlights ",[16,185,186],{},"technical debt accumulation",", allowing teams to refactor code before it becomes a major problem. ",[12,189,93,190,193],{},[16,191,192],{},"predictive maintenance analytics"," will have a competitive advantage in reducing downtime and optimizing performance. ",[52,195,197],{"id":196},"_4-the-growing-importance-of-engineering-data-privacy-governance","4. The Growing Importance of Engineering Data Privacy & Governance ",[12,199,200,201,204,205,208,209,50],{},"With increasing ",[16,202,203],{},"data regulations"," and heightened awareness of ",[16,206,207],{},"cybersecurity",", companies must ensure that engineering analytics platforms comply with ",[16,210,211],{},"privacy and governance standards",[12,213,214],{},"Challenges in Engineering Analytics: ",[70,216,217,227,234],{},[73,218,219,220,223,224,50],{},"Managing ",[16,221,222],{},"sensitive engineering data"," while maintaining ",[16,225,226],{},"accessibility",[73,228,229,230,233],{},"Ensuring ",[16,231,232],{},"compliance"," with industry standards like GDPR, SOC2, and ISO27001. ",[73,235,236,237,240],{},"Preventing ",[16,238,239],{},"data leaks"," when integrating multiple analytics tools. ",[12,242,243,244,247,248,251,252,255],{},"Companies that implement ",[16,245,246],{},"secure data access policies"," and ",[16,249,250],{},"role-based permissions"," will balance transparency with privacy, keeping ",[16,253,254],{},"engineering data quality and reliability"," intact. ",[52,257,259],{"id":258},"_5-cloud-native-engineering-analytics-platforms","5. Cloud-Native Engineering Analytics Platforms ",[12,261,262,263,266,267,270,271,50],{},"Cloud adoption continues to accelerate, and in 2025, ",[16,264,265],{},"cloud-native analytics solutions"," are becoming the default for engineering teams. As more organizations shift away from ",[16,268,269],{},"on-premises solutions",", cloud-based platforms offer better ",[16,272,273],{},"scalability, accessibility, and lower infrastructure maintenance",[12,275,276],{},"Why Cloud-Native Analytics is Growing: ",[70,278,279,286,289],{},[73,280,281,282,285],{},"Supports ",[16,283,284],{},"hybrid and remote workforces"," by providing global access. ",[73,287,288],{},"Reduces dependency on internal IT infrastructure. ",[73,290,291,292,295],{},"Enables ",[16,293,294],{},"seamless integration"," with existing engineering tools. ",[12,297,298,299,302],{},"Companies leveraging ",[16,300,301],{},"cloud-native engineering analytics"," will benefit from increased flexibility and efficiency. ",[52,304,306],{"id":305},"_6-advanced-data-visualization-actionable-engineering-insights","6. Advanced Data Visualization & Actionable Engineering Insights ",[12,308,309,312,313,316,317,320],{},[16,310,311],{},"Engineering analytics tools"," must go beyond simply collecting data—they must help teams ",[16,314,315],{},"understand and act on it",". In 2025, we expect to see a rise in ",[16,318,319],{},"interactive dashboards, real-time anomaly detection, and visually rich reports"," that make complex data easier to interpret. ",[12,322,323],{},"Emerging Trends in Data Visualization: ",[70,325,326,332,338],{},[73,327,328,331],{},[16,329,330],{},"Customizable dashboards:"," Different teams (developers, managers, executives) need different views of performance data. ",[73,333,334,337],{},[16,335,336],{},"Real-time alerts:"," Detect and notify teams about slow pipelines, failing deployments, and performance degradation. ",[73,339,340,343],{},[16,341,342],{},"AI-powered recommendations:"," Some analytics tools are starting to suggest optimizations based on past patterns. ",[12,345,346,347,350,351,354],{},"With ",[16,348,349],{},"better engineering data visualization",", teams will be able to move from ",[16,352,353],{},"data overload to actionable insights"," faster. ",[52,356,358],{"id":357},"_7-automation-in-engineering-data-collection-reporting","7. Automation in Engineering Data Collection & Reporting ",[12,360,361,362,365,366,369,370,50],{},"Engineering teams spend ",[16,363,364],{},"too much time manually collecting and analyzing data",". ",[16,367,368],{},"Automation"," is solving this problem by integrating engineering analytics with workflows, providing ",[16,371,372],{},"automated reporting and performance insights",[12,374,375],{},"Key Benefits of Automated Engineering Analytics: ",[70,377,378,384,393],{},[73,379,380,383],{},[16,381,382],{},"Less time spent on manual reports:"," Automatic data gathering speeds up analysis. ",[73,385,386,389,390,50],{},[16,387,388],{},"More accurate metrics:"," Eliminates human error in tracking ",[16,391,392],{},"DORA metrics, lead time, and deployment frequency",[73,394,395,398],{},[16,396,397],{},"Faster incident resolution:"," Automated alerts ensure that teams react immediately to issues. ",[52,400,402],{"id":401},"_8-ais-emerging-role-in-engineering-analytics","8. AI’s Emerging Role in Engineering Analytics ",[12,404,405,406,409,410,413,414,417],{},"Artificial Intelligence is starting to play a role in ",[16,407,408],{},"engineering analytics",", but its adoption remains mixed. While ",[16,411,412],{},"AI-powered anomaly detection and automated recommendations"," are growing, many engineering managers still ",[16,415,416],{},"prefer transparent, human-driven analytics"," over AI black-box models. ",[12,419,420],{},"Where AI is Heading in Engineering Analytics: ",[70,422,423,430,437],{},[73,424,425,426,429],{},"AI is ",[16,427,428],{},"enhancing anomaly detection"," by identifying performance trends before human reviewers can. ",[73,431,432,433,436],{},"Some tools use AI to ",[16,434,435],{},"suggest workflow optimizations",", reducing bottlenecks automatically. ",[73,438,439,440,443,444,50],{},"However, ",[16,441,442],{},"trust and explainability"," remain a challenge, leading many teams to balance ",[16,445,446],{},"AI-driven insights with manual validation",[12,448,449],{},"Why Proactive Analytics is the Future of Engineering Analytics ",[12,451,452,453,456,457,460,461,50],{},"As engineering analytics continues to evolve, ",[16,454,455],{},"real-time, predictive, and automated analytics"," will become the norm. Organizations that adopt ",[16,458,459],{},"proactive analytics"," will have a competitive advantage in ",[16,462,463],{},"identifying issues before they cause downtime, optimizing workflows, and ensuring continuous improvement",[12,465,466,467,470,471,474],{},"Platforms like ",[16,468,469],{},"Oobeya"," are helping teams stay ahead by offering ",[16,472,473],{},"real-time issue detection, proactive engineering insights, and automated recommendations"," that enable engineering managers to make data-driven decisions confidently. ",[52,476,478],{"id":477},"conclusion","Conclusion ",[12,480,481,482,484,485,488,489,492],{},"The future of ",[16,483,408],{}," is defined by ",[16,486,487],{},"real-time insights, predictive analytics, cloud adoption, and automation",". Teams that invest in ",[16,490,491],{},"scalable, secure, and proactive analytics solutions"," will improve software quality, accelerate development cycles, and reduce operational risks. ",[12,494,495,496,499],{},"By adopting ",[16,497,498],{},"the right engineering analytics platform",", companies can transform data into actionable insights, ensuring long-term success in the evolving software development landscape. ",[501,502],"hr",{},[12,504,505,506,509],{},"Want to bring ",[16,507,508],{},"proactive engineering analytics"," to your team? ",[12,511,512,513,520,521,524],{},"➡️ ",[514,515,519],"a",{"href":516,"rel":517},"https:\u002F\u002Foobeya.io\u002F",[518],"nofollow","Book a Demo"," and experience ",[16,522,523],{},"the future of engineering analytics"," today.",{"title":526,"searchDepth":527,"depth":527,"links":528},"",2,[529,531,532,533,534,535,536,537,538],{"id":54,"depth":530,"text":55},3,{"id":100,"depth":530,"text":101},{"id":147,"depth":530,"text":148},{"id":196,"depth":530,"text":197},{"id":258,"depth":530,"text":259},{"id":305,"depth":530,"text":306},{"id":357,"depth":530,"text":358},{"id":401,"depth":530,"text":402},{"id":477,"depth":530,"text":478},[540,541],"engineering-intelligence","software-engineering",null,"2025-02-04","Explore the top engineering analytics trends of 2025, from real-time insights to predictive maintenance and automation. Stay ahead with the latest innovations.","md",{},true,"\u002Fblog\u002Fengineering-analytics-trends-2025",{"title":5,"description":544},"blog\u002Fengineering-analytics-trends-2025",[552,540,553],"software-development-analytics","engineering-efficiency","d7nmTKOO7po53Dniz93kMf3tphOz_iq95Cl9Jn4i4Ps",{"id":556,"title":6,"body":557,"description":561,"extension":545,"meta":564,"navigation":547,"path":566,"seo":567,"stem":568,"__hash__":569},"author\u002Fauthor\u002Fomer-celebioglu.md",{"type":9,"value":558,"toc":562},[559],[12,560,561],{},"Omer is a driven business leader with a passion for growth and transformation. Currently Head of Growth & Partnership Operations at Oobeya, he has also held roles such as Global Growth Specialist and Manager of Strategic Partnerships. With expertise in scaling operations, building partnerships, and leading cross-functional teams, he excels in driving impactful results. Outside of work, he enjoys public speaking, mentoring, and exploring new cultures.",{"title":526,"searchDepth":527,"depth":527,"links":563},[],{"avatar":7,"createAt":565},"JAN 22, 2025","\u002Fauthor\u002Fomer-celebioglu",{"title":6,"description":561},"author\u002Fomer-celebioglu","ImY9BmwAHBgP1KtViDV7p7m9CiG7t1JJci5hnYtXu6g",[571,1262,1900,2623,3345,4142,4242,4498,4845,5072,5559,6088,6457,6696,7381,7804,8107,8442,8867,9229,9550,9842,10398,10789,10931,11215,11531,11958,12289,12569,12992,13232,13532,13747,14055,14531,14806,15133,15457,15650,15863,16230,16560,16696,16845,17002,17151,17447,18375,18616,18662,18884,19363,19464,19587,19934,20197,20330,20599,21022,21357,21744],{"id":572,"title":573,"author":574,"avatar":575,"body":576,"categories":1230,"createAt":542,"date":1233,"description":1234,"extension":545,"meta":1235,"navigation":547,"path":1252,"position":542,"seo":1253,"spotImage":1254,"spotText":1255,"stem":1256,"tags":1257,"__hash__":1261},"blog\u002Fblog\u002Fsoftware-engineering-metrics-complete-guide-2026.md","Software Engineering Metrics: The Complete Guide for 2026","Emre Dundar","emre-dundar.png",{"type":9,"value":577,"toc":1186},[578,581,584,587,593,596,612,617,685,688,691,701,704,707,714,717,720,726,729,732,747,753,759,766,769,772,778,781,787,795,798,801,804,808,811,814,822,826,829,832,836,839,842,850,853,856,860,863,866,870,880,883,887,894,897,901,904,912,915,918,922,925,928,932,935,941,945,948,951,954,957,960,992,995,998,1001,1004,1007,1011,1014,1018,1021,1025,1028,1031,1054,1057,1060,1066,1072,1078,1081,1084,1088,1091,1095,1098,1102,1105,1109,1112,1116,1119,1122,1126,1129,1133,1136,1140,1143,1147,1150,1154,1157,1160,1163,1166,1180,1183],[12,579,580],{},"Most engineering dashboards have the same problem: everything is green, and delivery still feels broken.",[12,582,583],{},"Deployment frequency is up. Code coverage looks fine. PRs are being merged at a healthy pace. And yet features are late, senior engineers are burned out, and nobody can explain why the roadmap keeps slipping.",[12,585,586],{},"The dashboard did not fail you. You measured the wrong things, or the right things in the wrong way.",[12,588,589,592],{},[16,590,591],{},"Software engineering metrics"," are one of the most powerful tools an engineering leader has. Used well, they reveal bottlenecks before they become crises, align engineering performance with business outcomes, and give teams a shared language for continuous improvement. Used poorly, they create perverse incentives, surveillance cultures, and the illusion of progress with none of the substance.",[12,594,595],{},"This guide covers what actually matters: which metrics to track, which to abandon, how to avoid the traps that derail most measurement programs, and how to build a system that makes your engineering organization better, not just better at hitting numbers.",[12,597,598,599,23,603,27,607,611],{},"If you want to compare this broader measurement model with a more AI-specific lens, start with ",[514,600,602],{"href":601},"\u002Fblog\u002Fengineering-metrics-in-the-ai-era","Engineering Metrics in the AI Era",[514,604,606],{"href":605},"\u002Fblog\u002Fdora-metrics-not-enough-2026","DORA Metrics Are Not Enough in 2026",[514,608,610],{"href":609},"\u002Fai-coding-assistants","AI Coding Assistant Impact",".",[613,614,616],"h2",{"id":615},"table-of-contents","Table of Contents",[70,618,619,625,631,637,643,649,655,661,667,673,679],{},[73,620,621],{},[514,622,624],{"href":623},"#the-fundamental-problem-with-engineering-metrics","The Fundamental Problem with Engineering Metrics",[73,626,627],{},[514,628,630],{"href":629},"#goodharts-law-the-hidden-trap-in-every-metric-program","Goodhart's Law: The Hidden Trap in Every Metric Program",[73,632,633],{},[514,634,636],{"href":635},"#activity-vs-outcome-metrics-the-most-important-distinction","Activity vs. Outcome Metrics: The Most Important Distinction",[73,638,639],{},[514,640,642],{"href":641},"#the-delivery-metrics-that-actually-matter","The Delivery Metrics That Actually Matter",[73,644,645],{},[514,646,648],{"href":647},"#quality-metrics-the-guardrails-you-cannot-skip","Quality Metrics: The Guardrails You Cannot Skip",[73,650,651],{},[514,652,654],{"href":653},"#team-health-metrics-the-human-signal","Team Health Metrics: The Human Signal",[73,656,657],{},[514,658,660],{"href":659},"#2026-industry-benchmarks-what-good-looks-like","2026 Industry Benchmarks: What Good Looks Like",[73,662,663],{},[514,664,666],{"href":665},"#how-to-build-a-metrics-system-not-a-metrics-list","How to Build a Metrics System, Not a Metrics List",[73,668,669],{},[514,670,672],{"href":671},"#connecting-engineering-metrics-to-business-outcomes","Connecting Engineering Metrics to Business Outcomes",[73,674,675],{},[514,676,678],{"href":677},"#common-mistakes-and-how-to-avoid-them","Common Mistakes and How to Avoid Them",[73,680,681],{},[514,682,684],{"href":683},"#frequently-asked-questions","Frequently Asked Questions",[613,686,624],{"id":687},"the-fundamental-problem-with-engineering-metrics",[12,689,690],{},"Only about half of tech managers say their companies even attempt to measure developer productivity, and just a small minority have dedicated specialists for it. The teams that do measure often measure the wrong things, creating a peculiar situation where dashboards look excellent and engineering feels dysfunctional at the same time.",[12,692,693,694,247,697,700],{},"The root cause is confusion between ",[16,695,696],{},"metrics",[16,698,699],{},"KPIs",". Metrics are descriptive: they capture what is happening. KPIs are interpretive: they help explain whether what is happening is good or bad, and why. Most teams collect metrics. Very few build KPIs.",[12,702,703],{},"A commit count is a metric. Whether that commit count reflects meaningful, value-delivering work or an inflated number designed to look productive requires context and pairing with other signals. Engineering leaders who mistake metrics for performance often end up with teams that are excellent at optimizing numbers while delivery outcomes stagnate.",[12,705,706],{},"The second problem is the individual versus system confusion. Software development is collaborative. The engineer who spends a day helping three teammates get unstuck may contribute enormously while their commit count is zero. The engineer who writes a thousand lines of code that create technical debt for years may look great on activity metrics. Measuring individual output in a collaborative system produces individual gaming, not team improvement.",[12,708,709,710,713],{},"The solution begins with a clear mental model: ",[16,711,712],{},"metrics measure motion; KPIs describe direction",". And direction can only be understood at the system level, not the individual level.",[613,715,630],{"id":716},"goodharts-law-the-hidden-trap-in-every-metric-program",[12,718,719],{},"Before choosing any metric, you need to understand the principle that breaks more measurement programs than almost anything else: Goodhart's Law.",[12,721,722,723],{},"Formulated by British economist Charles Goodhart in 1975, the law states simply: ",[16,724,725],{},"\"When a measure becomes a target, it ceases to be a good measure.\"",[12,727,728],{},"In engineering, this plays out constantly. Teams rewarded for lines of code write more code than necessary. Teams chasing code coverage targets write tests that technically cover lines but do not verify meaningful behavior. Teams measured on story points inflate estimates until velocity numbers are meaningless for planning.",[12,730,731],{},"Here are the three most common Goodhart traps in engineering:",[12,733,734,737,738,742,743,746],{},[16,735,736],{},"Story point inflation."," When velocity becomes a performance target, teams estimate ",[739,740,741],"code",{},"3"," as ",[739,744,745],{},"5"," to look more productive. Cross-team comparisons become meaningless. Sprint planning stops reflecting actual capacity.",[12,748,749,752],{},[16,750,751],{},"Coverage theater."," When code coverage becomes a target, tests are written to hit percentages rather than verify behavior. A test that calls a function without asserting results increases coverage while catching nothing.",[12,754,755,758],{},[16,756,757],{},"Deployment frequency gaming."," Faster deployments are valuable, but shipping unstable changes to inflate deployment count creates more fire-fighting than value delivery. Speed without paired quality measurement is Goodhart in action.",[12,760,761,762,765],{},"The solution is not to stop measuring. It is to design a measurement system that is structurally resistant to gaming. The most reliable technique is ",[16,763,764],{},"paired, oppositional metrics",". For every speed metric, add a quality guardrail. If you track deployment frequency, also track change failure rate. If you track cycle time, also track post-release defect rate. A team can inflate one signal. Inflating both simultaneously usually requires actually improving the underlying system, which is the point.",[613,767,636],{"id":768},"activity-vs-outcome-metrics-the-most-important-distinction",[12,770,771],{},"Every software engineering metric falls into one of two categories, and knowing the difference determines whether your measurement program helps or harms.",[12,773,774,777],{},[16,775,776],{},"Activity metrics"," measure effort and output: lines of code, commit count, PR volume, hours logged, meetings attended, tickets closed. They are easy to collect because they are already captured by your tools. They feel productive to report on because the numbers are always moving.",[12,779,780],{},"The problem is that activity metrics can improve without business outcomes improving. Developers can write more code, merge more PRs, and close more tickets while shipping fewer meaningful features, introducing more bugs, and falling further behind on roadmap work. Activity metrics describe motion, not direction.",[12,782,783,786],{},[16,784,785],{},"Outcome metrics"," measure results: features delivered to customers, defects resolved before reaching production, time saved in the delivery pipeline, reliability improvements experienced by users. They are harder to collect and harder to define, but they describe whether engineering work is actually creating value.",[12,788,789,790,794],{},"The practical test for distinguishing the two is simple: ",[791,792,793],"em",{},"Can this metric improve without the thing I care about improving?"," If lines of code rise but shipping velocity stays flat, the metric passed the wrong test. If deployment frequency rises and lead time falls simultaneously, the metric is much more likely to reflect real improvement.",[12,796,797],{},"This does not mean activity metrics have no place. PR review time, for example, is an activity signal, but it is also a leading indicator of cycle time and a direct input to developer experience. The rule is not to ban activity metrics. The rule is to avoid using them as standalone KPIs.",[613,799,642],{"id":800},"the-delivery-metrics-that-actually-matter",[12,802,803],{},"Delivery metrics measure how efficiently your team moves work from idea to production. These are the closest thing the industry has to a shared standard for engineering performance.",[52,805,807],{"id":806},"cycle-time","Cycle Time",[12,809,810],{},"Cycle time measures the end-to-end elapsed time from when a developer starts working on a task to when that work reaches production. It captures coding, review, automated testing, deployment queues, and the deployment step itself.",[12,812,813],{},"Cycle time is one of the most useful single delivery metrics because it exposes bottlenecks wherever they actually are, not where you assume they are. A team with fast coding but slow review will still have a long cycle time, which correctly identifies review as the constraint.",[12,815,816,817,821],{},"If you want a comparative lens for what strong looks like, use ",[514,818,820],{"href":819},"\u002Fbenchmarks","Engineering Benchmarks"," as context rather than as a pass-fail scoreboard.",[52,823,825],{"id":824},"deployment-frequency","Deployment Frequency",[12,827,828],{},"Deployment frequency measures how often your team ships code to production. High deployment frequency is not valuable by itself; it is a proxy for small batch size, confidence in release processes, and the ability to respond to customer needs quickly.",[12,830,831],{},"When deployment frequency is low, look beyond the number. Manual approvals, brittle CI\u002FCD pipelines, insufficient test automation, and deployment anxiety are usually the real issues.",[52,833,835],{"id":834},"lead-time-for-changes","Lead Time for Changes",[12,837,838],{},"Lead time measures the time between a code commit and a successful production deployment. It is one of the clearest measures of pipeline speed and responsiveness.",[12,840,841],{},"An organization with short lead time can respond to a production bug, customer request, or market opportunity much faster than one with long lead times. That makes lead time not just an engineering metric but a business responsiveness metric.",[12,843,844,845,849],{},"If you are using ",[514,846,848],{"href":847},"\u002Fdora-metrics-four-key","DORA metrics",", lead time is one of the core signals you should keep, but always interpret it alongside review pressure, quality outcomes, and team capacity.",[613,851,648],{"id":852},"quality-metrics-the-guardrails-you-cannot-skip",[12,854,855],{},"Speed metrics without quality guardrails are how dashboards turn green while engineering falls apart. Every delivery metric needs a paired quality signal.",[52,857,859],{"id":858},"change-failure-rate","Change Failure Rate",[12,861,862],{},"Change failure rate is the percentage of deployments that cause a degraded service, incident, rollback, or outage. It is the most important companion metric to deployment frequency.",[12,864,865],{},"A team that deploys more often while holding change failure rate steady has probably improved. A team that deploys more often while change failure rate rises may simply be shipping instability faster.",[52,867,869],{"id":868},"defect-density-and-defect-escape-rate","Defect Density and Defect Escape Rate",[12,871,872,873,879],{},"Defect density measures the concentration of defects in a given code volume. More actionable for many teams is ",[16,874,875],{},[514,876,878],{"href":877},"\u002Fglossary\u002Fdefect-escape-rate","defect escape rate",", the percentage of issues that reach production rather than being caught in review, testing, or staging.",[12,881,882],{},"A rising defect escape rate usually means your quality gates are not keeping up with your delivery velocity. That is especially important in AI-assisted environments, where code output may rise faster than review capacity.",[52,884,886],{"id":885},"code-churn-rate","Code Churn Rate",[12,888,889,893],{},[514,890,892],{"href":891},"\u002Fglossary\u002Fcode-churn","Code churn"," measures how often recently written code is rewritten or deleted shortly after creation. High churn often points to unclear requirements, rushed design decisions, or code that was never stable in the first place.",[12,895,896],{},"It can also be a useful diagnostic when you are trying to explain why throughput looks healthy while delivery confidence keeps dropping.",[52,898,900],{"id":899},"mean-time-to-recovery","Mean Time to Recovery",[12,902,903],{},"Mean time to recovery measures how quickly your team restores service after a production incident. It reflects operational maturity: monitoring quality, runbooks, rollback capability, and incident response discipline.",[12,905,906,907,911],{},"If you want a broader operating picture, ",[514,908,910],{"href":909},"\u002Fsymptoms","Symptoms"," can help frame where quality and delivery friction are showing up before they become chronic.",[613,913,654],{"id":914},"team-health-metrics-the-human-signal",[12,916,917],{},"Delivery and quality metrics measure what your engineering system produces. Team health metrics measure the people operating inside it. Teams that optimize delivery metrics at the expense of team health consistently underperform over longer time horizons.",[52,919,921],{"id":920},"developer-satisfaction-and-enps","Developer Satisfaction and eNPS",[12,923,924],{},"Developer satisfaction measures how fulfilled and engaged engineers are with their work, tools, and team environment. Employee Net Promoter Score, or eNPS, measures how likely engineers are to recommend their organization as a place to work.",[12,926,927],{},"Strong delivery metrics with weak team health are a warning sign. A team may appear productive while accumulating burnout, distrust in tooling, and avoidable friction.",[52,929,931],{"id":930},"pr-review-load","PR Review Load",[12,933,934],{},"PR review time is one of the most common bottlenecks in modern delivery systems. Long review times increase merge conflicts, slow feedback loops, and create costly context switching.",[12,936,937,938,940],{},"In AI-assisted environments, this problem often gets worse. More generated code can mean more review work for the same senior engineers. That is one reason ",[514,939,610],{"href":609}," has become an important measurement layer for engineering leaders.",[52,942,944],{"id":943},"sprint-predictability","Sprint Predictability",[12,946,947],{},"Sprint predictability measures how closely actual delivery matches planned scope. When unplanned work consistently consumes a large share of capacity, it usually points to quality issues, technical debt, operational churn, or poor planning assumptions.",[12,949,950],{},"Healthy engineering systems make room for new feature work, maintenance, and rework in a balanced way. Measurement should make that balance visible rather than hiding it under a single velocity number.",[613,952,660],{"id":953},"_2026-industry-benchmarks-what-good-looks-like",[12,955,956],{},"Industry benchmark reports are useful when treated as directional context rather than rigid judgment.",[12,958,959],{},"Here are the kinds of ranges leaders often use to calibrate performance:",[70,961,962,968,974,980,986],{},[73,963,964,967],{},[16,965,966],{},"Cycle time:"," elite under 48 hours, median around 83 hours, red flag above 124 hours",[73,969,970,973],{},[16,971,972],{},"Deployment frequency:"," elite multiple times per service per day, strong teams around daily, concern when it drops well below that",[73,975,976,979],{},[16,977,978],{},"PR size:"," smaller PRs are strongly correlated with better review speed and healthier cycle time",[73,981,982,985],{},[16,983,984],{},"Lead time:"," strong teams consistently keep low-risk changes moving quickly",[73,987,988,991],{},[16,989,990],{},"Change failure rate:"," elite teams keep it extremely low, strong teams still stay under clear risk thresholds",[12,993,994],{},"One critical principle: the goal is not to compare absolute numbers against industry peers as if engineering were a league table. A team improving from a 200-hour cycle time to a 100-hour cycle time has made meaningful progress even if it has not reached elite thresholds. Use benchmarks as directional targets, not pass-fail judgments.",[613,996,666],{"id":997},"how-to-build-a-metrics-system-not-a-metrics-list",[12,999,1000],{},"The most common failure mode in engineering metrics programs is treating metrics as a list to be collected rather than a system to be designed.",[12,1002,1003],{},"A list of 20 metrics with no relationships between them creates 20 simultaneous optimization pressures, each of which can be gamed independently. A system has structure.",[12,1005,1006],{},"Three principles matter most:",[52,1008,1010],{"id":1009},"paired-metrics-prevent-gaming","Paired metrics prevent gaming",[12,1012,1013],{},"Every speed metric needs a quality counterpart. Deployment frequency should be paired with change failure rate. Cycle time should be paired with post-release defect rate. PR volume should be paired with PR review load.",[52,1015,1017],{"id":1016},"leading-indicators-enable-proactive-intervention","Leading indicators enable proactive intervention",[12,1019,1020],{},"DORA-style delivery metrics are often lagging indicators. They tell you what already happened. Leading indicators such as PR size, PR pickup time, build success rate, and developer satisfaction trends tell you what is likely to happen next.",[52,1022,1024],{"id":1023},"different-audiences-need-different-cadences","Different audiences need different cadences",[12,1026,1027],{},"A single dashboard for developers, managers, engineering leadership, and executives usually serves none of them well.",[12,1029,1030],{},"A practical structure looks like this:",[70,1032,1033,1039,1048],{},[73,1034,1035,1038],{},[16,1036,1037],{},"Weekly team view:"," PR cycle time by stage, PR pickup time, build success rate, work in progress",[73,1040,1041,1044,1045,1047],{},[16,1042,1043],{},"Monthly leadership view:"," ",[514,1046,848],{"href":847},", developer experience, quality trends, and AI-specific signals where relevant",[73,1049,1050,1053],{},[16,1051,1052],{},"Quarterly executive view:"," engineering performance mapped to roadmap delivery, customer outcomes, incident cost, and investment efficiency",[613,1055,672],{"id":1056},"connecting-engineering-metrics-to-business-outcomes",[12,1058,1059],{},"Engineering metrics that live only in engineering dashboards are doing half their job. The highest-leverage use of a mature metrics program is translating technical performance into business language.",[12,1061,1062,1065],{},[16,1063,1064],{},"Deployment frequency to time-to-market."," Faster, safer releases mean customers experience product improvements sooner.",[12,1067,1068,1071],{},[16,1069,1070],{},"Change failure rate to incident cost."," Fewer failed changes mean less engineering time spent on recovery, lower support burden, and less customer disruption.",[12,1073,1074,1077],{},[16,1075,1076],{},"Developer experience to retention cost."," Satisfaction and friction indicators often reveal attrition risk long before headcount loss shows up in finance reporting.",[12,1079,1080],{},"When engineering leaders connect metrics to these business outcomes, measurement stops being a reporting exercise and becomes a decision tool.",[613,1082,678],{"id":1083},"common-mistakes-and-how-to-avoid-them",[52,1085,1087],{"id":1086},"mistake-1-using-metrics-for-individual-evaluation","Mistake 1: Using metrics for individual evaluation",[12,1089,1090],{},"Commits per day, PRs merged, and lines of code almost always measure the wrong thing in a collaborative system. Use metrics for team-level learning and system-level improvement.",[52,1092,1094],{"id":1093},"mistake-2-tracking-everything","Mistake 2: Tracking everything",[12,1096,1097],{},"If everything is a priority, nothing is. Start with a small balanced set covering delivery, quality, and team health. Add more signals only when a specific diagnostic question requires them.",[52,1099,1101],{"id":1100},"mistake-3-ignoring-the-measurement-culture","Mistake 3: Ignoring the measurement culture",[12,1103,1104],{},"Metrics introduced without context create surveillance anxiety. Make metrics visible to teams, use them in retrospectives, and frame them as tools for improvement rather than evaluation.",[52,1106,1108],{"id":1107},"mistake-4-comparing-teams-against-each-other","Mistake 4: Comparing teams against each other",[12,1110,1111],{},"Every team operates in a different context. Use metrics for longitudinal improvement within a team, not for simplistic rankings across teams.",[52,1113,1115],{"id":1114},"mistake-5-setting-metrics-and-forgetting-them","Mistake 5: Setting metrics and forgetting them",[12,1117,1118],{},"Metrics become stale as systems evolve. Review your measurement program regularly and ask whether the signals still reflect what matters.",[613,1120,684],{"id":1121},"frequently-asked-questions",[52,1123,1125],{"id":1124},"what-are-the-most-important-software-engineering-metrics","What are the most important software engineering metrics?",[12,1127,1128],{},"The most important software engineering metrics usually fall into three groups: delivery metrics such as deployment frequency, lead time, and cycle time; quality metrics such as change failure rate, code churn, and defect escape rate; and team health metrics such as PR review load, developer satisfaction, and predictability.",[52,1130,1132],{"id":1131},"what-is-goodharts-law-and-why-does-it-matter-for-engineering-metrics","What is Goodhart's Law and why does it matter for engineering metrics?",[12,1134,1135],{},"Goodhart's Law says that when a measure becomes a target, it stops being a good measure. In engineering, this happens when teams optimize the number rather than the underlying outcome, such as inflating story points or chasing code coverage without improving real quality.",[52,1137,1139],{"id":1138},"what-are-vanity-metrics-in-software-engineering","What are vanity metrics in software engineering?",[12,1141,1142],{},"Vanity metrics are numbers that look impressive but do not help explain performance or guide better decisions. Lines of code, raw commit count, and hours logged are common examples when used without context.",[52,1144,1146],{"id":1145},"what-are-the-dora-metrics-and-why-are-they-important","What are the DORA metrics and why are they important?",[12,1148,1149],{},"DORA metrics are deployment frequency, lead time for changes, change failure rate, and mean time to recovery. They matter because they provide a widely used evidence-based baseline for delivery performance.",[52,1151,1153],{"id":1152},"how-do-you-measure-developer-productivity-without-creating-a-surveillance-culture","How do you measure developer productivity without creating a surveillance culture?",[12,1155,1156],{},"Measure at the team level, not the individual level. Use metrics to support retrospectives, diagnosis, and improvement. Pair quantitative signals with qualitative team feedback so that delivery gains do not come at the cost of sustainability.",[613,1158,1159],{"id":477},"Conclusion",[12,1161,1162],{},"Software engineering metrics are neither a dashboard exercise nor a management surveillance tool. Used with discipline, they are the clearest window an engineering organization has into its own performance: where value is being delivered, where bottlenecks are accumulating, and whether the pace of delivery is sustainable.",[12,1164,1165],{},"The core principles are straightforward:",[70,1167,1168,1171,1174,1177],{},[73,1169,1170],{},"measure outcomes, not just activity",[73,1172,1173],{},"pair speed metrics with quality guardrails",[73,1175,1176],{},"track team health with the same seriousness as delivery performance",[73,1178,1179],{},"translate engineering metrics into business language",[12,1181,1182],{},"Start small. Pick one delivery metric, one quality metric, and one team health metric. Establish a baseline. Understand the system. Then improve it.",[12,1184,1185],{},"That sequence, measure, understand, then improve, is what separates organizations that use metrics to get better from those that use metrics to look good.",{"title":526,"searchDepth":527,"depth":527,"links":1187},[1188,1189,1190,1191,1192,1197,1203,1208,1209,1214,1215,1222,1229],{"id":615,"depth":527,"text":616},{"id":687,"depth":527,"text":624},{"id":716,"depth":527,"text":630},{"id":768,"depth":527,"text":636},{"id":800,"depth":527,"text":642,"children":1193},[1194,1195,1196],{"id":806,"depth":530,"text":807},{"id":824,"depth":530,"text":825},{"id":834,"depth":530,"text":835},{"id":852,"depth":527,"text":648,"children":1198},[1199,1200,1201,1202],{"id":858,"depth":530,"text":859},{"id":868,"depth":530,"text":869},{"id":885,"depth":530,"text":886},{"id":899,"depth":530,"text":900},{"id":914,"depth":527,"text":654,"children":1204},[1205,1206,1207],{"id":920,"depth":530,"text":921},{"id":930,"depth":530,"text":931},{"id":943,"depth":530,"text":944},{"id":953,"depth":527,"text":660},{"id":997,"depth":527,"text":666,"children":1210},[1211,1212,1213],{"id":1009,"depth":530,"text":1010},{"id":1016,"depth":530,"text":1017},{"id":1023,"depth":530,"text":1024},{"id":1056,"depth":527,"text":672},{"id":1083,"depth":527,"text":678,"children":1216},[1217,1218,1219,1220,1221],{"id":1086,"depth":530,"text":1087},{"id":1093,"depth":530,"text":1094},{"id":1100,"depth":530,"text":1101},{"id":1107,"depth":530,"text":1108},{"id":1114,"depth":530,"text":1115},{"id":1121,"depth":527,"text":684,"children":1223},[1224,1225,1226,1227,1228],{"id":1124,"depth":530,"text":1125},{"id":1131,"depth":530,"text":1132},{"id":1138,"depth":530,"text":1139},{"id":1145,"depth":530,"text":1146},{"id":1152,"depth":530,"text":1153},{"id":477,"depth":527,"text":1159},[540,1231,1232],"developer-productivity","dora-metrics","2026-03-30","Learn which software engineering metrics matter in 2026 and how to connect delivery, quality, and team health to business outcomes.",{"faq":1236},[1237,1240,1243,1246,1249],{"question":1238,"answer":1239},"What are software engineering metrics?","Software engineering metrics are measurements that help teams understand how software delivery is performing across speed, quality, workflow, team health, and business alignment. Their value comes from interpretation, not from collecting as many numbers as possible.",{"question":1241,"answer":1242},"Which software engineering metrics matter most in 2026?","The most useful 2026 metrics usually combine DORA, cycle time, review flow, defect and quality guardrails, team health signals, and business-facing outcomes. Strong teams avoid single-metric thinking and look at the engineering system as a whole.",{"question":1244,"answer":1245},"What is the difference between engineering metrics and KPIs?","Metrics describe what is happening, while KPIs help leaders interpret whether what is happening is healthy, risky, or improving. A number becomes useful only when it is tied to context, thresholds, and a real decision-making process.",{"question":1247,"answer":1248},"Why do engineering dashboards often look healthy while delivery still feels broken?","That usually happens when dashboards emphasize easy-to-collect activity metrics instead of system-level performance. Teams can look productive on paper while still carrying review bottlenecks, quality debt, overloaded engineers, and poor business alignment.",{"question":1250,"answer":1251},"How can engineering leaders avoid Goodhart's Law in metrics programs?","Leaders can reduce Goodhart's Law by avoiding single-target optimization and using paired metrics with quality guardrails. For example, speed metrics should be interpreted alongside quality, failure, rework, and team health signals.","\u002Fblog\u002Fsoftware-engineering-metrics-complete-guide-2026",{"title":573,"description":1234},"\u002Fassets\u002Fimg\u002Fdora-metrics-timeline.png","A practical 2026 guide to software engineering metrics, from DORA and cycle time to quality guardrails, team health, and business alignment.","blog\u002Fsoftware-engineering-metrics-complete-guide-2026",[1258,1259,1232,1231,1260],"software-engineering-metrics","engineering-kpis","goodharts-law","3KCpXjoNlREoWZ07-jVOzzeFDaBdmRh2_AVIBDKlq84",{"id":1263,"title":1264,"author":1265,"avatar":1266,"body":1267,"categories":1875,"createAt":542,"date":1877,"description":1878,"extension":545,"meta":1879,"navigation":547,"path":1890,"position":542,"seo":1891,"spotImage":1892,"spotText":1893,"stem":1894,"tags":1895,"__hash__":1899},"blog\u002Fblog\u002Fcto-dashboard-best-practices-2026.md","CTO Dashboard Best Practices: The Complete Guide for 2026","Sukru Cakmak","sukru-cakmak.png",{"type":9,"value":1268,"toc":1853},[1269,1272,1275,1278,1281,1284,1293,1295,1365,1368,1371,1374,1380,1386,1396,1399,1402,1422,1425,1432,1435,1438,1448,1454,1460,1466,1472,1475,1478,1484,1490,1496,1510,1513,1516,1519,1537,1548,1554,1560,1566,1572,1578,1581,1584,1636,1639,1642,1645,1648,1654,1660,1666,1669,1675,1681,1687,1693,1699,1702,1705,1710,1716,1722,1728,1734,1737,1740,1743,1758,1761,1763,1769,1775,1781,1787,1793,1795,1799,1802,1806,1809,1813,1816,1820,1823,1827,1830,1832,1835,1838,1841],[12,1270,1271],{},"You walk into the board meeting. A board member asks a simple question: \"Is our technology investment actually paying off?\"",[12,1273,1274],{},"You have dashboards. You have data. But somewhere between your engineering metrics and that question, the translation breaks down.",[12,1276,1277],{},"That gap — between what your systems measure and what your board needs to understand — is the central problem that CTO dashboard best practices exist to solve.",[12,1279,1280],{},"A CTO dashboard is not just a collection of engineering metrics. It is a translation layer: a system that converts deployment frequency into time-to-market advantage, change failure rate into incident cost, and developer experience scores into retention risk. Done well, it turns board reporting into strategic leadership.",[12,1282,1283],{},"This guide covers the best practices that separate CTO dashboards that drive decisions from dashboards that produce noise — organized around the foundational insight that the best CTO dashboards are not one thing, but three.",[12,1285,1286,1287,1289,1290,611],{},"If you want the delivery baseline behind this guide, start with ",[514,1288,848],{"href":847}," and the expanded view in ",[514,1291,1292],{"href":605},"DORA metrics in 2026",[613,1294,616],{"id":615},[70,1296,1297,1303,1309,1315,1321,1327,1333,1339,1345,1351,1357,1361],{},[73,1298,1299],{},[514,1300,1302],{"href":1301},"#why-most-cto-dashboards-fail","Why Most CTO Dashboards Fail",[73,1304,1305],{},[514,1306,1308],{"href":1307},"#the-three-layer-dashboard-architecture","The Three-Layer Dashboard Architecture",[73,1310,1311],{},[514,1312,1314],{"href":1313},"#layer-1-the-operational-view-engineering-teams","Layer 1: The Operational View (Engineering Teams)",[73,1316,1317],{},[514,1318,1320],{"href":1319},"#layer-2-the-strategic-view-cto-and-engineering-leadership","Layer 2: The Strategic View (CTO and Engineering Leadership)",[73,1322,1323],{},[514,1324,1326],{"href":1325},"#layer-3-the-board-view-executives-and-directors","Layer 3: The Board View (Executives and Directors)",[73,1328,1329],{},[514,1330,1332],{"href":1331},"#the-translation-framework-engineering-language-to-business-language","The Translation Framework: Engineering Language to Business Language",[73,1334,1335],{},[514,1336,1338],{"href":1337},"#what-to-include--and-what-to-drop","What to Include — and What to Drop",[73,1340,1341],{},[514,1342,1344],{"href":1343},"#design-principles-for-decision-driven-dashboards","Design Principles for Decision-Driven Dashboards",[73,1346,1347],{},[514,1348,1350],{"href":1349},"#adding-the-ai-layer-new-metrics-for-2026","Adding the AI Layer: New Metrics for 2026",[73,1352,1353],{},[514,1354,1356],{"href":1355},"#connecting-your-dashboard-to-okrs-and-strategic-initiatives","Connecting Your Dashboard to OKRs and Strategic Initiatives",[73,1358,1359],{},[514,1360,678],{"href":677},[73,1362,1363],{},[514,1364,684],{"href":683},[613,1366,1302],{"id":1367},"why-most-cto-dashboards-fail",[12,1369,1370],{},"Recent research shows that 47% of organizations admit they lack sufficient visibility into their own engineering structure. Yet most of those organizations have dashboards. The problem is rarely an absence of data — it is an abundance of the wrong data presented to the wrong audience in the wrong language.",[12,1372,1373],{},"There are three failure modes that account for almost every ineffective CTO dashboard.",[12,1375,1376,1379],{},[16,1377,1378],{},"Failure Mode 1: One dashboard, all audiences."," A dashboard built for a senior engineer and a dashboard built for a CFO are fundamentally different artifacts. The CFO asks, \"Are we getting value from our engineering investment?\" The CTO asks, \"Are we shipping reliably and safely?\" The engineering manager asks, \"Where is work getting stuck?\" A single undifferentiated dashboard rarely answers any of these questions well — because the metrics, the language, and the decision cadence are different for each audience.",[12,1381,1382,1385],{},[16,1383,1384],{},"Failure Mode 2: Metrics without translation."," Deployment frequency, change failure rate, lead time for changes, and mean time to recovery are precise engineering terms with direct business translations — but most dashboards never make those translations explicit. When a board member sees \"deployment frequency: 4.2 per week,\" they do not know whether to be impressed or concerned. When they see \"time-to-market for new features: reduced by 18 days this quarter,\" they can make a decision.",[12,1387,1388,1391,1392,1395],{},[16,1389,1390],{},"Failure Mode 3: Data without context."," A number in isolation is noise. A trend is a story. A trend compared to a ",[514,1393,1394],{"href":819},"benchmark"," is a decision. Boards care more about direction and trajectory than raw numbers. A dashboard that shows a single data point for each metric — without historical trend lines, without industry benchmarks, without the narrative of what changed and why — produces confusion rather than clarity.",[613,1397,1308],{"id":1398},"the-three-layer-dashboard-architecture",[12,1400,1401],{},"The most effective CTO dashboards are not a single view — they are a layered system with three distinct audiences, three distinct cadences, and three distinct vocabularies.",[70,1403,1404,1410,1416],{},[73,1405,1406,1409],{},[16,1407,1408],{},"Layer 1: Operational View"," — for engineering teams and engineering managers. Daily or continuous refresh. Focused on the signals that help teams course-correct in real time.",[73,1411,1412,1415],{},[16,1413,1414],{},"Layer 2: Strategic View"," — for the CTO and VP of Engineering. Weekly refresh. Focused on delivery performance trends, team health, and system stability across teams.",[73,1417,1418,1421],{},[16,1419,1420],{},"Layer 3: Board View"," — for the CEO, CFO, and board members. Monthly or quarterly refresh. Focused on business outcomes: technology ROI, delivery against strategic commitments, reliability, and risk.",[12,1423,1424],{},"Each layer draws on the same underlying data — but presents it in the language appropriate for its audience, at the granularity required for its decisions, and at the cadence that matches how frequently that audience needs to act.",[12,1426,1427,1428,1431],{},"A critical principle: ",[16,1429,1430],{},"layers drill down, not up."," Board members need to trust that if they drill into a metric, they will find the operational data that supports it. Engineering teams need to understand how their daily work connects to the board-level metrics their CTO reports. Layers that do not connect in both directions produce silos, not intelligence.",[613,1433,1314],{"id":1434},"layer-1-the-operational-view-engineering-teams",[12,1436,1437],{},"The operational view is where engineers and engineering managers live day-to-day. Its purpose is to surface the signals that require immediate attention — before they appear in delivery metrics or board reports.",[12,1439,1440,1443,1444,1447],{},[16,1441,1442],{},"PR Cycle Time by Stage."," Breaking cycle time into segments — coding time, pickup time, review time, and deploy time — reveals where work is actually stalling. PR pickup time is frequently the silent bottleneck: PRs sitting unreviewed for 12+ hours create merge conflicts, context-switching overhead, and delivery delays that will not appear in DORA metrics for weeks. Teams that want to spot early friction should also track ",[514,1445,1446],{"href":909},"workflow symptoms"," that appear before delivery numbers degrade.",[12,1449,1450,1453],{},[16,1451,1452],{},"Build Success Rate on Main Branch."," Industry benchmark: 90% is healthy; the current average across engineering organizations is approximately 70.8%. A declining build success rate on main is a leading indicator of integration problems — and the gap between 70.8% and 90% represents real delivery risk that operational teams can address before it cascades.",[12,1455,1456,1459],{},[16,1457,1458],{},"Active Incidents and MTTR Trend."," Not just whether an incident is open, but whether your mean time to recovery is trending up or down. A rising MTTR trend is the earliest signal of degrading operational maturity — insufficient monitoring coverage, unclear runbooks, or on-call overload.",[12,1461,1462,1465],{},[16,1463,1464],{},"Work in Progress (WIP) Count."," High WIP is a leading indicator of context-switching, delayed delivery, and team overload. Teams with too many concurrent tasks in flight consistently underperform teams with focused, smaller batches — regardless of headcount.",[12,1467,1468,1471],{},[791,1469,1470],{},"Design principle for the operational layer:"," Update as close to real-time as your toolchain allows. This view is read by people who need to act within hours, not quarters.",[613,1473,1320],{"id":1474},"layer-2-the-strategic-view-cto-and-engineering-leadership",[12,1476,1477],{},"The strategic view answers the question you are responsible for: is the engineering organization performing in a way that is sustainable, improving, and aligned with company priorities?",[12,1479,1480,1483],{},[16,1481,1482],{},"Delivery Performance (DORA metrics + extensions)."," DORA’s five metrics — deployment frequency, lead time for changes, change failure rate, failed deployment recovery time, and rework rate — provide the most empirically validated baseline for delivery performance. Elite performers on DORA metrics are 4x more likely to meet their organizational performance targets. Go deeper than the headline numbers: segment deployment frequency by team, break lead time into stages, and track rework rate alongside change failure rate to catch quality problems before they surface in stability metrics.",[12,1485,1486,1489],{},[16,1487,1488],{},"Team Health."," Developer satisfaction scores and eNPS are leading indicators of attrition risk and sustainable delivery. DORA scores can look excellent while teams are burning out — and team health metrics are the only way to detect this before it appears in attrition numbers. Track PR review load per senior engineer carefully: in AI-augmented environments, AI-generated pull requests wait an average of 4.6x longer for review than human-authored ones, concentrating burden in ways traditional PR volume metrics do not capture.",[12,1491,1492,1495],{},[16,1493,1494],{},"Investment Allocation."," A healthy engineering organization typically directs approximately 40% of engineering capacity toward new feature development, 20% toward rework and bug fixes, and 40% toward maintenance and operational work. Track your actual allocation against this benchmark. When maintenance consistently exceeds 50% of capacity, technical debt is absorbing resources that should be building competitive advantage. Frame this as your KTLO ratio: how much engineering time is reactive versus proactive?",[12,1497,1498,1501,1502,1505,1506,611],{},[16,1499,1500],{},"AI Impact Line."," In 2026, the strategic view needs an AI section. Track AI code share, AI-assisted PR cycle time versus human-authored, and code churn rate for AI-generated code. These three signals together tell you whether your AI tooling is producing durable delivery improvements or accelerating code volume without proportional quality. For deeper attribution, review ",[514,1503,1504],{"href":609},"AI coding assistant impact"," and the guide to ",[514,1507,1509],{"href":1508},"\u002Fblog\u002Fhow-to-measure-ai-assisted-software-development","measuring AI-assisted development",[613,1511,1326],{"id":1512},"layer-3-the-board-view-executives-and-directors",[12,1514,1515],{},"The board view requires the most aggressive translation. Board members are not thinking about deployment frequency or change failure rate — they are thinking about growth, margins, risk, and competitive position.",[12,1517,1518],{},"Every metric on the board view should answer one of five questions:",[1520,1521,1522,1525,1528,1531,1534],"ol",{},[73,1523,1524],{},"Is our technology investment delivering financial return?",[73,1526,1527],{},"Is our platform reliable enough to support our customer commitments?",[73,1529,1530],{},"Are we delivering on our strategic technology roadmap?",[73,1532,1533],{},"What are our material technology risks?",[73,1535,1536],{},"Is our engineering organization healthy enough to sustain current growth?",[12,1538,1539,1542,1543,1547],{},[16,1540,1541],{},"Technology ROI."," Frame engineering investment as a value generator, not just a cost center. Show how technology improvements translated into business outcomes: faster feature delivery supporting a product launch, reduced incident costs from reliability improvements, engineering capacity recaptured by automation and redeployed to roadmap work. If you need a consistent model, use a simple ",[514,1544,1546],{"href":1545},"\u002Froi-calculator","ROI calculator"," so the board can see assumptions.",[12,1549,1550,1553],{},[16,1551,1552],{},"System Reliability."," Platform uptime for customer-facing systems is one of the clearest technology-to-customer-experience connections available. Express it as uptime percentage and connect it to customer impact: downtime hours per quarter, estimated revenue exposure from outages, and MTTR trend.",[12,1555,1556,1559],{},[16,1557,1558],{},"Roadmap Delivery."," How much of what was committed for this quarter was delivered? This is the accountability metric boards care about most. \"We delivered 84% of committed roadmap items this quarter, up from 71% last quarter\" is a board-ready sentence. Be honest when the number is low — and have a root cause narrative ready.",[12,1561,1562,1565],{},[16,1563,1564],{},"Tech Spend as Percentage of Revenue."," This benchmark contextualizes your engineering investment in language CFOs understand. Track this ratio over time to reveal whether your technology cost structure is scaling efficiently with the business.",[12,1567,1568,1571],{},[16,1569,1570],{},"Security Risk Posture."," A single traffic-light indicator (green\u002Famber\u002Fred) with a one-sentence explanation of your current vulnerability status is often sufficient. Detail belongs in an appendix; the board view shows status and trend.",[12,1573,1574,1577],{},[791,1575,1576],{},"Design principle for the board layer:"," Aim for 8–10 tiles maximum. Show at least four to eight quarters of historical trend for every metric. Never show numbers that contradict what your CFO is reporting — data credibility is the foundation of board trust.",[613,1579,1332],{"id":1580},"the-translation-framework-engineering-language-to-business-language",[12,1582,1583],{},"The most important design decision in your CTO dashboard is not which metrics to show — it is how to translate them. The same four DORA metrics read through two different lenses:",[1585,1586,1587,1600],"table",{},[1588,1589,1590],"thead",{},[1591,1592,1593,1597],"tr",{},[1594,1595,1596],"th",{},"Engineering Lens",[1594,1598,1599],{},"Board Lens",[1601,1602,1603,1612,1620,1628],"tbody",{},[1591,1604,1605,1609],{},[1606,1607,1608],"td",{},"Deployment frequency: 4.2\u002Fweek",[1606,1610,1611],{},"Time to market: new features reach customers 3 weeks faster than 18 months ago",[1591,1613,1614,1617],{},[1606,1615,1616],{},"Lead time for changes: 3.2 days",[1606,1618,1619],{},"Customer responsiveness: critical fixes ship within 3 days of discovery",[1591,1621,1622,1625],{},[1606,1623,1624],{},"Change failure rate: 8%",[1606,1626,1627],{},"Incident cost: 8% of deployments create incidents averaging $50K each = $800K annual risk",[1591,1629,1630,1633],{},[1606,1631,1632],{},"MTTR: 47 minutes",[1606,1634,1635],{},"SLA exposure: we restore service within the 60-minute SLA commitment 94% of the time",[12,1637,1638],{},"None of the underlying data changes. Only the framing changes — from engineering performance to business risk, from technical capability to financial exposure.",[12,1640,1641],{},"Build this translation layer into your dashboard design, not your presentation layer. For every board-view metric, write a single sentence a CFO can read and immediately understand the business implication. That sentence becomes the tooltip, the axis label, or the subtitle of the metric tile — not something you explain verbally in the board meeting.",[613,1643,1338],{"id":1644},"what-to-include-and-what-to-drop",[12,1646,1647],{},"Most CTO dashboards suffer from too many metrics, not too few. Every metric added to a board view increases cognitive load and reduces the clarity of the metrics that actually matter.",[12,1649,1650,1653],{},[16,1651,1652],{},"Include metrics that:"," connect directly to a board question; show trend over time, not just current state; are resistant to gaming — improving the metric genuinely improves the business; have a clear benchmark or target for context; and can be explained in one sentence to a non-technical executive.",[12,1655,1656,1659],{},[16,1657,1658],{},"Drop metrics that:"," are activity signals rather than outcome signals (tickets closed, commits per week, lines of code); board members cannot act on even if they understand them; require deep technical context to interpret; appear solely because your tools produce them automatically; or cannot survive the \"so what?\" test.",[12,1661,1662,1665],{},[16,1663,1664],{},"The vanity metric test:"," A metric is a vanity metric for the board view if it can increase without any improvement in business outcomes. Number of deployments can rise while features still ship late. Code coverage can increase while production bugs multiply. PR count can surge while delivery velocity stays flat. Drop them from the board view. Keep them in the operational layer where they have diagnostic value.",[613,1667,1344],{"id":1668},"design-principles-for-decision-driven-dashboards",[12,1670,1671,1674],{},[16,1672,1673],{},"Show trends, not snapshots."," A single data point is ambiguous. A trend line is diagnostic. A trend line with a benchmark is actionable. For every metric on your board view, show at least four quarters of history so the board can evaluate trajectory rather than just current state.",[12,1676,1677,1680],{},[16,1678,1679],{},"Use traffic-light indicators with explicit thresholds."," A green\u002Famber\u002Fred status indicator is useful only if the thresholds are published and consistently defined. \"Change failure rate: green below 5%, amber 5–10%, red above 10%\" is actionable. Hold thresholds consistent across quarters so the board develops calibrated trust in the system.",[12,1682,1683,1686],{},[16,1684,1685],{},"Annotate context directly on the dashboard."," Mark significant events — major releases, infrastructure migrations, team restructuring, security incidents — directly on trend graphs. When a board member sees a spike in change failure rate, the annotation explaining \"major platform migration in progress\" completely changes the interpretation. Without it, boards form their own explanations.",[12,1688,1689,1692],{},[16,1690,1691],{},"Keep the board view to one screen."," If your board-level dashboard requires scrolling, it is too dense. The primary view should function like the cockpit of a plane — an at-a-glance health assessment that surfaces problems without requiring deep investigation. Details belong in drill-downs or appendices.",[12,1694,1695,1698],{},[16,1696,1697],{},"Ensure data consistency with finance."," Nothing destroys board trust faster than numbers that contradict what the CFO is showing. Tech spend figures should match CFO reports to the dollar. Build your technology dashboard from the same data sources as your financial systems wherever they overlap, and fix data pipeline discrepancies before the next board meeting — not after.",[613,1700,1350],{"id":1701},"adding-the-ai-layer-new-metrics-for-2026",[12,1703,1704],{},"In 2026, boards are asking about AI investment in a serious, accountability-oriented way for the first time. The days of \"we are exploring AI\" as a sufficient board answer are over. Boards now want to know what AI has actually delivered — and whether the investment is producing measurable returns.",[12,1706,1707],{},[16,1708,1709],{},"At the strategic layer, track three AI-specific metrics:",[12,1711,1712,1715],{},[16,1713,1714],{},"AI Code Share."," The percentage of merged code that was AI-generated or AI-assisted. Industry telemetry shows approximately 22% of merged code is AI-authored across large developer samples in 2025. Your organization's number tells you whether you are ahead or behind on adoption — and segments all other metrics by AI involvement.",[12,1717,1718,1721],{},[16,1719,1720],{},"AI vs. Human PR Cycle Time Delta."," Segment PR cycle time by AI-assisted versus human-authored pull requests. If AI PRs are moving faster, you have evidence of productivity improvement. If they are slower — which is common, since AI-generated code often requires more careful review — you have identified where to invest in review governance.",[12,1723,1724,1727],{},[16,1725,1726],{},"AI-Generated Code Churn Rate."," How often is recently written AI code rewritten or deleted within 30 days? Rising churn is a leading indicator of quality debt accumulating beneath your DORA metrics — the early warning signal that AI adoption is creating more rework than it is preventing.",[12,1729,1730,1733],{},[16,1731,1732],{},"At the board layer,"," translate AI investment into a financial ROI calculation. If AI tooling saves an average of 3.6 hours per developer per week (per industry benchmarks), and you have 100 engineers, that is 360 hours per week of recaptured capacity. At your average fully loaded engineering cost, what is the annual dollar value of that recaptured time? Compare it to your AI tool costs, factor in review overhead, and you have a board-ready ROI figure.",[613,1735,1356],{"id":1736},"connecting-your-dashboard-to-okrs-and-strategic-initiatives",[12,1738,1739],{},"The most effective CTO dashboards connect every metric to a specific strategic commitment. This connection transforms your dashboard from a reporting artifact into a strategic accountability system.",[12,1741,1742],{},"For each OKR or strategic initiative on your quarterly roadmap, your board view should answer three questions: how much engineering capacity was allocated to this initiative, what did we deliver against our commitment, and what is the measurable business outcome so far?",[12,1744,1745,1746,1749,1750,1753,1754,1757],{},"One practical framework: categorize every engineering work item into three buckets. ",[16,1747,1748],{},"New value"," — features that generate new revenue or market position. ",[16,1751,1752],{},"Existing value"," — maintenance and improvement of current products. ",[16,1755,1756],{},"KTLO"," — operational work that does not advance the product. Track the percentage of engineering capacity in each bucket over time. Organizations that explicitly measure this ratio achieve measurably better delivery outcomes and executive alignment — because they can have an evidence-based conversation about trade-offs rather than defending engineering investment in the abstract.",[12,1759,1760],{},"For a strategic initiative like entering a new market, the board view should show the engineering capacity allocated to that work, delivery progress against the roadmap, and the time-to-market impact — how much sooner the market entry became possible because of engineering execution. This is the difference between defensive engineering reporting and strategic technology leadership.",[613,1762,678],{"id":1083},[12,1764,1765,1768],{},[16,1766,1767],{},"Mistake 1: Building one dashboard for all audiences."," The most common and most costly mistake. Build the three-layer system. It requires more upfront work; it produces dramatically better outcomes for all three audiences.",[12,1770,1771,1774],{},[16,1772,1773],{},"Mistake 2: Showing metrics without benchmarks."," If you report that your lead time is 3.2 days, your board has no basis for judgment. Add two anchors: your historical trend and an industry benchmark (elite teams are under 24 hours; median is 3.8 days). With those anchors, 3.2 days becomes clearly strong — and the board can evaluate performance rather than just receive a number.",[12,1776,1777,1780],{},[16,1778,1779],{},"Mistake 3: Using BI tools designed for finance."," General-purpose tools like Tableau, Power BI, or Looker show charts; they do not understand engineering context. For your engineering-specific layers, use engineering intelligence platforms that understand the domain. For your board view, simple, well-designed presentation formats often outperform complex BI dashboards.",[12,1782,1783,1786],{},[16,1784,1785],{},"Mistake 4: Reporting metrics that contradict the CFO's report."," Nothing damages credibility faster. Establish a shared data pipeline for any metrics that appear in both reports. If numbers cannot be reconciled, disclose the difference and explain why before the board asks.",[12,1788,1789,1792],{},[16,1790,1791],{},"Mistake 5: Treating the dashboard as a reporting artifact rather than a decision tool."," The goal of a CTO dashboard is not to prove that engineering is productive. It is to help the board and engineering leadership make better decisions about where to invest, what to prioritize, and which risks to address. If a metric does not inform a decision your board needs to make, it belongs in a drill-down — not on the primary view.",[613,1794,684],{"id":1121},[52,1796,1798],{"id":1797},"what-should-be-on-a-cto-dashboard","What should be on a CTO dashboard?",[12,1800,1801],{},"A CTO dashboard should be organized in three layers: an operational layer for engineering teams (cycle time, deployment frequency, PR review time, incident MTTR), a strategic layer for the CTO and engineering leadership (DORA metrics, developer experience, AI ROI, team health), and a board layer (technology ROI, system uptime, roadmap delivery, tech spend as % of revenue, security risk posture). Each layer serves a different audience with a different decision-making cadence.",[52,1803,1805],{"id":1804},"what-kpis-should-a-cto-track","What KPIs should a CTO track?",[12,1807,1808],{},"CTOs should track five categories of KPIs: delivery performance (deployment frequency, lead time, change failure rate, cycle time), system reliability (uptime, MTTR, error rate), team health (developer satisfaction, eNPS, PR review load), business alignment (roadmap delivery ratio, R&D investment allocation, revenue per engineer), and AI impact (AI code share, AI-assisted PR cycle time, code churn rate for AI-generated code). The specific KPIs should map directly to the board questions the CTO needs to answer.",[52,1810,1812],{"id":1811},"what-is-the-difference-between-a-cto-dashboard-and-an-engineering-dashboard","What is the difference between a CTO dashboard and an engineering dashboard?",[12,1814,1815],{},"An engineering dashboard focuses on team-level operational signals designed for developers and engineering managers. A CTO dashboard connects those signals to strategy, risk, and business outcomes — acting as a translation layer where deployment frequency becomes time-to-market, change failure rate becomes incident cost, and MTTR becomes SLA risk. The audience and the language are fundamentally different.",[52,1817,1819],{"id":1818},"how-often-should-a-cto-review-their-dashboard","How often should a CTO review their dashboard?",[12,1821,1822],{},"CTO dashboard review cadence should match the decision it supports. Operational metrics warrant daily monitoring. Delivery and team performance metrics should be reviewed weekly by engineering leadership. Board-level metrics — technology ROI, roadmap delivery, security posture, AI investment outcomes — are reviewed monthly or quarterly. A single dashboard with a single refresh cadence serves none of these audiences well.",[52,1824,1826],{"id":1825},"what-are-the-most-common-cto-dashboard-mistakes","What are the most common CTO dashboard mistakes?",[12,1828,1829],{},"The five most common CTO dashboard mistakes are: building one dashboard for all audiences instead of layered views; including vanity metrics like lines of code or ticket counts that cannot survive board scrutiny; showing data without context — a number means nothing without a trend and a benchmark; not aligning metrics with OKRs or strategic initiatives; and using BI tools designed for finance rather than engineering intelligence platforms.",[613,1831,1159],{"id":477},[12,1833,1834],{},"A CTO dashboard done well is not a reporting artifact — it is a leadership system. It gives engineering teams the operational clarity to course-correct daily. It gives you and your engineering leadership the strategic visibility to identify problems before they become crises. And it gives your board the business language they need to make confident decisions about technology investment.",[12,1836,1837],{},"The foundation is the three-layer architecture: operational, strategic, and board views built for different audiences, different cadences, and different vocabularies. The principle that holds all three together is translation — the discipline of connecting engineering performance to business outcomes in language that each audience can immediately use.",[12,1839,1840],{},"Start by defining the five to seven questions your board needs to answer about technology this quarter. Design your board view around those questions. Build backward from there into the strategic and operational layers. The dashboard that emerges will be smaller, clearer, and more influential than any dashboard built by starting with a list of metrics and working forward to an audience.",[12,1842,1843,1844,1848,1849,1852],{},"If you want help designing the three-layer system, explore the ",[514,1845,1847],{"href":1846},"\u002Fplatform","Oobeya platform"," and the ",[514,1850,1851],{"href":819},"engineering intelligence benchmarks"," it supports.",{"title":526,"searchDepth":527,"depth":527,"links":1854},[1855,1856,1857,1858,1859,1860,1861,1862,1863,1864,1865,1866,1867,1874],{"id":615,"depth":527,"text":616},{"id":1367,"depth":527,"text":1302},{"id":1398,"depth":527,"text":1308},{"id":1434,"depth":527,"text":1314},{"id":1474,"depth":527,"text":1320},{"id":1512,"depth":527,"text":1326},{"id":1580,"depth":527,"text":1332},{"id":1644,"depth":527,"text":1338},{"id":1668,"depth":527,"text":1344},{"id":1701,"depth":527,"text":1350},{"id":1736,"depth":527,"text":1356},{"id":1083,"depth":527,"text":678},{"id":1121,"depth":527,"text":684,"children":1868},[1869,1870,1871,1872,1873],{"id":1797,"depth":530,"text":1798},{"id":1804,"depth":530,"text":1805},{"id":1811,"depth":530,"text":1812},{"id":1818,"depth":530,"text":1819},{"id":1825,"depth":530,"text":1826},{"id":477,"depth":527,"text":1159},[540,1876,1231],"engineering-metrics","2026-03-28","CTO dashboard best practices for 2026, including three-layer architecture, the metrics that matter, and how to translate engineering data into board-ready language.",{"faq":1880},[1881,1882,1884,1886,1888],{"question":1798,"answer":1801},{"question":1805,"answer":1883},"CTOs should track five categories of KPIs: delivery performance (deployment frequency, lead time, change failure rate, cycle time), system reliability (uptime, MTTR, error rate), team health (developer satisfaction, eNPS, PR review load), business alignment (roadmap delivery ratio, R&D investment allocation, revenue per engineer), and AI impact (AI code share, AI-assisted PR cycle time, code churn rate for AI-generated code).",{"question":1812,"answer":1885},"An engineering dashboard focuses on team-level operational signals designed for developers and engineering managers. A CTO dashboard connects those signals to strategy, risk, and business outcomes by translating deployment frequency into time-to-market, change failure rate into incident cost, and MTTR into SLA risk.",{"question":1819,"answer":1887},"Operational metrics warrant daily monitoring. Delivery and team performance metrics should be reviewed weekly by engineering leadership. Board-level metrics such as technology ROI, roadmap delivery, security posture, and AI investment outcomes are typically reviewed monthly or quarterly.",{"question":1826,"answer":1889},"The most common mistakes include building one dashboard for all audiences, using vanity metrics like lines of code, showing data without context or benchmarks, not aligning metrics with OKRs, and relying on finance-first BI tools that miss engineering context.","\u002Fblog\u002Fcto-dashboard-best-practices-2026",{"title":1264,"description":1878},"\u002Fassets\u002Fblog\u002Fcto-dashboard-mock.svg","A practical CTO dashboard guide for 2026, covering layered views, metric translation, and AI-era visibility.","blog\u002Fcto-dashboard-best-practices-2026",[1896,1876,1232,1897,1898],"cto-dashboard","board-reporting","ai-impact","4v8oarwP8GrOibFeC1wr9b8YedtS83fXHTeY4NCk8ek",{"id":1901,"title":1902,"author":1265,"avatar":1266,"body":1903,"categories":2596,"createAt":542,"date":2597,"description":2598,"extension":545,"meta":2599,"navigation":547,"path":605,"position":542,"seo":2615,"spotImage":2616,"spotText":2617,"stem":2618,"tags":2619,"__hash__":2622},"blog\u002Fblog\u002Fdora-metrics-not-enough-2026.md","DORA Metrics Are Not Enough in 2026: What Elite Engineering Teams Track Instead",{"type":9,"value":1904,"toc":2554},[1905,1908,1914,1917,1920,1922,1982,1985,1988,1991,2009,2016,2019,2022,2026,2029,2037,2040,2044,2047,2050,2067,2070,2074,2077,2080,2083,2092,2095,2098,2102,2105,2108,2112,2115,2138,2141,2144,2147,2158,2162,2165,2179,2182,2186,2189,2206,2212,2216,2219,2236,2243,2246,2249,2252,2274,2277,2280,2283,2286,2300,2303,2306,2309,2312,2315,2319,2322,2325,2329,2332,2336,2339,2342,2346,2349,2353,2356,2371,2374,2377,2381,2384,2388,2391,2406,2410,2413,2424,2428,2431,2450,2453,2456,2459,2462,2486,2489,2491,2495,2498,2502,2505,2509,2512,2516,2519,2523,2526,2528,2531,2534,2548,2551],[12,1906,1907],{},"Your DORA metrics look fine. Deployment frequency is up. Lead time is down. And yet something still feels off. Your roadmap is slipping, senior engineers are drowning in review work, and it is still unclear whether your AI investment is truly improving delivery.",[12,1909,1910,1911,1913],{},"You are not imagining it. ",[514,1912,848],{"href":847}," were never designed to answer those questions by themselves.",[12,1915,1916],{},"The 2025 DORA State of AI-assisted Software Development report, based on nearly 5,000 technology professionals, reinforced what many engineering leaders already feel in practice: software delivery metrics alone are no longer sufficient. They tell you what is happening, but not why it is happening.",[12,1918,1919],{},"That gap is what this article is about. We will walk through what DORA can and cannot tell you in 2026, what elite teams track beyond it, and how to build a measurement system that supports decisions instead of just dashboards.",[613,1921,616],{"id":615},[70,1923,1924,1930,1936,1942,1948,1954,1960,1966,1972,1978],{},[73,1925,1926],{},[514,1927,1929],{"href":1928},"#what-dora-metrics-are-and-what-they-were-designed-to-do","What DORA Metrics Are and What They Were Designed to Do",[73,1931,1932],{},[514,1933,1935],{"href":1934},"#the-three-blind-spots-dora-cannot-see","The Three Blind Spots DORA Cannot See",[73,1937,1938],{},[514,1939,1941],{"href":1940},"#what-the-2025-dora-report-changed","What the 2025 DORA Report Changed",[73,1943,1944],{},[514,1945,1947],{"href":1946},"#what-elite-engineering-teams-track-beyond-dora","What Elite Engineering Teams Track Beyond DORA",[73,1949,1950],{},[514,1951,1953],{"href":1952},"#the-dx-core-4-framework","The DX Core 4 Framework",[73,1955,1956],{},[514,1957,1959],{"href":1958},"#the-ai-attribution-problem","The AI Attribution Problem",[73,1961,1962],{},[514,1963,1965],{"href":1964},"#five-ai-specific-metrics-dora-ignores","Five AI-Specific Metrics DORA Ignores",[73,1967,1968],{},[514,1969,1971],{"href":1970},"#how-to-build-a-complete-engineering-intelligence-stack","How to Build a Complete Engineering Intelligence Stack",[73,1973,1974],{},[514,1975,1977],{"href":1976},"#connecting-metrics-to-business-outcomes","Connecting Metrics to Business Outcomes",[73,1979,1980],{},[514,1981,684],{"href":683},[613,1983,1929],{"id":1984},"what-dora-metrics-are-and-what-they-were-designed-to-do",[12,1986,1987],{},"The DORA framework gave software engineering something it badly needed: a shared and evidence-based language for delivery performance.",[12,1989,1990],{},"Its four original metrics still matter:",[70,1992,1993,1997,2001,2005],{},[73,1994,1995],{},[739,1996,825],{},[73,1998,1999],{},[739,2000,835],{},[73,2002,2003],{},[739,2004,859],{},[73,2006,2007],{},[739,2008,900],{},[12,2010,2011,2012,2015],{},"In 2025, the DORA team added a fifth metric: ",[739,2013,2014],{},"Rework Rate",", which helps show how much engineering activity is reactive instead of planned. At the same time, Mean Time to Recovery was reframed as Failed Deployment Recovery Time and repositioned within the model.",[12,2017,2018],{},"These metrics are still useful. The problem is not that DORA is wrong. The problem is that DORA is incomplete.",[613,2020,1935],{"id":2021},"the-three-blind-spots-dora-cannot-see",[52,2023,2025],{"id":2024},"_1-dora-tells-you-what-not-why","1. DORA tells you what, not why",[12,2027,2028],{},"DORA is excellent at showing outcomes. It is not built to explain causes.",[12,2030,2031,2032,2036],{},"If your change failure rate rises, DORA will show the trend. It will not tell you whether the issue is PR review delay, pipeline fragility, AI-generated code quality, ",[514,2033,2035],{"href":2034},"\u002Fblog\u002Fstop-the-guesswork-see-who-is-overloaded-or-underutilized","overloaded teams",", or a specific codebase.",[12,2038,2039],{},"DORA starts the conversation. It does not finish it.",[52,2041,2043],{"id":2042},"_2-dora-ignores-the-people-inside-the-system","2. DORA ignores the people inside the system",[12,2045,2046],{},"DORA measures the delivery pipeline. It does not tell you how the developers inside that pipeline are experiencing the work.",[12,2048,2049],{},"It cannot show:",[70,2051,2052,2055,2058,2061,2064],{},[73,2053,2054],{},"review overload on senior engineers",[73,2056,2057],{},"trust erosion in AI-generated code",[73,2059,2060],{},"rising cognitive load",[73,2062,2063],{},"low collaboration quality",[73,2065,2066],{},"burnout hidden behind acceptable delivery numbers",[12,2068,2069],{},"That is why strong delivery numbers can coexist with weak developer experience.",[52,2071,2073],{"id":2072},"_3-dora-cannot-see-ais-real-impact","3. DORA cannot see AI's real impact",[12,2075,2076],{},"This is the most important blind spot in 2026.",[12,2078,2079],{},"A team can improve deployment frequency because AI generates more code faster, while change failure rate worsens because the code is harder to review or maintain. DORA captures the output but not the source. It does not know whether code was AI-assisted or human-authored.",[12,2081,2082],{},"That is the attribution gap. And without attribution, AI-era decisions get much harder.",[12,2084,2085,2086,2088,2089,611],{},"If your team is actively measuring this layer, explore ",[514,2087,610],{"href":609}," and our guide to ",[514,2090,2091],{"href":1508},"How to Measure AI-Assisted Software Development",[613,2093,1941],{"id":2094},"what-the-2025-dora-report-changed",[12,2096,2097],{},"The 2025 DORA report introduced two major shifts that matter directly for engineering leaders.",[52,2099,2101],{"id":2100},"from-four-tiers-to-seven-archetypes","From four tiers to seven archetypes",[12,2103,2104],{},"Instead of simple performance tiers, the report introduced seven team archetypes that combine delivery, stability, and well-being patterns.",[12,2106,2107],{},"This matters because two teams can show similar DORA scores for completely different reasons. One may be genuinely healthy and well balanced. Another may be performing under unsustainable pressure. The dashboard alone does not reveal that.",[52,2109,2111],{"id":2110},"the-dora-ai-capabilities-model","The DORA AI Capabilities Model",[12,2113,2114],{},"The report also introduced a seven-part AI capabilities model:",[1520,2116,2117,2120,2123,2126,2129,2132,2135],{},[73,2118,2119],{},"Clear and communicated AI stance",[73,2121,2122],{},"Healthy data ecosystems",[73,2124,2125],{},"AI-accessible internal data",[73,2127,2128],{},"Strong version control practices",[73,2130,2131],{},"User-centric focus",[73,2133,2134],{},"Robust feedback loops",[73,2136,2137],{},"AI governance",[12,2139,2140],{},"The core insight is simple: AI is an amplifier, not a fixer. Strong systems get stronger. Weak systems become more visibly unstable.",[613,2142,1947],{"id":2143},"what-elite-engineering-teams-track-beyond-dora",[12,2145,2146],{},"Top-performing teams in 2026 do not discard DORA. They layer it with three additional dimensions:",[70,2148,2149,2152,2155],{},[73,2150,2151],{},"developer experience",[73,2153,2154],{},"AI-specific attribution",[73,2156,2157],{},"business outcome alignment",[52,2159,2161],{"id":2160},"delivery-lifecycle-depth","Delivery lifecycle depth",[12,2163,2164],{},"Elite teams break lead time into more actionable components:",[70,2166,2167,2170,2173,2176],{},[73,2168,2169],{},"coding time",[73,2171,2172],{},"pickup time",[73,2174,2175],{},"review time",[73,2177,2178],{},"deploy time",[12,2180,2181],{},"This helps them identify exactly where the bottleneck moved.",[52,2183,2185],{"id":2184},"developer-workflow-signals","Developer workflow signals",[12,2187,2188],{},"Elite teams measure the human side of delivery too:",[70,2190,2191,2194,2197,2200,2203],{},[73,2192,2193],{},"satisfaction and well-being",[73,2195,2196],{},"cognitive load",[73,2198,2199],{},"trust in tools",[73,2201,2202],{},"workflow friction",[73,2204,2205],{},"review burden",[12,2207,2208,2209,2211],{},"This is where ",[514,2210,602],{"href":601}," becomes relevant. Output can rise while flow gets worse.",[52,2213,2215],{"id":2214},"business-alignment","Business alignment",[12,2217,2218],{},"The strongest teams also translate engineering metrics into executive language:",[70,2220,2221,2224,2227,2230,2233],{},[73,2222,2223],{},"revenue or value per engineer",[73,2225,2226],{},"roadmap delivery ratio",[73,2228,2229],{},"maintenance vs. new capability time",[73,2231,2232],{},"incident cost",[73,2234,2235],{},"time-to-market impact",[12,2237,2208,2238,247,2240,2242],{},[514,2239,820],{"href":819},[514,2241,910],{"href":909}," become useful complements to DORA.",[613,2244,1953],{"id":2245},"the-dx-core-4-framework",[12,2247,2248],{},"One of the most useful post-DORA measurement models is DX Core 4, developed with input from several of the same thinkers behind DORA, SPACE, and DevEx research.",[12,2250,2251],{},"It organizes measurement into four balancing zones:",[70,2253,2254,2259,2264,2269],{},[73,2255,2256],{},[739,2257,2258],{},"Speed",[73,2260,2261],{},[739,2262,2263],{},"Effectiveness",[73,2265,2266],{},[739,2267,2268],{},"Quality",[73,2270,2271],{},[739,2272,2273],{},"Business Impact",[12,2275,2276],{},"The power of this model is that it resists metric gaming.",[12,2278,2279],{},"A team can inflate speed by merging more AI-generated PRs. It cannot simultaneously inflate effectiveness if review pressure, developer satisfaction, and trust are falling. That makes DX Core 4 especially relevant in AI-heavy delivery environments.",[613,2281,1959],{"id":2282},"the-ai-attribution-problem",[12,2284,2285],{},"AI adoption often creates a confusing pattern:",[70,2287,2288,2291,2294,2297],{},[73,2289,2290],{},"throughput rises",[73,2292,2293],{},"delivery does not improve as much as expected",[73,2295,2296],{},"review load increases",[73,2298,2299],{},"instability can rise alongside output",[12,2301,2302],{},"This is where DORA becomes difficult to interpret without segmentation.",[12,2304,2305],{},"If deployment frequency goes up but change failure rate also increases, you still do not know whether AI is helping or hurting unless you can separate AI-assisted work from human-authored work.",[12,2307,2308],{},"That is why engineering intelligence in 2026 increasingly requires attribution layers, not just aggregate delivery dashboards.",[613,2310,1965],{"id":2311},"five-ai-specific-metrics-dora-ignores",[12,2313,2314],{},"To close that gap, elite teams now track an explicit AI measurement layer.",[52,2316,2318],{"id":2317},"_1-ai-code-share","1. AI code share",[12,2320,2321],{},"What percentage of merged code was AI-assisted or AI-generated?",[12,2323,2324],{},"This is the segmentation layer that makes the rest of the analysis possible.",[52,2326,2328],{"id":2327},"_2-ai-vs-human-pr-cycle-time","2. AI vs. human PR cycle time",[12,2330,2331],{},"If AI-assisted PRs take longer to review, you have identified a likely delivery bottleneck.",[52,2333,2335],{"id":2334},"_3-ai-code-churn-rate","3. AI code churn rate",[12,2337,2338],{},"How much recently written AI-assisted code is deleted or rewritten?",[12,2340,2341],{},"High churn is often a hidden quality signal.",[52,2343,2345],{"id":2344},"_4-ai-suggestion-acceptance-trend","4. AI suggestion acceptance trend",[12,2347,2348],{},"Acceptance rate matters, but its direction over time matters more. A declining trend often indicates trust or relevance problems.",[52,2350,2352],{"id":2351},"_5-pr-review-load-per-senior-engineer","5. PR review load per senior engineer",[12,2354,2355],{},"This is one of the strongest leading indicators of future friction, burnout, and review degradation in AI-assisted environments.",[12,2357,2358,2359,23,2363,27,2367,611],{},"If you want this in a more operational product view, look at the dedicated pages for ",[514,2360,2362],{"href":2361},"\u002Fai-coding-assistants\u002Fgithub-copilot","GitHub Copilot",[514,2364,2366],{"href":2365},"\u002Fai-coding-assistants\u002Fcursor","Cursor",[514,2368,2370],{"href":2369},"\u002Fai-coding-assistants\u002Fclaude","Claude",[613,2372,1971],{"id":2373},"how-to-build-a-complete-engineering-intelligence-stack",[12,2375,2376],{},"The most practical stack in 2026 is layered.",[52,2378,2380],{"id":2379},"layer-1-dora-baseline","Layer 1: DORA baseline",[12,2382,2383],{},"Start with consistent DORA definitions across teams and collect enough historical data to establish a reliable baseline.",[52,2385,2387],{"id":2386},"layer-2-developer-experience","Layer 2: Developer experience",[12,2389,2390],{},"Add a lightweight monthly pulse on:",[70,2392,2393,2396,2398,2400,2403],{},[73,2394,2395],{},"perceived productivity",[73,2397,2202],{},[73,2399,2196],{},[73,2401,2402],{},"trust in AI output",[73,2404,2405],{},"review load",[52,2407,2409],{"id":2408},"layer-3-ai-attribution","Layer 3: AI attribution",[12,2411,2412],{},"Instrument:",[70,2414,2415,2418,2421],{},[73,2416,2417],{},"AI code share",[73,2419,2420],{},"AI vs. human PR cycle time",[73,2422,2423],{},"code churn segmented by AI involvement",[52,2425,2427],{"id":2426},"layer-4-business-alignment","Layer 4: Business alignment",[12,2429,2430],{},"Translate delivery and quality metrics into business language:",[70,2432,2433,2436,2439,2442,2445],{},[73,2434,2435],{},"time-to-market",[73,2437,2438],{},"downtime cost",[73,2440,2441],{},"support burden",[73,2443,2444],{},"R&D allocation",[73,2446,2447],{},[514,2448,2449],{"href":1545},"AI ROI",[12,2451,2452],{},"The goal is not a bigger dashboard. The goal is a system that tells leadership what is happening, why it is happening, and what should change next.",[613,2454,1977],{"id":2455},"connecting-metrics-to-business-outcomes",[12,2457,2458],{},"Most engineering leaders can explain their DORA scores. Fewer can explain what those numbers mean in commercial terms.",[12,2460,2461],{},"A more useful executive translation looks like this:",[70,2463,2464,2469,2474,2480],{},[73,2465,2466,2468],{},[739,2467,825],{}," -> time-to-market advantage",[73,2470,2471,2473],{},[739,2472,859],{}," -> incident cost and release risk",[73,2475,2476,2479],{},[739,2477,2478],{},"Recovery Time"," -> operational impact and support load",[73,2481,2482,2485],{},[739,2483,2484],{},"AI investment"," -> measurable delivery and quality delta",[12,2487,2488],{},"Once metrics are framed this way, engineering discussions become easier to connect to portfolio, board, and finance conversations.",[613,2490,684],{"id":1121},[52,2492,2494],{"id":2493},"are-dora-metrics-still-relevant-in-2026","Are DORA metrics still relevant in 2026?",[12,2496,2497],{},"Yes. They are still the strongest common baseline for delivery performance. They are just no longer enough on their own.",[52,2499,2501],{"id":2500},"what-changed-in-the-2025-dora-report","What changed in the 2025 DORA report?",[12,2503,2504],{},"The report moved beyond simple linear tiers, introduced seven team archetypes, and added the DORA AI Capabilities Model as a framework for understanding whether AI is stabilizing or destabilizing delivery.",[52,2506,2508],{"id":2507},"what-do-elite-engineering-teams-track-beyond-dora","What do elite engineering teams track beyond DORA?",[12,2510,2511],{},"They add developer experience metrics, AI-specific attribution signals, and business outcome alignment on top of their DORA baseline.",[52,2513,2515],{"id":2514},"what-is-dx-core-4","What is DX Core 4?",[12,2517,2518],{},"It is a balancing model built around Speed, Effectiveness, Quality, and Business Impact. Its value is that it helps organizations avoid optimizing one dimension at the expense of the others.",[52,2520,2522],{"id":2521},"why-does-dora-struggle-with-ai","Why does DORA struggle with AI?",[12,2524,2525],{},"Because DORA is outcome-focused, not attribution-focused. It does not know whether the code being measured was AI-assisted or human-authored.",[613,2527,1159],{"id":477},[12,2529,2530],{},"DORA gave software engineering its first rigorously useful delivery framework. It still matters. But in a world where AI is accelerating output, shifting bottlenecks, and complicating review and quality patterns, DORA by itself is no longer the whole answer.",[12,2532,2533],{},"The strongest teams in 2026 build engineering intelligence stacks:",[70,2535,2536,2539,2542,2545],{},[73,2537,2538],{},"DORA as the delivery foundation",[73,2540,2541],{},"developer experience as the human layer",[73,2543,2544],{},"AI attribution as the accountability layer",[73,2546,2547],{},"business alignment as the executive layer",[12,2549,2550],{},"Together, those layers answer not only what is happening, but why it is happening, who is affected, whether AI is helping, and what it means for the business.",[12,2552,2553],{},"If you are still relying on DORA alone, the next useful step is not a bigger dashboard. It is a better measurement model.",{"title":526,"searchDepth":527,"depth":527,"links":2555},[2556,2557,2558,2563,2567,2572,2573,2574,2581,2587,2588,2595],{"id":615,"depth":527,"text":616},{"id":1984,"depth":527,"text":1929},{"id":2021,"depth":527,"text":1935,"children":2559},[2560,2561,2562],{"id":2024,"depth":530,"text":2025},{"id":2042,"depth":530,"text":2043},{"id":2072,"depth":530,"text":2073},{"id":2094,"depth":527,"text":1941,"children":2564},[2565,2566],{"id":2100,"depth":530,"text":2101},{"id":2110,"depth":530,"text":2111},{"id":2143,"depth":527,"text":1947,"children":2568},[2569,2570,2571],{"id":2160,"depth":530,"text":2161},{"id":2184,"depth":530,"text":2185},{"id":2214,"depth":530,"text":2215},{"id":2245,"depth":527,"text":1953},{"id":2282,"depth":527,"text":1959},{"id":2311,"depth":527,"text":1965,"children":2575},[2576,2577,2578,2579,2580],{"id":2317,"depth":530,"text":2318},{"id":2327,"depth":530,"text":2328},{"id":2334,"depth":530,"text":2335},{"id":2344,"depth":530,"text":2345},{"id":2351,"depth":530,"text":2352},{"id":2373,"depth":527,"text":1971,"children":2582},[2583,2584,2585,2586],{"id":2379,"depth":530,"text":2380},{"id":2386,"depth":530,"text":2387},{"id":2408,"depth":530,"text":2409},{"id":2426,"depth":530,"text":2427},{"id":2455,"depth":527,"text":1977},{"id":1121,"depth":527,"text":684,"children":2589},[2590,2591,2592,2593,2594],{"id":2493,"depth":530,"text":2494},{"id":2500,"depth":530,"text":2501},{"id":2507,"depth":530,"text":2508},{"id":2514,"depth":530,"text":2515},{"id":2521,"depth":530,"text":2522},{"id":477,"depth":527,"text":1159},[540,1232,1898],"2026-03-26","DORA metrics still matter, but they are no longer enough on their own. Learn what elite engineering teams track in 2026 across developer experience, AI attribution, and business outcomes.",{"faq":2600},[2601,2604,2607,2609,2612],{"question":2602,"answer":2603},"Why are DORA metrics not enough in 2026?","DORA metrics still describe software delivery outcomes well, but they do not explain enough of the modern engineering system on their own. They miss developer experience, AI attribution, review pressure, cognitive load, and the workflow causes behind the numbers.",{"question":2605,"answer":2606},"Should engineering teams stop using DORA metrics?","No. Teams should keep using DORA metrics, but they should stop treating them as a complete operating model. The strongest measurement systems now combine DORA with quality, workflow, AI, and human-centered engineering signals.",{"question":2508,"answer":2608},"Elite teams usually add developer experience, rework, review burden, AI-assisted development signals, and business-aligned engineering outcomes. This broader model gives leaders a better explanation of why performance improves or degrades over time.",{"question":2610,"answer":2611},"Can DORA metrics show whether AI coding assistants are working?","Not by themselves. DORA can show delivery movement, but it cannot isolate whether AI usage is improving review flow, reducing rework, or creating new quality pressure. Teams need AI-specific attribution metrics for that.",{"question":2613,"answer":2614},"What is the best way to use DORA in an AI-assisted environment?","The best approach is to keep DORA as a delivery foundation, then layer workflow, quality, DevEx, and AI impact signals on top. That turns DORA from a static dashboard into part of a more complete engineering intelligence system.",{"title":1902,"description":2598},"\u002Fassets\u002Fblog\u002FDORA-Metrics.png","Why elite engineering teams now layer DORA with developer experience, AI attribution, and business outcome alignment.","blog\u002Fdora-metrics-not-enough-2026",[1232,1876,2620,2621,540],"developer-experience","ai-assisted-development","LErWFrnnJsNAC4nehEEVU4uRVIZtUXwJTV_MzDz6SWo",{"id":2624,"title":2625,"author":574,"avatar":575,"body":2626,"categories":3319,"createAt":542,"date":3320,"description":3321,"extension":545,"meta":3322,"navigation":547,"path":601,"position":542,"seo":3338,"spotImage":3339,"spotText":3340,"stem":3341,"tags":3342,"__hash__":3344},"blog\u002Fblog\u002Fengineering-metrics-in-the-ai-era.md","Engineering Metrics in the AI Era: A Complete Guide for 2026",{"type":9,"value":2627,"toc":3274},[2628,2631,2634,2637,2640,2647,2649,2713,2716,2719,2722,2725,2728,2754,2757,2760,2763,2766,2770,2776,2780,2783,2787,2790,2794,2797,2800,2803,2808,2811,2830,2833,2836,2853,2856,2864,2867,2876,2879,2896,2899,2902,2910,2913,2916,2919,2932,2935,2938,2941,2944,2947,2950,2953,2956,2959,2962,2965,2968,2971,2975,2978,2981,2984,2987,2990,3002,3005,3008,3012,3015,3031,3035,3038,3055,3059,3062,3080,3093,3096,3103,3114,3117,3120,3123,3125,3128,3131,3133,3136,3138,3141,3144,3158,3163,3166,3170,3173,3177,3180,3184,3187,3191,3194,3198,3201,3203,3207,3210,3214,3217,3221,3224,3228,3231,3235,3238,3240,3243,3246,3249,3252,3255],[12,2629,2630],{},"Your developers are producing more code than ever. PR volumes are up. Commit graphs look impressive. And yet the roadmap is still slipping.",[12,2632,2633],{},"That is the defining leadership challenge of 2026: the gap between what looks productive and what actually is.",[12,2635,2636],{},"Research across more than 10,000 developers and 1,255 teams points to the same pattern. Developers on high-AI-adoption teams complete more tasks and merge more pull requests, but PR review time rises sharply and the system bottleneck moves downstream to human approval. Individual output goes up. System-level delivery often does not.",[12,2638,2639],{},"This is not just a tooling problem. It is a measurement problem.",[12,2641,2642,2643,2088,2645,611],{},"If your organization wants a practical model for measuring AI-assisted development directly, start with ",[514,2644,610],{"href":609},[514,2646,2091],{"href":1508},[613,2648,616],{"id":615},[70,2650,2651,2657,2663,2669,2675,2681,2687,2693,2699,2703,2709],{},[73,2652,2653],{},[514,2654,2656],{"href":2655},"#why-ai-breaks-traditional-metrics","Why AI Breaks Traditional Metrics",[73,2658,2659],{},[514,2660,2662],{"href":2661},"#the-four-stage-ai-adoption-timeline","The Four-Stage AI Adoption Timeline",[73,2664,2665],{},[514,2666,2668],{"href":2667},"#dora-metrics-still-essential-but-not-enough","DORA Metrics: Still Essential, But Not Enough",[73,2670,2671],{},[514,2672,2674],{"href":2673},"#space-framework-the-human-layer","SPACE Framework: The Human Layer",[73,2676,2677],{},[514,2678,2680],{"href":2679},"#devex-and-dx-core-4","DevEx and DX Core 4",[73,2682,2683],{},[514,2684,2686],{"href":2685},"#the-five-ai-specific-metrics-every-team-needs","The Five AI-Specific Metrics Every Team Needs",[73,2688,2689],{},[514,2690,2692],{"href":2691},"#building-your-ai-era-dashboard","Building Your AI-Era Dashboard",[73,2694,2695],{},[514,2696,2698],{"href":2697},"#the-40-20-40-rule","The 40-20-40 Rule",[73,2700,2701],{},[514,2702,1977],{"href":1976},[73,2704,2705],{},[514,2706,2708],{"href":2707},"#common-measurement-mistakes","Common Measurement Mistakes",[73,2710,2711],{},[514,2712,684],{"href":683},[613,2714,2656],{"id":2715},"why-ai-breaks-traditional-metrics",[12,2717,2718],{},"Think of software delivery as a factory. The total output of the factory is not determined by the fastest station, but by the slowest one.",[12,2720,2721],{},"For years, coding was the main constraint. AI changed that. Code generation accelerated, and the constraint shifted to code review, integration, testing, security scanning, and deployment approval.",[12,2723,2724],{},"If you speed up one machine on an assembly line without fixing the others, you do not get a faster factory. You get a pile-up.",[12,2726,2727],{},"That is why traditional output metrics are now risky:",[70,2729,2730,2736,2742,2748],{},[73,2731,2732,2735],{},[739,2733,2734],{},"Lines of code"," rewards verbosity instead of clarity",[73,2737,2738,2741],{},[739,2739,2740],{},"Commit count"," encourages activity instead of meaningful change",[73,2743,2744,2747],{},[739,2745,2746],{},"PR volume"," can rise even while delivery slows down",[73,2749,2750,2753],{},[739,2751,2752],{},"Story points velocity"," is easy to game and hard to compare",[12,2755,2756],{},"In the AI era, these metrics are easier than ever to inflate and harder than ever to trust.",[12,2758,2759],{},"The old job was writing, reviewing, and deploying code. The new job increasingly includes orchestrating AI tools, steering multiple parallel workstreams, reviewing generated output, and making the judgment calls AI still cannot make. Your metrics need to reflect that shift.",[613,2761,2662],{"id":2762},"the-four-stage-ai-adoption-timeline",[12,2764,2765],{},"One of the most common patterns in AI-augmented engineering teams is a four-stage adoption curve.",[52,2767,2769],{"id":2768},"_1-the-enthusiasm-phase","1. The Enthusiasm Phase",[12,2771,2772,2773,611],{},"In the first few weeks, developer sentiment is high. PR counts rise. Individuals report feeling faster. This is the phase where many leaders conclude AI is already delivering ",[514,2774,2775],{"href":1545},"ROI",[52,2777,2779],{"id":2778},"_2-the-review-queue-crisis","2. The Review Queue Crisis",[12,2781,2782],{},"By month two, senior engineers are spending far more time reviewing AI-generated pull requests. Review queues back up. Merge times slow. What looked like a productivity win starts to create downstream pressure.",[52,2784,2786],{"id":2785},"_3-the-quality-debt-phase","3. The Quality Debt Phase",[12,2788,2789],{},"By month three, quality issues begin to emerge. Code may pass CI, yet fail in edge cases, introduce churn, or increase rework. Delivery looks fast on the surface but becomes expensive in maintenance and review load.",[52,2791,2793],{"id":2792},"_4-the-delivery-paradox","4. The Delivery Paradox",[12,2795,2796],{},"By month four, teams often discover that lead time is not improving the way they expected. Work is stuck in review, rework, and incident response. This is where disciplined measurement becomes essential.",[12,2798,2799],{},"The most common leadership mistake is judging AI in phase one using only phase-one signals.",[613,2801,2668],{"id":2802},"dora-metrics-still-essential-but-not-enough",[12,2804,2805,2807],{},[514,2806,848],{"href":847}," remain one of the strongest baselines for engineering performance.",[12,2809,2810],{},"They still matter:",[70,2812,2813,2817,2821,2825],{},[73,2814,2815],{},[739,2816,825],{},[73,2818,2819],{},[739,2820,835],{},[73,2822,2823],{},[739,2824,859],{},[73,2826,2827],{},[739,2828,2829],{},"Mean Time to Restore",[12,2831,2832],{},"But in the AI era, DORA alone is not enough.",[12,2834,2835],{},"AI can increase code output without improving delivery flow. That means leaders need to read DORA with more context:",[70,2837,2838,2841,2844,2847,2850],{},[73,2839,2840],{},"review pressure",[73,2842,2843],{},"AI-assisted PR volume",[73,2845,2846],{},"code quality and rework",[73,2848,2849],{},"incident and failure patterns",[73,2851,2852],{},"team-level ownership and workload",[12,2854,2855],{},"If PR volume is up but lead time is flat, the bottleneck has moved. If deployment frequency rises while change failure rate also rises, quality gates are not keeping up. DORA still tells the truth, but only when paired with the right surrounding signals.",[12,2857,2858,2859,247,2861,2863],{},"If you want a more comparative lens, see ",[514,2860,820],{"href":819},[514,2862,910],{"href":909}," as complementary ways to diagnose what DORA is not telling you directly.",[613,2865,2674],{"id":2866},"space-framework-the-human-layer",[12,2868,2869,2870,2875],{},"DORA tells you how the delivery system performs. ",[514,2871,2874],{"href":2872,"rel":2873},"https:\u002F\u002Fqueue.acm.org\u002Fdetail.cfm?id=3454124",[518],"SPACE"," helps explain what the team is experiencing while that system runs.",[12,2877,2878],{},"SPACE includes:",[70,2880,2881,2884,2887,2890,2893],{},[73,2882,2883],{},"Satisfaction and well-being",[73,2885,2886],{},"Performance",[73,2888,2889],{},"Activity",[73,2891,2892],{},"Communication and collaboration",[73,2894,2895],{},"Efficiency and flow",[12,2897,2898],{},"This matters because AI can increase visible activity while damaging deeper team health. A team may merge more PRs yet feel less confident, less focused, and more overloaded.",[12,2900,2901],{},"That is why AI-era measurement needs both:",[70,2903,2904,2907],{},[73,2905,2906],{},"delivery metrics for the system",[73,2908,2909],{},"experience metrics for the people inside the system",[613,2911,2680],{"id":2912},"devex-and-dx-core-4",[12,2914,2915],{},"Developer Experience and DX Core 4 extend the same idea further.",[12,2917,2918],{},"They help teams measure:",[70,2920,2921,2923,2926,2929],{},[73,2922,2196],{},[73,2924,2925],{},"feedback loop quality",[73,2927,2928],{},"flow state disruption",[73,2930,2931],{},"friction across the developer journey",[12,2933,2934],{},"This is especially important in AI-assisted environments. AI can save time at the moment of generation while increasing cognitive overhead later through larger reviews, unfamiliar patterns, or harder-to-maintain code.",[12,2936,2937],{},"The practical lesson is simple: if AI makes output easier but ownership, review quality, and confidence worse, the organization is not actually improving.",[613,2939,2686],{"id":2940},"the-five-ai-specific-metrics-every-team-needs",[12,2942,2943],{},"Standard frameworks were not built for a world where AI writes a large share of code. Teams now need an explicit AI measurement layer.",[52,2945,2946],{"id":2317},"1. AI Code Share",[12,2948,2949],{},"How much merged code was AI-assisted or AI-generated?",[12,2951,2952],{},"This becomes the base layer for segmenting every other metric.",[52,2954,2955],{"id":2327},"2. AI vs. Human PR Cycle Time",[12,2957,2958],{},"Compare cycle time between AI-assisted and human-authored pull requests.",[12,2960,2961],{},"If AI-generated PRs are slower to review, you have found a real bottleneck.",[52,2963,2964],{"id":2334},"3. AI Code Churn Rate",[12,2966,2967],{},"How much AI-generated code is rewritten or deleted within 30 days?",[12,2969,2970],{},"High churn is often a leading indicator of quality debt.",[52,2972,2974],{"id":2973},"_4-ai-suggestion-acceptance-rate","4. AI Suggestion Acceptance Rate",[12,2976,2977],{},"This shows whether developers still trust the tool and whether the suggestions remain relevant over time.",[12,2979,2980],{},"The trend matters more than the raw number.",[52,2982,2983],{"id":2351},"5. PR Review Load per Senior Engineer",[12,2985,2986],{},"This is one of the most important AI-era metrics.",[12,2988,2989],{},"If output rises but review burden concentrates on a few senior engineers, the organization may be moving toward burnout, slower approvals, and lower review quality.",[12,2991,2992,2993,2995,2996,23,2998,27,3000,611],{},"If your team wants a more productized way to track these signals, explore ",[514,2994,610],{"href":609}," and the dedicated pages for ",[514,2997,2362],{"href":2361},[514,2999,2366],{"href":2365},[514,3001,2370],{"href":2369},[613,3003,2692],{"id":3004},"building-your-ai-era-dashboard",[12,3006,3007],{},"The most useful engineering dashboard in 2026 is layered.",[52,3009,3011],{"id":3010},"tier-1-weekly-system-health","Tier 1: Weekly System Health",[12,3013,3014],{},"Use leading indicators to catch problems early:",[70,3016,3017,3020,3023,3025,3028],{},[73,3018,3019],{},"PR cycle time segmented by AI-assisted vs. human-authored work",[73,3021,3022],{},"review load per senior engineer",[73,3024,2417],{},[73,3026,3027],{},"main branch build success rate",[73,3029,3030],{},"work in progress",[52,3032,3034],{"id":3033},"tier-2-monthly-delivery-performance","Tier 2: Monthly Delivery Performance",[12,3036,3037],{},"Use DORA outcomes to evaluate delivery over complete cycles:",[70,3039,3040,3043,3046,3049,3052],{},[73,3041,3042],{},"deployment frequency",[73,3044,3045],{},"lead time for changes",[73,3047,3048],{},"change failure rate",[73,3050,3051],{},"mean time to restore",[73,3053,3054],{},"post-release defect rate segmented by AI involvement",[52,3056,3058],{"id":3057},"tier-3-quarterly-team-and-business-health","Tier 3: Quarterly Team and Business Health",[12,3060,3061],{},"Translate engineering performance into leadership language:",[70,3063,3064,3067,3070,3072,3075],{},[73,3065,3066],{},"developer satisfaction",[73,3068,3069],{},"engineering eNPS",[73,3071,2226],{},[73,3073,3074],{},"revenue or value impact per engineer",[73,3076,3077,3079],{},[514,3078,2449],{"href":1545}," against measurable delivery outcomes",[12,3081,3082,3083,23,3086,27,3089,3092],{},"In practice, the strongest dashboards combine ",[514,3084,3085],{"href":847},"DORA",[514,3087,3088],{"href":609},"AI impact",[514,3090,3091],{"href":819},"benchmarking"," in one shared operating model.",[613,3094,2698],{"id":3095},"the-40-20-40-rule",[12,3097,3098,3099,3102],{},"One of the most useful diagnostic ratios for sustainable engineering is the ",[739,3100,3101],{},"40-20-40"," rule:",[70,3104,3105,3108,3111],{},[73,3106,3107],{},"40% new feature work",[73,3109,3110],{},"20% rework",[73,3112,3113],{},"40% maintenance and operational work",[12,3115,3116],{},"This matters more in the AI era because AI accelerates all three buckets at once.",[12,3118,3119],{},"It can increase feature output, but it can also increase rework and maintenance if quality controls are weak. If new feature work rises while change failure rate also rises, the team may be generating debt faster than the system can absorb it.",[12,3121,3122],{},"Track this ratio quarterly. It can reveal unhealthy delivery patterns long before they become obvious in top-line output charts.",[613,3124,1977],{"id":2455},[12,3126,3127],{},"Engineering metrics matter most when they can be translated into business language.",[12,3129,3130],{},"Two examples:",[52,3132,835],{"id":834},[12,3134,3135],{},"If lead time drops from three weeks to one week, features reach users faster. That means earlier feedback, earlier revenue realization, and faster competitive response.",[52,3137,859],{"id":858},[12,3139,3140],{},"If your change failure rate drops from 10% to 5% across a large deployment volume, the incident cost savings can be substantial. This creates a direct line from engineering quality to business impact.",[12,3142,3143],{},"In the AI era, you also need an AI line item:",[70,3145,3146,3149,3152,3155],{},[73,3147,3148],{},"cost of AI tools",[73,3150,3151],{},"measurable effect on lead time",[73,3153,3154],{},"measurable effect on quality and failure rate",[73,3156,3157],{},"measurable effect on team sustainability",[12,3159,3160,3161,611],{},"That is the basis of real ",[514,3162,2449],{"href":1545},[613,3164,2708],{"id":3165},"common-measurement-mistakes",[52,3167,3169],{"id":3168},"_1-measuring-ai-at-the-tool-level-only","1. Measuring AI at the Tool Level Only",[12,3171,3172],{},"Tool dashboards show usage. They do not show whether delivery actually improved.",[52,3174,3176],{"id":3175},"_2-drawing-conclusions-too-early","2. Drawing Conclusions Too Early",[12,3178,3179],{},"The first 4-8 weeks of adoption are noisy. Short-term enthusiasm is not the same as system-level improvement.",[52,3181,3183],{"id":3182},"_3-overweighting-individual-metrics","3. Overweighting Individual Metrics",[12,3185,3186],{},"The shift is from individual productivity to system efficiency. Outcome metrics matter more than activity metrics.",[52,3188,3190],{"id":3189},"_4-skipping-the-pre-ai-baseline","4. Skipping the Pre-AI Baseline",[12,3192,3193],{},"Without baseline measurements, attribution becomes guesswork.",[52,3195,3197],{"id":3196},"_5-treating-adoption-as-success","5. Treating Adoption as Success",[12,3199,3200],{},"High adoption without better delivery, quality, or developer experience is not success.",[613,3202,684],{"id":1121},[52,3204,3206],{"id":3205},"what-are-the-most-important-engineering-metrics-in-the-ai-era","What are the most important engineering metrics in the AI era?",[12,3208,3209],{},"The most important set combines delivery flow metrics, AI-specific signals, and developer experience metrics. That typically means DORA, AI code share, PR cycle time segmented by AI involvement, code churn, review load, and team experience signals such as satisfaction or cognitive load.",[52,3211,3213],{"id":3212},"why-do-traditional-engineering-kpis-fail-when-teams-adopt-ai","Why do traditional engineering KPIs fail when teams adopt AI?",[12,3215,3216],{},"Because they were designed to approximate human effort. AI breaks that assumption by inflating output metrics like code volume and PR count without guaranteeing faster or better delivery.",[52,3218,3220],{"id":3219},"what-is-the-ai-productivity-paradox","What is the AI productivity paradox?",[12,3222,3223],{},"It is the gap between individual output gains and organizational delivery outcomes. AI can make individuals faster while making the system slower if bottlenecks in review, testing, or integration are left untouched.",[52,3225,3227],{"id":3226},"how-should-dora-space-and-devex-work-together","How should DORA, SPACE, and DevEx work together?",[12,3229,3230],{},"Use DORA for system delivery performance, SPACE for team health, and DevEx for friction diagnosis. Together they help teams avoid optimizing one dimension at the expense of another.",[52,3232,3234],{"id":3233},"why-does-the-40-20-40-rule-matter-in-the-ai-era","Why does the 40-20-40 rule matter in the AI era?",[12,3236,3237],{},"Because AI can increase feature velocity and rework at the same time. Tracking the balance between new work, rework, and maintenance helps leaders spot unsustainable acceleration early.",[613,3239,1159],{"id":477},[12,3241,3242],{},"Engineering metrics in the AI era require a shift in philosophy: from counting what developers produce to measuring how value flows through the full delivery system.",[12,3244,3245],{},"DORA gives you the delivery baseline. SPACE gives you the human signal. DevEx gives you friction diagnostics. AI-specific metrics give you attribution.",[12,3247,3248],{},"Together, these layers create a more honest measurement model for 2026.",[12,3250,3251],{},"The strongest teams will not be the ones with the highest PR volume or the most exciting AI adoption dashboards. They will be the ones that establish baselines, pair speed with quality guardrails, monitor review bottlenecks, and translate engineering performance into decisions leadership can trust.",[12,3253,3254],{},"If you want to operationalize this in practice, start with:",[70,3256,3257,3262,3266,3270],{},[73,3258,3259],{},[514,3260,3261],{"href":847},"DORA Metrics",[73,3263,3264],{},[514,3265,610],{"href":609},[73,3267,3268],{},[514,3269,820],{"href":819},[73,3271,3272],{},[514,3273,2091],{"href":1508},{"title":526,"searchDepth":527,"depth":527,"links":3275},[3276,3277,3278,3284,3285,3286,3287,3294,3299,3300,3304,3311,3318],{"id":615,"depth":527,"text":616},{"id":2715,"depth":527,"text":2656},{"id":2762,"depth":527,"text":2662,"children":3279},[3280,3281,3282,3283],{"id":2768,"depth":530,"text":2769},{"id":2778,"depth":530,"text":2779},{"id":2785,"depth":530,"text":2786},{"id":2792,"depth":530,"text":2793},{"id":2802,"depth":527,"text":2668},{"id":2866,"depth":527,"text":2674},{"id":2912,"depth":527,"text":2680},{"id":2940,"depth":527,"text":2686,"children":3288},[3289,3290,3291,3292,3293],{"id":2317,"depth":530,"text":2946},{"id":2327,"depth":530,"text":2955},{"id":2334,"depth":530,"text":2964},{"id":2973,"depth":530,"text":2974},{"id":2351,"depth":530,"text":2983},{"id":3004,"depth":527,"text":2692,"children":3295},[3296,3297,3298],{"id":3010,"depth":530,"text":3011},{"id":3033,"depth":530,"text":3034},{"id":3057,"depth":530,"text":3058},{"id":3095,"depth":527,"text":2698},{"id":2455,"depth":527,"text":1977,"children":3301},[3302,3303],{"id":834,"depth":530,"text":835},{"id":858,"depth":530,"text":859},{"id":3165,"depth":527,"text":2708,"children":3305},[3306,3307,3308,3309,3310],{"id":3168,"depth":530,"text":3169},{"id":3175,"depth":530,"text":3176},{"id":3182,"depth":530,"text":3183},{"id":3189,"depth":530,"text":3190},{"id":3196,"depth":530,"text":3197},{"id":1121,"depth":527,"text":684,"children":3312},[3313,3314,3315,3316,3317],{"id":3205,"depth":530,"text":3206},{"id":3212,"depth":530,"text":3213},{"id":3219,"depth":530,"text":3220},{"id":3226,"depth":530,"text":3227},{"id":3233,"depth":530,"text":3234},{"id":477,"depth":527,"text":1159},[1898,540,1231],"2026-03-25","Learn which engineering metrics matter in the AI era and how DORA, SPACE, DevEx, and flow signals work together.",{"faq":3323},[3324,3326,3329,3332,3335],{"question":3206,"answer":3325},"The most important metrics combine delivery flow, quality, developer experience, and AI-specific indicators. Teams need DORA metrics, human-centered signals such as DevEx, and AI adoption measures that show whether faster code generation is actually improving system-level outcomes.",{"question":3327,"answer":3328},"Why are traditional output metrics weaker in AI-assisted development?","Traditional output metrics such as commit count, PR volume, and lines of code are easier to inflate in AI-assisted environments. They can rise while review queues, integration pressure, and quality risk also rise, which is why leaders need system-level metrics instead of activity-only reporting.",{"question":3330,"answer":3331},"Are DORA metrics still useful in AI-assisted software delivery?","Yes. DORA metrics still matter because they describe delivery performance, but they are no longer enough on their own. Engineering teams also need workflow, quality, and AI attribution signals to understand whether AI is improving the full delivery system.",{"question":3333,"answer":3334},"How should engineering leaders measure AI coding assistant impact?","Leaders should connect AI coding assistant usage to review speed, cycle time, quality signals, rework, and delivery outcomes rather than looking at usage alone. That is the difference between adoption reporting and engineering impact measurement.",{"question":3336,"answer":3337},"What should teams track beyond DORA in 2026?","Beyond DORA, strong teams often track developer experience, cognitive load, AI review pressure, rework, workflow bottlenecks, and code quality guardrails. The goal is to build a measurement system that explains both outcomes and the conditions producing them.",{"title":2625,"description":3321},"\u002Fassets\u002Fblog\u002Foobeya-ai-impact-framework-details.png","A practical guide to engineering metrics in the AI era, from DORA and SPACE to AI-specific indicators, DevEx, and sustainable delivery.","blog\u002Fengineering-metrics-in-the-ai-era",[1876,2621,1232,3343,2620],"space-framework","F1xiqY8qizkCtM7PnKRV-xzHOjmE8l5omq4gMAm5J18",{"id":3346,"title":3347,"author":1265,"avatar":1266,"body":3348,"categories":4129,"createAt":542,"date":4131,"description":4132,"extension":545,"meta":4133,"navigation":547,"path":1508,"position":4134,"seo":4135,"spotImage":4136,"spotText":4137,"stem":4138,"tags":4139,"__hash__":4141},"blog\u002Fblog\u002Fhow-to-measure-ai-assisted-software-development.md","How to Measure AI-Assisted Software Development: A Complete Guide for Engineering Leaders",{"type":9,"value":3349,"toc":4085},[3350,3353,3359,3362,3365,3367,3429,3432,3435,3438,3445,3459,3462,3465,3468,3471,3474,3477,3481,3484,3488,3491,3494,3508,3511,3514,3517,3537,3540,3543,3552,3555,3558,3561,3577,3580,3584,3587,3598,3601,3604,3609,3612,3615,3624,3627,3629,3632,3635,3637,3640,3643,3645,3648,3651,3653,3656,3659,3662,3673,3676,3679,3687,3690,3702,3705,3720,3723,3726,3738,3741,3744,3747,3751,3754,3759,3762,3772,3775,3779,3781,3786,3788,3800,3803,3807,3809,3814,3816,3833,3836,3839,3850,3858,3861,3864,3867,3870,3878,3881,3884,3904,3907,3910,3914,3917,3921,3924,3928,3931,3935,3938,3942,3945,3948,3951,3954,3975,3978,3981,3995,3998,4003,4006,4009,4013,4016,4020,4023,4027,4030,4034,4037,4044,4047,4049,4052,4055,4069,4077],[12,3351,3352],{},"AI coding assistants have moved from experimental novelty to everyday infrastructure. By 2026, most engineering organizations are no longer asking whether AI tools matter. They are asking a harder question:",[3354,3355,3356],"blockquote",{},[12,3357,3358],{},"How do we measure the real impact of AI-assisted software development without falling into vanity metrics?",[12,3360,3361],{},"That question is more important than it looks. In a world where AI can generate entire modules, suggest pull requests, and accelerate repetitive engineering work, traditional signals such as lines of code, commit counts, and raw pull request volume stop being reliable indicators of value. In many cases, they become actively misleading.",[12,3363,3364],{},"This guide explains how engineering leaders can build a practical measurement approach for AI-assisted development by combining delivery performance, quality guardrails, adoption signals, and developer experience.",[613,3366,616],{"id":615},[70,3368,3369,3375,3381,3387,3393,3399,3405,3411,3417,3423],{},[73,3370,3371],{},[514,3372,3374],{"href":3373},"#the-measurement-paradox-why-more-code-does-not-mean-more-value","The Measurement Paradox: Why More Code Does Not Mean More Value",[73,3376,3377],{},[514,3378,3380],{"href":3379},"#why-traditional-metrics-fail-in-the-ai-era","Why Traditional Metrics Fail in the AI Era",[73,3382,3383],{},[514,3384,3386],{"href":3385},"#the-metrics-that-actually-matter","The Metrics That Actually Matter",[73,3388,3389],{},[514,3390,3392],{"href":3391},"#dora-measuring-ais-impact-on-delivery-performance","DORA: Measuring AI's Impact on Delivery Performance",[73,3394,3395],{},[514,3396,3398],{"href":3397},"#space-the-human-dimension-of-ai-productivity","SPACE: The Human Dimension of AI Productivity",[73,3400,3401],{},[514,3402,3404],{"href":3403},"#a-3-layer-ai-measurement-framework","A 3-Layer AI Measurement Framework",[73,3406,3407],{},[514,3408,3410],{"href":3409},"#establishing-a-baseline-before-you-draw-conclusions","Establishing a Baseline Before You Draw Conclusions",[73,3412,3413],{},[514,3414,3416],{"href":3415},"#common-measurement-pitfalls-to-avoid","Common Measurement Pitfalls to Avoid",[73,3418,3419],{},[514,3420,3422],{"href":3421},"#real-world-benchmarks-and-expected-results","Real-World Benchmarks and Expected Results",[73,3424,3425],{},[514,3426,3428],{"href":3427},"#faq","FAQ",[613,3430,3374],{"id":3431},"the-measurement-paradox-why-more-code-does-not-mean-more-value",[12,3433,3434],{},"One of the most common mistakes in AI adoption is assuming that more output automatically means better outcomes.",[12,3436,3437],{},"AI-assisted developers can produce more code, open more pull requests, and push more commits in the same amount of time. On the surface, that looks like a clear productivity gain. But engineering value is not created by code volume alone. It is created when work moves through the entire system and results in stable releases, useful features, and fewer operational problems.",[12,3439,3440,3441,3444],{},"This creates what many teams now experience as the ",[16,3442,3443],{},"individual velocity vs. systemic value gap",":",[70,3446,3447,3450,3453,3456],{},[73,3448,3449],{},"individual developers can move faster with AI",[73,3451,3452],{},"review queues can get heavier",[73,3454,3455],{},"quality checks can become bottlenecks",[73,3457,3458],{},"deployment processes can absorb the extra output poorly",[12,3460,3461],{},"The result is familiar: more activity, but not necessarily faster or better delivery.",[12,3463,3464],{},"That is why AI measurement must begin at the system level, not at the activity level.",[613,3466,3380],{"id":3467},"why-traditional-metrics-fail-in-the-ai-era",[12,3469,3470],{},"Traditional productivity proxies were already imperfect before generative AI. After AI adoption, they become even less trustworthy.",[52,3472,2734],{"id":3473},"lines-of-code",[12,3475,3476],{},"Lines of code are now a pure vanity metric. AI can generate large code blocks in seconds. A developer who produces a 1,000-line AI-assisted pull request may appear productive, while a reviewer who spends hours reducing it to 250 maintainable lines may appear slow. The metric reverses reality.",[52,3478,3480],{"id":3479},"commit-frequency-and-pull-request-volume","Commit frequency and pull request volume",[12,3482,3483],{},"AI can increase the number of commits and pull requests without improving the value delivered to users. Counting those artifacts after AI adoption is often little more than tracking mechanical activity.",[52,3485,3487],{"id":3486},"story-points-and-sprint-velocity","Story points and sprint velocity",[12,3489,3490],{},"Story points were designed for estimation, not performance measurement. Using them to judge AI-assisted productivity creates incentives to inflate estimates and distorts the signal you are trying to understand.",[12,3492,3493],{},"The core distinction to remember is:",[70,3495,3496,3502],{},[73,3497,3498,3501],{},[16,3499,3500],{},"Outputs"," are artifacts such as code written, PRs merged, and tickets closed.",[73,3503,3504,3507],{},[16,3505,3506],{},"Outcomes"," are results such as features delivered, stability maintained, rework reduced, and time saved across the system.",[12,3509,3510],{},"AI increases outputs easily. The real question is whether it improves outcomes.",[613,3512,3386],{"id":3513},"the-metrics-that-actually-matter",[12,3515,3516],{},"In practice, the most useful AI measurement models combine three metric families:",[70,3518,3519,3525,3531],{},[73,3520,3521,3524],{},[16,3522,3523],{},"Delivery metrics",": Are we shipping faster?",[73,3526,3527,3530],{},[16,3528,3529],{},"Quality metrics",": Are we shipping better?",[73,3532,3533,3536],{},[16,3534,3535],{},"Adoption metrics",": Is AI actually being used and trusted?",[52,3538,3523],{"id":3539},"delivery-metrics",[12,3541,3542],{},"Useful delivery metrics include:",[70,3544,3545,3547,3549],{},[73,3546,3045],{},[73,3548,3042],{},[73,3550,3551],{},"cycle time",[12,3553,3554],{},"These help you understand whether AI-assisted coding is accelerating the end-to-end flow of delivery, not just the authoring step.",[52,3556,3529],{"id":3557},"quality-metrics",[12,3559,3560],{},"Useful quality metrics include:",[70,3562,3563,3565,3568,3571,3574],{},[73,3564,3048],{},[73,3566,3567],{},"mean time to recovery",[73,3569,3570],{},"post-release defect rate",[73,3572,3573],{},"code churn on AI-assisted changes",[73,3575,3576],{},"security findings per release",[12,3578,3579],{},"These metrics tell you whether faster code generation is introducing hidden costs.",[52,3581,3583],{"id":3582},"adoption-and-ai-specific-metrics","Adoption and AI-specific metrics",[12,3585,3586],{},"Useful AI-specific metrics include:",[70,3588,3589,3592,3595],{},[73,3590,3591],{},"AI suggestion acceptance rate",[73,3593,3594],{},"AI-assisted commit ratio",[73,3596,3597],{},"active AI users as a share of total developers",[12,3599,3600],{},"These are useful leading indicators, but they should never be treated as success metrics by themselves.",[12,3602,3603],{},"One practical rule matters more than any other:",[3354,3605,3606],{},[12,3607,3608],{},"Never track a speed metric without pairing it with a quality metric.",[12,3610,3611],{},"If deployment frequency improves while change failure rate gets worse, your system has not improved. It has simply shifted debt.",[613,3613,3392],{"id":3614},"dora-measuring-ais-impact-on-delivery-performance",[12,3616,3617,3618,3623],{},"The ",[514,3619,3622],{"href":3620,"rel":3621},"https:\u002F\u002Foobeya.io\u002Fdora-metrics-four-key",[518],"DORA framework"," remains one of the best ways to evaluate whether AI is improving software delivery as a system.",[12,3625,3626],{},"The four key DORA metrics still apply directly in an AI-assisted environment:",[52,3628,825],{"id":824},[12,3630,3631],{},"How often your team successfully releases to production.",[12,3633,3634],{},"AI can increase deployment frequency by reducing time spent on repetitive implementation work. But if pull request volume rises faster than review capacity, deployment frequency may stagnate or even worsen.",[52,3636,835],{"id":834},[12,3638,3639],{},"How long it takes for a code change to move from commit to production.",[12,3641,3642],{},"This is one of the clearest ways to measure whether AI is creating systemic improvement instead of only local speed gains.",[52,3644,859],{"id":858},[12,3646,3647],{},"The percentage of changes that cause incidents, rollbacks, or production failures.",[12,3649,3650],{},"This is the quality guardrail for AI-assisted development. If AI accelerates throughput but raises failure rates, you are not getting healthy leverage from it.",[52,3652,900],{"id":899},[12,3654,3655],{},"How quickly teams restore service after a failure.",[12,3657,3658],{},"MTTR helps contextualize whether quality regressions introduced by AI are increasing operational cost.",[12,3660,3661],{},"The best way to use DORA in this context is simple:",[1520,3663,3664,3667,3670],{},[73,3665,3666],{},"Establish a baseline before broad AI adoption.",[73,3668,3669],{},"Track all four metrics continuously after rollout.",[73,3671,3672],{},"Compare the delta across at least one full quarter.",[12,3674,3675],{},"That tells you what AI is doing to your delivery system in reality, not in vendor marketing.",[613,3677,3398],{"id":3678},"space-the-human-dimension-of-ai-productivity",[12,3680,3681,3682,3686],{},"DORA measures system performance. The ",[514,3683,3685],{"href":2872,"rel":3684},[518],"SPACE framework"," adds the human side of productivity.",[12,3688,3689],{},"SPACE looks at five dimensions:",[70,3691,3692,3694,3696,3698,3700],{},[73,3693,2883],{},[73,3695,2886],{},[73,3697,2889],{},[73,3699,2892],{},[73,3701,2895],{},[12,3703,3704],{},"This matters because AI adoption changes more than delivery speed. It changes:",[70,3706,3707,3710,3712,3715,3718],{},[73,3708,3709],{},"developer trust in generated code",[73,3711,2196],{},[73,3713,3714],{},"review burden on senior engineers",[73,3716,3717],{},"collaboration dynamics",[73,3719,2395],{},[12,3721,3722],{},"For example, developers may feel more productive while objective delivery data says otherwise. Or they may report frustration long before throughput metrics show visible damage.",[12,3724,3725],{},"That is why AI measurement should always include a lightweight developer experience layer, such as a monthly pulse survey covering:",[70,3727,3728,3730,3732,3734,3736],{},[73,3729,2395],{},[73,3731,2402],{},[73,3733,2202],{},[73,3735,2405],{},[73,3737,2196],{},[12,3739,3740],{},"Without that layer, leaders risk overestimating success or missing adoption problems until they become systemic.",[613,3742,3404],{"id":3743},"a-3-layer-ai-measurement-framework",[12,3745,3746],{},"The most practical measurement model for engineering leaders is a three-layer framework.",[52,3748,3750],{"id":3749},"layer-1-delivery-outcomes","Layer 1: Delivery Outcomes",[12,3752,3753],{},"This layer answers:",[3354,3755,3756],{},[12,3757,3758],{},"Did AI actually improve delivery performance?",[12,3760,3761],{},"Track:",[70,3763,3764,3766,3768,3770],{},[73,3765,3042],{},[73,3767,3045],{},[73,3769,3048],{},[73,3771,3567],{},[12,3773,3774],{},"This layer is objective, system-oriented, and resistant to gaming. It is also lagging, which means you need enough time to see the effect.",[52,3776,3778],{"id":3777},"layer-2-ai-usage-signals","Layer 2: AI Usage Signals",[12,3780,3753],{},[3354,3782,3783],{},[12,3784,3785],{},"Is AI being used, and is it being used well?",[12,3787,3761],{},[70,3789,3790,3792,3794,3797],{},[73,3791,3591],{},[73,3793,3594],{},[73,3795,3796],{},"daily or weekly active AI users",[73,3798,3799],{},"license utilization",[12,3801,3802],{},"This layer is useful for understanding adoption health, tool fit, and enablement gaps. It tells you what is happening before delivery metrics fully respond.",[52,3804,3806],{"id":3805},"layer-3-developer-experience","Layer 3: Developer Experience",[12,3808,3753],{},[3354,3810,3811],{},[12,3812,3813],{},"What is the real story behind the numbers?",[12,3815,3761],{},[70,3817,3818,3821,3824,3826,3828,3830],{},[73,3819,3820],{},"monthly developer pulse surveys",[73,3822,3823],{},"trust in AI-generated code",[73,3825,2395],{},[73,3827,2205],{},[73,3829,2196],{},[73,3831,3832],{},"friction in day-to-day workflow",[12,3834,3835],{},"This layer protects you from the perception-reality gap that often appears in AI adoption. Teams may feel faster but deliver worse outcomes, or feel friction while still creating meaningful gains. You need both signals to interpret the situation correctly.",[12,3837,3838],{},"Together, these three layers give engineering leaders a complete view:",[70,3840,3841,3844,3847],{},[73,3842,3843],{},"what the system is doing",[73,3845,3846],{},"how AI is being used",[73,3848,3849],{},"how developers are experiencing the change",[12,3851,3852,3853,611],{},"If you want a platform-specific view of this model, see Oobeya's ",[514,3854,3857],{"href":3855,"rel":3856},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fai-measurement-framework",[518],"AI measurement framework",[613,3859,3410],{"id":3860},"establishing-a-baseline-before-you-draw-conclusions",[12,3862,3863],{},"One of the most expensive mistakes organizations make is declaring success after AI rollout without a pre-AI baseline.",[12,3865,3866],{},"Before you can measure improvement, you need to know where you started.",[12,3868,3869],{},"The strongest approach is to compare:",[70,3871,3872,3875],{},[73,3873,3874],{},"teams with similar context before and after adoption",[73,3876,3877],{},"or groups with different AI usage intensity over a fixed time period",[12,3879,3880],{},"If formal A\u002FB testing is not possible, the next best option is to track baseline metrics for at least one full quarter before broad rollout, then compare quarterly snapshots after adoption.",[12,3882,3883],{},"A practical timeline:",[70,3885,3886,3892,3898],{},[73,3887,3888,3891],{},[16,3889,3890],{},"Weeks 1-8",": focus on adoption and developer experience signals",[73,3893,3894,3897],{},[16,3895,3896],{},"Months 3-6",": evaluate delivery and quality outcomes",[73,3899,3900,3903],{},[16,3901,3902],{},"After 1-2 quarters",": assess ROI and sustained impact",[12,3905,3906],{},"This matters because AI adoption includes a learning curve. Measuring too early often produces misleading conclusions, usually because teams are still adjusting their workflows.",[613,3908,3416],{"id":3909},"common-measurement-pitfalls-to-avoid",[52,3911,3913],{"id":3912},"_1-celebrating-speed-without-quality-guardrails","1. Celebrating speed without quality guardrails",[12,3915,3916],{},"Faster coding is not a win if it creates more production issues, more churn, or more review debt.",[52,3918,3920],{"id":3919},"_2-measuring-individuals-instead-of-systems","2. Measuring individuals instead of systems",[12,3922,3923],{},"AI can dramatically increase individual output. But if reviewers, QA, or pipelines become bottlenecks, the organization may still be getting slower overall.",[52,3925,3927],{"id":3926},"_3-trusting-self-reports-without-objective-verification","3. Trusting self-reports without objective verification",[12,3929,3930],{},"Developers often overestimate or underestimate the impact of new tools. Pair surveys with delivery data.",[52,3932,3934],{"id":3933},"_4-ignoring-security-and-maintainability-signals","4. Ignoring security and maintainability signals",[12,3936,3937],{},"AI-assisted code should be treated as draft material, not automatically trusted output. Security findings, code smells, and churn rates matter.",[52,3939,3941],{"id":3940},"_5-using-adoption-rate-as-the-main-success-metric","5. Using adoption rate as the main success metric",[12,3943,3944],{},"High adoption with flat delivery performance is not success. Moderate adoption with measurable DORA improvement is more meaningful.",[613,3946,3422],{"id":3947},"real-world-benchmarks-and-expected-results",[12,3949,3950],{},"A realistic measurement strategy should be grounded in what organizations can actually expect.",[12,3952,3953],{},"Across enterprise AI adoption data from 2025-2026, the most practical expectations are:",[70,3955,3956,3962,3968],{},[73,3957,3958,3959],{},"around ",[16,3960,3961],{},"3.6 hours saved per developer per week",[73,3963,3964,3967],{},[16,3965,3966],{},"16% to 41% throughput improvement"," for high-adoption teams with good process maturity",[73,3969,3970,3971,3974],{},"roughly ",[16,3972,3973],{},"$3.70 in value for every $1 invested"," for early adopters",[12,3976,3977],{},"At the same time, engineering leaders should stay skeptical of headline claims.",[12,3979,3980],{},"The best-performing organizations tend to share the same habits:",[70,3982,3983,3986,3989,3992],{},[73,3984,3985],{},"they establish a baseline before rollout",[73,3987,3988],{},"they track DORA and quality metrics together",[73,3990,3991],{},"they treat AI output as something that still needs governance",[73,3993,3994],{},"they review outcomes over quarters, not days",[12,3996,3997],{},"A practical early benchmark for most teams is this:",[3354,3999,4000],{},[12,4001,4002],{},"Within two quarters of full rollout, aim to improve at least two of the four DORA metrics while keeping quality metrics flat or better.",[12,4004,4005],{},"That is a more useful target than any raw adoption dashboard.",[613,4007,3428],{"id":4008},"faq",[52,4010,4012],{"id":4011},"what-is-the-best-metric-to-measure-ai-assisted-software-development-productivity","What is the best metric to measure AI-assisted software development productivity?",[12,4014,4015],{},"There is no single best metric. The most effective approach combines DORA metrics, SPACE dimensions, and AI-specific signals such as suggestion acceptance rate and AI-assisted commit ratio.",[52,4017,4019],{"id":4018},"how-do-dora-metrics-apply-to-ai-assisted-development","How do DORA metrics apply to AI-assisted development?",[12,4021,4022],{},"DORA metrics remain highly relevant. AI can improve deployment frequency and lead time, but it can also increase change failure rate if generated code moves too quickly without sufficient review and governance.",[52,4024,4026],{"id":4025},"how-long-should-teams-wait-before-measuring-ais-impact","How long should teams wait before measuring AI's impact?",[12,4028,4029],{},"Most organizations should allow at least 3 to 6 months before drawing strong conclusions. The first 4 to 8 weeks are usually an adoption and workflow-adjustment period.",[52,4031,4033],{"id":4032},"what-are-the-biggest-mistakes-when-measuring-ai-developer-productivity","What are the biggest mistakes when measuring AI developer productivity?",[12,4035,4036],{},"The biggest mistakes are relying on vanity metrics, measuring only speed, skipping a baseline, drawing conclusions too early, and focusing on individuals instead of team or system outcomes.",[52,4038,4040,4041,4043],{"id":4039},"what-roi-can-engineering-teams-realistically-expect-from-ai-coding-tools","What ",[514,4042,2775],{"href":1545}," can engineering teams realistically expect from AI coding tools?",[12,4045,4046],{},"Realistic expectations from 2025-2026 enterprise data include measurable weekly time savings, throughput improvement for high-adoption teams, and positive ROI when process changes support the tooling.",[613,4048,1159],{"id":477},[12,4050,4051],{},"Measuring AI-assisted software development is not really about finding one magical AI metric. It is about applying measurement discipline to a new category of tooling.",[12,4053,4054],{},"The teams that get the most value from AI are usually not the ones with the highest adoption rates or the biggest pull request counts. They are the ones that:",[70,4056,4057,4060,4063,4066],{},[73,4058,4059],{},"establish baselines before rollout",[73,4061,4062],{},"measure delivery outcomes and quality together",[73,4064,4065],{},"pair AI usage metrics with developer experience signals",[73,4067,4068],{},"give the organization enough time to adapt",[12,4070,4071,4072,4076],{},"If you want to build that kind of measurement system, start with your ",[514,4073,4075],{"href":3620,"rel":4074},[518],"DORA metrics baseline",", add a lightweight monthly developer experience survey, and create visibility into AI usage patterns across the SDLC.",[12,4078,4079,4080,611],{},"If you want help operationalizing that model across Git, PRs, delivery flow, and AI adoption data, ",[514,4081,4084],{"href":4082,"rel":4083},"https:\u002F\u002Foobeya.io\u002Fschedule-a-demo",[518],"schedule a demo with Oobeya",{"title":526,"searchDepth":527,"depth":527,"links":4086},[4087,4088,4089,4094,4099,4105,4106,4111,4112,4119,4120,4128],{"id":615,"depth":527,"text":616},{"id":3431,"depth":527,"text":3374},{"id":3467,"depth":527,"text":3380,"children":4090},[4091,4092,4093],{"id":3473,"depth":530,"text":2734},{"id":3479,"depth":530,"text":3480},{"id":3486,"depth":530,"text":3487},{"id":3513,"depth":527,"text":3386,"children":4095},[4096,4097,4098],{"id":3539,"depth":530,"text":3523},{"id":3557,"depth":530,"text":3529},{"id":3582,"depth":530,"text":3583},{"id":3614,"depth":527,"text":3392,"children":4100},[4101,4102,4103,4104],{"id":824,"depth":530,"text":825},{"id":834,"depth":530,"text":835},{"id":858,"depth":530,"text":859},{"id":899,"depth":530,"text":900},{"id":3678,"depth":527,"text":3398},{"id":3743,"depth":527,"text":3404,"children":4107},[4108,4109,4110],{"id":3749,"depth":530,"text":3750},{"id":3777,"depth":530,"text":3778},{"id":3805,"depth":530,"text":3806},{"id":3860,"depth":527,"text":3410},{"id":3909,"depth":527,"text":3416,"children":4113},[4114,4115,4116,4117,4118],{"id":3912,"depth":530,"text":3913},{"id":3919,"depth":530,"text":3920},{"id":3926,"depth":530,"text":3927},{"id":3933,"depth":530,"text":3934},{"id":3940,"depth":530,"text":3941},{"id":3947,"depth":527,"text":3422},{"id":4008,"depth":527,"text":3428,"children":4121},[4122,4123,4124,4125,4126],{"id":4011,"depth":530,"text":4012},{"id":4018,"depth":530,"text":4019},{"id":4025,"depth":530,"text":4026},{"id":4032,"depth":530,"text":4033},{"id":4039,"depth":530,"text":4127},"What ROI can engineering teams realistically expect from AI coding tools?",{"id":477,"depth":527,"text":1159},[1898,4130,1231],"ai-coding-assistants","2026-03-24","Learn how to measure AI-assisted software development with DORA, SPACE, quality guardrails, and realistic ROI benchmarks.",{},"home",{"title":3347,"description":4132},"\u002Fassets\u002Fblog\u002Foobeya-ai-impact-framework.png","A practical guide to measuring AI-assisted development with DORA, SPACE, quality guardrails, adoption signals, and realistic ROI expectations.","blog\u002Fhow-to-measure-ai-assisted-software-development",[4140,4130,1231,1232,3343],"measure-ai-impact","y_WoiU8f-POJBJvk_1SJIAU3orXg3wOSq5a2si-9wZU",{"id":4143,"title":4144,"author":6,"avatar":7,"body":4145,"categories":4231,"createAt":542,"date":4233,"description":4234,"extension":545,"meta":4235,"navigation":547,"path":4236,"position":4134,"seo":4237,"spotImage":542,"spotText":542,"stem":4238,"tags":4239,"__hash__":4241},"blog\u002Fblog\u002Foobeya-g2-category-leader-spring-2026.md","Oobeya Recognized Again as a Category Leader in Software Development Analytics Tools",{"type":9,"value":4146,"toc":4227},[4147,4153,4163,4165,4169,4172,4175,4186,4188,4192,4195,4200,4203,4206],[12,4148,4149,4150,611],{},"We are proud to share that ",[16,4151,4152],{},"Oobeya has once again been recognized as a Category Leader in the Software Development Analytics Tools category",[12,4154,4155,4156,4159,4160,611],{},"This Spring 2026 recognition continues Oobeya's run of seasonal ",[16,4157,4158],{},"Leader"," placements in this category since ",[16,4161,4162],{},"Winter 2025",[501,4164],{},[613,4166,4168],{"id":4167},"why-this-matters","Why This Matters",[12,4170,4171],{},"Oobeya is built for engineering organizations that need more than isolated dashboards. We help leaders understand delivery, workflow, quality, and AI-assisted development signals in one operating view.",[12,4173,4174],{},"This recognition reinforces the value of a broader engineering intelligence approach:",[70,4176,4177,4180,4183],{},[73,4178,4179],{},"turning fragmented SDLC data into one leadership-ready view",[73,4181,4182],{},"helping organizations measure delivery, quality, workflow, and AI-assisted development together",[73,4184,4185],{},"giving engineering leaders more clarity without forcing teams to change how they work",[501,4187],{},[613,4189,4191],{"id":4190},"a-recognition-grounded-in-verified-reviews","A Recognition Grounded in Verified Reviews",[12,4193,4194],{},"As G2 explains:",[3354,4196,4197],{},[12,4198,4199],{},"“Earning a Leader position in a G2 Report is highly competitive and rooted in verified customer reviews,” said Godard Abel, co-founder and CEO, G2. “Congratulations to Oobeya for achieving this distinction. Buyers can be confident this ranking reflects the authentic experiences of real users.”",[12,4201,4202],{},"We are grateful to every customer and reviewer who made this possible.",[12,4204,4205],{},"If you want to see why engineering organizations choose Oobeya, we would be glad to show you.",[70,4207,4208,4215,4222],{},[73,4209,4210],{},[514,4211,4214],{"href":4212,"rel":4213},"https:\u002F\u002Foobeya.io\u002Fplatform",[518],"Explore the Platform",[73,4216,4217],{},[514,4218,4221],{"href":4219,"rel":4220},"https:\u002F\u002Foobeya.io\u002Fintegrations",[518],"Browse Integrations",[73,4223,4224],{},[514,4225,519],{"href":4082,"rel":4226},[518],{"title":526,"searchDepth":527,"depth":527,"links":4228},[4229,4230],{"id":4167,"depth":527,"text":4168},{"id":4190,"depth":527,"text":4191},[4232,540,1231],"announcements","2026-03-18","Oobeya has been recognized again as a Category Leader in G2's Software Development Analytics Tools category for Spring 2026.",{},"\u002Fblog\u002Foobeya-g2-category-leader-spring-2026",{"title":4144,"description":4234},"blog\u002Foobeya-g2-category-leader-spring-2026",[4240,4232,552,540,1231],"g2","3qu-ArKFpoxxExwwzkrOeyT2BWSHstqPYgi20mJjAa4",{"id":4243,"title":4244,"author":4245,"avatar":575,"body":4246,"categories":4479,"createAt":542,"date":4481,"description":4482,"extension":545,"meta":4483,"navigation":547,"path":4488,"position":4134,"seo":4489,"spotImage":4490,"spotText":4491,"stem":4492,"tags":4493,"__hash__":4497},"blog\u002Fblog\u002Fsonar-summit-2026-key-takeaways.md","Sonar Summit 2026: Key Takeaways on Agentic Development and Engineering Visibility","Emre Dündar",{"type":9,"value":4247,"toc":4471},[4248,4255,4258,4269,4273,4282,4285,4290,4293,4296,4310,4323,4327,4330,4335,4343,4347,4355,4359,4366,4370,4377,4381,4384,4388,4391,4405,4408,4412,4415,4429,4432,4440,4444,4447,4458,4461,4465,4468],[12,4249,4250,4251,4254],{},"Last week, we had the pleasure of attending ",[16,4252,4253],{},"Sonar Summit 2026"," as a proud sponsor. Huge thanks to the Sonar team for organizing such a strong event and for continuing to build a high-impact ecosystem around code quality and security.",[12,4256,4257],{},"First of all, a big thank you to the entire Sonar team for organizing such a fantastic event and for continuing to build an incredible ecosystem around code quality and security. It was inspiring to see engineering leaders, platform teams, and developers from across the industry come together to discuss how software development is evolving in the age of AI.",[12,4259,4260,4261,4264,4265,4268],{},"At Oobeya, this ecosystem matters deeply to us. We are both a ",[16,4262,4263],{},"Technology Partner"," and a ",[16,4266,4267],{},"Channel Partner"," of Sonar, and currently the only company that holds both partnerships. This helps us support organizations that want to combine deep SonarQube quality and security insights with organization-wide, AI-powered engineering visibility through Oobeya.",[613,4270,4272],{"id":4271},"our-session-visibility-and-productivity-in-the-age-of-ai","Our Session: Visibility and Productivity in the Age of AI",[12,4274,4275,4276,4281],{},"At the ",[514,4277,4280],{"href":4278,"rel":4279},"https:\u002F\u002Fevents.sonarsource.com\u002Fthe-sonar-summit\u002F",[518],"Sonar Summit",", we hosted a Fireside Chat together with my colleagues, Şükrü Çakmak — CTO and Omer Celebioglu — Head of Partnerships at Oobeya.",[12,4283,4284],{},"In the session, we explored one of the most important questions engineering leaders face today:",[12,4286,4287],{},[16,4288,4289],{},"What changes when AI becomes a daily collaborator in software development?",[12,4291,4292],{},"AI coding assistants are accelerating delivery. Pull request volume rises, change volume grows, and development cycles move faster. But speed alone is not enough. Engineering leaders need visibility, governance, and control to ensure AI-accelerated development still produces secure and high-quality outcomes.",[12,4294,4295],{},"We covered:",[70,4297,4298,4301,4304,4307],{},[73,4299,4300],{},"How AI-assisted development changes productivity dynamics",[73,4302,4303],{},"Why engineering visibility is now a leadership requirement",[73,4305,4306],{},"How leaders can maintain ownership, quality, and accountability",[73,4308,4309],{},"A short demo of Oobeya's AI-powered Engineering Intelligence platform",[4311,4312,4314,4315],"div",{"style":4313},"position:relative;padding-bottom:56.25%;height:0;overflow:hidden;max-width:100%;","\n  ",[4316,4317],"iframe",{"src":4318,"title":4319,"style":4320,"allow":4321,"referrerPolicy":4322,"allowFullScreen":547},"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002Fo3_zN4U-1a8","Sonar Summit 2026 Fireside Chat","position:absolute;top:0;left:0;width:100%;height:100%;border:0;","accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share","strict-origin-when-cross-origin",[613,4324,4326],{"id":4325},"key-announcements-from-sonar-summit-2026","Key Announcements from Sonar Summit 2026",[12,4328,4329],{},"The Summit introduced several innovations that highlight how AI is reshaping software development.",[4331,4332,4334],"h4",{"id":4333},"_1-agent-centric-development-cycle-acdc","1. Agent-Centric Development Cycle (AC\u002FDC)",[12,4336,4337,4338,611],{},"A new approach where AI agents take an active role in creating, reviewing, verifying, and improving code. Learn more about ",[514,4339,4342],{"href":4340,"rel":4341},"https:\u002F\u002Fwww.sonarsource.com\u002Fblog\u002Fthe-future-is-ac-dc-the-agent-centric-development-cycle\u002F",[518],"AC\u002FDC",[4331,4344,4346],{"id":4345},"_2-agentic-analysis-beta","2. Agentic Analysis (Beta)",[12,4348,4349,4350,611],{},"Brings SonarQube analysis into agent workflows so generated code can be validated and improved automatically. Learn more ",[514,4351,4354],{"href":4352,"rel":4353},"https:\u002F\u002Fwww.sonarsource.com\u002Fblog\u002Fagentic-analysis-beta\u002F",[518],"here",[4331,4356,4358],{"id":4357},"_3-sonar-context-augmentation","3. Sonar Context Augmentation",[12,4360,4361,4362,611],{},"Injects real-time SonarQube insights into AI agent workflows to improve safety and code quality at generation time. Learn more ",[514,4363,4354],{"href":4364,"rel":4365},"https:\u002F\u002Fwww.sonarsource.com\u002Fblog\u002Fintroducing-sonar-context-augmentation\u002F",[518],[4331,4367,4369],{"id":4368},"_4-sonarqube-architecture-management-ga","4. SonarQube Architecture Management (GA)",[12,4371,4372,4373,611],{},"Helps teams monitor architecture drift and protect long-term system design integrity. Learn more ",[514,4374,4354],{"href":4375,"rel":4376},"https:\u002F\u002Fwww.sonarsource.com\u002Fblog\u002Fcode-architecture-management-general-availability-in-sonarqube\u002F",[518],[4331,4378,4380],{"id":4379},"_5-sonarqube-remediation-agent-public-beta","5. SonarQube Remediation Agent (Public Beta)",[12,4382,4383],{},"Automatically fixes detected issues and verifies results, creating a closed loop across review, fix, and validation.",[613,4385,4387],{"id":4386},"the-bigger-shift-ai-driven-engineering-systems","The Bigger Shift: AI-Driven Engineering Systems",[12,4389,4390],{},"Software delivery is moving toward agent-driven environments where:",[70,4392,4393,4396,4399,4402],{},[73,4394,4395],{},"AI generates code",[73,4397,4398],{},"AI verifies quality",[73,4400,4401],{},"AI fixes issues",[73,4403,4404],{},"Humans supervise the system",[12,4406,4407],{},"This dramatically increases development velocity, but it also creates new challenges for engineering leadership.",[613,4409,4411],{"id":4410},"why-engineering-visibility-matters-more-than-ever","Why Engineering Visibility Matters More Than Ever",[12,4413,4414],{},"AI-accelerated development introduces new pressures:",[70,4416,4417,4420,4423,4426],{},[73,4418,4419],{},"Pull request volumes can increase rapidly",[73,4421,4422],{},"Code review pressure grows across teams",[73,4424,4425],{},"Quality signals become harder to interpret",[73,4427,4428],{},"Ownership and accountability can blur",[12,4430,4431],{},"That is why engineering leaders need organization-wide visibility across the SDLC. Platforms like Oobeya help leaders understand what is happening across repositories, CI\u002FCD systems, issue trackers, and quality tools so they can manage productivity, quality, and risk together.",[12,4433,4434,4435],{},"Learn more about our integration approach: ",[514,4436,4439],{"href":4437,"rel":4438},"https:\u002F\u002Foobeya.io\u002Fsonarqube",[518],"Oobeya + SonarQube",[613,4441,4443],{"id":4442},"our-perspective-at-oobeya","Our Perspective at Oobeya",[12,4445,4446],{},"We see the industry evolving through three stages:",[1520,4448,4449,4452,4455],{},[73,4450,4451],{},"Understanding how developers work",[73,4453,4454],{},"Understanding how developers work with AI",[73,4456,4457],{},"Preparing to measure and control how AI agents work.",[12,4459,4460],{},"Our mission is to help engineering leaders keep visibility, governance, and control in this new era of AI-accelerated software development.",[613,4462,4464],{"id":4463},"thank-you","Thank You",[12,4466,4467],{},"Beyond the announcements and sessions, one of the best parts of Sonar Summit was connecting with engineering leaders, DevSecOps, and platform teams across the ecosystem.",[12,4469,4470],{},"Thanks again to the Sonar team for hosting a forward-looking and well-organized event.",{"title":526,"searchDepth":527,"depth":527,"links":4472},[4473,4474,4475,4476,4477,4478],{"id":4271,"depth":527,"text":4272},{"id":4325,"depth":527,"text":4326},{"id":4386,"depth":527,"text":4387},{"id":4410,"depth":527,"text":4411},{"id":4442,"depth":527,"text":4443},{"id":4463,"depth":527,"text":4464},[4480,540],"events","2026-03-05","Highlights from Sonar Summit 2026 and what engineering leaders need for visibility, governance, and control in AI-accelerated delivery.",{"homeFeatured":547,"canonical":4484,"ogTitle":4485,"ogDescription":4482,"ogType":4486,"spotImageAlt":4487},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fsonar-summit-2026-key-takeaways","Sonar Summit 2026: What Changed in the Agentic Development Era","article","Oobeya co-founders at Sonar Summit 2026 discussing engineering visibility and AI-assisted development","\u002Fblog\u002Fsonar-summit-2026-key-takeaways",{"title":4244,"description":4482},"\u002Fassets\u002Fblog\u002Fsonar-summit-2026.jpg","Key takeaways from Sonar Summit 2026 on agentic development, engineering visibility, and what leaders now need from delivery governance.","blog\u002Fsonar-summit-2026-key-takeaways",[4494,4495,4496,2621],"sonarqube","agentic-ai","engineering-visibility","pD1Una_p8HlCmwhbxVYczKcLb4Jj7aXTLrKyBdQCtBA",{"id":4499,"title":4500,"author":6,"avatar":7,"body":4501,"categories":4835,"createAt":542,"date":4836,"description":4837,"extension":545,"meta":4838,"navigation":547,"path":4839,"position":4134,"seo":4840,"spotImage":542,"spotText":542,"stem":4841,"tags":4842,"__hash__":4844},"blog\u002Fblog\u002Foobeya-becomes-an-official-github-technology-partner.md","Oobeya Becomes an Official GitHub Technology Partner",{"type":9,"value":4502,"toc":4826},[4503,4509,4516,4518,4522,4538,4541,4562,4572,4574,4578,4588,4591,4608,4620,4629,4635,4637,4641,4651,4654,4665,4672,4683,4685,4689,4692,4702,4709,4726,4737,4744,4746,4750,4756,4770,4772,4776,4779,4786,4789,4801,4810,4812,4816],[12,4504,4505,4506,611],{},"We’re excited to announce that ",[16,4507,4508],{},"Oobeya is now an official GitHub Technology Partner",[12,4510,4511,4512,4515],{},"This milestone strengthens Oobeya’s position in the software engineering ecosystem and deepens our ability to help engineering organizations turn GitHub activity into ",[16,4513,4514],{},"actionable engineering intelligence"," — from delivery performance and DORA metrics to understanding the real impact of AI-assisted development.",[501,4517],{},[613,4519,4521],{"id":4520},"why-this-partnership-matters","Why This Partnership Matters",[12,4523,4524,4529,4530,4533,4534,4537],{},[514,4525,4528],{"href":4526,"rel":4527},"https:\u002F\u002Fgithub.com\u002F",[518],"GitHub"," sits at the center of modern software development.",[4531,4532],"br",{},"\nIt’s where code is written, reviewed, shipped — and increasingly where ",[16,4535,4536],{},"AI-assisted development"," takes place.",[12,4539,4540],{},"Becoming a GitHub Technology Partner reflects a shared vision:",[70,4542,4543,4549,4556],{},[73,4544,4545,4546],{},"Engineering data should be ",[16,4547,4548],{},"usable, trustworthy, and decision-ready",[73,4550,4551,4552,4555],{},"Metrics should ",[16,4553,4554],{},"drive improvement",", not just reporting",[73,4557,4558,4559],{},"AI adoption should be ",[16,4560,4561],{},"measured, not assumed",[12,4563,4564,4565,42,4568,4571],{},"For Oobeya, this partnership reinforces our mission to help engineering leaders move from ",[16,4566,4567],{},"raw activity data",[16,4569,4570],{},"clear insights"," across productivity, quality, predictability, and delivery health.",[501,4573],{},[613,4575,4577],{"id":4576},"deep-github-integration-built-for-engineering-intelligence","Deep GitHub Integration, Built for Engineering Intelligence",[12,4579,4580,4581,4583,4584,4587],{},"Oobeya’s GitHub integration goes beyond basic data ingestion.",[4531,4582],{},"\nIt is designed to provide a ",[16,4585,4586],{},"system-level view"," of how software is developed and delivered.",[12,4589,4590],{},"Through the GitHub integration, Oobeya enables:",[70,4592,4593,4596,4602,4605],{},[73,4594,4595],{},"End-to-end visibility into code activity, pull requests, and delivery flow",[73,4597,4598,4599,4601],{},"Accurate calculation of ",[16,4600,848],{}," based on real GitHub data",[73,4603,4604],{},"Multi-level insights across organization, tribe, and team",[73,4606,4607],{},"Configurable analytics that adapt to each organization’s way of working",[12,4609,4610,4611,4614,4616],{},"📘 ",[16,4612,4613],{},"GitHub Integration Documentation",[4531,4615],{},[514,4617,4618],{"href":4618,"rel":4619},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fall-integrations\u002Fscm-addons\u002Fgithub-integrations",[518],[12,4621,4610,4622,4625],{},[16,4623,4624],{},"Step-by-Step Integration Instructions for the Oobeya GitHub Application",[514,4626,4627],{"href":4627,"rel":4628},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fall-integrations\u002Fscm-addons\u002Fstep-by-step-integration-instructions-for-the-oobeya-github-application",[518],[12,4630,4631,4632,611],{},"This allows engineering leaders to rely on GitHub data not just as an activity log, but as a ",[16,4633,4634],{},"foundation for continuous improvement",[501,4636],{},[613,4638,4640],{"id":4639},"accurate-dora-metrics-from-github-data","Accurate DORA Metrics from GitHub Data",[12,4642,4643,4647,4648,611],{},[514,4644,4646],{"href":3620,"rel":4645},[518],"Measuring DORA metrics"," correctly requires more than counting events — it requires ",[16,4649,4650],{},"context, flow, and consistency",[12,4652,4653],{},"With Oobeya’s GitHub integration, organizations can calculate:",[70,4655,4656,4658,4660,4662],{},[73,4657,825],{},[73,4659,835],{},[73,4661,859],{},[73,4663,4664],{},"Mean Time to Recovery (MTTR)",[12,4666,4667,4668,4671],{},"All based on ",[16,4669,4670],{},"real delivery signals"," extracted from GitHub repositories and workflows.",[12,4673,4610,4674,4677,4679],{},[16,4675,4676],{},"How Oobeya Calculates DORA Metrics",[4531,4678],{},[514,4680,4681],{"href":4681,"rel":4682},"https:\u002F\u002Fdocs.oobeya.io\u002Fdeployment-analytics\u002Fdora-metrics-introduction",[518],[501,4684],{},[613,4686,4688],{"id":4687},"measuring-the-real-impact-of-github-copilot-and-ai-coding-assistants","Measuring the Real Impact of GitHub Copilot and AI Coding Assistants",[12,4690,4691],{},"AI-assisted development is rapidly becoming the norm — but its real impact is often unclear.",[12,4693,4694,4695,4701],{},"As part of our GitHub integration, Oobeya enables organizations to measure the ",[16,4696,4697],{},[514,4698,4700],{"href":3855,"rel":4699},[518],"actual impact of GitHub Copilot"," on engineering outcomes.",[12,4703,4704,4705,4708],{},"With Oobeya’s ",[16,4706,4707],{},"AI Impact"," capabilities, organizations can:",[70,4710,4711,4714,4717,4720,4723],{},[73,4712,4713],{},"Track Copilot adoption at organization, team, and user level",[73,4715,4716],{},"Distinguish between licensed users and actively engaged users",[73,4718,4719],{},"Analyze acceptance vs. suggestion patterns to understand real usage",[73,4721,4722],{},"Identify adoption differences across teams and roles",[73,4724,4725],{},"Detect usage and engagement patterns that indicate where enablement or standardization is needed",[12,4727,4610,4728,4731,4733],{},[16,4729,4730],{},"AI Impact & Copilot Insights",[4531,4732],{},[514,4734,4735],{"href":4735,"rel":4736},"https:\u002F\u002Fdocs.oobeya.io\u002Fai-impact\u002Fgithub-copilot-ai-impact",[518],[12,4738,4739,4740,4743],{},"Instead of relying on assumptions or anecdotal feedback, engineering leaders gain ",[16,4741,4742],{},"data-driven insight"," into how AI tools influence their development process.",[501,4745],{},[613,4747,4749],{"id":4748},"built-for-enterprise-grade-visibility-and-governance","Built for Enterprise-Grade Visibility and Governance",[12,4751,4752,4753,3444],{},"Oobeya’s GitHub integration is designed for ",[16,4754,4755],{},"enterprise environments",[70,4757,4758,4761,4764,4767],{},[73,4759,4760],{},"Works across multiple GitHub organizations",[73,4762,4763],{},"Supports role-based access and visibility",[73,4765,4766],{},"Aligns with existing SDLC tools and processes",[73,4768,4769],{},"Enables organization-wide and team-level analysis",[501,4771],{},[613,4773,4775],{"id":4774},"a-growing-ecosystem-a-clear-direction","A Growing Ecosystem, A Clear Direction",[12,4777,4778],{},"Becoming a GitHub Technology Partner is an important step in Oobeya’s journey — but it’s also part of a broader direction.",[12,4780,4781,4782,4785],{},"As engineering organizations grow more complex and AI becomes embedded in daily development, the need for ",[16,4783,4784],{},"engineering intelligence"," becomes critical.",[12,4787,4788],{},"Oobeya sits at the intersection of:",[70,4790,4791,4794,4797,4799],{},[73,4792,4793],{},"Engineering performance",[73,4795,4796],{},"Delivery predictability",[73,4798,3088],{},[73,4800,2215],{},[12,4802,4803,4804,42,4807,611],{},"This partnership reinforces our commitment to helping organizations move from ",[16,4805,4806],{},"measuring engineering",[16,4808,4809],{},"optimizing engineering as a system",[501,4811],{},[613,4813,4815],{"id":4814},"see-it-in-action","See It in Action",[12,4817,4818,4819,4825],{},"If you’d like to learn more about Oobeya’s GitHub integration and Copilot insights, ",[16,4820,4821],{},[514,4822,4824],{"href":4082,"rel":4823},[518],"book a demo"," to see it in action.",{"title":526,"searchDepth":527,"depth":527,"links":4827},[4828,4829,4830,4831,4832,4833,4834],{"id":4520,"depth":527,"text":4521},{"id":4576,"depth":527,"text":4577},{"id":4639,"depth":527,"text":4640},{"id":4687,"depth":527,"text":4688},{"id":4748,"depth":527,"text":4749},{"id":4774,"depth":527,"text":4775},{"id":4814,"depth":527,"text":4815},[4232,1231,540,4130],"2026-01-21","Oobeya is an official GitHub Technology Partner, helping teams turn GitHub data into delivery, DORA, and AI impact insights.",{},"\u002Fblog\u002Foobeya-becomes-an-official-github-technology-partner",{"title":4500,"description":4837},"blog\u002Foobeya-becomes-an-official-github-technology-partner",[4232,4843,4140,1231,540],"github-copilot","2ZykykmDjOOfanfR29WxvB_E0yz4_91NQoTlJYFO68M",{"id":4846,"title":4847,"author":6,"avatar":7,"body":4848,"categories":5063,"createAt":542,"date":5064,"description":5065,"extension":545,"meta":5066,"navigation":547,"path":5067,"position":4134,"seo":5068,"spotImage":542,"spotText":542,"stem":5069,"tags":5070,"__hash__":5071},"blog\u002Fblog\u002Foobeya-and-linktech-announce-partnership-for-taiwan.md","Oobeya and Linktech Announce Partnership to Strengthen Engineering Excellence in Taiwan",{"type":9,"value":4849,"toc":5054},[4850,4863,4870,4872,4877,4881,4887,4890,4894,4897,4900,4904,4907,4910,4913,4930,4934,4942,4955,4963,4967,4970,4973,4976,4986,4994,4996,5000,5005,5015,5017,5021,5034,5045],[12,4851,4852,4855,4856,4859,4860,4862],{},[16,4853,4854],{},"Taipei, Taiwan — November, 2025"," — ",[16,4857,4858],{},"Linktech",", a leading Taiwan-based IT consulting and technology services provider, has partnered with ",[16,4861,469],{},",\nthe leading Software Engineering Intelligence (SEI) and Developer Productivity Platform trusted by enterprises worldwide. Through this collaboration,\norganizations across Taiwan will gain modern, data-driven capabilities to improve engineering productivity, quality, and delivery performance—without disrupting\nexisting tools or workflows.",[12,4864,4865],{},[4866,4867],"img",{"alt":4868,"src":4869},"Oobeya and Linktech Announce Partnership for Taiwan and Asia","\u002Fassets\u002Fblog\u002Flinktech-oobeya-partnership.png",[501,4871],{},[12,4873,4874],{},[16,4875,4876],{},"Read Linktech's announcement:",[52,4878,4880],{"id":4879},"linktech-becomes-the-official-taiwan-partner-of-oobeya-the-essential-solution-for-data-driven-engineering-excellence","Linktech Becomes the Official Taiwan Partner of Oobeya! -The Essential Solution for Data-Driven Engineering Excellence",[12,4882,4883,4884,4886],{},"In software development, teams constantly seek the perfect balance between delivery speed and system stability. Linktech is proud to announce our official\npartnership as the Taiwan reseller of Oobeya!",[4531,4885],{},"\nThis Gartner-recommended platform helps organizations eliminate blind spots in the development process and make engineering decisions based on data, not assumptions.",[12,4888,4889],{},"If you’re looking to boost engineering efficiency, implement DORA metrics, or optimize your DevOps practices, this article will help you quickly get to know Oobeya.",[52,4891,4893],{"id":4892},"what-is-oobeya","What is Oobeya?",[12,4895,4896],{},"Oobeya is a Software Engineering Intelligence Platform (SEIP). Just as sales teams rely on CRM systems and finance teams depend on ERP systems, engineering teams also need a centralized command center — yet this has been\nlacking for many organizations.",[12,4898,4899],{},"Oobeya fills this critical gap by consolidating fragmented data from various development tools, helping engineering teams collect, analyze, and interpret\ninformation across the entire software lifecycle.",[52,4901,4903],{"id":4902},"how-does-oobeya-work","How Does Oobeya Work?",[12,4905,4906],{},"Oobeya operates on two key pillars: data collection and analysis.",[12,4908,4909],{},"It integrates with more than 20 mainstream SDLC tools (GitHub, GitLab, Jira, Jenkins, SonarQube, etc.) to provide complete end-to-end visibility — from development to delivery.",[12,4911,4912],{},"Engineering leaders gain insights across individual, team, and organizational dimensions, along with essential engineering metrics such as:",[70,4914,4915,4917,4920,4923,4925],{},[73,4916,807],{},[73,4918,4919],{},"Lead Time",[73,4921,4922],{},"Agile Metrics",[73,4924,3261],{},[73,4926,4927],{},[791,4928,4929],{},"50+ Key Engineering Metrics",[52,4931,4933],{"id":4932},"key-advantages-of-oobeya","Key Advantages of Oobeya",[12,4935,4936,4939,4941],{},[16,4937,4938],{},"Shorter Development Cycles:",[4531,4940],{},"\nReal customer results show a 30% reduction in cycle time, 25% productivity improvement, and fewer critical production bugs — thanks to earlier issue detection\nand lower rework\u002Foperations costs.",[12,4943,4944,4947,4949,4950,4954],{},[16,4945,4946],{},"Enterprise-Grade Deployment Flexibility:",[4531,4948],{},"\nDesigned for industries with stringent requirements such as finance, government, and high tech, Oobeya supports ",[514,4951,4953],{"href":4952},"\u002Fon-premise","On-Premise (Self-Hosted)"," and Private SaaS\ndeployments, along with SSO and RBAC.",[12,4956,4957,4960,4962],{},[16,4958,4959],{},"Automated Process Diagnostics:",[4531,4961],{},"\nWith its built-in Suggestion Module, Oobeya automatically identifies anti-patterns and abnormal workflow symptoms, providing proactive recommendations for improvement.",[52,4964,4966],{"id":4965},"linktech-x-oobeya-local-consulting-services","Linktech x Oobeya Local Consulting Services",[12,4968,4969],{},"Oobeya turns software development from an opaque process into a measurable and predictable strategic asset.",[12,4971,4972],{},"Linktech’s professional team provides full technical support and consulting services.",[12,4974,4975],{},"If you’d like to understand how Oobeya can elevate your engineering performance or need project-specific guidance, feel free to reach out anytime.",[3354,4977,4978],{},[12,4979,4980,4981],{},"👉 Contact the Linktech team now to arrange a free demo! ",[514,4982,4985],{"href":4983,"rel":4984},"https:\u002F\u002Fwww.linktech.com.tw\u002Fcontactus",[518],"Contact Us",[12,4987,4988,4989,611],{},"Click to read the original ",[514,4990,4993],{"href":4991,"rel":4992},"https:\u002F\u002Fwww.linktech.com.tw\u002Fpost\u002Foobeya-reseller",[518],"announcement",[501,4995],{},[52,4997,4999],{"id":4998},"about-linktech","About Linktech",[12,5001,5002,5004],{},[16,5003,4858],{}," is a Taiwan-based IT consulting and technology services company specializing in software development consulting, enterprise solutions,\nand digital transformation enablement. With strong technical capabilities and experience across industries, Linktech helps organizations modernize their technology landscape, adopt best practices,\nand improve software delivery performance.",[12,5006,5007,5008],{},"Learn more at ",[16,5009,5010],{},[514,5011,5014],{"href":5012,"rel":5013},"https:\u002F\u002Fwww.linktech.com.tw",[518],"linktech.com.tw",[501,5016],{},[52,5018,5020],{"id":5019},"about-oobeya","About Oobeya",[12,5022,5023,5025,5026,5029,5030,5033],{},[16,5024,469],{}," is a Software Engineering Intelligence Platform (SEIP) that helps enterprises improve productivity, quality, and developer experience.\nRecognized by ",[16,5027,5028],{},"Gartner"," as a Representative Provider in the SEIP market and a multi-category leader on ",[16,5031,5032],{},"G2",", Oobeya unifies engineering data across the\nentire SDLC — including code, issues, deployments, testing, quality, and operations — into a single actionable, AI-powered platform.",[12,5035,5036,5037,5040,5041,5044],{},"By going beyond dashboards, Oobeya identifies ",[16,5038,5039],{},"“symptoms”"," of unhealthy engineering practices and provides ",[16,5042,5043],{},"AI-driven recommendations"," that help leaders\nmake better decisions, foster healthier teams, and accelerate delivery at scale.",[12,5046,5007,5047],{},[16,5048,5049],{},[514,5050,5053],{"href":5051,"rel":5052},"https:\u002F\u002Foobeya.io",[518],"oobeya.io",{"title":526,"searchDepth":527,"depth":527,"links":5055},[5056,5057,5058,5059,5060,5061,5062],{"id":4879,"depth":530,"text":4880},{"id":4892,"depth":530,"text":4893},{"id":4902,"depth":530,"text":4903},{"id":4932,"depth":530,"text":4933},{"id":4965,"depth":530,"text":4966},{"id":4998,"depth":530,"text":4999},{"id":5019,"depth":530,"text":5020},[4232,1231,540],"2025-11-27","Oobeya and Linktech partner to help engineering leaders in Taiwan improve SDLC visibility, delivery performance, and decision-making.",{},"\u002Fblog\u002Foobeya-and-linktech-announce-partnership-for-taiwan",{"title":4847,"description":5065},"blog\u002Foobeya-and-linktech-announce-partnership-for-taiwan",[4232,1231,540],"56wmnr6opVON1o8fngFMdaKM2z51Nd65m_-RWVQSKtE",{"id":5073,"title":5074,"author":4245,"avatar":575,"body":5075,"categories":5549,"createAt":542,"date":5551,"description":5552,"extension":545,"meta":5553,"navigation":547,"path":5554,"position":4134,"seo":5555,"spotImage":542,"spotText":542,"stem":5556,"tags":5557,"__hash__":5558},"blog\u002Fblog\u002Fdx-alternative.md","Oobeya: The Secure, On-Premise DX Alternative for Regulated and EU-Based Engineering Organizations",{"type":9,"value":5076,"toc":5530},[5077,5086,5089,5096,5099,5101,5105,5125,5131,5141,5143,5147,5152,5157,5166,5168,5172,5183,5188,5193,5206,5208,5212,5217,5222,5231,5233,5237,5242,5247,5254,5256,5260,5268,5273,5277,5289,5291,5295,5300,5305,5314,5316,5320,5325,5330,5339,5341,5345,5350,5355,5364,5366,5370,5374,5397,5401,5418,5425,5428,5430,5434,5441,5471,5473,5478,5489,5491,5493,5496,5507,5512,5514],[12,5078,5079,5080,247,5082,5085],{},"For engineering leaders evaluating software engineering intelligence or DevEx platforms, ",[16,5081,469],{},[16,5083,5084],{},"DX (GetDX)"," often appear in the same shortlist.\nBoth aim to improve software delivery performance and developer experience — but they differ significantly in architecture, analytics depth, deployment options,\nand enterprise readiness.",[12,5087,5088],{},"The most critical difference?",[3354,5090,5091],{},[12,5092,5093],{},[16,5094,5095],{},"DX is cloud-only. Oobeya offers both cloud SaaS (with preferred region data residency) and true on-premise deployment (kubernetes, docker, podman, Openshift, and many more options) — making it the secure, compliant choice for banks, telcos, government teams, and regulated industries.",[12,5097,5098],{},"Below is the complete DX vs. Oobeya comparison to help you evaluate both platforms.",[501,5100],{},[52,5102,5104],{"id":5103},"_1-integrations-sdlc-coverage","1. Integrations & SDLC Coverage",[12,5106,5107,5110,5111,5115,5116,5121,5122,611],{},[16,5108,5109],{},"Oobeya:","\n20+ effectively used SDLC ",[514,5112,5114],{"href":4219,"rel":5113},[518],"integrations"," — Git platforms, Jira, Azure DevOps, Azure Boards, CI\u002FCD systems, APM, quality tools (e.g., ",[514,5117,5120],{"href":5118,"rel":5119},"https:\u002F\u002Fwww.sonarsource.com\u002Fproducts\u002Fsonarqube\u002F",[518],"SonarQube","), and test tools (e.g., XRay) — with full support for on-premise tool versions ",[16,5123,5124],{},"at no extra cost",[12,5126,5127,5130],{},[16,5128,5129],{},"DX:","\nGood SDLC coverage on paper, but primarily focused on Atlassian stack. Most of the integrations don't provide effective analytics. Additional costs and complexity for on-premise tool integrations.",[12,5132,5133,1044,5136,5138,5140],{},[16,5134,5135],{},"Advantage:",[16,5137,469],{},[4531,5139],{},"\nBroader integration landscape and stronger enterprise readiness.",[501,5142],{},[52,5144,5146],{"id":5145},"_2-development-analytics-dora-accuracy","2. Development Analytics & DORA Accuracy",[12,5148,5149,5151],{},[16,5150,5109],{},"\nDeep Git analytics with granular insights and precise DORA metric calculations.",[12,5153,5154,5156],{},[16,5155,5129],{},"\nUses the DX Core 4 framework with less depth in analytics.",[12,5158,5159,1044,5161,5163,5165],{},[16,5160,5135],{},[16,5162,469],{},[4531,5164],{},"\nIdeal for organizations that depend on DORA accuracy and detailed delivery performance insights.",[501,5167],{},[52,5169,5171],{"id":5170},"_3-team-health-devex","3. Team Health & DevEx",[12,5173,5174,5176,5177,5182],{},[16,5175,5109],{},"\nAutomated ",[514,5178,5181],{"href":5179,"rel":5180},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fsymptoms-and-engineering-kpis",[518],"Symptoms detection"," and Team Health dashboards without relying on survey fatigue.",[12,5184,5185,5187],{},[16,5186,5129],{},"\nStrong survey and sentiment sampling capability.",[12,5189,5190,5192],{},[16,5191,5135],{}," Depends",[70,5194,5195,5201],{},[73,5196,5197,5200],{},[16,5198,5199],{},"DX"," → If you want heavy survey-based DevEx insights.",[73,5202,5203,5205],{},[16,5204,469],{}," → If you want objective, evidence-based automated signals without survey bias.",[501,5207],{},[52,5209,5211],{"id":5210},"_4-actionable-insights","4. Actionable Insights",[12,5213,5214,5216],{},[16,5215,5109],{},"\nProactive recommendations tied directly to detected symptoms and engineering bottlenecks.",[12,5218,5219,5221],{},[16,5220,5129],{},"\nProvides insights and benchmarks but is less prescriptive.",[12,5223,5224,1044,5226,5228,5230],{},[16,5225,5135],{},[16,5227,469],{},[4531,5229],{},"\nBetter for organizations that want continuous improvement without manual analysis.",[501,5232],{},[52,5234,5236],{"id":5235},"_5-executive-reporting","5. Executive Reporting",[12,5238,5239,5241],{},[16,5240,5109],{},"\nEnterprise scorecards, organizational hierarchy mapping (Cluster → Tribe → Squad, e.g.), vendor performance dashboards.",[12,5243,5244,5246],{},[16,5245,5129],{},"\nStrong benchmarking and executive-level views, mostly through survey outputs.",[12,5248,5249,1044,5251,5253],{},[16,5250,5135],{},[16,5252,469],{}," (for enterprise-wide leadership visibility)\nDX remains strong in DevEx benchmarks.",[501,5255],{},[52,5257,5259],{"id":5258},"_6-ai-capabilities","6. AI Capabilities",[12,5261,5262,5264,5265,5267],{},[16,5263,5109],{},"\nAI-driven recommendations (Oobeya AI Engineering Coach), anomaly detection, and ",[16,5266,610],{}," metrics and insights.",[12,5269,5270,5272],{},[16,5271,5129],{},"\nAI analysis based on survey data + Core 4 metrics, and additional costs.",[12,5274,5275,5192],{},[16,5276,5135],{},[70,5278,5279,5284],{},[73,5280,5281,5283],{},[16,5282,469],{}," → Better for SDLC, Git, and AI-driven development analytics.",[73,5285,5286,5288],{},[16,5287,5199],{}," → Better for survey-driven DevEx AI with additional costs.",[501,5290],{},[52,5292,5294],{"id":5293},"_7-customization-flexibility","7. Customization & Flexibility",[12,5296,5297,5299],{},[16,5298,5109],{},"\nFully customizable thresholds, mappings, and dashboards.",[12,5301,5302,5304],{},[16,5303,5129],{},"\nCustomizable but tied closely to the DX Core 4 model.",[12,5306,5307,1044,5309,5311,5313],{},[16,5308,5135],{},[16,5310,469],{},[4531,5312],{},"\nMore suitable for complex, large-scale engineering organizations.",[501,5315],{},[52,5317,5319],{"id":5318},"_8-ease-of-use-adoption","8. Ease of Use & Adoption",[12,5321,5322,5324],{},[16,5323,5109],{},"\nFast onboarding, intuitive UI, minimal setup time, and no additional costs.",[12,5326,5327,5329],{},[16,5328,5129],{},"\n1+ month implementation with workshops and additional onboarding costs.",[12,5331,5332,1044,5334,5336,5338],{},[16,5333,5135],{},[16,5335,469],{},[4531,5337],{},"\nFaster time-to-value and lower onboarding complexity and costs.",[501,5340],{},[52,5342,5344],{"id":5343},"_9-pricing-scalability","9. Pricing & Scalability",[12,5346,5347,5349],{},[16,5348,5109],{},"\nTransparent and scalable pricing (contributor-based) with enterprise flexibility. Volume discounts are available.",[12,5351,5352,5354],{},[16,5353,5129],{},"\nCustom pricing with higher total cost due to surveys, benchmarking, and several uncertain module scopes.",[12,5356,5357,1044,5359,5361,5363],{},[16,5358,5135],{},[16,5360,469],{},[4531,5362],{},"\nMore cost-efficient for any engineering organizations.",[501,5365],{},[52,5367,5369],{"id":5368},"_10-deployment-options-the-most-important-difference","10. Deployment Options (The Most Important Difference)",[12,5371,5372],{},[16,5373,5109],{},[70,5375,5376,5382,5388,5394],{},[73,5377,5378,5381],{},[16,5379,5380],{},"On-premise:"," Fully On-Premise deployment (no internet connection required)",[73,5383,5384,5387],{},[16,5385,5386],{},"Cloud SaaS:"," Cloud deployment (single-tenant SaaS option -secure and flexible for clients' needs)",[73,5389,5390,5393],{},[16,5391,5392],{},"SaaS with selectable AWS regions"," (e.g., Frankfurt, Ireland, UAE)",[73,5395,5396],{},"Supports strict EU and industry-specific data residency rules.",[12,5398,5399],{},[16,5400,5129],{},[70,5402,5403,5409,5412,5415],{},[73,5404,5405,5408],{},[16,5406,5407],{},"Cloud-only SaaS",", supports US-based data residency",[73,5410,5411],{},"No on-premise or private cloud option",[73,5413,5414],{},"Limited data residency control",[73,5416,5417],{},"Data transfer for benchmarking.",[3354,5419,5420],{},[12,5421,5422],{},[16,5423,5424],{},"Oobeya is the secure, on-premise alternative to DX — trusted by banks, telcos, and government teams to improve productivity without compromising compliance.",[12,5426,5427],{},"For EU companies, Oobeya’s SaaS offering ensures data stays strictly within EU borders, helping teams remain GDPR-compliant without sacrificing analytics depth.",[501,5429],{},[613,5431,5433],{"id":5432},"summary-oobeya-vs-dx","Summary: Oobeya vs. DX",[52,5435,5437,5438,5440],{"id":5436},"choose-oobeya-if-you-want","Choose ",[16,5439,469],{}," if you want:",[70,5442,5443,5446,5449,5452,5455,5462,5465],{},[73,5444,5445],{},"Deep SDLC analytics, accurate DORA metrics",[73,5447,5448],{},"Objective, automated signals",[73,5450,5451],{},"Enterprise-wide dashboards and multi-level reporting",[73,5453,5454],{},"Fast onboarding",[73,5456,5457,5458,5461],{},"Secure ",[16,5459,5460],{},"On-Premise"," deployment",[73,5463,5464],{},"EU-only cloud hosting",[73,5466,5467,5470],{},[16,5468,5469],{},"Lower TCO"," and higher configuration flexibility.",[501,5472],{},[52,5474,5437,5476,5440],{"id":5475},"choose-dx-if-you-want",[16,5477,5199],{},[70,5479,5480,5483,5486],{},[73,5481,5482],{},"Strong survey-driven DevEx insights",[73,5484,5485],{},"Benchmarking across teams",[73,5487,5488],{},"A survey-first approach to developer experience.",[501,5490],{},[52,5492,1159],{"id":477},[12,5494,5495],{},"Oobeya and DX serve different engineering goals. DX focuses on surveys and developer sentiment, while Oobeya provides accurate SDLC analytics, proactive engineering intelligence, and enterprise-grade compliance.",[12,5497,5498,5499,5502,5503,5506],{},"For regulated industries, government teams, and EU-based companies that require ",[16,5500,5501],{},"on-premise deployment"," or ",[16,5504,5505],{},"strict data residency",", there is a clear choice:",[12,5508,5509],{},[16,5510,5511],{},"Oobeya is the only DX alternative that combines deep engineering analytics with the security, governance, and deployment models required by modern enterprises.",[501,5513],{},[3354,5515,5516],{},[12,5517,5518,5521,5523,5529],{},[16,5519,5520],{},"Want to understand how Oobeya fits your environment?",[4531,5522],{},[16,5524,5525],{},[514,5526,5528],{"href":4082,"rel":5527},[518],"Book a demo"," to see the platform in action and discuss your requirements.",{"title":526,"searchDepth":527,"depth":527,"links":5531},[5532,5533,5534,5535,5536,5537,5538,5539,5540,5541,5542],{"id":5103,"depth":530,"text":5104},{"id":5145,"depth":530,"text":5146},{"id":5170,"depth":530,"text":5171},{"id":5210,"depth":530,"text":5211},{"id":5235,"depth":530,"text":5236},{"id":5258,"depth":530,"text":5259},{"id":5293,"depth":530,"text":5294},{"id":5318,"depth":530,"text":5319},{"id":5343,"depth":530,"text":5344},{"id":5368,"depth":530,"text":5369},{"id":5432,"depth":527,"text":5433,"children":5543},[5544,5546,5548],{"id":5436,"depth":530,"text":5545},"Choose Oobeya if you want:",{"id":5475,"depth":530,"text":5547},"Choose DX if you want:",{"id":477,"depth":530,"text":1159},[5550,540,1232,2620,1231],"dx-alternative","2025-11-26","Compare Oobeya vs DX for secure on-premise analytics, DORA accuracy, deeper SDLC visibility, and enterprise data residency.",{},"\u002Fblog\u002Fdx-alternative",{"title":5074,"description":5552},"blog\u002Fdx-alternative",[540,2620,1231],"bQ0UwFe3Tf2A7gwokZ_vXlxLtJG0zkadkQlYwj7eH0U",{"id":5560,"title":5561,"author":4245,"avatar":575,"body":5562,"categories":6079,"createAt":542,"date":6080,"description":6081,"extension":545,"meta":6082,"navigation":547,"path":6083,"position":4134,"seo":6084,"spotImage":542,"spotText":542,"stem":6085,"tags":6086,"__hash__":6087},"blog\u002Fblog\u002Fai-measurement-framework.md","AI Measurement Framework: The Practical Framework for Measuring Impact of AI Coding Assistants",{"type":9,"value":5563,"toc":6068},[5564,5568,5573,5593,5600,5603,5617,5620,5640,5651,5653,5657,5667,5674,5700,5706,5711,5713,5717,5720,5723,5745,5752,5754,5758,5761,5767,5791,5794,5801,5803,5807,5810,5813,5839,5842,5849,5851,5855,5858,5864,5878,5881,5883,5887,5890,5916,5919,5926,5928,5932,5936,6032,6034,6038,6041,6055,6057],[52,5565,5567],{"id":5566},"how-engineering-leaders-use-oobeya-to-understand-real-productivity-quality-and-roi","How Engineering Leaders Use Oobeya to Understand Real Productivity, Quality, and ROI",[12,5569,5570],{},[4866,5571],{"alt":5572,"src":4136},"Oobeya AI Measurement Framework",[12,5574,5575,5576,5578,5579,5583,5584,27,5588,5592],{},"AI-powered coding assistants such as ",[16,5577,2362],{},", Cursor, ",[514,5580,5582],{"href":5581},"\u002Fglossary\u002Fwindsurf","Windsurf",", Claude, ",[514,5585,5587],{"href":5586},"\u002Fglossary\u002Ftabnine","Tabnine",[514,5589,5591],{"href":5590},"\u002Fglossary\u002Fgemini-code-assist","Gemini Code Assist"," are rapidly transforming the way software is built.\nBut despite the industry hype, most engineering leaders still struggle with one essential question:",[3354,5594,5595],{},[12,5596,5597],{},[16,5598,5599],{},"How do we measure the real impact of AI-assisted development across teams, delivery pipelines, and business outcomes?",[12,5601,5602],{},"Many organizations currently rely on surface-level indicators:",[70,5604,5605,5608,5611,5614],{},[73,5606,5607],{},"Developer surveys and anecdotal productivity claims",[73,5609,5610],{},"IDE-level suggestions and acceptance metrics",[73,5612,5613],{},"Local scripts with limited visibility",[73,5615,5616],{},"Incomplete license usage stats",[12,5618,5619],{},"These metrics fail to answer the deeper, strategic organizational questions that drive investment decisions:",[70,5621,5622,5625,5631,5637],{},[73,5623,5624],{},"Is AI actually improving end-to-end delivery and quality?",[73,5626,5627,5628,5630],{},"How does AI affect crucial metrics like ",[16,5629,807],{},", rework, or review load?",[73,5632,5633,5634,5636],{},"Are we overpaying for underused licenses? (What is the true ",[16,5635,2775],{},"?)",[73,5638,5639],{},"Where do teams need coaching, governance, or targeted training?",[12,5641,5642,5643,5646,5647,5650],{},"Oobeya’s ",[16,5644,5645],{},"AI Coding Assistant Impact framework"," addresses these gaps by providing a comprehensive, ",[16,5648,5649],{},"SDLC-wide approach","\nto measuring AI adoption and its effects. This framework is fully supported by the Oobeya platform’s dedicated AI Impact module.",[501,5652],{},[52,5654,5656],{"id":5655},"_1-visibility-layer-understand-adoption-and-engagement","1. Visibility Layer: Understand Adoption and Engagement",[12,5658,5659,5660,5663,5664,611],{},"Before analyzing organizational outcomes, leaders must establish clear, continuous visibility into ",[791,5661,5662],{},"who"," is using the AI assistants\nand ",[791,5665,5666],{},"how often",[12,5668,5669,5670,5673],{},"Oobeya provides this through ",[16,5671,5672],{},"Copilot Engagement & Acceptance Trends",", which offer concrete insights:",[70,5675,5676,5682,5688,5694],{},[73,5677,5678,5681],{},[16,5679,5680],{},"Active Users:"," Users who have coding assistant (Copilot) installed and interacted with it.",[73,5683,5684,5687],{},[16,5685,5686],{},"Engaged Users:"," Users who accepted at least one coding assistant suggestion. (indicating successful integration into their workflow).",[73,5689,5690,5693],{},[16,5691,5692],{},"Adoption Rate:"," The ratio of engaged users to active users. And the percentage of the engineering organization actively benefiting from AI-assisted development.",[73,5695,5696,5699],{},[16,5697,5698],{},"Code Acceptance Ratio:"," The percentage of AI-generated suggestions accepted.",[12,5701,5702,5703],{},"This initial layer pinpoints successful adopters, highlights teams with low or inconsistent use, and quickly identifies underutilized licenses.\nThis answers the foundational question: ",[16,5704,5705],{},"Are people actually using the AI coding assistants?",[12,5707,5708],{},[16,5709,5710],{},"Crucially, usage alone does not equal impact.",[501,5712],{},[52,5714,5716],{"id":5715},"_2-productivity-impact-layer-measure-meaningful-output-changes","2. Productivity Impact Layer: Measure Meaningful Output Changes",[12,5718,5719],{},"The next step is to link usage to real engineering outcomes. Oobeya analyzes how AI-generated contributions flow through the SDLC.",[12,5721,5722],{},"Key metrics for measuring productivity change include:",[70,5724,5725,5731],{},[73,5726,5727,5730],{},[16,5728,5729],{},"Coding Impact Score:"," A sophisticated performance indicator based on code contribution patterns, ownership, complexity, and structural analysis.",[73,5732,5733,5736,5737,5740,5741,5744],{},[16,5734,5735],{},"Coding Efficiency Change:"," Shows whether developers produce meaningful code more efficiently when assisted by AI. Oobeya compares teams ",[791,5738,5739],{},"with"," AI versus ",[791,5742,5743],{},"without"," AI.",[12,5746,5747,5748,5751],{},"The platform provides granular ",[16,5749,5750],{},"AI-assisted contribution detection",", identifying AI-generated code blocks, multi-line suggestions, repeated patterns, and structural similarity with AI-generated code.\nThis layer shows how AI affects real throughput and value creation—not just volume.",[501,5753],{},[52,5755,5757],{"id":5756},"_3-quality-impact-layer-ensure-ai-does-not-introduce-hidden-risks","3. Quality Impact Layer: Ensure AI Does Not Introduce Hidden Risks",[12,5759,5760],{},"Increased output is only beneficial when code quality remains stable or improves. Unchecked AI assistance can inadvertently introduce debt or vulnerabilities.",[12,5762,5763,5764,5766],{},"Through integrations with static analysis tools like ",[16,5765,5120],{},", test reporting systems, and CI\u002FCD pipelines, Oobeya measures:",[70,5768,5769,5779,5785],{},[73,5770,5771,5774,5775],{},[16,5772,5773],{},"AI vs. Non-AI Code Quality:"," Tracking SonarQube bugs, vulnerabilities, code smells, and technical debt patterns introduced by AI-assisted code.\nSee how it integrates: ",[514,5776,5778],{"href":5777},"\u002Fsonarqube","Oobeya + SonarQube Integration",[73,5780,5781,5784],{},[16,5782,5783],{},"Rework & Review Rejections:"," Shows whether AI suggestions create additional, unnecessary review loops, increasing reviewer burden.",[73,5786,5787,5790],{},[16,5788,5789],{},"Test Coverage Impact:"," Analyzes whether AI-generated tests improve quality or introduce brittleness.",[12,5792,5793],{},"This layer answers the crucial question:",[3354,5795,5796],{},[12,5797,5798],{},[16,5799,5800],{},"Is AI helping us deliver better quality, or is it creating new risks and increasing long-term debt?",[501,5802],{},[52,5804,5806],{"id":5805},"_4-delivery-flow-layer-evaluate-software-delivery-impact-end-to-end","4. Delivery & Flow Layer: Evaluate Software Delivery Impact End-to-End",[12,5808,5809],{},"Unlike local IDE or commit-level tools, Oobeya provides a full SDLC view across Jira, Azure Boards, GitHub, GitLab, SonarQube, and CI\u002FCD systems.",[12,5811,5812],{},"This holistic analysis evaluates how AI usage affects the entire flow of value:",[70,5814,5815,5821,5827,5833],{},[73,5816,5817,5820],{},[16,5818,5819],{},"Lead Time for Changes:"," Do AI-assisted developers deliver user stories faster from inception to production?",[73,5822,5823,5826],{},[16,5824,5825],{},"Cycle Time Breakdown:"," Granular insights into coding, review, merge, and deployment phases to pinpoint exactly where AI acceleration occurs.",[73,5828,5829,5832],{},[16,5830,5831],{},"Review Workload:"," Does AI increase or decrease the overall reviewer burden?",[73,5834,5835,5838],{},[16,5836,5837],{},"Flow Efficiency:"," Evaluates whether AI reduces wait time or accelerates active work progress.",[12,5840,5841],{},"This comprehensive view confirms:",[3354,5843,5844],{},[12,5845,5846],{},[16,5847,5848],{},"Is AI improving delivery performance, not just local coding speed?",[501,5850],{},[52,5852,5854],{"id":5853},"_5-developer-experience-dx-layer-understand-the-human-impact","5. Developer Experience (DX) Layer: Understand the Human Impact",[12,5856,5857],{},"AI adoption fundamentally changes how developers work, think, and collaborate. A sustainable AI strategy must prioritize the human element.",[12,5859,5860,5861,5863],{},"Oobeya provides ",[16,5862,5199],{}," signals by correlating AI usage with:",[70,5865,5866,5869,5872,5875],{},[73,5867,5868],{},"Cognitive load indicators",[73,5870,5871],{},"Work intensity patterns and review responsibilities",[73,5873,5874],{},"Context switching frequency",[73,5876,5877],{},"Frustration signals (e.g., excessive rework or abandoned changes)",[12,5879,5880],{},"This layer highlights healthy usage patterns, flags overuse or dependency risks, identifies craftsmanship decline signals,\nand indicates where targeted coaching is required. This completes the human perspective on responsible AI adoption.",[501,5882],{},[52,5884,5886],{"id":5885},"_6-organizational-roi-layer-quantify-the-business-value","6. Organizational ROI Layer: Quantify the Business Value",[12,5888,5889],{},"Engineering leaders must justify AI-related investments with quantifiable data.\nThe final layer provides metrics that transform AI investment decisions from subjective judgment to data-backed strategy:",[70,5891,5892,5898,5904,5910],{},[73,5893,5894,5897],{},[16,5895,5896],{},"License Utilization:"," Ensures AI licenses match real organizational needs, optimizing cost.",[73,5899,5900,5903],{},[16,5901,5902],{},"Output per License Cost:"," Analyzes the value created per user, providing a direct efficiency metric.",[73,5905,5906,5909],{},[16,5907,5908],{},"Delivery Cost Reduction:"," Shorter cycle times and lower rework translate into measurable, auditable savings.",[73,5911,5912,5915],{},[16,5913,5914],{},"Team Benchmarking:"," Identifies and celebrates high-performing, AI-effective teams for knowledge sharing.",[12,5917,5918],{},"This layer provides the definitive answer:",[3354,5920,5921],{},[12,5922,5923],{},[16,5924,5925],{},"Is the investment in AI coding assistants worth the organizational cost?",[501,5927],{},[52,5929,5931],{"id":5930},"summary-the-oobeya-ai-measurement-framework","Summary: The Oobeya AI Measurement Framework",[12,5933,5934],{},[4866,5935],{"alt":5572,"src":3339},[1585,5937,5938,5952],{},[1588,5939,5940],{},[1591,5941,5942,5946,5949],{},[1594,5943,5945],{"align":5944},"left","Layer",[1594,5947,5948],{"align":5944},"Key Question",[1594,5950,5951],{"align":5944},"Example Metrics",[1601,5953,5954,5967,5980,5993,6006,6019],{},[1591,5955,5956,5961,5964],{},[1606,5957,5958],{"align":5944},[16,5959,5960],{},"Adoption & Engagement",[1606,5962,5963],{"align":5944},"Are teams successfully using AI?",[1606,5965,5966],{"align":5944},"Active Users, Adoption Rate, Acceptance Ratio",[1591,5968,5969,5974,5977],{},[1606,5970,5971],{"align":5944},[16,5972,5973],{},"Productivity Impact",[1606,5975,5976],{"align":5944},"Does AI increase meaningful output?",[1606,5978,5979],{"align":5944},"Coding Impact Score, Efficiency Change",[1591,5981,5982,5987,5990],{},[1606,5983,5984],{"align":5944},[16,5985,5986],{},"Quality Impact",[1606,5988,5989],{"align":5944},"Does AI introduce risks?",[1606,5991,5992],{"align":5944},"SonarQube Issues, Rework, Test Coverage",[1591,5994,5995,6000,6003],{},[1606,5996,5997],{"align":5944},[16,5998,5999],{},"Delivery & Flow",[1606,6001,6002],{"align":5944},"Does AI improve delivery performance?",[1606,6004,6005],{"align":5944},"Lead Time, Cycle Time, Review Load",[1591,6007,6008,6013,6016],{},[1606,6009,6010],{"align":5944},[16,6011,6012],{},"Developer Experience",[1606,6014,6015],{"align":5944},"How does AI affect people?",[1606,6017,6018],{"align":5944},"Flow Efficiency, Workload Patterns",[1591,6020,6021,6026,6029],{},[1606,6022,6023],{"align":5944},[16,6024,6025],{},"Organizational ROI",[1606,6027,6028],{"align":5944},"Is AI worth the investment?",[1606,6030,6031],{"align":5944},"License ROI, Team Benchmarks",[501,6033],{},[52,6035,6037],{"id":6036},"how-to-start-measuring-ai-impact-with-oobeya","How to Start Measuring AI Impact with Oobeya",[12,6039,6040],{},"You can begin today by activating Oobeya’s AI Coding Assistant Impact module. It provides the end-to-end visibility required for strategic AI governance:",[70,6042,6043,6046,6049,6052],{},[73,6044,6045],{},"Organization-wide AI usage visibility",[73,6047,6048],{},"Productivity and quality comparisons",[73,6050,6051],{},"Team-level benchmarks",[73,6053,6054],{},"ROI signals for strategic planning.",[501,6056],{},[3354,6058,6059],{},[12,6060,6061,6062,6067],{},"Ready to move beyond anecdotal evidence?\n",[16,6063,6064],{},[514,6065,5528],{"href":4082,"rel":6066},[518]," to see how Oobeya transforms your AI investment into measurable value.",{"title":526,"searchDepth":527,"depth":527,"links":6069},[6070,6071,6072,6073,6074,6075,6076,6077,6078],{"id":5566,"depth":530,"text":5567},{"id":5655,"depth":530,"text":5656},{"id":5715,"depth":530,"text":5716},{"id":5756,"depth":530,"text":5757},{"id":5805,"depth":530,"text":5806},{"id":5853,"depth":530,"text":5854},{"id":5885,"depth":530,"text":5886},{"id":5930,"depth":530,"text":5931},{"id":6036,"depth":530,"text":6037},[1898,4130],"2025-11-21","Measure AI coding assistant impact with a practical framework for adoption, productivity, quality, delivery, and ROI.",{},"\u002Fblog\u002Fai-measurement-framework",{"title":5561,"description":6081},"blog\u002Fai-measurement-framework",[1898,4130,4140,4843,1231],"jeenW9XKK_vaUq1AL0_Zsgamk7Elf48l27NOfcbEZNs",{"id":6089,"title":6090,"author":4245,"avatar":575,"body":6091,"categories":6445,"createAt":542,"date":6080,"description":6448,"extension":545,"meta":6449,"navigation":547,"path":6450,"position":4134,"seo":6451,"spotImage":542,"spotText":542,"stem":6452,"tags":6453,"__hash__":6456},"blog\u002Fblog\u002Foobeya-resource-allocation-insights.md","Where Is Your Engineering Time Going? Introducing Oobeya’s Resource Allocation Insights",{"type":9,"value":6092,"toc":6437},[6093,6099,6102,6109,6111,6115,6118,6121,6124,6152,6159,6161,6165,6168,6171,6185,6188,6190,6194,6197,6201,6204,6273,6276,6280,6283,6286,6290,6293,6295,6299,6302,6305,6348,6351,6353,6357,6363,6366,6397,6411,6413,6417,6420,6423,6426,6428],[12,6094,6095,6096],{},"Every engineering leader has asked the same critical question at some point: ",[16,6097,6098],{},"Where is all our development time going?",[12,6100,6101],{},"Teams are constantly busy, yet projects slip, priorities collide, and workloads feel uneven. The issue isn’t effort—it’s visibility.\nIn agile environments where priorities shift rapidly across projects and sprints, understanding how engineering time is actually allocated is more difficult than ever.",[12,6103,6104,6105,6108],{},"That’s why Oobeya is introducing the ",[16,6106,6107],{},"Resource Allocation module","—a data-driven way to visualize how engineering capacity is distributed across teams and projects.\nBy revealing where effort is really going, Oobeya empowers leaders to optimize workloads, balance priorities, and make confident decisions rooted in real data.",[501,6110],{},[52,6112,6114],{"id":6113},"the-challenge-why-engineering-resource-management-is-so-complex","The Challenge: Why Engineering Resource Management Is So Complex",[12,6116,6117],{},"Managing engineering resources in an agile organization is nothing like managing traditional departments.\nTeams are fluid, projects overlap, and priorities evolve sprint by sprint.",[12,6119,6120],{},"Without clear visibility into how time is split across different types of work—feature development, bug fixing, refactoring, or\ntechnical debt—it’s easy to lose alignment between what teams are doing and what the business needs.",[12,6122,6123],{},"Common challenges that obscure true resource allocation include:",[70,6125,6126,6134,6140,6146],{},[73,6127,6128,6133],{},[16,6129,6130,3444],{},[514,6131,6132],{"href":2034},"Overloaded or Underutilized Teams"," Some developers are stretched thin while others are waiting on dependencies.",[73,6135,6136,6139],{},[16,6137,6138],{},"Disconnected Tools:"," Jira, Azure Boards, and Git repositories all track work differently, fragmenting data.",[73,6141,6142,6145],{},[16,6143,6144],{},"Manual Reporting:"," Spreadsheets and ad hoc reports cannot keep pace with agile change, rendering insights immediately outdated.",[73,6147,6148,6151],{},[16,6149,6150],{},"Hidden Imbalances:"," Too much time going into unplanned work or maintenance drains innovation capacity.",[12,6153,6154,6155,6158],{},"In short, leaders have activity data—but not genuine ",[16,6156,6157],{},"allocation insight",". That’s the gap Oobeya’s Resource Allocation module was built to fill.",[501,6160],{},[52,6162,6164],{"id":6163},"introducing-oobeyas-resource-allocation-module-the-clarity-leaders-need","Introducing Oobeya’s Resource Allocation Module: The Clarity Leaders Need",[12,6166,6167],{},"The new Resource Allocation module gives engineering organizations a transparent view of where their teams’ time and effort\nare truly going—directly within Oobeya’s Software Engineering Intelligence platform.",[12,6169,6170],{},"The module automatically analyzes data from integrated agile tools (such as Jira or Azure Boards), calculating two key indicators for actionable planning:",[1520,6172,6173,6179],{},[73,6174,6175,6178],{},[16,6176,6177],{},"Resource Utilization %:"," How much of a team’s total capacity is being used.",[73,6180,6181,6184],{},[16,6182,6183],{},"Project Allocation %:"," How a team’s or contributor’s effort is distributed across projects.",[12,6186,6187],{},"By combining these two perspectives, Oobeya provides a comprehensive snapshot of engineering focus and workload.\nYou can instantly see which teams are optimally utilized, which are overloaded, and exactly where your resources are being invested.",[501,6189],{},[52,6191,6193],{"id":6192},"how-it-works-from-raw-data-to-actionable-insight","How It Works: From Raw Data to Actionable Insight",[12,6195,6196],{},"Oobeya’s Resource Allocation module leverages existing AgileSpace data and contributor information to calculate utilization and allocation metrics in real time.",[4331,6198,6200],{"id":6199},"_1-resource-utilization-detecting-imbalance-early","1. Resource Utilization %: Detecting Imbalance Early",[12,6202,6203],{},"This metric shows whether a team’s workload is balanced, stretched, or under capacity, allowing managers to intervene proactively:",[1585,6205,6206,6219],{},[1588,6207,6208],{},[1591,6209,6210,6213,6216],{},[1594,6211,6212],{"align":5944},"Utilization Range",[1594,6214,6215],{"align":5944},"Status",[1594,6217,6218],{"align":5944},"Risk\u002FAction",[1601,6220,6221,6234,6247,6260],{},[1591,6222,6223,6226,6231],{},[1606,6224,6225],{"align":5944},"\u003C= 85%",[1606,6227,6228],{"align":5944},[16,6229,6230],{},"Underutilized",[1606,6232,6233],{"align":5944},"Available capacity remains unused; opportunities for new work.",[1591,6235,6236,6239,6244],{},[1606,6237,6238],{"align":5944},"85% - 110%",[1606,6240,6241],{"align":5944},[16,6242,6243],{},"Optimal Utilization",[1606,6245,6246],{"align":5944},"Healthy workload distribution and sustainable pace.",[1591,6248,6249,6252,6257],{},[1606,6250,6251],{"align":5944},"110% - 130%",[1606,6253,6254],{"align":5944},[16,6255,6256],{},"Slightly Overloaded",[1606,6258,6259],{"align":5944},"Requires short-term adjustment to avoid strain.",[1591,6261,6262,6265,6270],{},[1606,6263,6264],{"align":5944},"> 130%",[1606,6266,6267],{"align":5944},[16,6268,6269],{},"Overloaded",[1606,6271,6272],{"align":5944},"High risk of burnout, delays, or quality issues.",[12,6274,6275],{},"By visualizing these values, Oobeya helps managers detect imbalance early—before it impacts delivery performance or developer experience.",[4331,6277,6279],{"id":6278},"_2-project-allocation-ensuring-alignment","2. Project Allocation %: Ensuring Alignment",[12,6281,6282],{},"This metric reflects how a contributor or team divides effort across multiple projects.\nIf a developer spends 60% of their capacity on Project A and 40% on Project B, leaders can instantly see that split in Oobeya’s dashboard.",[12,6284,6285],{},"This clarity ensures that strategic priorities stay aligned and critical initiatives receive the focused effort they deserve.",[4331,6287,6289],{"id":6288},"_3-excluding-irrelevant-work-types-for-precision","3. Excluding Irrelevant Work Types for Precision",[12,6291,6292],{},"To maintain analytical accuracy, Oobeya is designed to exclude certain high-level work item types (like epics or initiatives) from the calculation, focusing only on actionable, measurable work units.\nThis ensures precise, meaningful results that eliminate the guesswork around capacity planning.",[501,6294],{},[52,6296,6298],{"id":6297},"why-it-matters-visibility-that-drives-better-decisions","Why It Matters: Visibility That Drives Better Decisions",[12,6300,6301],{},"In 2025, engineering organizations are expected to deliver faster, more predictably, and with better alignment than ever before. But this is impossible without understanding the true flow of time.",[12,6303,6304],{},"With Oobeya’s Resource Allocation insights, leaders can:",[70,6306,6307,6313,6319,6325,6331],{},[73,6308,6309,6312],{},[16,6310,6311],{},"Balance Workloads Intelligently:"," Prevent overloads that harm code quality and morale.",[73,6314,6315,6318],{},[16,6316,6317],{},"Plan Capacity with Confidence:"," Base sprint and quarter planning on real historical utilization data.",[73,6320,6321,6324],{},[16,6322,6323],{},"Detect Misalignment Early:"," Know when too much effort is going into non-strategic or unplanned work.",[73,6326,6327,6330],{},[16,6328,6329],{},"Improve Developer Experience:"," Distribute work fairly and proactively avoid burnout across teams.",[73,6332,6333,6336,6337,6339,6340,6347],{},[16,6334,6335],{},"Connect Effort to Outcomes:"," Link resource allocation with ",[16,6338,3085],{}," and delivery performance metrics already tracked in Oobeya. (See: ",[791,6341,6342],{},[514,6343,6346],{"href":6344,"rel":6345},"https:\u002F\u002Fwww.oobeya.io\u002Fblog\u002Fkey-devops-metrics-beyond-dora",[518],"Key DevOps Metrics Beyond DORA",")",[12,6349,6350],{},"This level of transparency fundamentally transforms how organizations plan, prioritize, and deliver value.",[501,6352],{},[52,6354,6356],{"id":6355},"how-oobeya-stands-apart-from-work-items-to-effort","How Oobeya Stands Apart: From Work Items to Effort",[12,6358,6359,6360],{},"While traditional agile tools show only static work items, ",[16,6361,6362],{},"Oobeya also shows effort.",[12,6364,6365],{},"By combining real-time allocation data with its broader Software Engineering Intelligence ecosystem, Oobeya delivers context other platforms cannot:",[70,6367,6368,6374,6387],{},[73,6369,6370,6373],{},[16,6371,6372],{},"Unified Visibility:"," See capacity and allocation across all agile projects and integrated systems.",[73,6375,6376,6379,6380,6347],{},[16,6377,6378],{},"Integrated Engineering Metrics:"," Connect resource data with DORA, Developer Experience, and productivity indicators. (Reference: ",[791,6381,6382],{},[514,6383,6386],{"href":6384,"rel":6385},"https:\u002F\u002Fwww.oobeya.io\u002Fblog\u002Fdeveloper-productivity-insight-platforms-in-2025",[518],"Developer Productivity Insight Platforms in 2025",[73,6388,6389,6392,6393,6396],{},[16,6390,6391],{},"Automatic Inefficiency Detection:"," When used with the ",[16,6394,6395],{},"Symptoms Module",", Oobeya highlights exactly where over-allocation is causing rework, lead-time spikes, or burnout.",[12,6398,6399,6400,6402,6403,6406,6407,6410],{},"It’s the clarity engineering leaders have been missing—the ability to connect ",[16,6401,5662],{}," is working on ",[16,6404,6405],{},"what"," with ",[16,6408,6409],{},"how"," it impacts performance.",[501,6412],{},[52,6414,6416],{"id":6415},"conclusion-from-guesswork-to-clarity","Conclusion: From Guesswork to Clarity",[12,6418,6419],{},"In agile engineering, time is your most valuable resource. Without visibility, it’s impossible to know if that time is being spent wisely.",[12,6421,6422],{},"Oobeya’s Resource Allocation module gives leaders a clear, data-driven picture of engineering focus—helping them make smarter, fairer, and more effective decisions.",[12,6424,6425],{},"When you can see how your teams are truly allocated, you can plan confidently, support your developers, and deliver faster.",[501,6427],{},[12,6429,6430,6431],{},"See how Oobeya helps engineering leaders visualize and optimize their teams’ focus. ",[16,6432,6433],{},[514,6434,6436],{"href":4082,"rel":6435},[518],"Book a demo today.",{"title":526,"searchDepth":527,"depth":527,"links":6438},[6439,6440,6441,6442,6443,6444],{"id":6113,"depth":530,"text":6114},{"id":6163,"depth":530,"text":6164},{"id":6192,"depth":530,"text":6193},{"id":6297,"depth":530,"text":6298},{"id":6355,"depth":530,"text":6356},{"id":6415,"depth":530,"text":6416},[6446,6447],"team-health","allocation","See where engineering time goes with Oobeya Resource Allocation insights for team capacity, project focus, and utilization.",{},"\u002Fblog\u002Foobeya-resource-allocation-insights",{"title":6090,"description":6448},"blog\u002Foobeya-resource-allocation-insights",[540,6454,1231,6455],"resource-allocation","engineering-utilization","YS09iWkXhk14LZ7eNw65i2Hn2LQPDXc5pTCRfekQcUo",{"id":6458,"title":6459,"author":6,"avatar":7,"body":6460,"categories":6687,"createAt":542,"date":6688,"description":6689,"extension":545,"meta":6690,"navigation":547,"path":6691,"position":4134,"seo":6692,"spotImage":542,"spotText":542,"stem":6693,"tags":6694,"__hash__":6695},"blog\u002Fblog\u002Foobeya-and-poldynamic-announce-strategic-partnership.md","Oobeya and PolDynamic Announce Strategic Partnership to Accelerate Software Engineering Efficiency in Poland and EMEA",{"type":9,"value":6461,"toc":6679},[6462,6483,6489,6491,6495,6498,6509,6519,6521,6525,6528,6565,6573,6582,6584,6588,6634,6636,6640,6658,6660,6662,6673],[12,6463,6464,4855,6467,6472,6473,6478,6479,6482],{},[16,6465,6466],{},"Warsaw, Poland — October, 2025",[514,6468,6471],{"href":6469,"target":6470},"https:\u002F\u002Fpoldynamic.com","_blank","PolDynamic",", a trusted Warsaw-based IT services company and enterprise software reseller,\nhas partnered with ",[514,6474,6476],{"href":5051,"rel":6475},[518],[16,6477,469],{},", a leading ",[16,6480,6481],{},"Developer Productivity Platform",", to help organizations across Poland and the EMEA region\ngain end-to-end visibility into their software delivery lifecycle and improve productivity and cost-effectiveness at scale.",[12,6484,6485],{},[4866,6486],{"alt":6487,"src":6488},"Oobeya and PolDynamic Announce Partnership for Poland and EMEA","\u002Fassets\u002Fblog\u002Fpoldynamic-oobeya-partnership.png",[501,6490],{},[613,6492,6494],{"id":6493},"helping-cios-and-engineering-leaders-drive-measurable-outcomes","Helping CIOs and Engineering Leaders Drive Measurable Outcomes",[12,6496,6497],{},"This partnership combines PolDynamic’s strong relationships with enterprise technology leaders and expertise in delivering and supporting developer and DevOps tools\nwith Oobeya’s advanced engineering intelligence capabilities. Together, the companies will help CIOs, CTOs, and engineering leaders identify inefficiencies,\nmeasure performance across teams, and accelerate continuous improvement.",[3354,6499,6500],{},[12,6501,6502,6503,6505,6506],{},"“At PolDynamic, we see productivity and cost-effectiveness as top priorities for every technology leader in Poland. Partnering with Oobeya enables us to deliver a proven solution that helps organizations measure and optimize their engineering operations with real data and real impact.”",[4531,6504],{},"\n— ",[16,6507,6508],{},"Andrzej (Andrew) Stobierski, Founder, PolDynamic",[3354,6510,6511],{},[12,6512,6513,6514,6505,6516],{},"“PolDynamic’s trusted relationships with enterprise IT managers and their deep understanding of the Polish market make them an ideal partner for Oobeya. Together, we’ll help organizations enhance SDLC visibility, productivity, and performance across software development and delivery.”",[4531,6515],{},[16,6517,6518],{},"Sukru Cakmak, Co-Founder, Oobeya",[501,6520],{},[613,6522,6524],{"id":6523},"driving-engineering-efficiency-across-the-sdlc","Driving Engineering Efficiency Across the SDLC",[12,6526,6527],{},"Through this partnership, enterprises will gain access to:",[70,6529,6530,6536,6549,6559],{},[73,6531,6532,6535],{},[16,6533,6534],{},"Comprehensive visibility"," across all SDLC stages — from code to deployments, testing, quality, and operations",[73,6537,6538,6541,6542,247,6547],{},[16,6539,6540],{},"Accurate productivity and efficiency insights"," using industry-standard metrics such as ",[16,6543,6544],{},[514,6545,3085],{"href":3620,"rel":6546},[518],[16,6548,2874],{},[73,6550,6551,247,6554,6558],{},[16,6552,6553],{},"Proactive detection of bottlenecks",[514,6555,6557],{"href":6556,"target":6470},"https:\u002F\u002Fdocs.oobeya.io\u002Fuse-cases\u002Fproactive-issue-detection","actionable recommendations"," for improvement",[73,6560,6561,6564],{},[16,6562,6563],{},"Unified reporting and benchmarking"," across tools, teams, and business units",[12,6566,6567,6568,247,6570,6572],{},"Together, ",[16,6569,469],{},[16,6571,6471],{}," will enable engineering organizations to reduce waste, improve delivery speed, and make smarter, data-driven decisions that maximize ROI.",[12,6574,6575,6576,6581],{},"To continue these conversations in person, join us during the ",[514,6577,6580],{"href":6578,"rel":6579},"https:\u002F\u002Foobeya.io\u002Fevents\u002Fpoland-2026",[518],"Oobeya Poland Tour 2026",", where we will be meeting CIOs, CTOs, and engineering leaders across Warsaw and Krakow.",[501,6583],{},[52,6585,6587],{"id":6586},"oobeyas-unique-approach","Oobeya’s Unique Approach",[70,6589,6590,6601,6607,6613,6619,6625],{},[73,6591,6592,6595,6596,6600],{},[16,6593,6594],{},"Drives a culture of productivity"," – embeds ",[514,6597,6599],{"href":6598,"target":6470},"https:\u002F\u002Fdocs.oobeya.io\u002Fuse-cases\u002Fgamification-for-engineering-kpis","Gamification"," and continuous improvement to make performance growth engaging and sustainable.",[73,6602,6603,6606],{},[16,6604,6605],{},"Turns measurement into action"," – every metric is actionable, enabling teams to measure, analyze, and immediately implement changes.",[73,6608,6609,6612],{},[16,6610,6611],{},"Boosts developer engagement"," – promotes transparency and shared ownership through open visibility of key metrics.",[73,6614,6615,6618],{},[16,6616,6617],{},"Creates a common language through data"," – bridges Developers, Managers, and Executives by turning metrics into an effective communication and alignment tool.",[73,6620,6621,6624],{},[16,6622,6623],{},"Customizable to client needs"," – Oobeya partners closely with organizations to develop tailored features and integrations.",[73,6626,6627,6630,6631,6633],{},[16,6628,6629],{},"Flexible deployment: On-Prem and SaaS"," – ",[514,6632,5460],{"href":4952}," is particularly valued in highly regulated industries such as banking, insurance, and government.",[501,6635],{},[52,6637,6639],{"id":6638},"about-poldynamic","About PolDynamic",[12,6641,6642,6647,6648,6650,6651,6653,6654,611],{},[514,6643,6645],{"href":6469,"rel":6644},[518],[16,6646,6471],{}," is a Warsaw-based IT services company specializing in enterprise software reselling and digital transformation solutions.",[4531,6649],{},"\nWith strong ties to CIOs and IT managers across Poland and EMEA, PolDynamic helps organizations boost developer productivity, streamline software delivery,\nand achieve measurable performance improvements.",[4531,6652],{},"\nLearn more at ",[514,6655,6657],{"href":6469,"rel":6656},[518],"poldynamic.com",[501,6659],{},[52,6661,5020],{"id":5019},[12,6663,6664,6669,6670,6672],{},[514,6665,6667],{"href":5051,"rel":6666},[518],[16,6668,469],{}," is a Developer Productivity Platform that helps enterprises improve productivity, quality, and developer experience across their software organizations.",[4531,6671],{},"\nRecognized by Gartner as a Representative Provider in the SEIP market and a multi-category leader on G2, Oobeya unifies metrics from the entire software delivery\nlifecycle—covering code, issues, deployments, quality, and operations —into one actionable, AI-powered platform.",[12,6674,6675,6676,611],{},"By going beyond dashboards, Oobeya detects “symptoms” of unhealthy practices and provides AI-powered recommendations that empower engineering leaders\nto make better decisions, foster healthier teams, and accelerate delivery at scale.\nLearn more at ",[514,6677,5053],{"href":5051,"rel":6678},[518],{"title":526,"searchDepth":527,"depth":527,"links":6680},[6681,6682],{"id":6493,"depth":527,"text":6494},{"id":6523,"depth":527,"text":6524,"children":6683},[6684,6685,6686],{"id":6586,"depth":530,"text":6587},{"id":6638,"depth":530,"text":6639},{"id":5019,"depth":530,"text":5020},[4232,1231,540],"2025-10-30","Oobeya and PolDynamic partner to improve software engineering visibility, productivity, and decision-making across Poland and EMEA.",{},"\u002Fblog\u002Foobeya-and-poldynamic-announce-strategic-partnership",{"title":6459,"description":6689},"blog\u002Foobeya-and-poldynamic-announce-strategic-partnership",[4232,1231,540],"0yBSVn91FU9fQToKRYavBmxooVEgtAR-FME3YYXT9gI",{"id":6697,"title":6698,"author":4245,"avatar":575,"body":6699,"categories":7369,"createAt":542,"date":7372,"description":7373,"extension":545,"meta":7374,"navigation":547,"path":7375,"position":4134,"seo":7376,"spotImage":542,"spotText":542,"stem":7377,"tags":7378,"__hash__":7380},"blog\u002Fblog\u002Fsymptoms-and-engineering-kpis.md","Symptoms and KPIs: A Better Way to Improve Developer Experience in 2025",{"type":9,"value":6700,"toc":7344},[6701,6704,6724,6727,6747,6749,6753,6769,6783,6786,6797,6806,6808,6812,6829,6832,6862,6872,6874,6878,6886,6893,6912,6916,6988,7002,7004,7008,7021,7040,7043,7074,7076,7080,7090,7094,7101,7112,7114,7118,7125,7136,7138,7142,7145,7156,7158,7162,7170,7174,7177,7181,7191,7195,7198,7211,7215,7218,7222,7225,7227,7231,7237,7265,7268,7270,7272,7294,7304,7306,7310,7318,7320,7324],[12,6702,6703],{},"How can engineering leaders ensure a consistently high-quality Developer Experience (DevEx) in a distributed and complex software engineering world?",[12,6705,6706,6707,23,6710,23,6713,27,6716,6719,6720,6723],{},"DevEx is more than a feel-good metric — it directly impacts ",[16,6708,6709],{},"productivity",[16,6711,6712],{},"delivery velocity",[16,6714,6715],{},"quality",[16,6717,6718],{},"retention",". Yet most teams still rely on ",[16,6721,6722],{},"lagging indicators"," or scattered signals to understand how developers are doing.",[12,6725,6726],{},"What if there was a better, more actionable approach?",[12,6728,6729,6730,6406,6733,6736,6737,6742,6743,6746],{},"In 2025, progressive engineering organizations are combining ",[16,6731,6732],{},"automatically detected Symptoms",[16,6734,6735],{},"team- and individual-level KPIs"," to continuously monitor and improve DevEx. This approach, pioneered by ",[16,6738,6739],{},[514,6740,469],{"href":516,"rel":6741},[518],", offers engineering leaders ",[16,6744,6745],{},"real-time visibility"," into the friction points developers face — and clear, data-driven paths to fix them.",[501,6748],{},[613,6750,6752],{"id":6751},"understanding-developer-experience-in-2025","Understanding Developer Experience in 2025",[12,6754,6755,6756,23,6759,23,6762,27,6765,6768],{},"Developer Experience refers to how developers interact with their ",[16,6757,6758],{},"tools",[16,6760,6761],{},"systems",[16,6763,6764],{},"teams",[16,6766,6767],{},"processes",". A strong DevEx correlates with:",[70,6770,6771,6774,6777,6780],{},[73,6772,6773],{},"Higher engagement",[73,6775,6776],{},"Faster delivery",[73,6778,6779],{},"Better code quality",[73,6781,6782],{},"Lower turnover.",[12,6784,6785],{},"Historically, DevEx has been measured through surveys or manual feedback. While useful, these methods:",[70,6787,6788,6791,6794],{},[73,6789,6790],{},"Don’t scale",[73,6792,6793],{},"Can be biased",[73,6795,6796],{},"Fail to deliver real-time insight.",[12,6798,6799,6800,42,6803,611],{},"The 2025 trend is toward quantifiable, observable, and real-time signals — moving from ",[791,6801,6802],{},"intuition",[16,6804,6805],{},"insight",[501,6807],{},[613,6809,6811],{"id":6810},"why-traditional-kpis-alone-arent-enough","Why Traditional KPIs Alone Aren’t Enough",[12,6813,6814,6815,23,6817,6819,6820,6822,6823,6825,6826,611],{},"KPIs like ",[16,6816,3042],{},[16,6818,3048],{},", or ",[16,6821,3551],{}," are essential. But they mostly tell you ",[16,6824,6405],{}," is happening, not ",[16,6827,6828],{},"why",[12,6830,6831],{},"When performance drops, leaders are left guessing:",[70,6833,6834,6841,6850,6856],{},[73,6835,6836,6837,6840],{},"Is it due to ",[16,6838,6839],{},"high cognitive load","?",[73,6842,6843,6844,5502,6847,6840],{},"Too much ",[16,6845,6846],{},"rework",[16,6848,6849],{},"poor code quality",[73,6851,6852,6855],{},[16,6853,6854],{},"Bottlenecks"," in reviews or CI\u002FCD?",[73,6857,6858,6861],{},[16,6859,6860],{},"Weekend activity"," indicating burnout?",[12,6863,6864,6865,6868,6869,611],{},"Without ",[16,6866,6867],{},"root-cause visibility",", fixes risk being ",[16,6870,6871],{},"misdirected",[501,6873],{},[613,6875,6877],{"id":6876},"introducing-symptoms-diagnosing-devex-issues-automatically","Introducing Symptoms: Diagnosing DevEx Issues Automatically",[12,6879,2208,6880,6885],{},[16,6881,6882],{},[514,6883,910],{"href":6556,"rel":6884},[518]," come in.",[12,6887,6888,6889,6892],{},"In engineering, a ",[791,6890,6891],{},"symptom"," is an observable pattern that suggests something might be going wrong — or is about to.",[12,6894,5642,6895,6897,6898,23,6901,23,6903,23,6906,23,6909,6911],{},[16,6896,6395],{}," detects these patterns automatically by analyzing activity across ",[16,6899,6900],{},"Jira",[16,6902,4528],{},[16,6904,6905],{},"Azure DevOps",[16,6907,6908],{},"GitLab",[16,6910,5120],{},", and more.",[52,6913,6915],{"id":6914},"examples-of-symptoms-oobeya-detects","Examples of Symptoms Oobeya Detects",[70,6917,6918,6928,6938,6948,6958,6968,6978],{},[73,6919,6920,6927],{},[16,6921,6922],{},[514,6923,6926],{"href":6924,"rel":6925},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs4-high-code-review-time\u002F",[518],"High Code Review Time"," – Indicates slow feedback loops and potential delays",[73,6929,6930,6937],{},[16,6931,6932],{},[514,6933,6936],{"href":6934,"rel":6935},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs2-recurring-high-rework-rate\u002F",[518],"Recurring High Rework Rate"," – Suggests unclear requirements or unstable code",[73,6939,6940,6947],{},[16,6941,6942],{},[514,6943,6946],{"href":6944,"rel":6945},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs9-unreviewed-pull-requests\u002F",[518],"Unreviewed Pull Requests"," – Risks to quality and context-sharing",[73,6949,6950,6957],{},[16,6951,6952],{},[514,6953,6956],{"href":6954,"rel":6955},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs3-high-weekend-activity\u002F",[518],"High Weekend Activity"," – Signs of burnout or poor planning",[73,6959,6960,6967],{},[16,6961,6962],{},[514,6963,6966],{"href":6964,"rel":6965},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs5-high-technical-debt-on-sonar\u002F",[518],"High Technical Debt on Sonar"," – Long-term maintainability risk",[73,6969,6970,6977],{},[16,6971,6972],{},[514,6973,6976],{"href":6974,"rel":6975},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs11-oversize-pull-requests\u002F",[518],"Oversized Pull Requests"," – Harder to review, more error-prone",[73,6979,6980,6987],{},[16,6981,6982],{},[514,6983,6986],{"href":6984,"rel":6985},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs1-recurring-high-cognitive-load\u002F",[518],"Recurring High Cognitive Load"," – Reduces focus and increases fatigue",[12,6989,6990,6991,6994,6995,6998,6999,611],{},"By tracking dozens of these symptoms ",[16,6992,6993],{},"in real time",", leaders can ",[16,6996,6997],{},"connect KPIs to root causes"," — turning metrics into ",[16,7000,7001],{},"actionable insight",[501,7003],{},[613,7005,7007],{"id":7006},"how-symptoms-kpis-drive-developer-experience","How Symptoms + KPIs Drive Developer Experience",[12,7009,7010,7011,6406,7014,7017,7018,3444],{},"Pairing ",[16,7012,7013],{},"high-level KPIs",[16,7015,7016],{},"symptom detection"," gives the ",[16,7019,7020],{},"full picture",[70,7022,7023,7029,7034],{},[73,7024,7025,7028],{},[16,7026,7027],{},"KPI"," → “Deployment Frequency dropped 30%”",[73,7030,7031,7033],{},[16,7032,910],{}," → “Code review times spiked” + “Oversized PRs increased”",[73,7035,7036,7039],{},[16,7037,7038],{},"Action"," → Improve review process, encourage smaller PRs, adjust priorities",[12,7041,7042],{},"This approach enables:",[70,7044,7045,7056,7062,7068],{},[73,7046,7047,7050,7051,7053,7054],{},[16,7048,7049],{},"Faster Root Cause Analysis"," – See ",[791,7052,6828],{},", not just ",[791,7055,6405],{},[73,7057,7058,7061],{},[16,7059,7060],{},"Preventative Action"," – Catch early warning signs before KPIs degrade",[73,7063,7064,7067],{},[16,7065,7066],{},"Personalized Coaching"," – Targeted feedback based on real friction points",[73,7069,7070,7073],{},[16,7071,7072],{},"Objective Conversations"," – Data-driven improvement discussions",[501,7075],{},[613,7077,7079],{"id":7078},"using-symptoms-inside-the-oobeya-gamification-module","Using Symptoms Inside the Oobeya Gamification Module",[12,7081,7082,7083,7089],{},"Symptoms aren’t only for diagnostics — they can also be part of ",[16,7084,7085],{},[514,7086,7088],{"href":7087},"\u002Fblog\u002Fgamification-and-engineerin-kpis","Oobeya’s Gamification for Engineering KPIs"," to drive motivation and improvement.",[52,7091,7093],{"id":7092},"example-selecting-symptoms-in-league-setup","Example: Selecting Symptoms in League Setup",[12,7095,7096,7097,7100],{},"In ",[16,7098,7099],{},"League Setup",", leaders can select which Symptoms to include in performance scoring.",[12,7102,7103,7107,7109],{},[4866,7104],{"alt":7105,"src":7106},"Oobeya Gamification League Setup - Selecting Engineering Symptoms","\u002Fassets\u002Fblog\u002Foobeya-gamification-league-setup-symptoms.png",[4531,7108],{},[791,7110,7111],{},"Selecting key engineering Symptoms such as High Code Review Time, Recurring High Cognitive Load, and Unreviewed Pull Requests for KPI scoring in Oobeya's Gamification module.",[501,7113],{},[52,7115,7117],{"id":7116},"example-kpi-scoring-for-symptoms","Example: KPI Scoring for Symptoms",[12,7119,7120,7121,7124],{},"Once Symptoms are selected, you can assign ",[16,7122,7123],{},"point values"," for when they occur or do not occur.",[12,7126,7127,7131,7133],{},[4866,7128],{"alt":7129,"src":7130},"Oobeya Gamification KPI Scoring for Developer Experience Symptoms","\u002Fassets\u002Fblog\u002Foobeya-gamification-kpi-scoring-symptoms.png",[4531,7132],{},[791,7134,7135],{},"Assigning points for Recurring High Cognitive Load and other engineering Symptoms in Oobeya’s Gamification module.",[501,7137],{},[52,7139,7141],{"id":7140},"example-automated-symptom-tracking","Example: Automated Symptom Tracking",[12,7143,7144],{},"Oobeya automatically tracks the occurrence of each Symptom, allowing leaders to see trends without manual data collection.",[12,7146,7147,7151,7153],{},[4866,7148],{"alt":7149,"src":7150},"Oobeya Automated Symptom Tracking Table for Engineering KPIs","\u002Fassets\u002Fblog\u002Foobeya-symptom-tracking-kpi-table.png",[4531,7152],{},[791,7154,7155],{},"Automated tracking of Symptoms such as High Weekend Activity, Oversized Pull Requests, and High Change Failure Rate for continuous engineering performance monitoring.",[501,7157],{},[613,7159,7161],{"id":7160},"how-oobeya-powers-this-transformation","How Oobeya Powers This Transformation",[12,7163,5642,7164,247,7166,7169],{},[16,7165,6395],{},[16,7167,7168],{},"KPI tracking"," work together to deliver:",[52,7171,7173],{"id":7172},"_1-automatic-detection-of-bottlenecks-anti-patterns","1. Automatic Detection of Bottlenecks & Anti-Patterns",[12,7175,7176],{},"Monitors cognitive load, rework, review practices, risky deployments, and more.",[52,7178,7180],{"id":7179},"_2-real-time-cross-platform-analysis","2. Real-Time, Cross-Platform Analysis",[12,7182,7183,7184,7190],{},"Unifies data across planning, coding, CI\u002FCD, and quality tools for accurate ",[16,7185,7186],{},[514,7187,848],{"href":7188,"rel":7189},"https:\u002F\u002Foobeya.io\u002Fdora-metrics-four-key\u002F",[518]," and context.",[52,7192,7194],{"id":7193},"_3-continuous-kpi-monitoring","3. Continuous KPI Monitoring",[12,7196,7197],{},"Automatically calculates:",[70,7199,7200,7202,7205,7208],{},[73,7201,3261],{},[73,7203,7204],{},"Developer Experience Metrics",[73,7206,7207],{},"Code Quality Metrics",[73,7209,7210],{},"Agile Delivery Metrics",[52,7212,7214],{"id":7213},"_4-actionable-role-based-insights","4. Actionable, Role-Based Insights",[12,7216,7217],{},"Tailors insights to the organization, team, or individual level.",[52,7219,7221],{"id":7220},"_5-trend-tracking","5. Trend Tracking",[12,7223,7224],{},"Shows whether DevEx is improving over time and which interventions work.",[501,7226],{},[613,7228,7230],{"id":7229},"best-practices-for-leaders-in-2025","Best Practices for Leaders in 2025",[12,7232,7233,7234,3444],{},"To maximize value from ",[16,7235,7236],{},"Symptoms + KPIs",[70,7238,7239,7245,7252,7258],{},[73,7240,7241,7242],{},"Instrument workflows with ",[16,7243,7244],{},"integrated visibility tools",[73,7246,7247,7248,7251],{},"Use ",[16,7249,7250],{},"automated detection"," to replace manual guesswork",[73,7253,7254,7255],{},"Share insights to ",[16,7256,7257],{},"spark curiosity, not fear",[73,7259,7260,7261,7264],{},"Track ",[16,7262,7263],{},"DevEx improvement goals"," over time",[12,7266,7267],{},"Shift from reactive to preventive, from anecdote to insight.",[501,7269],{},[613,7271,1159],{"id":477},[12,7273,7274,7275,611,7278,7280,7281,6406,7283,7286,7287,7290,7291,611],{},"Improving Developer Experience is now a ",[16,7276,7277],{},"strategic imperative",[4531,7279],{},"\nBy pairing ",[16,7282,7168],{},[16,7284,7285],{},"automatic symptom detection",", leaders gain the ",[16,7288,7289],{},"diagnostic clarity"," needed to reduce friction, unblock teams, and build a ",[16,7292,7293],{},"high-performance culture",[12,7295,3617,7296,7303],{},[16,7297,7298],{},[514,7299,7302],{"href":7300,"rel":7301},"https:\u002F\u002Foobeya.io\u002Fsymptoms\u002F",[518],"Oobeya Symptoms Module"," delivers real-time detection, accurate metrics, and tailored insights — empowering leaders to act with precision.",[501,7305],{},[613,7307,7309],{"id":7308},"ready-to-improve-your-devex","Ready to Improve Your DevEx?",[12,7311,7312,7317],{},[514,7313,7315],{"href":4082,"rel":7314},[518],[16,7316,5528],{}," to see how Symptoms + KPIs can help your teams perform better, deliver faster, and work happier.",[501,7319],{},[52,7321,7323],{"id":7322},"related-resources","Related Resources",[70,7325,7326,7332,7338],{},[73,7327,7328],{},[514,7329,6386],{"href":7330,"rel":7331},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fdeveloper-productivity-insight-platforms-in-2025\u002F",[518],[73,7333,7334],{},[514,7335,6346],{"href":7336,"rel":7337},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fkey-devops-metrics-beyond-dora\u002F",[518],[73,7339,7340],{},[514,7341,7343],{"href":6556,"rel":7342},[518],"Proactive Engineering Issue Detection",{"title":526,"searchDepth":527,"depth":527,"links":7345},[7346,7347,7348,7351,7352,7357,7364,7365,7366],{"id":6751,"depth":527,"text":6752},{"id":6810,"depth":527,"text":6811},{"id":6876,"depth":527,"text":6877,"children":7349},[7350],{"id":6914,"depth":530,"text":6915},{"id":7006,"depth":527,"text":7007},{"id":7078,"depth":527,"text":7079,"children":7353},[7354,7355,7356],{"id":7092,"depth":530,"text":7093},{"id":7116,"depth":530,"text":7117},{"id":7140,"depth":530,"text":7141},{"id":7160,"depth":527,"text":7161,"children":7358},[7359,7360,7361,7362,7363],{"id":7172,"depth":530,"text":7173},{"id":7179,"depth":530,"text":7180},{"id":7193,"depth":530,"text":7194},{"id":7213,"depth":530,"text":7214},{"id":7220,"depth":530,"text":7221},{"id":7229,"depth":527,"text":7230},{"id":477,"depth":527,"text":1159},{"id":7308,"depth":527,"text":7309,"children":7367},[7368],{"id":7322,"depth":530,"text":7323},[7370,1259,7371,2620,1231],"gamificaiton","symptoms","2025-08-13","Discover how combining KPI tracking with automatic symptom detection can transform developer experience and performance in 2025.",{},"\u002Fblog\u002Fsymptoms-and-engineering-kpis",{"title":6698,"description":7373},"blog\u002Fsymptoms-and-engineering-kpis",[7370,7379,7371,1231,2620],"engineerign-kpis","6IeyVHbIcw5eMtxKTHgujrgJ46Bd7jAWTAWRMPGCQIA",{"id":7382,"title":7383,"author":4245,"avatar":575,"body":7384,"categories":7796,"createAt":542,"date":7797,"description":7798,"extension":545,"meta":7799,"navigation":547,"path":7087,"position":4134,"seo":7800,"spotImage":542,"spotText":542,"stem":7801,"tags":7802,"__hash__":7803},"blog\u002Fblog\u002Fgamification-and-engineerin-kpis.md","Gamification and Engineering KPIs: A Data-Driven Strategy for Team Performance in 2025",{"type":9,"value":7385,"toc":7779},[7386,7393,7396,7398,7402,7407,7411,7437,7440,7442,7446,7449,7453,7485,7491,7493,7497,7500,7541,7549,7555,7557,7561,7564,7602,7608,7610,7614,7624,7628,7685,7694,7696,7698,7705,7708,7728,7734,7736,7740,7748,7750,7754],[12,7387,7388,7389,7392],{},"In 2025, the pressure to deliver high-performing, innovative software teams has never been greater. Engineering leaders are expected to manage not only delivery velocity but also team alignment, quality, and developer well-being. As responsibilities grow more complex, performance tracking must evolve — and this is where ",[16,7390,7391],{},"gamification"," plays a vital role.",[12,7394,7395],{},"Gamification isn’t about turning work into play. It’s about using motivational techniques and transparent feedback loops to foster accountability, drive improvement, and enable data-driven coaching. When paired with Engineering KPIs, it becomes a powerful strategy for optimizing performance.",[501,7397],{},[613,7399,7401],{"id":7400},"what-is-gamification-in-software-engineering","What Is Gamification in Software Engineering?",[12,7403,7404,7406],{},[16,7405,6599],{}," refers to applying game design elements — such as goals, feedback, competition, and rewards — to non-game contexts. In software engineering, it means helping teams engage with their performance metrics in a transparent, collaborative, and motivating way.",[52,7408,7410],{"id":7409},"examples-of-gamification-in-engineering","Examples of Gamification in Engineering:",[70,7412,7413,7419,7425,7431],{},[73,7414,7415,7418],{},[16,7416,7417],{},"Scorecards"," that track team KPIs in real-time",[73,7420,7421,7424],{},[16,7422,7423],{},"Leaderboards"," that compare performance across teams",[73,7426,7427,7430],{},[16,7428,7429],{},"Achievement tracking"," (e.g., reducing cycle time below a threshold)",[73,7432,7433,7436],{},[16,7434,7435],{},"Streak milestones"," for continuous improvement",[12,7438,7439],{},"However, gamification only works when grounded in real-time data, fair comparisons, and meaningful KPIs that align with engineering performance goals.",[501,7441],{},[613,7443,7445],{"id":7444},"why-gamification-matters-for-engineering-leaders-in-2025","Why Gamification Matters for Engineering Leaders in 2025",[12,7447,7448],{},"With distributed teams and increasingly complex delivery pipelines, leaders need better tools for visibility, alignment, and performance management.",[52,7450,7452],{"id":7451},"key-benefits","Key Benefits:",[70,7454,7455,7461,7467,7473,7479],{},[73,7456,7457,7460],{},[16,7458,7459],{},"Data Transparency",": Real-time insight into individual and team performance",[73,7462,7463,7466],{},[16,7464,7465],{},"Alignment",": Shared KPIs help teams align on what success looks like",[73,7468,7469,7472],{},[16,7470,7471],{},"Ownership",": Developers take more responsibility when they see their impact",[73,7474,7475,7478],{},[16,7476,7477],{},"Better Coaching",": Leaders can identify trends and coach without micromanaging",[73,7480,7481,7484],{},[16,7482,7483],{},"Higher Engagement",": Teams stay motivated by seeing and celebrating progress",[12,7486,7487,7488,611],{},"For more on this shift, see ",[514,7489,6386],{"href":7330,"rel":7490},[518],[501,7492],{},[613,7494,7496],{"id":7495},"which-kpis-should-be-gamified","Which KPIs Should Be Gamified?",[12,7498,7499],{},"While each organization has unique metrics, the following are especially effective for gamification:",[70,7501,7502,7507,7513,7519,7524,7530,7535],{},[73,7503,7504,7506],{},[16,7505,807],{},": Reinforces lean development practices",[73,7508,7509,7512],{},[16,7510,7511],{},"Pull Request Throughput",": Encourages consistent contributions",[73,7514,7515,7518],{},[16,7516,7517],{},"Code Review Responsiveness",": Promotes faster, more collaborative reviews",[73,7520,7521,7523],{},[16,7522,825],{},": Drives fast, iterative delivery",[73,7525,7526,7529],{},[16,7527,7528],{},"Bug Resolution Time",": Focuses teams on quality and responsiveness",[73,7531,7532,7534],{},[16,7533,7204],{},": Includes satisfaction scores and feedback loops",[73,7536,7537,7540],{},[16,7538,7539],{},"Comparative Metrics",": Enables benchmarking across teams or projects",[3354,7542,7543],{},[12,7544,7545,7548],{},[16,7546,7547],{},"Note",": Gamification should never shame individuals. It's about team context, improvement, and insight — not pressure.",[12,7550,7551,7552,611],{},"For more on which KPIs matter, check out ",[514,7553,6346],{"href":7336,"rel":7554},[518],[501,7556],{},[613,7558,7560],{"id":7559},"best-practices-for-gamifying-engineering-metrics","Best Practices for Gamifying Engineering Metrics",[12,7562,7563],{},"Done right, gamification empowers teams. Done wrong, it can create stress or mistrust. Follow these principles for success:",[70,7565,7566,7572,7578,7584,7590,7596],{},[73,7567,7568,7571],{},[16,7569,7570],{},"Make Metrics Meaningful",": Tie gamified metrics to real outcomes",[73,7573,7574,7577],{},[16,7575,7576],{},"Keep It Team-Centric",": Promote collaboration over individual rivalry",[73,7579,7580,7583],{},[16,7581,7582],{},"Normalize Comparisons",": Account for team size and complexity",[73,7585,7586,7589],{},[16,7587,7588],{},"Provide Frequent Feedback",": Weekly or real-time updates keep teams engaged",[73,7591,7592,7595],{},[16,7593,7594],{},"Celebrate Wins",": Recognize achievements in retros, dashboards, or meetings",[73,7597,7598,7601],{},[16,7599,7600],{},"Enable Action",": Supplement scores with improvement suggestions",[12,7603,7604,7605,611],{},"Oobeya makes this easy by offering real-time data and contextual insights through modules like Team Scorecards and ",[514,7606,910],{"href":7300,"rel":7607},[518],[501,7609],{},[613,7611,7613],{"id":7612},"how-oobeyas-gamification-module-elevates-kpi-monitoring","How Oobeya’s Gamification Module Elevates KPI Monitoring",[12,7615,7616,7617,7619,7620,7623],{},"At ",[16,7618,469],{},", we believe performance tracking should be ",[16,7621,7622],{},"visible, fair, and actionable"," — and our Gamification Module is designed with these principles in mind.",[52,7625,7627],{"id":7626},"key-features","Key Features:",[70,7629,7630,7642,7650,7658,7670],{},[73,7631,7632,7635,7637,7638,7641],{},[16,7633,7634],{},"Auto-Calculated KPIs",[4531,7636],{},"\nOobeya captures and calculates key metrics — including cycle time, PR throughput, ",[514,7639,848],{"href":7188,"rel":7640},[518],", and team velocity — directly from your integrated tools.",[73,7643,7644,7647,7649],{},[16,7645,7646],{},"Team Benchmarking",[4531,7648],{},"\nLeaderboards and dashboards help leaders compare team performance over time and against peers, identifying what works and where support is needed.",[73,7651,7652,7655,7657],{},[16,7653,7654],{},"Progress Tracking",[4531,7656],{},"\nWeekly and monthly reports allow teams to track progress toward strategic goals and course-correct early.",[73,7659,7660,7663,7665,7666,7669],{},[16,7661,7662],{},"Constructive Motivation",[4531,7664],{},"\nEmphasis is on ",[16,7667,7668],{},"team-level improvement",", not unhealthy competition. Insights are designed to support learning and growth.",[73,7671,7672,7675,7677,7678,23,7680,27,7682,7684],{},[16,7673,7674],{},"Seamless Integration",[4531,7676],{},"\nOobeya integrates with the tools your teams already use — including ",[16,7679,6900],{},[16,7681,4528],{},[16,7683,6905],{}," — eliminating manual overhead.",[3354,7686,7687],{},[12,7688,7689,7690,7693],{},"With Oobeya, KPI discussions become part of ",[16,7691,7692],{},"everyday improvement",", not just quarterly reviews.",[501,7695],{},[613,7697,1159],{"id":477},[12,7699,7700,7701,7704],{},"In 2025, gamification isn’t a gimmick — it’s a ",[16,7702,7703],{},"strategic approach"," to making engineering KPIs visible, motivating, and actionable.",[12,7706,7707],{},"By presenting performance data in a clear and engaging way, organizations can:",[70,7709,7710,7716,7722],{},[73,7711,7712,7713],{},"Foster ",[16,7714,7715],{},"team alignment",[73,7717,7718,7719],{},"Boost ",[16,7720,7721],{},"developer engagement",[73,7723,7724,7725],{},"Create a culture of ",[16,7726,7727],{},"continuous improvement",[12,7729,7730,7733],{},[16,7731,7732],{},"Oobeya’s Gamification Module"," combines automation, benchmarking, and coaching insights in one platform — enabling engineering managers and DevOps leaders to align strategy with execution.",[501,7735],{},[613,7737,7739],{"id":7738},"ready-to-drive-performance-with-data","Ready to Drive Performance With Data?",[12,7741,7742,7747],{},[514,7743,7745],{"href":4082,"rel":7744},[518],[16,7746,5528],{}," to explore how gamification can help your teams hit their KPIs, improve continuously, and stay ahead of the curve.",[501,7749],{},[52,7751,7753],{"id":7752},"more-from-oobeya","More from Oobeya",[70,7755,7756,7761,7766,7773],{},[73,7757,7758],{},[514,7759,6386],{"href":7330,"rel":7760},[518],[73,7762,7763],{},[514,7764,6346],{"href":7336,"rel":7765},[518],[73,7767,7768],{},[514,7769,7772],{"href":7770,"rel":7771},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fdora-metrics-2025-best-practices\u002F",[518],"DORA Metrics in 2025: Best Practices for Accurate Calculation and Monitoring",[73,7774,7775],{},[514,7776,7778],{"href":7300,"rel":7777},[518],"Symptoms: Proactive Engineering Issue Detection",{"title":526,"searchDepth":527,"depth":527,"links":7780},[7781,7784,7787,7788,7789,7792,7793],{"id":7400,"depth":527,"text":7401,"children":7782},[7783],{"id":7409,"depth":530,"text":7410},{"id":7444,"depth":527,"text":7445,"children":7785},[7786],{"id":7451,"depth":530,"text":7452},{"id":7495,"depth":527,"text":7496},{"id":7559,"depth":527,"text":7560},{"id":7612,"depth":527,"text":7613,"children":7790},[7791],{"id":7626,"depth":530,"text":7627},{"id":477,"depth":527,"text":1159},{"id":7738,"depth":527,"text":7739,"children":7794},[7795],{"id":7752,"depth":530,"text":7753},[7370,1259,696,1231],"2025-08-06","Discover how gamifying engineering KPIs can boost team performance in 2025, and how Oobeya’s module makes tracking and improving metrics effortless.",{},{"title":7383,"description":7798},"blog\u002Fgamification-and-engineerin-kpis",[7370,7379,696,1231],"o4yWHqpHufOOJMX3seNDhS9NJRCCMJ1Z6pyDbNWXoJ0",{"id":7805,"title":7806,"author":4245,"avatar":575,"body":7807,"categories":8097,"createAt":542,"date":8099,"description":8100,"extension":545,"meta":8101,"navigation":547,"path":2034,"position":542,"seo":8102,"spotImage":542,"spotText":542,"stem":8103,"tags":8104,"__hash__":8106},"blog\u002Fblog\u002Fstop-the-guesswork-see-who-is-overloaded-or-underutilized.md","Stop the Guesswork: See Who’s Overloaded or Underutilized in Seconds",{"type":9,"value":7808,"toc":8082},[7809,7817,7820,7822,7826,7835,7838,7840,7844,7849,7863,7866,7868,7872,7879,7890,7893,7895,7899,7903,7913,7917,7928,7932,7942,7946,7953,7955,7959,7970,7976,7983,7994,7997,7999,8003,8006,8026,8028,8032,8038,8041,8052,8054,8058,8061],[12,7810,7811,7814,7816],{},[16,7812,7813],{},"Struggling with overloaded developers and underused teammates?",[4531,7815],{},"\nYou’re not alone. Misaligned resource distribution silently kills team efficiency — delaying delivery, increasing burnout, and wasting potential.",[12,7818,7819],{},"But there’s a better way.",[501,7821],{},[613,7823,7825],{"id":7824},"introducing-the-resource-allocation-module-by-oobeya","Introducing the Resource Allocation Module by Oobeya",[12,7827,5642,7828,7831,7832,611],{},[16,7829,7830],{},"Resource Allocation Module"," gives engineering managers the clarity they need to ",[16,7833,7834],{},"balance workloads, improve utilization, and unlock delivery capacity—without guesswork",[12,7836,7837],{},"Whether you're scaling fast or stabilizing delivery, this feature ensures your people are working on the right projects at the right time.",[501,7839],{},[613,7841,7843],{"id":7842},"what-is-it","What Is It?",[12,7845,3617,7846,7848],{},[16,7847,7830],{}," provides real-time visibility into:",[70,7850,7851,7854,7857,7860],{},[73,7852,7853],{},"Who’s working on what",[73,7855,7856],{},"Which projects are overstaffed or at risk",[73,7858,7859],{},"How individual contributors are spread across efforts",[73,7861,7862],{},"Utilization trends across the organization",[12,7864,7865],{},"Unlike static spreadsheets, this dynamic view updates as your teams work—so you can act with confidence, not assumptions.",[501,7867],{},[613,7869,7871],{"id":7870},"why-it-matters","Why It Matters",[12,7873,7874,7875,7878],{},"Misallocation is one of the ",[16,7876,7877],{},"top hidden productivity killers"," in software teams. You’ve likely seen it:",[70,7880,7881,7884,7887],{},[73,7882,7883],{},"One team member is on three projects — burning out fast",[73,7885,7886],{},"Another is twiddling their thumbs — unclear what to prioritize",[73,7888,7889],{},"High-priority projects are under-supported — and slipping",[12,7891,7892],{},"With Oobeya, you’ll spot these issues instantly — and fix them before they cost you.",[501,7894],{},[613,7896,7898],{"id":7897},"key-features-youll-love","Key Features You’ll Love",[52,7900,7902],{"id":7901},"project-individual-views","Project & Individual Views",[12,7904,7905,7906,5502,7909,7912],{},"See allocations by ",[16,7907,7908],{},"project",[16,7910,7911],{},"person",". Perfect for syncing with both delivery leads and individual team members.",[52,7914,7916],{"id":7915},"real-time-utilization-status","Real-Time Utilization Status",[12,7918,7919,7920,23,7922,6819,7925,7927],{},"Track whether contributors are ",[16,7921,6269],{},[16,7923,7924],{},"Optimally Utilized",[16,7926,6230],{}," — with customizable thresholds.",[52,7929,7931],{"id":7930},"count-vs-effort-toggle","Count vs Effort Toggle",[12,7933,7934,7935,5502,7938,7941],{},"Switch between ",[16,7936,7937],{},"work item count",[16,7939,7940],{},"effort (story points\u002Ftime estimates)"," to match your estimation style.",[52,7943,7945],{"id":7944},"admin-controls","Admin Controls",[12,7947,7948,7949,7952],{},"Define ",[16,7950,7951],{},"roles to include",", adjust thresholds, and manage contributor visibility directly from the admin panel.",[501,7954],{},[613,7956,7958],{"id":7957},"real-world-example","Real-World Example",[12,7960,7961,7962,7965,7966,7969],{},"Let’s say your backend team delivered ",[16,7963,7964],{},"80 story points"," across ",[16,7967,7968],{},"4 developers"," in the last 30 days.",[12,7971,7972,7973,611],{},"That’s an average capacity of ",[16,7974,7975],{},"20 story points per developer",[12,7977,7978,7979,7982],{},"This sprint, you planned ",[16,7980,7981],{},"35 story points for Jane"," — her utilization is:",[12,7984,7985,7988,7990,7991,611],{},[16,7986,7987],{},"(35 \u002F 20) × 100 = 175%",[4531,7989],{},"\nShe’s clearly ",[16,7992,7993],{},"overloaded",[12,7995,7996],{},"Oobeya surfaces this instantly — so you can redistribute before it’s too late.",[501,7998],{},[613,8000,8002],{"id":8001},"how-to-get-started","How to Get Started",[12,8004,8005],{},"Getting value from this feature is fast and simple:",[1520,8007,8008,8011,8014,8020,8023],{},[73,8009,8010],{},"Enable the module from your Oobeya dashboard",[73,8012,8013],{},"Make sure roles are correctly set (e.g., Developers)",[73,8015,8016,8017],{},"Visit the Resource Allocation page under ",[739,8018,8019],{},"Insights",[73,8021,8022],{},"Adjust thresholds and filters to match your team’s workflow",[73,8024,8025],{},"Start optimizing — identify misallocations and act.",[501,8027],{},[613,8029,8031],{"id":8030},"manage-smarter-deliver-better","Manage Smarter. Deliver Better.",[12,8033,8034,8035,611],{},"In today’s fast-moving dev environment, ",[16,8036,8037],{},"visibility is leverage",[12,8039,8040],{},"The Resource Allocation Module helps you:",[70,8042,8043,8046,8049],{},[73,8044,8045],{},"Prevent burnout",[73,8047,8048],{},"Increase throughput",[73,8050,8051],{},"Plan more effectively",[501,8053],{},[613,8055,8057],{"id":8056},"ready-to-see-it-in-action","Ready to See It in Action?",[12,8059,8060],{},"Start optimizing your team today:",[70,8062,8063,8070,8075],{},[73,8064,8065],{},[514,8066,8069],{"href":8067,"rel":8068},"https:\u002F\u002Foobeya.io\u002Fproduct-tour",[518],"Take a Product Tour",[73,8071,8072],{},[514,8073,519],{"href":4082,"rel":8074},[518],[73,8076,8077],{},[514,8078,8081],{"href":8079,"rel":8080},"https:\u002F\u002Fdocs.oobeya.io",[518],"Explore Our Help Center",{"title":526,"searchDepth":527,"depth":527,"links":8083},[8084,8085,8086,8087,8093,8094,8095,8096],{"id":7824,"depth":527,"text":7825},{"id":7842,"depth":527,"text":7843},{"id":7870,"depth":527,"text":7871},{"id":7897,"depth":527,"text":7898,"children":8088},[8089,8090,8091,8092],{"id":7901,"depth":530,"text":7902},{"id":7915,"depth":530,"text":7916},{"id":7930,"depth":530,"text":7931},{"id":7944,"depth":530,"text":7945},{"id":7957,"depth":527,"text":7958},{"id":8001,"depth":527,"text":8002},{"id":8030,"depth":527,"text":8031},{"id":8056,"depth":527,"text":8057},[1876,8098,6709],"resource-allocations","2025-07-29","See overloaded and underutilized contributors faster with Oobeya Resource Allocation insights and real-time workload visibility.",{},{"title":7806,"description":8100},"blog\u002Fstop-the-guesswork-see-who-is-overloaded-or-underutilized",[8105,696],"allocations","ESbv18iwqS281hjmZ6WBDdJnIdSk8UOeDXWVz9C2e0M",{"id":8108,"title":8109,"author":6,"avatar":7,"body":8110,"categories":8432,"createAt":542,"date":8433,"description":8434,"extension":545,"meta":8435,"navigation":547,"path":8436,"position":542,"seo":8437,"spotImage":542,"spotText":542,"stem":8438,"tags":8439,"__hash__":8441},"blog\u002Fblog\u002Fdeveloper-productivity-insight-platforms-in-2025.md","Developer Productivity Insight Platforms in 2025: The New Standard for Engineering Success",{"type":9,"value":8111,"toc":8424},[8112,8116,8119,8125,8128,8130,8134,8142,8177,8180,8182,8186,8197,8227,8229,8233,8236,8266,8287,8289,8293,8299,8303,8360,8367,8369,8371,8377,8383,8385,8394,8396,8402],[52,8113,8115],{"id":8114},"introduction","Introduction",[12,8117,8118],{},"In the evolving world of software development, the demands placed on engineering teams have never been greater. From faster delivery cycles to increasingly complex architectures and hybrid work environments, the pressure to produce high-quality software at speed has pushed engineering leaders to seek new ways of gaining visibility into team performance and output. ",[12,8120,8121,8122,50],{},"Traditional engineering dashboards are no longer enough. Organizations now require platforms that not only report on activity but also offer context, trends, and actionable recommendations. This shift has led to the rise of a new category of tools: ",[16,8123,8124],{},"Developer Productivity Insight Platforms",[12,8126,8127],{},"These platforms are designed to help leaders understand the full story behind developer activity, enable better decision-making, and create healthier, more productive teams. In 2025, adopting these tools is no longer optional for organizations that want to remain competitive — it's foundational. ",[501,8129],{},[52,8131,8133],{"id":8132},"what-are-developer-productivity-insight-platforms","What Are Developer Productivity Insight Platforms?",[12,8135,8136,8137,8141],{},"Developer Productivity Insight Platforms are advanced engineering intelligence tools that aggregate data from across the software delivery lifecycle and transform it into meaningful, actionable insights. Unlike traditional reporting tools that simply track ",[514,8138,8140],{"href":8139},"\u002Fglossary\u002Fcommit","commits"," or deployments, these platforms: ",[70,8143,8144,8151,8158,8170],{},[73,8145,8146,8147,8150],{},"Provide a ",[16,8148,8149],{},"holistic view"," of the development process from idea to delivery.",[73,8152,8153,8154,8157],{},"Surface ",[16,8155,8156],{},"bottlenecks, inefficiencies, and risks"," across teams and workflows.",[73,8159,8160,8161,8164,8165,8169],{},"Offer ",[16,8162,8163],{},"real-time, continuous insights"," for engineering managers and executives. If you are evaluating the tooling landscape more broadly, our guide to the ",[514,8166,8168],{"href":8167},"\u002Fblog\u002Ftop-5-tools-for-engineering-managers-in-2024","top tools for engineering managers in 2024"," is a useful companion read.",[73,8171,8172,8173,8176],{},"Correlate ",[16,8174,8175],{},"developer experience (DevEx)"," with delivery outcomes.",[12,8178,8179],{},"They are built to empower leaders with the ability to proactively manage engineering performance, drive continuous improvement, and align technical metrics with business goals. ",[501,8181],{},[52,8183,8185],{"id":8184},"why-developer-productivity-insight-platforms-matter-in-2025","Why Developer Productivity Insight Platforms Matter in 2025",[12,8187,8188,8189,8192,8193,8196],{},"The rise of ",[16,8190,8191],{},"remote-first development",", coupled with the growing need for ",[16,8194,8195],{},"engineering transparency",", has fueled the demand for smarter platforms. In 2025, several macro trends are driving the need for Developer Productivity Insight Platforms: ",[70,8198,8199,8205,8215,8221],{},[73,8200,8201,8204],{},[16,8202,8203],{},"Increased Complexity",": Teams use dozens of tools (Git, Jira, CI\u002FCD, monitoring) that need to be analyzed together to tell the full story.",[73,8206,8207,8210,8211,8214],{},[16,8208,8209],{},"Developer Retention",": Organizations are prioritizing ",[16,8212,8213],{},"DevEx"," to improve satisfaction and reduce burnout.",[73,8216,8217,8220],{},[16,8218,8219],{},"Business Alignment",": Engineering is now expected to demonstrate its impact on business outcomes. Insights must go beyond DORA to include context-rich productivity metrics.",[73,8222,8223,8226],{},[16,8224,8225],{},"Data-Driven Leadership",": Leaders need actionable insights to guide decisions on hiring, planning, and delivery.",[501,8228],{},[52,8230,8232],{"id":8231},"the-leading-developer-productivity-insight-platforms","The Leading Developer Productivity Insight Platforms",[12,8234,8235],{},"As demand grows, a variety of platforms have emerged to meet the needs of engineering organizations. Some of the most notable include: ",[1520,8237,8238,8244,8250,8256,8261],{},[73,8239,8240,8243],{},[16,8241,8242],{},"Plandek",": Known for its deep focus on cycle time analysis and customizable dashboards.",[73,8245,8246,8249],{},[16,8247,8248],{},"LinearB",": Emphasizes workflow automation and real-time metrics to improve engineering efficiency and speed up delivery pipelines.",[73,8251,8252,8255],{},[16,8253,8254],{},"Sleuth",": Pairs DORA metrics with deployment insights and change tracking.",[73,8257,8258,8260],{},[16,8259,5129],{}," Uniquely focuses on developer experience (DevEx) by combining sentiment analysis, surveys, and productivity signals.",[73,8262,8263,8265],{},[16,8264,469],{},": A comprehensive engineering intelligence platform designed to unify insights across 20+ DevOps tools and provide proactive guidance. It excels in combining technical performance with organizational outcomes, surfacing real-time, actionable signals across the entire delivery pipeline.",[12,8267,8268,8269,8275,8276,8278,8279,247,8283,611],{},"These tools are gaining increasing recognition from industry analysts such as ",[514,8270,8273],{"href":8271,"rel":8272},"https:\u002F\u002Fwww.gartner.com\u002Freviews\u002Fmarkets",[518],[16,8274,5028],{},", which is beginning to spotlight ",[16,8277,8124],{}," as a distinct and vital category for modern software organizations. For teams comparing vendors more directly, it can also help to review ",[514,8280,8282],{"href":8281},"\u002Foobeya-vs-blueoptima-blueoptima-alternatives","Oobeya vs BlueOptima",[514,8284,8286],{"href":8285},"\u002Foobeya-vs-code-climate-velocity","Oobeya vs Code Climate Velocity",[501,8288],{},[52,8290,8292],{"id":8291},"oobeyas-edge-developer-productivity-reimagined","Oobeya’s Edge: Developer Productivity Reimagined",[12,8294,8295,8296,8298],{},"Among these platforms, ",[16,8297,469],{}," stands out for its holistic approach and depth of insight. Purpose-built for modern engineering organizations, Oobeya brings together every layer of the delivery process, providing a clear, accurate, and real-time picture of engineering productivity. ",[4331,8300,8302],{"id":8301},"what-makes-oobeya-different","What makes Oobeya different?",[70,8304,8305,8316,8322,8344,8354],{},[73,8306,8307,8310,8311,611],{},[16,8308,8309],{},"Cross-Tool Integration",": Seamlessly connects with GitHub, GitLab, Jira, Jenkins, Azure DevOps, and more.  Explore all ",[514,8312,8315],{"href":8313,"rel":8314},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fall-integrations",[518],"integrations here",[73,8317,8318,8321],{},[16,8319,8320],{},"Real-Time Accurate Insights",": Continuously updates to reflect the latest performance data.",[73,8323,8324,8327,8328,23,8334,23,8337,23,8340,27,8342,611],{},[16,8325,8326],{},"Comprehensive Metrics Coverage",": Tracks ",[514,8329,8332],{"href":8330,"rel":8331},"https:\u002F\u002Fdora.dev\u002Fguides\u002Fdora-metrics-four-keys\u002F",[518],[16,8333,848],{},[16,8335,8336],{},"Agile velocity",[16,8338,8339],{},"DevEx indicators",[16,8341,807],{},[16,8343,7539],{},[73,8345,8346,8348,8349,611],{},[16,8347,6395],{},": Proactively detects inefficiencies and flags issues before they cause delivery slowdowns. See Oobeya's ",[514,8350,8353],{"href":8351,"rel":8352},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog",[518],"Symptoms Catalog",[73,8355,8356,8359],{},[16,8357,8358],{},"Executive Dashboards",": Simplifies reporting with visual, goal-oriented views of team and organizational health.",[12,8361,8362,8363,8366],{},"Where many platforms stop at reporting, ",[16,8364,8365],{},"Oobeya delivers context",". Engineering leaders can see not only what’s happening but why — and what to do about it. ",[501,8368],{},[52,8370,1159],{"id":477},[12,8372,8373,8374,8376],{},"In 2025, the need to understand and improve developer productivity has moved from a \"nice-to-have\" to a strategic necessity. As engineering organizations evolve, ",[16,8375,8124],{}," have become essential to making informed, timely, and impactful decisions. ",[12,8378,8379,8380,50],{},"Organizations can unlock their teams’ potential, reduce delivery risk, and elevate the developer experience by choosing the right platform. In a field full of data and dashboards, ",[16,8381,8382],{},"Oobeya leads by turning product insight into action",[501,8384],{},[12,8386,8387,8393],{},[514,8388,8390],{"href":4082,"rel":8389},[518],[16,8391,8392],{},"Book a demo with Oobeya platform experts"," to unlock actionable insights and elevate developer productivity.",[501,8395],{},[12,8397,8398,8399],{}," ",[16,8400,8401],{},"Related Blog Posts:",[70,8403,8404,8411,8418],{},[73,8405,8406],{},[514,8407,8410],{"href":8408,"rel":8409},"https:\u002F\u002Foobeya.io\u002Fblog\u002Ftop-software-engineering-intelligence-tools-2025",[518],"Top Software Engineering Intelligence Tools of 2025",[73,8412,8413],{},[514,8414,8417],{"href":8415,"rel":8416},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fengineering-analytics-trends-2025",[518],"The Future of Engineering Analytics: Trends to Watch in 2025",[73,8419,8420],{},[514,8421,7772],{"href":8422,"rel":8423},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fdora-metrics-2025-best-practices",[518],{"title":526,"searchDepth":527,"depth":527,"links":8425},[8426,8427,8428,8429,8430,8431],{"id":8114,"depth":530,"text":8115},{"id":8132,"depth":530,"text":8133},{"id":8184,"depth":530,"text":8185},{"id":8231,"depth":530,"text":8232},{"id":8291,"depth":530,"text":8292},{"id":477,"depth":530,"text":1159},[1231,1232,540],"2025-04-09","Discover why Developer Productivity Insight Platforms are essential in 2025 and how Oobeya leads the way with real-time insights and engineering intelligence.",{},"\u002Fblog\u002Fdeveloper-productivity-insight-platforms-in-2025",{"title":8109,"description":8434},"blog\u002Fdeveloper-productivity-insight-platforms-in-2025",[1231,8440,696],"dora","woRAoiCNl41j4v161W7CxvoTknJzeQaw2_EwRAH9y58",{"id":8443,"title":8444,"author":4245,"avatar":575,"body":8445,"categories":8857,"createAt":542,"date":8858,"description":8859,"extension":545,"meta":8860,"navigation":547,"path":8861,"position":542,"seo":8862,"spotImage":542,"spotText":542,"stem":8863,"tags":8864,"__hash__":8866},"blog\u002Fblog\u002Fkey-devops-metrics-beyond-dora.md","Key DevOps Metrics Beyond DORA: What Engineering Leaders Should Track in 2025",{"type":9,"value":8446,"toc":8848},[8447,8450,8460,8469,8471,8475,8481,8486,8506,8511,8531,8533,8537,8541,8544,8558,8562,8565,8579,8583,8586,8600,8604,8607,8621,8625,8628,8642,8646,8649,8663,8666,8668,8672,8698,8700,8704,8739,8741,8745,8749,8764,8768,8779,8783,8795,8799,8814,8816,8820,8827,8833,8837],[52,8448,8449],{"id":8114},"Introduction ",[12,8451,8452,8453,8455,8456,8459],{},"While ",[16,8454,848],{}," (Deployment Frequency, Lead Time For Changes, Change Failure Rate, MTTR) are essential for DevOps evaluation, they only provide a limited view of engineering performance. As software development becomes more complex, engineering leaders must track additional ",[16,8457,8458],{},"DevOps KPIs"," to uncover inefficiencies, enhance team productivity, and drive business outcomes. ",[12,8461,8462,8463,8468],{},"This comprehensive guide explores crucial ",[514,8464,8467],{"href":8465,"rel":8466},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fwhat-are-the-key-devops-metrics",[518],"DevOps metrics"," beyond DORA, explaining their significance and how they drive continuous improvement. ",[501,8470],{},[52,8472,8474],{"id":8473},"why-engineering-leaders-must-expand-beyond-dora-metrics","Why Engineering Leaders Must Expand Beyond DORA Metrics ",[12,8476,8452,8477,8480],{},[514,8478,848],{"href":3620,"rel":8479},[518]," are essential, they omit key dimensions like productivity, security, and developer satisfaction. Engineering leaders who incorporate broader metrics can drive operational efficiency, reduce bottlenecks, and make data-driven decisions. ",[12,8482,8483,8398],{},[16,8484,8485],{},"The Need for Additional Metrics:",[70,8487,8488,8494,8500],{},[73,8489,8490,8493],{},[16,8491,8492],{},"Comprehensive Performance Insight:"," Tracks inefficiencies across coding, testing, and operations. ",[73,8495,8496,8499],{},[16,8497,8498],{},"Improved Developer Experience:"," Uncovers pain points that affect team morale and productivity. ",[73,8501,8502,8505],{},[16,8503,8504],{},"Accelerated Delivery Cycles:"," Reduces blockers and shortens feedback loops. ",[12,8507,8508,8398],{},[16,8509,8510],{},"Trends Driving Expanded Metrics Adoption:",[70,8512,8513,8519,8525],{},[73,8514,8515,8518],{},[16,8516,8517],{},"AI-Driven Engineering Insights:"," Real-time anomaly detection and predictive alerts. ",[73,8520,8521,8524],{},[16,8522,8523],{},"Platform Engineering:"," Building internal platforms to streamline developer workflows. ",[73,8526,8527,8530],{},[16,8528,8529],{},"Cross-Platform Analytics:"," Unifying & analyzing data from all SDLC tools for a complete performance overview. ",[501,8532],{},[52,8534,8536],{"id":8535},"key-devops-metrics-beyond-dora","Key DevOps Metrics Beyond DORA ",[4331,8538,8540],{"id":8539},"cycle-time-measuring-efficiency-across-development-stages","Cycle Time: Measuring Efficiency Across Development Stages ",[12,8542,8543],{},"Cycle time measures how long it takes to complete a work item from start to finish, highlighting bottlenecks across coding, reviews, and deployments. ",[70,8545,8546,8552],{},[73,8547,8548,8551],{},[16,8549,8550],{},"Detailed Insight:"," It breaks down into coding time, PR review time, and deployment time. ",[73,8553,8554,8557],{},[16,8555,8556],{},"Improvement Strategies:"," Introduce automated testing, streamline code reviews, and use parallel deployments. ",[4331,8559,8561],{"id":8560},"throughput-tracking-engineering-output","Throughput: Tracking Engineering Output",[12,8563,8564],{},"Throughput measures the number of tasks (features, bug fixes, stories) completed over a specific period. ",[70,8566,8567,8573],{},[73,8568,8569,8572],{},[16,8570,8571],{},"In-Depth Understanding:"," Tracks both completed and in-progress tasks for capacity planning. ",[73,8574,8575,8578],{},[16,8576,8577],{},"Boosting Throughput:"," Implement agile methodologies, shorten feedback loops, and automate deployments. ",[4331,8580,8582],{"id":8581},"developer-experience-devex-gauging-team-productivity-and-satisfaction","Developer Experience (DevEx): Gauging Team Productivity and Satisfaction ",[12,8584,8585],{},"DevEx metrics assess how effectively developers can do their jobs. This includes tool efficiency, onboarding time, and satisfaction scores. ",[70,8587,8588,8594],{},[73,8589,8590,8593],{},[16,8591,8592],{},"Why It’s Vital:"," DevEx directly impacts productivity and retention rates. ",[73,8595,8596,8599],{},[16,8597,8598],{},"How to Enhance DevEx:"," Offer intuitive tools, reduce administrative burdens, and provide faster feedback loops. ",[4331,8601,8603],{"id":8602},"pull-request-pr-cycle-time-improving-code-review-efficiency","Pull Request (PR) Cycle Time: Improving Code Review Efficiency ",[12,8605,8606],{},"This metric tracks the time from pull request creation to merge, highlighting review process delays. ",[70,8608,8609,8615],{},[73,8610,8611,8614],{},[16,8612,8613],{},"Key Causes of Long PR Times:"," Lack of reviewer availability and unclear coding standards. ",[73,8616,8617,8620],{},[16,8618,8619],{},"Ways to Reduce PR Time:"," Automate code checks, implement review SLAs, and use collaborative tools. ",[4331,8622,8624],{"id":8623},"work-allocation-efficiency-maximizing-developer-focus-time","Work Allocation Efficiency: Maximizing Developer Focus Time ",[12,8626,8627],{},"This metric tracks how engineers split their time between coding, meetings, and overhead tasks. ",[70,8629,8630,8636],{},[73,8631,8632,8635],{},[16,8633,8634],{},"Detailed Breakdown:"," Analyzes productive versus unproductive time. ",[73,8637,8638,8641],{},[16,8639,8640],{},"Boosting Focus Time:"," Minimize meetings, automate administrative tasks, and promote asynchronous collaboration. ",[4331,8643,8645],{"id":8644},"security-and-compliance-metrics-ensuring-risk-free-deployments","Security and Compliance Metrics: Ensuring Risk-Free Deployments ",[12,8647,8648],{},"These metrics track the frequency of security vulnerabilities, compliance violations, and security test coverage. ",[70,8650,8651,8657],{},[73,8652,8653,8656],{},[16,8654,8655],{},"What to Watch:"," Number of failed security scans, average time to resolve vulnerabilities. ",[73,8658,8659,8662],{},[16,8660,8661],{},"How to Improve Security Metrics:"," Integrate security checks into CI\u002FCD and  ",[12,8664,8665],{},"conduct regular audits. ",[501,8667],{},[52,8669,8671],{"id":8670},"emerging-devops-metrics-to-watch-in-2025","Emerging DevOps Metrics to Watch in 2025 ",[70,8673,8674,8680,8686,8692],{},[73,8675,8676,8679],{},[16,8677,8678],{},"AI-Driven Anomaly Detection:"," Tracks unexpected patterns to prevent incidents before they occur. ",[73,8681,8682,8685],{},[16,8683,8684],{},"Platform Engineering Efficiency:"," Measures usage and effectiveness of internal developer platforms. ",[73,8687,8688,8691],{},[16,8689,8690],{},"CI\u002FCD Deployment Speed:"," Monitors the speed of automated delivery pipelines. ",[73,8693,8694,8697],{},[16,8695,8696],{},"Sustainability Metrics:"," Tracks energy usage and helps reduce cloud infrastructure costs. ",[501,8699],{},[52,8701,8703],{"id":8702},"best-practices-for-implementing-devops-kpis","Best Practices for Implementing DevOps KPIs ",[70,8705,8706,8715,8721,8727,8733],{},[73,8707,8708,8711,8712,8714],{},[16,8709,8710],{},"Automate Data Collection:"," Use SEI platforms like ",[16,8713,469],{}," to collect and analyze metrics in real time. ",[73,8716,8717,8720],{},[16,8718,8719],{},"Focus on Business Impact:"," Choose metrics that connect to outcomes like delivery speed and quality. ",[73,8722,8723,8726],{},[16,8724,8725],{},"Align KPIs Across Teams:"," Collaborate with stakeholders to define shared success metrics. ",[73,8728,8729,8732],{},[16,8730,8731],{},"Monitor Long-Term Trends:"," Use historical data to identify and address systemic issues. ",[73,8734,8735,8738],{},[16,8736,8737],{},"Incorporate Security Metrics Early:"," Ensure that security KPIs are part of the delivery process from the start. ",[501,8740],{},[52,8742,8744],{"id":8743},"how-oobeya-empowers-teams-to-track-and-optimize-devops-metrics","How Oobeya Empowers Teams to Track and Optimize DevOps Metrics ",[4331,8746,8748],{"id":8747},"cross-platform-engineering-analytics","Cross-Platform Engineering Analytics ",[70,8750,8751,8761],{},[73,8752,8753,8754,23,8757,8760],{},"Integrates and analyzes data across tools like ",[16,8755,8756],{},"Jira, GitHub, Jenkins",[16,8758,8759],{},"Azure, Sonar,"," and more into a unified view. ",[73,8762,8763],{},"Provides a holistic analysis of engineering performance across the entire delivery pipeline. ",[4331,8765,8767],{"id":8766},"proactive-issue-detection-with-symptoms-module","Proactive Issue Detection with Symptoms Module ",[70,8769,8770,8776],{},[73,8771,8772,8773,50],{},"Automatically identifies performance bottlenecks such as ",[16,8774,8775],{},"long cycle times or slow PR reviews",[73,8777,8778],{},"Provides actionable recommendations based on real-time engineering data. ",[4331,8780,8782],{"id":8781},"real-time-dashboards-for-enhanced-visibility","Real-Time Dashboards for Enhanced Visibility ",[70,8784,8785,8792],{},[73,8786,8787,8788,8791],{},"Offers ",[16,8789,8790],{},"customizable dashboards"," to track metrics like cycle time, throughput, and security compliance. ",[73,8793,8794],{},"Provides engineering leaders with clear insights to address issues promptly. ",[4331,8796,8798],{"id":8797},"developer-experience-devex-insights-for-productivity-improvement","Developer Experience (DevEx) Insights for Productivity Improvement ",[70,8800,8801,8808],{},[73,8802,8803,8804,8807],{},"Tracks ",[16,8805,8806],{},"workload distribution"," and work types that each developer is conducting analyzing their productivity and efficiency and identifying bottlenecks and improvement areas. ",[73,8809,8810,8811,50],{},"Offers recommendations to improve ",[16,8812,8813],{},"developers' efficiency, Reduce code churn, and workload balance",[501,8815],{},[52,8817,8818,8398],{"id":477},[16,8819,1159],{},[12,8821,8822,8823,8826],{},"In 2025, engineering leaders must broaden their KPIs beyond DORA to gain comprehensive insights into their teams' performance. Key metrics like ",[16,8824,8825],{},"cycle time, DevEx scores, PR cycle time, and security compliance"," drive continuous improvement and innovation. ",[12,8828,8829,8832],{},[16,8830,8831],{},"With Oobeya’s advanced analytics",", teams gain real-time visibility into their performance, automate data collection, and receive proactive recommendations to improve workflows and outcomes. ",[4331,8834,8836],{"id":8835},"ready-to-redefine-your-devops-performance-tracking","Ready to redefine your DevOps performance tracking?",[12,8838,512,8839,8843,8844,8847],{},[514,8840,8842],{"href":516,"rel":8841},[518],"Explore Oobeya’s Engineering Analytics"," to gain deeper insights. ➡️ ",[514,8845,519],{"href":4082,"rel":8846},[518]," and experience how Oobeya empowers your engineering success.",{"title":526,"searchDepth":527,"depth":527,"links":8849},[8850,8851,8852,8853,8854,8855,8856],{"id":8114,"depth":530,"text":8449},{"id":8473,"depth":530,"text":8474},{"id":8535,"depth":530,"text":8536},{"id":8670,"depth":530,"text":8671},{"id":8702,"depth":530,"text":8703},{"id":8743,"depth":530,"text":8744},{"id":477,"depth":530,"text":478},[1232,540],"2025-03-19","Discover essential DevOps metrics beyond DORA and learn how Oobeya helps engineering leaders drive performance, productivity, and continuous improvement.",{},"\u002Fblog\u002Fkey-devops-metrics-beyond-dora",{"title":8444,"description":8859},"blog\u002Fkey-devops-metrics-beyond-dora",[8440,696,8865],"devops","NgwA2DnoBvzTmupDUQE5W5lSFMArUC1Ypq4hNEtski8",{"id":8868,"title":7772,"author":4245,"avatar":575,"body":8869,"categories":9219,"createAt":542,"date":9220,"description":9221,"extension":545,"meta":9222,"navigation":547,"path":9223,"position":542,"seo":9224,"spotImage":542,"spotText":542,"stem":9225,"tags":9226,"__hash__":9228},"blog\u002Fblog\u002Fdora-metrics-2025-best-practices.md",{"type":9,"value":8870,"toc":9211},[8871,8889,8910,8914,8924,8927,8934,8959,8968,8972,8975,9001,9004,9008,9011,9014,9058,9062,9069,9073,9089,9093,9102,9106,9109,9113,9121,9125,9128,9132,9153,9162,9164,9168,9175,9177,9181],[12,8872,8873,8874,8877,8878,8881,8882,8885,8886,50],{},"In the evolving landscape of software development, ",[16,8875,8876],{},"DORA (DevOps Research and Assessment) metrics"," have solidified their position as the gold standard for assessing ",[16,8879,8880],{},"DevOps performance",". As we step into 2025, the emphasis on ",[16,8883,8884],{},"accurate calculation and monitoring"," of these metrics has intensified, driven by advancements in technology and the increasing complexity of development pipelines. This article delves into the best practices for effectively measuring and overseeing DORA metrics, ensuring that engineering teams remain at the forefront of ",[16,8887,8888],{},"software delivery performance",[3354,8890,8891,8898],{},[12,8892,8893,8894,8897],{},"Want to track and ",[16,8895,8896],{},"optimize your DORA metrics effortlessly","? ",[12,8899,8900,8901,8906,8907,50],{},"️",[514,8902,8904],{"href":4082,"rel":8903},[518],[16,8905,519],{}," and see how ",[16,8908,8909],{},"Oobeya transforms DevOps analytics",[52,8911,8913],{"id":8912},"understanding-dora-metrics-and-their-importance-in-2025","Understanding DORA Metrics and Their Importance in 2025 ",[12,8915,8916,8917,365,8920,8923],{},"As software development cycles accelerate, organizations need reliable benchmarks to measure and improve their ",[514,8918,8880],{"href":8465,"rel":8919},[518],[16,8921,8922],{},"DORA metrics have emerged as the industry standard",", offering engineering teams data-driven insights into software delivery efficiency. These metrics provide an objective way to evaluate how quickly and reliably software changes are delivered to end-users. By tracking these indicators, teams can identify bottlenecks, improve deployment processes, and enhance system resilience. ",[12,8925,8926],{},"DORA metrics are particularly critical in 2025 due to the growing reliance on automation, CI\u002FCD pipelines, and cloud-native development. As teams scale their operations, ensuring accurate measurement and monitoring of these metrics is essential to maintaining high-performance software delivery.  ",[12,8928,8929,8933],{},[514,8930,848],{"href":8931,"rel":8932},"https:\u002F\u002Fwww.oobeya.io\u002Fdora-metrics-four-key",[518]," consist of four key indicators that collectively provide a comprehensive view of a team's software delivery capabilities: ",[1520,8935,8936,8942,8948,8954],{},[73,8937,8938,8941],{},[16,8939,8940],{},"Deployment Frequency (DF)",": This measures how often an organization successfully deploys code to production. A higher frequency indicates a more agile and responsive development process, reflecting the ability to deliver value to customers at a faster pace. ",[73,8943,8944,8947],{},[16,8945,8946],{},"Lead Time for Changes (LTC)",": This metric tracks the duration from code commit to its deployment in production. Shorter lead times reflect a more efficient development pipeline, allowing teams to respond to business needs more quickly. ",[73,8949,8950,8953],{},[16,8951,8952],{},"Change Failure Rate (CFR)",": This represents the percentage of deployments that result in a failure in production, necessitating remediation. A lower CFR signifies more stable and reliable releases, reducing operational risks. ",[73,8955,8956,8958],{},[16,8957,4664],{},": This measures the average time taken to restore service following a production failure. A shorter MTTR indicates a team's proficiency in incident response and system resilience, ensuring minimal disruption to end-users. ",[12,8960,8961,8962,8964,8965,8967],{},"These metrics serve as critical benchmarks for organizations aiming to enhance their ",[16,8963,8888],{}," and achieve ",[16,8966,7727],{}," in their DevOps practices. ",[52,8969,8971],{"id":8970},"challenges-in-monitoring-dora-metrics","Challenges in Monitoring DORA Metrics ",[12,8973,8974],{},"While DORA metrics provide valuable insights into software delivery performance, accurately monitoring them poses several challenges that organizations must address. From fragmented data sources to a lack of real-time tracking, these obstacles can prevent teams from fully leveraging the power of DORA metrics to drive continuous improvement. Below are some of the most common challenges teams face when monitoring DORA metrics and how they can impact the effectiveness of DevOps performance measurement: ",[70,8976,8977,8983,8989,8995],{},[73,8978,8979,8982],{},[16,8980,8981],{},"Data Silos",": In many organizations, data is dispersed across various tools and platforms, leading to fragmented insights and hindering a holistic view of the development pipeline. ",[73,8984,8985,8988],{},[16,8986,8987],{},"Inconsistent Data Collection",": Variations in data collection methods across teams can result in inconsistencies, making it difficult to aggregate and analyze metrics effectively. ",[73,8990,8991,8994],{},[16,8992,8993],{},"Manual Tracking",": Reliance on manual processes for data collection increases the risk of errors and consumes valuable time that could be better spent on development activities. ",[73,8996,8997,9000],{},[16,8998,8999],{},"Lack of Real-Time Visibility",": Without real-time monitoring, teams may miss critical issues as they arise, delaying response times and impacting overall  ",[12,9002,9003],{},"Performance. ",[52,9005,9007],{"id":9006},"best-practices-for-accurate-calculation-and-monitoring","Best Practices for Accurate Calculation and Monitoring ",[12,9009,9010],{},"To ensure that organizations can effectively measure and monitor DORA metrics, they must adopt industry best practices that improve data accuracy, eliminate inefficiencies, and enhance visibility. By implementing automated tracking systems, standardizing metric definitions, and leveraging advanced analytics, teams can maximize the value of DORA metrics in optimizing their DevOps performance. ",[12,9012,9013],{},"To overcome these challenges and ensure precise measurement of DORA metrics, organizations should adopt the following best practices: ",[1520,9015,9016,9022,9028,9034,9040,9046,9052],{},[73,9017,9018,9021],{},[16,9019,9020],{},"Automate Data Collection",": Implementing automated data collection minimizes human error and provides real-time insights into the development process. Integrating tools such as CI\u002FCD pipelines, version control systems, and incident management platforms ensures seamless data flow and accurate metric calculation. ",[73,9023,9024,9027],{},[16,9025,9026],{},"Standardize Metrics Definitions",": Establishing clear and consistent definitions for each metric across all teams is crucial. This standardization ensures uniform data interpretation and facilitates meaningful comparisons and analyses. ",[73,9029,9030,9033],{},[16,9031,9032],{},"Implement Cross-Platform Analysis",": Modern development environments utilize multiple tools for various stages of the development lifecycle. For instance, code may be developed in one platform and deployed using another. Cross-platform analysis ensures that all tools involved in the software delivery pipeline are analyzed together, eliminating data gaps and providing a holistic view of engineering performance. ",[73,9035,9036,9039],{},[16,9037,9038],{},"Use Visual Dashboards",": Leveraging visual dashboards helps teams monitor trends and identify issues more effectively. Dashboards that provide real-time visibility into DORA metrics enable teams to make data-driven decisions quickly. ",[73,9041,9042,9045],{},[16,9043,9044],{},"Ensure Cross-Team Alignment",": Metrics should be understood and used by all teams, including development, operations, and leadership. Establishing a shared understanding of performance goals ensures that improvements are implemented across the entire organization. ",[73,9047,9048,9051],{},[16,9049,9050],{},"Set Realistic Benchmarks",": Comparing metrics against industry standards while considering the unique goals of your team provides a clear target for continuous improvement. Regularly reviewing and adjusting benchmarks ensures alignment with evolving business needs. ",[73,9053,9054,9057],{},[16,9055,9056],{},"Track Long-Term Trends, Not Just Daily Numbers",": Instead of reacting to daily fluctuations, analyzing long-term trends provides a clearer picture of software delivery performance. Observing trends over time helps teams identify patterns, measure improvements, and proactively address potential risks. ",[52,9059,9061],{"id":9060},"top-5-features-make-oobeya-the-best-dora-metrics-tracking-tool","Top 5 Features Make Oobeya The Best DORA Metrics Tracking Tool",[12,9063,9064,9065,9068],{},"While many tools provide basic tracking for DORA metrics, ",[16,9066,9067],{},"Oobeya takes it further"," with: ",[4331,9070,9072],{"id":9071},"_1-automated-data-collection-broad-integration-catalog","1- Automated Data Collection (broad integration catalog)",[12,9074,9075,9076,23,9080,9084,9085,611],{},"Oobeya seamlessly integrates with source code management, CI\u002FCD, and APM tools such as, ",[514,9077,4528],{"href":9078,"rel":9079},"https:\u002F\u002Fgithub.com\u002Fmarketplace\u002Foobeya-dora-metrics",[518],[514,9081,6905],{"href":9082,"rel":9083},"https:\u002F\u002Fdocs.oobeya.io\u002Fguides\u002Fazure-devops-guides\u002Fhow-to-calculate-dora-metrics-for-azure-devops",[518],", GitLab, Bitbucket, Jenkins, Octopus Deploy, New Relic, and others to ensure real-time tracking of DORA metrics. By automating data collection, teams can eliminate manual errors and gain instant visibility into their software delivery performance. View all Oobeya ",[514,9086,9088],{"href":4219,"rel":9087},[518],"SDLC tools integrations",[4331,9090,9092],{"id":9091},"_2-cross-platform-analysis","2- Cross-Platform Analysis",[12,9094,9095,9096,9101],{},"One of Oobeya’s standout features is its ability to perform ",[514,9097,9100],{"href":9098,"rel":9099},"https:\u002F\u002Fdocs.oobeya.io\u002Fgitwiser-repo-analytics\u002Fdeployment-analytics-dora-metrics",[518],"cross-platform analysis",". Many organizations develop code in one tool and deploy it in another, leading to fragmented data sources. Oobeya ensures that all tools involved in the software delivery process are analyzed together, providing accurate and reliable DORA metric calculations. ",[4331,9103,9105],{"id":9104},"_3-advanced-insights-recommendations","3- Advanced Insights & Recommendations",[12,9107,9108],{},"Beyond just tracking numbers, Oobeya’s analytics engine detects patterns and inefficiencies and offers actionable recommendations to improve deployment frequency, reduce lead time, and enhance overall DevOps performance. ",[4331,9110,9112],{"id":9111},"_4-symptoms-module-for-root-cause-analysis","4- Symptoms Module for Root Cause Analysis",[12,9114,9115,9116],{},"Oobeya’s Symptoms Module identifies the root causes of slow deployments, high failure rates, and inefficiencies within the development pipeline. This enables engineering teams to address issues proactively rather than reactively. Learn more: ",[514,9117,9120],{"href":9118,"rel":9119},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fbeyond-dora-metrics-identifying-symptoms-that-lead-to-poor-dora-metrics",[518],"Identifying Symptoms That Lead To Poor DORA Metrics",[4331,9122,9124],{"id":9123},"_5-customizable-dashboards","5- Customizable Dashboards",[12,9126,9127],{},"Oobeya provides real-time, customizable dashboards that give engineering managers a comprehensive view of key performance metrics. This allows teams to monitor DORA metrics efficiently and make data-driven decisions. ",[52,9129,9130,8398],{"id":477},[16,9131,1159],{},[12,9133,9134,9135,9138,9139,9141,9142,9145,9146,9149,9150,50],{},"As software ",[16,9136,9137],{},"delivery performance optimization"," continues to evolve, accurately calculating and monitoring ",[16,9140,848],{}," remains crucial for ensuring ",[16,9143,9144],{},"software delivery success",". Organizations that implement ",[16,9147,9148],{},"automation, cross-platform analysis, and real-time monitoring"," will gain a competitive advantage in ",[16,9151,9152],{},"reducing failures, optimizing deployment pipelines, and improving engineering efficiency",[12,9154,9155,6406,9158,9161],{},[16,9156,9157],{},"Oobeya empowers engineering teams",[16,9159,9160],{},"real-time tracking, cross-platform analysis, and automated analytics",", enabling them to stay ahead of industry challenges and continuously improve their DevOps processes. ",[501,9163],{},[4331,9165,9167],{"id":9166},"want-to-track-and-optimize-your-dora-metrics-effortlessly","Want to track and optimize your DORA metrics effortlessly? ",[12,9169,8900,9170,8906,9173,50],{},[514,9171,519],{"href":4082,"rel":9172},[518],[16,9174,8909],{},[501,9176],{},[52,9178,9180],{"id":9179},"learn-more","Learn More",[70,9182,9183,9190,9197,9204],{},[73,9184,9185],{},[514,9186,9189],{"href":9187,"rel":9188},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fhow-to-reduce-lead-time-for-changes-dora-metrics",[518],"How To Reduce Lead Time For Changes",[73,9191,9192],{},[514,9193,9196],{"href":9194,"rel":9195},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fimprove-change-failure-rate",[518],"How To Improve Change Failure Rate",[73,9198,9199],{},[514,9200,9203],{"href":9201,"rel":9202},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fdora-metrics-tracking-how-to-effectively-detect-production-failures",[518],"How to Effectively Detect Production Failures",[73,9205,9206],{},[514,9207,9210],{"href":9208,"rel":9209},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fhow-to-calculate-cycle-time",[518],"How to Calculate Cycle Time",{"title":526,"searchDepth":527,"depth":527,"links":9212},[9213,9214,9215,9216,9217,9218],{"id":8912,"depth":530,"text":8913},{"id":8970,"depth":530,"text":8971},{"id":9006,"depth":530,"text":9007},{"id":9060,"depth":530,"text":9061},{"id":477,"depth":530,"text":478},{"id":9179,"depth":530,"text":9180},[1232,540],"2025-02-12","Learn how to accurately measure and monitor DORA Metrics in 2025 with best practices for DevOps performance optimization and continuous improvement.",{},"\u002Fblog\u002Fdora-metrics-2025-best-practices",{"title":7772,"description":9221},"blog\u002Fdora-metrics-2025-best-practices",[8440,696,9227],"azure devops","gVXz3AyxLqMv_EsoqkOJLI_4_A1E3CHH7OGZWe_vkBY",{"id":4,"title":5,"author":6,"avatar":7,"body":9230,"categories":9546,"createAt":542,"date":543,"description":544,"extension":545,"meta":9547,"navigation":547,"path":548,"position":542,"seo":9548,"spotImage":542,"spotText":542,"stem":550,"tags":9549,"__hash__":554},{"type":9,"value":9231,"toc":9535},[9232,9242,9252,9254,9260,9262,9276,9280,9282,9290,9292,9306,9310,9312,9320,9322,9336,9340,9342,9350,9352,9368,9376,9378,9386,9388,9400,9404,9406,9414,9416,9430,9436,9438,9446,9448,9464,9466,9474,9476,9492,9494,9502,9508,9510,9518,9522,9524,9528],[12,9233,14,9234,19,9236,23,9238,27,9240,31],{},[16,9235,18],{},[16,9237,22],{},[16,9239,26],{},[16,9241,30],{},[12,9243,34,9244,38,9246,42,9248,46,9250,50],{},[16,9245,37],{},[16,9247,41],{},[16,9249,45],{},[16,9251,49],{},[52,9253,55],{"id":54},[12,9255,58,9256,62,9258,65],{},[16,9257,61],{},[16,9259,22],{},[12,9261,68],{},[70,9263,9264,9268,9272],{},[73,9265,9266,78],{},[16,9267,77],{},[73,9269,9270,84],{},[16,9271,83],{},[73,9273,9274,90],{},[16,9275,89],{},[12,9277,93,9278,97],{},[16,9279,96],{},[52,9281,101],{"id":100},[12,9283,9284,107,9286,111,9288,115],{},[16,9285,106],{},[16,9287,110],{},[16,9289,114],{},[12,9291,118],{},[70,9293,9294,9298,9302],{},[73,9295,9296,126],{},[16,9297,125],{},[73,9299,9300,132],{},[16,9301,131],{},[73,9303,9304,138],{},[16,9305,137],{},[12,9307,141,9308,144],{},[16,9309,18],{},[52,9311,148],{"id":147},[12,9313,151,9314,155,9316,158,9318,50],{},[16,9315,154],{},[16,9317,26],{},[16,9319,161],{},[12,9321,164],{},[70,9323,9324,9328,9332],{},[73,9325,169,9326,173],{},[16,9327,172],{},[73,9329,176,9330,180],{},[16,9331,179],{},[73,9333,183,9334,187],{},[16,9335,186],{},[12,9337,93,9338,193],{},[16,9339,192],{},[52,9341,197],{"id":196},[12,9343,200,9344,204,9346,208,9348,50],{},[16,9345,203],{},[16,9347,207],{},[16,9349,211],{},[12,9351,214],{},[70,9353,9354,9360,9364],{},[73,9355,219,9356,223,9358,50],{},[16,9357,222],{},[16,9359,226],{},[73,9361,229,9362,233],{},[16,9363,232],{},[73,9365,236,9366,240],{},[16,9367,239],{},[12,9369,243,9370,247,9372,251,9374,255],{},[16,9371,246],{},[16,9373,250],{},[16,9375,254],{},[52,9377,259],{"id":258},[12,9379,262,9380,266,9382,270,9384,50],{},[16,9381,265],{},[16,9383,269],{},[16,9385,273],{},[12,9387,276],{},[70,9389,9390,9394,9396],{},[73,9391,281,9392,285],{},[16,9393,284],{},[73,9395,288],{},[73,9397,291,9398,295],{},[16,9399,294],{},[12,9401,298,9402,302],{},[16,9403,301],{},[52,9405,306],{"id":305},[12,9407,9408,312,9410,316,9412,320],{},[16,9409,311],{},[16,9411,315],{},[16,9413,319],{},[12,9415,323],{},[70,9417,9418,9422,9426],{},[73,9419,9420,331],{},[16,9421,330],{},[73,9423,9424,337],{},[16,9425,336],{},[73,9427,9428,343],{},[16,9429,342],{},[12,9431,346,9432,350,9434,354],{},[16,9433,349],{},[16,9435,353],{},[52,9437,358],{"id":357},[12,9439,361,9440,365,9442,369,9444,50],{},[16,9441,364],{},[16,9443,368],{},[16,9445,372],{},[12,9447,375],{},[70,9449,9450,9454,9460],{},[73,9451,9452,383],{},[16,9453,382],{},[73,9455,9456,389,9458,50],{},[16,9457,388],{},[16,9459,392],{},[73,9461,9462,398],{},[16,9463,397],{},[52,9465,402],{"id":401},[12,9467,405,9468,409,9470,413,9472,417],{},[16,9469,408],{},[16,9471,412],{},[16,9473,416],{},[12,9475,420],{},[70,9477,9478,9482,9486],{},[73,9479,425,9480,429],{},[16,9481,428],{},[73,9483,432,9484,436],{},[16,9485,435],{},[73,9487,439,9488,443,9490,50],{},[16,9489,442],{},[16,9491,446],{},[12,9493,449],{},[12,9495,452,9496,456,9498,460,9500,50],{},[16,9497,455],{},[16,9499,459],{},[16,9501,463],{},[12,9503,466,9504,470,9506,474],{},[16,9505,469],{},[16,9507,473],{},[52,9509,478],{"id":477},[12,9511,481,9512,484,9514,488,9516,492],{},[16,9513,408],{},[16,9515,487],{},[16,9517,491],{},[12,9519,495,9520,499],{},[16,9521,498],{},[501,9523],{},[12,9525,505,9526,509],{},[16,9527,508],{},[12,9529,512,9530,520,9533,524],{},[514,9531,519],{"href":516,"rel":9532},[518],[16,9534,523],{},{"title":526,"searchDepth":527,"depth":527,"links":9536},[9537,9538,9539,9540,9541,9542,9543,9544,9545],{"id":54,"depth":530,"text":55},{"id":100,"depth":530,"text":101},{"id":147,"depth":530,"text":148},{"id":196,"depth":530,"text":197},{"id":258,"depth":530,"text":259},{"id":305,"depth":530,"text":306},{"id":357,"depth":530,"text":358},{"id":401,"depth":530,"text":402},{"id":477,"depth":530,"text":478},[540,541],{},{"title":5,"description":544},[552,540,553],{"id":9551,"title":8410,"author":6,"avatar":7,"body":9552,"categories":9834,"createAt":542,"date":9835,"description":9836,"extension":545,"meta":9837,"navigation":547,"path":9838,"position":542,"seo":9839,"spotImage":542,"spotText":542,"stem":9840,"tags":542,"__hash__":9841},"blog\u002Fblog\u002Ftop-software-engineering-intelligence-tools-2025.md",{"type":9,"value":9553,"toc":9817},[9554,9557,9561,9564,9567,9581,9595,9599,9606,9609,9647,9654,9658,9661,9664,9694,9701,9704,9711,9715,9721,9724,9730,9733,9744,9748,9751,9755,9779,9783,9789,9809,9812,9814],[12,9555,9556],{},"Engineering managers face increasing pressure to deliver quality software faster in the fast-evolving world of software development. Software Engineering Intelligence (SEI) tools have emerged as game-changers to meet these demands, empowering teams with actionable insights, performance metrics, and process optimization. As we step into 2025, let’s explore the top SEI tools driving the industry and how they’re helping teams excel. ",[613,9558,9560],{"id":9559},"the-role-of-software-engineering-intelligence-tools","The Role of Software Engineering Intelligence Tools",[12,9562,9563],{},"Software Engineering Intelligence tools play a pivotal role in modern development workflows. By providing real-time analytics and actionable insights, these tools enable engineering managers to identify bottlenecks, streamline processes, and improve team performance. SEI tools are not just about metrics; they offer a holistic view of the software development lifecycle, ensuring better decision-making and faster delivery without compromising quality. ",[12,9565,9566],{},"These tools help engineering leaders achieve: ",[70,9568,9569,9572,9575,9578],{},[73,9570,9571],{},"Streamlined development workflows. ",[73,9573,9574],{},"Identification and resolution of inefficiencies. ",[73,9576,9577],{},"Enhanced team performance through actionable data. ",[73,9579,9580],{},"Improved software quality and reduced delivery timelines.",[12,9582,9583,9584,247,9587,9590,9591,9594],{},"In 2025, the demand for ",[16,9585,9586],{},"Engineering Analytics Platforms",[16,9588,9589],{},"DevOps Performance Tools"," continues to grow as companies look to optimize their ",[16,9592,9593],{},"Continuous Integration and Delivery Tools"," and ensure seamless development cycles. ",[52,9596,9598],{"id":9597},"key-features-to-consider-in-sei-tools","Key Features to Consider in SEI Tools",[12,9600,9601,9602,9605],{},"Before selecting an SEI tool, it’s crucial to evaluate how well it aligns with your team’s unique challenges and goals. Here are some ",[16,9603,9604],{},"Top Features to Look for in Engineering Intelligence Platforms",": ",[12,9607,9608],{},"A robust SEI tool should:",[70,9610,9611,9617,9623,9629,9635,9641],{},[73,9612,9613,9616],{},[16,9614,9615],{},"Integrate Seamlessly:"," Ensure compatibility with existing tools like Jira, GitHub, or Azure DevOps to provide a unified data view. ",[73,9618,9619,9622],{},[16,9620,9621],{},"Deliver Real-Time Analytics:"," Equip teams with the ability to identify and address issues as they arise. ",[73,9624,9625,9628],{},[16,9626,9627],{},"Offer Customizable Dashboards:"," Allow managers to tailor metrics and insights to specific team needs. ",[73,9630,9631,9634],{},[16,9632,9633],{},"Provide Predictive Insights:"," Forecast potential challenges, enabling proactive intervention. ",[73,9636,9637,9640],{},[16,9638,9639],{},"Support Continuous Integration and Delivery Tools:"," Help streamline CI\u002FCD processes for faster and more reliable deployments. ",[73,9642,9643,9646],{},[16,9644,9645],{},"Offer Excellent Customer Support:"," Ensure a smooth experience with reliable support for troubleshooting and onboarding. ",[12,9648,9649,9650,9653],{},"By addressing these needs, tools not only improve software delivery but also provide the ",[16,9651,9652],{},"Software Development Performance Metrics"," essential for ongoing optimization. ",[613,9655,9657],{"id":9656},"top-software-engineering-intelligence-tools-in-2025","Top Software Engineering Intelligence Tools in 2025",[52,9659,469],{"id":9660},"oobeya",[12,9662,9663],{},"Oobeya stands out as a comprehensive SEI platform designed to help engineering managers optimize their teams’ performance and processes. With cutting-edge features and a focus on delivering actionable insights, Oobeya empowers leaders to stay ahead of challenges. Its platform delivers highly accurate data, allowing teams to track and improve key metrics such as DORA metrics, Cycle Time, Developer Productivity metrics, and many more. This comprehensive approach ensures that Oobeya covers all critical aspects of software development performance. ",[70,9665,9666,9672,9678,9684],{},[73,9667,9668,9671],{},[16,9669,9670],{},"Symptoms Module:"," Automatically detects issues and bottlenecks, offering actionable insights to resolve them efficiently. ",[73,9673,9674,9677],{},[16,9675,9676],{},"Integration Catalog:"," A wide range of integrations with popular tools like Jira, GitHub, and Azure DevOps provides a seamless experience. ",[73,9679,9680,9683],{},[16,9681,9682],{},"Tailored Insights:"," Delivers actionable data at different team levels, empowering managers to make informed decisions. ",[73,9685,9686,9689,9690,9693],{},[16,9687,9688],{},"Exceptional Customer Support:"," Recognized by ",[16,9691,9692],{},"G2 as an industry leader",", Oobeya ensures users receive outstanding assistance. ",[12,9695,9696,8398],{},[514,9697,9700],{"href":9698,"rel":9699},"https:\u002F\u002Foobeya.io\u002Foobeya-vs-linearb",[518],"Learn more about how Oobeya compares to competitors like LinearB.",[52,9702,8254],{"id":9703},"sleuth",[12,9705,9706,9707,9710],{},"Sleuth focuses on deployment tracking and DORA metrics to help teams improve their delivery performance. By tracking deploys and their impact, Sleuth ensures visibility into deployment health and supports better decision-making. It’s one of the ",[16,9708,9709],{},"Best Software Development Analytics Tools"," for teams prioritizing DORA metrics. ",[52,9712,9714],{"id":9713},"haystack","Haystack",[12,9716,9717,9718,50],{},"Haystack provides real-time insights into team productivity and delivery performance. Its features include alerts on bottlenecks and inefficiencies, as well as metrics on pull requests, commits, and deployments. For teams looking to refine workflows, Haystack is a strong contender among ",[16,9719,9720],{},"Leading Engineering Intelligence Software",[52,9722,8242],{"id":9723},"plandek",[12,9725,9726,9727,50],{},"Plandek emphasizes engineering efficiency and delivery pipelines. With customizable dashboards and detailed metrics, it enables continuous improvement. Integration with tools like Jira and GitHub further enhances its usability for process optimization, making it a valuable tool in the category of ",[16,9728,9729],{},"DevOps Analytics Platforms",[52,9731,8248],{"id":9732},"linearb",[12,9734,9735,9736,9739,9740,247,9742,611],{},"LinearB provides real-time metrics and automation to improve development workflows. With team performance metrics and workflow optimization tools, LinearB streamlines processes to accelerate delivery and enhance quality. Its focus on ",[16,9737,9738],{},"Tools for Measuring DORA Metrics"," makes it popular among DevOps teams. If you are evaluating alternatives in more detail, see our comparison pages for ",[514,9741,8282],{"href":8281},[514,9743,8286],{"href":8285},[613,9745,9747],{"id":9746},"the-tool-for-proactive-insights-why-oobeya-stands-out","The Tool for Proactive Insights: Why Oobeya Stands Out",[12,9749,9750],{},"Each company may have different needs that influence their choice of SEI tools. However, if you’re seeking a solution that integrates seamlessly with your existing tools, provides proactive and accurate insights, and maximizes developer productivity, then Oobeya is the perfect fit for you. With a focus on empowering engineering managers, Oobeya ensures your teams are equipped to excel in 2025 and beyond. ",[52,9752,9754],{"id":9753},"oobeyas-key-strengths","Oobeya’s Key Strengths:",[70,9756,9757,9763,9769,9774],{},[73,9758,9759,9762],{},[16,9760,9761],{},"Proactive Issue Detection:"," The Symptoms Module automatically identifies inefficiencies and provides solutions. ",[73,9764,9765,9768],{},[16,9766,9767],{},"Comprehensive Integrations:"," A wide integration catalog ensures seamless data flow across tools. ",[73,9770,9771,9773],{},[16,9772,9682],{}," Actionable data tailored to individual team roles improves decision-making. ",[73,9775,9776,9778],{},[16,9777,9688],{}," Recognized by G2 for industry-leading support, Oobeya ensures a smooth experience for all users. ",[613,9780,9782],{"id":9781},"future-trends-in-software-engineering-analytics-tools","Future Trends in Software Engineering Analytics Tools",[12,9784,9785,9786,9788],{},"Looking ahead, ",[16,9787,9782],{}," indicate a growing emphasis on: ",[70,9790,9791,9797,9803],{},[73,9792,9793,9796],{},[16,9794,9795],{},"Predictive Analytics in Software Engineering:"," Tools will increasingly forecast potential challenges and provide proactive recommendations. ",[73,9798,9799,9802],{},[16,9800,9801],{},"Automated Coding Assistants:"," Enhancing code quality and reducing technical debt through automated suggestions. ",[73,9804,9805,9808],{},[16,9806,9807],{},"Comprehensive Review of Software Engineering Intelligence Tools in 2025:"," Teams will prioritize tools that combine insights, seamless integration, and real-time analytics. ",[12,9810,9811],{},"By staying ahead of these trends, companies can ensure their engineering teams remain competitive and efficient. ",[613,9813,1159],{"id":477},[12,9815,9816],{},"Choosing the right SEI tool is essential for engineering managers aiming to optimize their teams’ performance and deliver quality software efficiently. While all the tools listed offer unique advantages, Oobeya’s proactive approach, extensive integrations, and exceptional support make it a standout choice for 2025.",{"title":526,"searchDepth":527,"depth":527,"links":9818},[9819,9822,9829,9832,9833],{"id":9559,"depth":527,"text":9560,"children":9820},[9821],{"id":9597,"depth":530,"text":9598},{"id":9656,"depth":527,"text":9657,"children":9823},[9824,9825,9826,9827,9828],{"id":9660,"depth":530,"text":469},{"id":9703,"depth":530,"text":8254},{"id":9713,"depth":530,"text":9714},{"id":9723,"depth":530,"text":8242},{"id":9732,"depth":530,"text":8248},{"id":9746,"depth":527,"text":9747,"children":9830},[9831],{"id":9753,"depth":530,"text":9754},{"id":9781,"depth":527,"text":9782},{"id":477,"depth":527,"text":1159},[540,541],"2025-01-23","Engineering managers face increasing pressure to deliver quality software faster in the fast evolving world of software development. Software...",{},"\u002Fblog\u002Ftop-software-engineering-intelligence-tools-2025",{"title":8410,"description":9836},"blog\u002Ftop-software-engineering-intelligence-tools-2025","wchSrQlbiakRgZobaX-9ZdHJX8817BtDrGlWcKj9hso",{"id":9843,"title":9844,"author":4245,"avatar":575,"body":9845,"categories":10389,"createAt":542,"date":10391,"description":10392,"extension":545,"meta":10393,"navigation":547,"path":10394,"position":542,"seo":10395,"spotImage":542,"spotText":542,"stem":10396,"tags":542,"__hash__":10397},"blog\u002Fblog\u002Fcode-review-checklist-for-developers.md","Code Review Checklist for Developers",{"type":9,"value":9846,"toc":10361},[9847,9850,9852,9858,9872,9877,9903,9905,9911,9914,9918,9921,9924,9935,9939,9942,9944,9955,9959,9962,9964,9975,9979,9982,9984,9995,9999,10002,10004,10015,10019,10022,10024,10035,10039,10042,10044,10055,10057,10063,10072,10078,10081,10087,10090,10115,10118,10120,10126,10129,10135,10138,10144,10147,10153,10156,10166,10168,10174,10177,10183,10186,10192,10195,10201,10204,10210,10213,10219,10222,10228,10231,10237,10240,10246,10249,10258,10267,10269,10275,10278,10284,10292,10302,10306,10315,10319,10326,10330,10337,10341,10348,10351],[12,9848,9849],{},"Code quality is essential for delivering maintainable, secure, and efficient software in today's fast-paced software development world. But how can you ensure your code meets high standards? A code review checklist helps engineering leaders and developers maintain high-quality code across teams and projects. This post explores how to use a code review checklist, its importance, and how it can significantly improve the software development process. ",[501,9851],{},[613,9853,9855,8398],{"id":9854},"what-is-the-purpose-of-the-code-review-checklist",[16,9856,9857],{},"What is The Purpose of The Code Review Checklist?",[12,9859,9860,9861,9866,9867,50],{},"A code review checklist serves as a guideline to ensure consistent quality and standards in your ",[514,9862,9865],{"href":9863,"rel":9864},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fwhat-is-software-development-life-cycle-sdlc\u002F",[518],"software development lifecycle"," stages. It provides software engineers, developers, and team leaders with a structured approach to checking code for errors, vulnerabilities, and inconsistencies, improving both the software coding process and overall ",[514,9868,9871],{"href":9869,"rel":9870},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fbalancing-speed-and-quality-in-software-delivery\u002F",[518],"software quality assurance",[12,9873,9874,8398],{},[16,9875,9876],{},"The checklist helps address several key areas, such as:",[70,9878,9879,9885,9891,9897],{},[73,9880,9881,9884],{},[16,9882,9883],{},"Readability:"," Ensuring the code is clean and easy to understand by other developers. ",[73,9886,9887,9890],{},[16,9888,9889],{},"Maintainability:"," The code should be modular and easy to update. ",[73,9892,9893,9896],{},[16,9894,9895],{},"Security:"," Identifying potential vulnerabilities early in the development process. ",[73,9898,9899,9902],{},[16,9900,9901],{},"Performance:"," Evaluating whether the code is optimized for speed and efficiency. ",[501,9904],{},[613,9906,9908,8398],{"id":9907},"the-ultimate-code-review-checklist-for-developers",[16,9909,9910],{},"The Ultimate Code Review Checklist for Developers",[12,9912,9913],{},"To effectively use a code review checklist, developers and engineering leaders should focus on the following areas. This list includes best practices, guidelines, and essential checks that ensure your code is optimized, secure, and maintainable. Incorporating these checks into your software development lifecycle models ensures a smoother code review process: ",[52,9915,9917],{"id":9916},"_1-code-readability-and-style","1. Code Readability and Style",[12,9919,9920],{},"Ensure the code is easy to read, properly formatted, and follows the project’s coding standards. Code consistency allows developers to maintain a unified approach throughout the project. ",[12,9922,9923],{},"Key points to check: ",[70,9925,9926,9929,9932],{},[73,9927,9928],{},"Proper indentation and spacing. ",[73,9930,9931],{},"Meaningful variable, function, and class names. ",[73,9933,9934],{},"Consistent use of comments to explain complex logic. ",[52,9936,9938],{"id":9937},"_2-functionality-testing","2. Functionality Testing",[12,9940,9941],{},"Ensure that the code works as intended and passes all tests. This step includes running both manual and automated tests, such as unit tests, to validate that the functionality meets the requirements. ",[12,9943,9923],{},[70,9945,9946,9949,9952],{},[73,9947,9948],{},"All features work as expected. ",[73,9950,9951],{},"Edge cases are covered in testing. ",[73,9953,9954],{},"Unit and integration tests pass without errors. ",[52,9956,9958],{"id":9957},"_3-security-best-practices","3. Security Best Practices",[12,9960,9961],{},"Developers need to ensure that their code adheres to security guidelines to prevent vulnerabilities such as SQL injection, XSS, and others. ",[12,9963,9923],{},[70,9965,9966,9969,9972],{},[73,9967,9968],{},"Input data is validated and sanitized. ",[73,9970,9971],{},"Sensitive information (e.g., passwords) is encrypted. ",[73,9973,9974],{},"Proper authentication and authorization practices are followed. ",[52,9976,9978],{"id":9977},"_4-code-optimization","4. Code Optimization",[12,9980,9981],{},"Optimized code ensures the application runs efficiently, with minimal use of resources. Developers should check for unnecessary computations or code that can be simplified. ",[12,9983,9923],{},[70,9985,9986,9989,9992],{},[73,9987,9988],{},"Loops and algorithms are efficient. ",[73,9990,9991],{},"The redundant code is eliminated. ",[73,9993,9994],{},"Resource management (e.g., memory, file handles) is handled properly. ",[52,9996,9998],{"id":9997},"_5-code-modularity-and-reusability","5. Code Modularity and Reusability",[12,10000,10001],{},"Modular code is easier to maintain, update, and debug. Reusing code wherever possible reduces duplication and enhances efficiency. ",[12,10003,9923],{},[70,10005,10006,10009,10012],{},[73,10007,10008],{},"Code is broken down into small, reusable functions. ",[73,10010,10011],{},"Redundancy is minimized by reusing existing code. ",[73,10013,10014],{},"Functions perform a single responsibility. ",[52,10016,10018],{"id":10017},"_6-error-handling-and-logging","6. Error Handling and Logging",[12,10020,10021],{},"Proper error handling ensures the code fails gracefully and logs meaningful error messages for debugging. ",[12,10023,9923],{},[70,10025,10026,10029,10032],{},[73,10027,10028],{},"Exceptions are caught and handled. ",[73,10030,10031],{},"Meaningful error messages are logged. ",[73,10033,10034],{},"System performance is not impacted by excessive logging. ",[52,10036,10038],{"id":10037},"_7-collaboration-and-communication","7. Collaboration and Communication",[12,10040,10041],{},"Code reviews are not just about the code itself. They’re also a valuable opportunity for knowledge sharing and collaboration among team members. ",[12,10043,9923],{},[70,10045,10046,10049,10052],{},[73,10047,10048],{},"Clear communication between developers and reviewers. ",[73,10050,10051],{},"Constructive feedback is provided respectfully. ",[73,10053,10054],{},"Documentation and comments are updated as needed.",[501,10056],{},[613,10058,10060,8398],{"id":10059},"why-do-you-need-quality-gates",[16,10061,10062],{},"Why Do You Need Quality Gates?",[12,10064,10065,10066,10071],{},"Quality gates are crucial in your development process to ensure that all code meets certain predefined quality standards. By integrating quality gates into your ",[514,10067,10070],{"href":10068,"rel":10069},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fci-cd-decoded-streamlining-your-development-process\u002F",[518],"continuous integration \u002F continuous deployment"," (CI\u002FCD) pipeline, you can automate checks that block poor-quality code from moving forward. ",[613,10073,10075,8398],{"id":10074},"what-is-the-main-purpose-of-a-quality-management-gate",[16,10076,10077],{},"What is The Main Purpose of a Quality Management Gate?",[12,10079,10080],{},"The main purpose of a quality management gate is to act as a checkpoint that prevents code from advancing in the pipeline unless it meets certain criteria, such as passing tests or adhering to security policies. These gates serve as safety measures to enforce software engineering software standards, keeping the code clean and secure. ",[613,10082,10084,8398],{"id":10083},"how-to-build-quality-gates-into-a-pipeline",[16,10085,10086],{},"How to Build Quality Gates into a Pipeline",[12,10088,10089],{},"To effectively integrate quality gates into your pipeline, follow these steps: ",[70,10091,10092,10098,10109],{},[73,10093,10094,10097],{},[16,10095,10096],{},"Define your criteria:"," Establish clear standards for code quality, such as passing all unit tests or meeting performance benchmarks. ",[73,10099,10100,10103,10104,10108],{},[16,10101,10102],{},"Automate checks:"," Use tools like ",[514,10105,5120],{"href":10106,"rel":10107},"https:\u002F\u002Foobeya.io\u002Foobeya-sonarqube-code-quality-metrics\u002F",[518],", Jenkins, or GitLab to automate these checks as part of your CI\u002FCD process. ",[73,10110,10111,10114],{},[16,10112,10113],{},"Monitor and adjust:"," Continuously monitor the effectiveness of your quality gates and adjust the criteria as your project evolves. ",[12,10116,10117],{},"By integrating quality gates into your pipeline, you can detect issues early, prevent regressions, and ensure a smooth software-making process. ",[501,10119],{},[613,10121,10123],{"id":10122},"code-review-metrics-in-oobeya",[16,10124,10125],{},"Code Review Metrics in Oobeya",[12,10127,10128],{},"Oobeya offers a comprehensive set of metrics to help you analyze and improve your pull request and code review process. Understanding these metrics can significantly enhance your development workflow by identifying bottlenecks and areas for improvement. Here are some of the key pull request metrics provided by Oobeya:",[4331,10130,10132],{"id":10131},"_1-average-time-to-merge",[16,10133,10134],{},"1. Average Time to Merge",[12,10136,10137],{},"The average time to merge measures the duration from when the first commit of a pull request is committed until the pull request is merged into a branch. This metric helps identify delays in the review and merging process, allowing teams to streamline their workflow for faster integration.",[4331,10139,10141],{"id":10140},"_2-of-pull-requests-merged-within-goal",[16,10142,10143],{},"2. % of Pull Requests Merged Within Goal",[12,10145,10146],{},"This metric shows the percentage of pull requests that are merged within a predefined goal time. It helps teams assess how well they are meeting their efficiency targets and can highlight the need for process improvements if a significant number of PRs are not meeting the goal.",[4331,10148,10150],{"id":10149},"_3-merged-pull-requests",[16,10151,10152],{},"3. Merged Pull Requests",[12,10154,10155],{},"The number of merged pull requests provides an overview of how many changes have been successfully integrated into the main branch over a specific period. This metric is useful for tracking activities on the code base and the overall pace of development.",[12,10157,10158],{},[514,10159,10162],{"href":10160,"rel":10161},"https:\u002F\u002Foobeya.io\u002Fget-started-with-oobeya\u002F",[518],[4866,10163],{"alt":10164,"src":10165},"Oobeya Pull Request Metrics","https:\u002F\u002Foobeya.io\u002Fassets\u002Fblog\u002Foobeya-pull-request-1-1024x590.png.webp",[12,10167,10164],{},[4331,10169,10171],{"id":10170},"_4-code-review-cycle-time",[16,10172,10173],{},"4. Code Review Cycle Time",[12,10175,10176],{},"Code review cycle time measures the time taken for a pull request to go through the review process from start to finish (PR opened to PR merged). This includes the time spent in review, addressing feedback, and final approval. This metric helps identify delays in the review process and the need for more efficient review practices.",[4331,10178,10180],{"id":10179},"_5-coding-time",[16,10181,10182],{},"5. Coding Time",[12,10184,10185],{},"Coding time tracks the duration from when coding begins on a feature or fix until the pull request is opened. This metric helps in understanding the development effort and identifying potential areas where coding efficiency can be improved.",[4331,10187,10189],{"id":10188},"_6-pull-request-size-change-volume",[16,10190,10191],{},"6. Pull Request Size \u002F Change Volume",[12,10193,10194],{},"Pull request size measures the number of lines of code changed in a pull request. Large pull requests can be challenging to review and might introduce more bugs. Keeping pull requests small and focused can lead to more manageable and higher-quality reviews.",[4331,10196,10198],{"id":10197},"_7-work-in-progress-open-prs",[16,10199,10200],{},"7. Work in Progress – Open PRs",[12,10202,10203],{},"This metric tracks the number of pull requests currently open and awaiting review or merging. A high number of open PRs can indicate potential bottlenecks in the review process or a need for better prioritization and resource allocation.",[4331,10205,10207],{"id":10206},"_8-reviewer-statistics",[16,10208,10209],{},"8. Reviewer Statistics",[12,10211,10212],{},"Reviewer stats provide insights into the activity and performance of individual reviewers. This includes the number of reviews completed, average review time, and feedback provided. Analyzing these stats helps in understanding reviewer workload and identifying areas for a balanced distribution of review responsibilities.",[4331,10214,10216],{"id":10215},"_9-pull-request-revert-rate",[16,10217,10218],{},"9. Pull Request Revert Rate",[12,10220,10221],{},"The pull request revert rate measures the frequency at which merged pull requests are reverted due to issues or bugs. A high revert rate may indicate problems with the review process or inadequate testing before merging.",[4331,10223,10225],{"id":10224},"_10-pr-risk-oversized-prs",[16,10226,10227],{},"10. PR Risk: Oversized PRs",[12,10229,10230],{},"This metric identifies pull requests that are larger than a specified threshold. Oversized PRs can be difficult to review thoroughly, increasing the risk of undetected issues. Breaking down large changes into smaller PRs can mitigate this risk.",[4331,10232,10234],{"id":10233},"_11-pr-risk-stale-prs",[16,10235,10236],{},"11. PR Risk: Stale PRs",[12,10238,10239],{},"Stale pull requests are those that have been open for an extended period. Stale PRs can indicate abandoned work, lack of reviewer availability, or other process inefficiencies. Identifying and addressing stale PRs helps in maintaining an efficient workflow.",[4331,10241,10243],{"id":10242},"_12-pr-risk-overdue-prs",[16,10244,10245],{},"12. PR Risk: Overdue PRs",[12,10247,10248],{},"Overdue pull requests are those that have exceeded their expected coding timelines. Monitoring overdue PRs helps in identifying process bottlenecks and ensuring timely code integration.",[12,10250,10251,10257],{},[514,10252,10254],{"href":10160,"rel":10253},[518],[4866,10255],{"alt":10164,"src":10256},"https:\u002F\u002Foobeya.io\u002Fassets\u002Fblog\u002Foobeya-pull-request-2-1024x306.png"," Oobeya Pull Request Metrics – Risky PRs",[12,10259,10260,10261,10266],{},"By leveraging these metrics, Oobeya provides a detailed view of your pull request and code review processes, helping you identify inefficiencies and optimize your development workflow. Learn more about key Oobeya metrics on our ",[514,10262,10265],{"href":10263,"rel":10264},"https:\u002F\u002Foobeya.io\u002Foobeya-metric-definitions\u002F",[518],"Oobeya Metric Definitions"," page.",[501,10268],{},[613,10270,10272],{"id":10271},"level-up-code-reviews-with-oobeya",[16,10273,10274],{},"Level Up Code Reviews with Oobeya",[12,10276,10277],{},"Effective code reviews are crucial for maintaining code quality, reliability, and performance. Oobeya provides insights into the code review process with actionable metrics and insights. By tracking and analyzing pull request metrics, you can identify areas for improvement and streamline your workflow.",[613,10279,10281],{"id":10280},"understanding-oobeyas-symptoms-catalog",[16,10282,10283],{},"Understanding Oobeya’s Symptoms Catalog",[12,10285,10286,10291],{},[514,10287,10290],{"href":10288,"rel":10289},"https:\u002F\u002Fdocs.oobeya.io\u002Fsymptoms\u002Fsymptoms-catalog",[518],"Oobeya’s Symptoms Catalog"," is a powerful tool for diagnosing issues in the code review process. Here are some critical code review process symptoms to watch out for:",[12,10293,10294,10301],{},[514,10295,10297],{"href":10160,"rel":10296},[518],[4866,10298],{"alt":10299,"src":10300},"Oobeya Code Review Symptoms","https:\u002F\u002Foobeya.io\u002Fassets\u002Fblog\u002Foobeya-pull-request-3-1024x715.png"," Oobeya Code Review Symptoms",[52,10303,10305],{"id":10304},"_1-unreviewed-pull-requests-symptom","1. Unreviewed Pull Requests Symptom",[12,10307,10308,10309,10314],{},"Unreviewed pull requests can indicate bottlenecks in your review process. When pull requests sit unreviewed for extended periods, it can delay the integration of important changes and impact team productivity. This symptom highlights the need for a more streamlined review process, potentially involving more reviewers or better prioritization. ",[514,10310,10313],{"href":10311,"rel":10312},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs9-unreviewed-pull-requests",[518],"Visit our documentation"," and learn more about this Symptom.",[52,10316,10318],{"id":10317},"_2-lightning-pull-requests-symptom","2. Lightning Pull Requests Symptom",[12,10320,10321,10322,10314],{},"Lightning pull requests are those that are reviewed and merged extremely quickly. While speed can be beneficial, overly rapid reviews may suggest superficial reviews, increasing the risk of undetected issues. Ensuring thorough reviews, even for smaller changes, is crucial for maintaining code quality. ",[514,10323,10313],{"href":10324,"rel":10325},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs10-lightning-pull-requests",[518],[52,10327,10329],{"id":10328},"_3-oversized-pull-requests-symptom","3. Oversized Pull Requests Symptom",[12,10331,10332,10333,10314],{},"Oversize pull requests involve a large number of changes, making them difficult to review effectively. They can overwhelm reviewers, leading to delays and potentially missed issues. Breaking down large changes into smaller, more manageable pull requests can improve review quality and efficiency. ",[514,10334,10313],{"href":10335,"rel":10336},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs11-oversize-pull-requests",[518],[52,10338,10340],{"id":10339},"_4-high-code-review-time-symptom","4. High Code Review Time Symptom",[12,10342,10343,10344,10314],{},"High code review times can signal inefficiencies in the review process. Prolonged review times might be due to complex changes, insufficient reviewer availability, or unclear code. Identifying the root causes and addressing them, such as by increasing reviewer availability or improving code documentation, can help reduce review times. ",[514,10345,10313],{"href":10346,"rel":10347},"https:\u002F\u002Fdocs.oobeya.io\u002Fteam-insights-and-symptoms\u002Fsymptoms-catalog\u002Fs4-high-code-review-time",[518],[12,10349,10350],{},"By leveraging these insights from Oobeya’s Symptoms Catalog, you can enhance your code review process, ensuring a more efficient and effective workflow.",[3354,10352,10353],{},[12,10354,10355,10360],{},[514,10356,10359],{"href":10357,"rel":10358},"https:\u002F\u002Foobeya.io\u002Fget-started-with-oobeya?utm_source=website&utm_medium=blog&utm_campaign=pullrequests",[518],"Fill out this form"," now and get started with Oobeya!",{"title":526,"searchDepth":527,"depth":527,"links":10362},[10363,10365,10375,10377,10379,10381,10382,10383],{"id":9854,"depth":527,"text":10364},"What is The Purpose of The Code Review Checklist? ",{"id":9907,"depth":527,"text":10366,"children":10367},"The Ultimate Code Review Checklist for Developers ",[10368,10369,10370,10371,10372,10373,10374],{"id":9916,"depth":530,"text":9917},{"id":9937,"depth":530,"text":9938},{"id":9957,"depth":530,"text":9958},{"id":9977,"depth":530,"text":9978},{"id":9997,"depth":530,"text":9998},{"id":10017,"depth":530,"text":10018},{"id":10037,"depth":530,"text":10038},{"id":10059,"depth":527,"text":10376},"Why Do You Need Quality Gates? ",{"id":10074,"depth":527,"text":10378},"What is The Main Purpose of a Quality Management Gate? ",{"id":10083,"depth":527,"text":10380},"How to Build Quality Gates into a Pipeline ",{"id":10122,"depth":527,"text":10125},{"id":10271,"depth":527,"text":10274},{"id":10280,"depth":527,"text":10283,"children":10384},[10385,10386,10387,10388],{"id":10304,"depth":530,"text":10305},{"id":10317,"depth":530,"text":10318},{"id":10328,"depth":530,"text":10329},{"id":10339,"depth":530,"text":10340},[10390,541],"quality-assurance","2024-09-24","Code quality is essential for delivering maintainable, secure, and efficient software in today's fast paced software development world. But how can you...",{},"\u002Fblog\u002Fcode-review-checklist-for-developers",{"title":9844,"description":10392},"blog\u002Fcode-review-checklist-for-developers","FWzia7v6wODxVByPURGAr7vdAQK7spukzEsYqXVh2o8",{"id":10399,"title":10400,"author":4245,"avatar":575,"body":10401,"categories":10781,"createAt":542,"date":10782,"description":10783,"extension":545,"meta":10784,"navigation":547,"path":10785,"position":542,"seo":10786,"spotImage":542,"spotText":542,"stem":10787,"tags":542,"__hash__":10788},"blog\u002Fblog\u002Fbalancing-speed-and-quality-in-software-delivery.md","Balancing Speed and Quality in Software Delivery",{"type":9,"value":10402,"toc":10750},[10403,10407,10410,10412,10418,10426,10429,10457,10459,10465,10468,10471,10495,10497,10503,10506,10509,10529,10531,10537,10540,10577,10579,10585,10588,10592,10609,10614,10626,10630,10642,10648,10660,10662,10668,10671,10675,10678,10682,10685,10689,10692,10694,10700,10703,10729,10731,10735,10738,10743],[613,10404,10405,8398],{"id":8114},[16,10406,8115],{},[12,10408,10409],{},"Today, engineering leaders are tasked with delivering high-quality software at an unprecedented speed. While speed and quality are often seen as conflicting goals, finding the right balance is crucial for successful software delivery. This blog post explores the meanings of speed and quality in software delivery, the importance of balancing these two elements, and highlights essential tools for engineering leaders to maintain that balance effectively.",[501,10411],{},[613,10413,10415,8398],{"id":10414},"what-does-speed-mean-in-software-delivery",[16,10416,10417],{},"What Does Speed Mean in Software Delivery?",[12,10419,10420,10421,247,10423,10425],{},"Speed in software delivery refers to how quickly a development team can bring a new feature, fix, or product to market. It's often measured through metrics like ",[16,10422,3042],{},[16,10424,3045],{}," (learn more about DORA Metrics). High speed is essential for staying competitive, responding to market demands, and ensuring customer satisfaction. However, focusing solely on speed can lead to rushed decisions, technical debt, and a compromised product. ",[12,10427,10428],{},"Key aspects of speed in software delivery include: ",[70,10430,10431,10437,10447],{},[73,10432,10433,10436],{},[16,10434,10435],{},"Deployment Frequency Metrics",": The rate at which new code is successfully deployed to production. ",[73,10438,10439,10441,10442,611],{},[16,10440,835],{},": The time it takes to go from code committed to code successfully running in production. Learn ",[514,10443,10446],{"href":10444,"rel":10445},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fhow-to-reduce-lead-time-for-changes-dora-metrics\u002F",[518],"how to reduce the Lead Time For Changes metric",[73,10448,10449,10451,10452,611],{},[16,10450,807],{},": The total time from the start of development to the deployment of a feature or fix. Learn ",[514,10453,10456],{"href":10454,"rel":10455},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fhow-to-calculate-cycle-time\u002F",[518],"how to improve the Cycle Time",[501,10458],{},[613,10460,10462,8398],{"id":10461},"what-does-quality-mean-in-software-delivery",[16,10463,10464],{},"What Does Quality Mean in Software Delivery?",[12,10466,10467],{},"Quality in software delivery encompasses the robustness, performance, security, and user experience of the software. It ensures that the product not only meets functional requirements but also delivers a seamless and reliable user experience. High-quality software is less prone to bugs, security vulnerabilities, and other issues that could affect users and the business. ",[12,10469,10470],{},"Key elements of quality in software delivery include: ",[70,10472,10473,10483,10489],{},[73,10474,10475,10478,10479,611],{},[16,10476,10477],{},"Code Quality",": Ensuring that code is clean, maintainable, and free of defects. Learn more about how ",[514,10480,10482],{"href":10106,"rel":10481},[518],"Oobeya and Sonarqube help your teams improve code quality",[73,10484,10485,10488],{},[16,10486,10487],{},"Testing",": Implementing comprehensive testing strategies, including unit tests, integration tests, and end-to-end tests. ",[73,10490,10491,10494],{},[16,10492,10493],{},"User Experience (UX)",": Designing software that is intuitive, accessible, and user-friendly. ",[501,10496],{},[613,10498,10500,8398],{"id":10499},"the-importance-of-balancing-speed-and-quality",[16,10501,10502],{},"The Importance of Balancing Speed and Quality",[12,10504,10505],{},"Balancing speed and quality is critical because focusing too much on one can negatively impact the other. For example, prioritizing speed over quality can lead to frequent bugs and customer dissatisfaction, while focusing solely on quality can slow down the delivery process, making the company less agile and responsive to changes. ",[12,10507,10508],{},"Benefits of balancing speed and quality include: ",[70,10510,10511,10517,10523],{},[73,10512,10513,10516],{},[16,10514,10515],{},"Reduced Technical Debt",": By maintaining quality while delivering quickly, teams can avoid the pitfalls of accumulating technical debt. ",[73,10518,10519,10522],{},[16,10520,10521],{},"Improved Customer Satisfaction",": Delivering features quickly while ensuring they are high-quality enhances user experience and satisfaction. ",[73,10524,10525,10528],{},[16,10526,10527],{},"Sustainable Development Pace",": Balancing speed and quality ensures that development teams can maintain a steady pace without burning out or compromising on standards. ",[501,10530],{},[613,10532,10534,8398],{"id":10533},"strategies-for-balancing-speed-and-quality",[16,10535,10536],{},"Strategies for Balancing Speed and Quality",[12,10538,10539],{},"Achieving the right balance between speed and quality requires a strategic approach. Here are some strategies to help: ",[70,10541,10542,10548,10554,10560,10571],{},[73,10543,10544,10547],{},[16,10545,10546],{},"Adopt Continuous Integration and Continuous Deployment (CI\u002FCD):"," CI\u002FCD pipelines automate the testing and deployment process, enabling teams to deploy code changes more frequently while maintaining high quality. By integrating changes regularly and automating tests, teams can catch issues early and reduce the risk of defects in production. ",[73,10549,10550,10553],{},[16,10551,10552],{},"Implement DevOps Practices:"," DevOps practices foster collaboration between development and operations teams, ensuring that both speed and quality are prioritized. DevOps metrics, such as deployment frequency and mean time to recovery (MTTR), help teams measure and optimize their performance. ",[73,10555,10556,10559],{},[16,10557,10558],{},"Prioritize Code Reviews and Pair Programming:"," Code reviews and pair programming are effective ways to maintain code quality without slowing down the development process. By having multiple developers review code changes, teams can catch potential issues before they reach production. ",[73,10561,10562,1044,10565,10570],{},[16,10563,10564],{},"Use Feature Flags:",[514,10566,10569],{"href":10567,"rel":10568},"https:\u002F\u002Fwww.optimizely.com\u002Foptimization-glossary\u002Ffeature-flags\u002F",[518],"Feature flags"," allow teams to deploy new features to production without exposing them to all users immediately. This enables faster deployment while giving teams the flexibility to test and refine features before a full release. ",[73,10572,10573,10576],{},[16,10574,10575],{},"Focus on Incremental Improvement:"," Instead of aiming for perfection, focus on incremental improvements. This approach allows teams to deliver small, high-quality updates quickly, making it easier to balance speed and quality over time. ",[501,10578],{},[613,10580,10582,8398],{"id":10581},"tools-to-enhance-speed-and-quality",[16,10583,10584],{},"Tools to Enhance Speed and Quality",[12,10586,10587],{},"Several tools can help engineering leaders achieve the right balance between speed and quality. These tools streamline processes, enhance collaboration, and provide insights that are crucial for making informed decisions. ",[52,10589,10590,8398],{"id":9660},[16,10591,469],{},[12,10593,10594,10597,10598,10603,10604,10608],{},[514,10595,469],{"href":516,"rel":10596},[518]," is a powerful tool that helps engineering teams monitor and improve their software delivery processes. With its focus on ",[514,10599,10602],{"href":10600,"rel":10601},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fwhat-are-the-key-devops-metrics\u002F",[518],"key DevOps metrics"," like deployment frequency and ",[514,10605,3048],{"href":10606,"rel":10607},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fimprove-change-failure-rate\u002F",[518],", Oobeya provides actionable insights that help teams balance speed and quality. By integrating with existing CI\u002FCD pipelines and offering real-time analytics, Oobeya enables teams to identify bottlenecks, optimize workflows, and maintain a sustainable pace of development. ",[52,10610,10612,8398],{"id":10611},"jira",[16,10613,6900],{},[12,10615,10616,10620,10621,611],{},[514,10617,6900],{"href":10618,"rel":10619},"https:\u002F\u002Fwww.atlassian.com\u002Fsoftware\u002Fjira",[518]," is a popular project management tool that helps teams track progress, manage tasks, and collaborate effectively. By using Jira to plan and monitor development sprints, teams can ensure that they are delivering high-quality software on time. Find out how to ",[514,10622,10625],{"href":10623,"rel":10624},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fall-integrations\u002Fproject-management-addons\u002Fjira-cloud-integration",[518],"connect Jira to Oobeya",[52,10627,10628,8398],{"id":4494},[16,10629,5120],{},[12,10631,10632,10636,10637,611],{},[514,10633,5120],{"href":10634,"rel":10635},"https:\u002F\u002Fwww.sonarsource.com\u002F",[518]," is a static code analysis tool that helps teams identify code quality issues early in development. By integrating SonarQube into the CI\u002FCD pipeline, teams can ensure that code meets quality standards before it is deployed to production. Find out how to ",[514,10638,10641],{"href":10639,"rel":10640},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fall-integrations\u002Fcode-quality-addons\u002Fsonarqube-integration",[518],"connect Sonarqube to Oobeya",[52,10643,10645,8398],{"id":10644},"sentry",[16,10646,10647],{},"Sentry",[12,10649,10650,10654,10655,611],{},[514,10651,10647],{"href":10652,"rel":10653},"https:\u002F\u002Fsentry.io\u002F",[518]," is an error-tracking tool that helps teams monitor and fix errors in real time. By providing detailed insights into production issues, Sentry enables teams to address quality concerns quickly without slowing down development. Find out how to ",[514,10656,10659],{"href":10657,"rel":10658},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fall-integrations\u002Fapm-monitoring-addons\u002Fsentry-integration",[518],"connect Sentry to Oobeya",[501,10661],{},[613,10663,10665,8398],{"id":10664},"challenges-in-balancing-speed-and-quality",[16,10666,10667],{},"Challenges in Balancing Speed and Quality",[12,10669,10670],{},"While balancing speed and quality is essential, it’s not without its challenges. Engineering leaders often face obstacles that can make it difficult to maintain this balance. ",[52,10672,10674],{"id":10673},"resource-constraints","Resource Constraints",[12,10676,10677],{},"Limited resources, including time, budget, and personnel, can make it challenging to achieve both speed and quality. Teams may need to make trade-offs, prioritizing certain features or fixes over others. ",[52,10679,10681],{"id":10680},"changing-requirements","Changing Requirements",[12,10683,10684],{},"Frequent changes in project requirements can disrupt development timelines and affect the balance between speed and quality. Teams need to be agile and adaptable to manage these changes effectively. ",[52,10686,10688],{"id":10687},"pressure-to-deliver","Pressure to Deliver",[12,10690,10691],{},"The pressure to meet tight deadlines can lead to shortcuts that compromise quality. Engineering leaders need to find ways to manage stakeholder expectations while maintaining high standards. ",[501,10693],{},[613,10695,10697,8398],{"id":10696},"best-practices-for-maintaining-balance",[16,10698,10699],{},"Best Practices for Maintaining Balance",[12,10701,10702],{},"To consistently balance speed and quality, engineering leaders can adopt the following best practices: ",[70,10704,10705,10711,10723],{},[73,10706,10707,10710],{},[16,10708,10709],{},"Set Clear Priorities:"," Establish clear priorities for each project, ensuring that both speed and quality are considered in decision-making. Communicate these priorities to the team to ensure alignment. ",[73,10712,10713,10716,10717,10722],{},[16,10714,10715],{},"Monitor Key Metrics:"," Regularly monitor key DevOps metrics, such as deployment frequency and deployment success rate, to track progress and identify areas for improvement. Use these metrics to make data-driven decisions. Learn ",[514,10718,10721],{"href":10719,"rel":10720},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fdata-driven-insights-optimize-engineering-workflow\u002F",[518],"how to optimize engineering workflow with data-driven insights"," in software development.",[73,10724,10725,10728],{},[16,10726,10727],{},"Encourage a Collaborative Culture:"," Foster a culture of collaboration between development, operations, and quality assurance teams. By working together, teams can find innovative solutions to balance speed and quality. ",[501,10730],{},[613,10732,10733,8398],{"id":477},[16,10734,1159],{},[12,10736,10737],{},"Balancing speed and quality in software delivery is a complex but essential task for engineering leaders. By understanding the importance of both elements, adopting the right strategies and tools, and overcoming challenges, teams can achieve a sustainable pace of development that delivers high-quality software quickly. As the industry continues to evolve, maintaining this balance will be key to staying competitive and meeting the demands of users. ",[12,10739,10740],{},[16,10741,10742],{},"Read More:",[12,10744,10745],{},[514,10746,10749],{"href":10747,"rel":10748},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fwhat-is-the-impact-of-mttr-mean-time-to-recovery-on-software-quality\u002F",[518],"What is the Impact of MTTR (Mean Time to Recovery) on Software Quality?",{"title":526,"searchDepth":527,"depth":527,"links":10751},[10752,10753,10755,10757,10759,10761,10772,10778,10780],{"id":8114,"depth":527,"text":8449},{"id":10414,"depth":527,"text":10754},"What Does Speed Mean in Software Delivery? ",{"id":10461,"depth":527,"text":10756},"What Does Quality Mean in Software Delivery? ",{"id":10499,"depth":527,"text":10758},"The Importance of Balancing Speed and Quality ",{"id":10533,"depth":527,"text":10760},"Strategies for Balancing Speed and Quality ",{"id":10581,"depth":527,"text":10762,"children":10763},"Tools to Enhance Speed and Quality ",[10764,10766,10768,10770],{"id":9660,"depth":530,"text":10765},"Oobeya ",{"id":10611,"depth":530,"text":10767},"Jira ",{"id":4494,"depth":530,"text":10769},"SonarQube ",{"id":10644,"depth":530,"text":10771},"Sentry ",{"id":10664,"depth":527,"text":10773,"children":10774},"Challenges in Balancing Speed and Quality ",[10775,10776,10777],{"id":10673,"depth":530,"text":10674},{"id":10680,"depth":530,"text":10681},{"id":10687,"depth":530,"text":10688},{"id":10696,"depth":527,"text":10779},"Best Practices for Maintaining Balance ",{"id":477,"depth":527,"text":478},[541],"2024-08-27","Today, engineering leaders are tasked with delivering high quality software at an unprecedented speed. While speed and quality are often seen as...",{},"\u002Fblog\u002Fbalancing-speed-and-quality-in-software-delivery",{"title":10400,"description":10783},"blog\u002Fbalancing-speed-and-quality-in-software-delivery","FcQpMqS120dUluZ-jNdpYMclwbvXYZjuOlJRB9Cbf1E",{"id":10790,"title":10791,"author":4245,"avatar":575,"body":10792,"categories":10923,"createAt":542,"date":10924,"description":10925,"extension":545,"meta":10926,"navigation":547,"path":10927,"position":542,"seo":10928,"spotImage":542,"spotText":542,"stem":10929,"tags":542,"__hash__":10930},"blog\u002Fblog\u002Fenterprise-technology-leadership-summit-2024.md","Oobeya at the Enterprise Technology Leadership Summit 2024: Join Us in Las Vegas!",{"type":9,"value":10793,"toc":10914},[10794,10805,10811,10817,10820,10822,10828,10831,10833,10839,10842,10845,10847,10853,10856,10862,10866,10889,10892,10894,10898],[12,10795,10796,10797,10800,10801,10804],{},"We are thrilled to announce that Oobeya will be one of the sponsors of the ",[16,10798,10799],{},"Enterprise Technology Leadership Summit 2024"," —an event renowned for bringing together the brightest minds and leaders in the technology sector. This prestigious summit, formerly known as the DevOps Enterprise Summit (DOES), will take place in Las Vegas from ",[16,10802,10803],{},"August 20-22, 2024",", and promises to be an event you won't want to miss.",[12,10806,10807,10810],{},[4866,10808],{"alt":10799,"src":10809,"title":10799},"\u002Fassets\u002Fblog\u002Fenterprise-technology-leadership-summit.jpeg"," Enterprise Technology Leadership Summit 2024",[613,10812,10814],{"id":10813},"why-you-should-attend",[16,10815,10816],{},"Why You Should Attend",[12,10818,10819],{},"The Enterprise Technology Leadership Summit has long been the go-to event for professionals who are passionate about transforming their organizations through technology and innovation. As a leading Software Engineering Intelligence Platform, Oobeya is dedicated to empowering teams with the insights and tools they need to optimize their software development processes. This summit is the perfect opportunity for us to connect with like-minded professionals, share our latest advancements, and learn from the best in the industry.",[501,10821],{},[613,10823,10825],{"id":10824},"meet-oobeya-in-las-vegas",[16,10826,10827],{},"Meet Oobeya in Las Vegas",[12,10829,10830],{},"We invite you to visit our booth at the summit, where our team will be on hand to demonstrate how Oobeya can help you achieve greater efficiency, improve developer productivity, and enhance the overall quality of your software. Whether you're already using Oobeya or are new to our platform, our experts will be available to answer your questions, provide live demonstrations, and discuss how we can support your organization's specific needs.",[501,10832],{},[613,10834,10836],{"id":10835},"what-to-expect-at-the-summit",[16,10837,10838],{},"What to Expect at the Summit",[12,10840,10841],{},"The Enterprise Technology Leadership Summit is set to feature a lineup of influential speakers, cutting-edge case studies, and immersive workshops designed to inspire and inform. Attendees will gain valuable insights into the latest trends and best practices in DevOps, Agile, and software engineering, with a focus on driving business value through technology.",[12,10843,10844],{},"As a sponsor, Oobeya is excited to contribute to the dialogue around the future of technology leadership and how organizations can leverage data-driven insights to make smarter decisions and deliver better outcomes.",[501,10846],{},[613,10848,10850],{"id":10849},"plan-your-visit",[16,10851,10852],{},"Plan Your Visit",[12,10854,10855],{},"Las Vegas is not only a hub for entertainment but also a vibrant setting for professional networking and collaboration. Take this opportunity to meet with industry peers, exchange ideas, and explore the latest innovations that are shaping the future of technology.",[12,10857,10858,10859,10861],{},"Be sure to mark your calendars for ",[16,10860,10803],{},", and join us at the Enterprise Technology Leadership Summit. We look forward to seeing you there and discussing how Oobeya can help your team reach new heights in software engineering excellence.",[52,10863,10865],{"id":10864},"event-details","Event Details:",[70,10867,10868,10874,10880],{},[73,10869,10870,10873],{},[16,10871,10872],{},"Date:"," August 20-22, 2024",[73,10875,10876,10879],{},[16,10877,10878],{},"Location:"," Las Vegas",[73,10881,10882,1044,10885],{},[16,10883,10884],{},"Event Link:",[514,10886,10799],{"href":10887,"rel":10888},"https:\u002F\u002Fitrevolution.com\u002Fproduct\u002Fenterprise-technology-leadership-summit-las-vegas-2024\u002F",[518],[12,10890,10891],{},"Don't miss out on this opportunity to connect with Oobeya and be part of an event that is shaping the future of enterprise technology. See you in Las Vegas!",[501,10893],{},[613,10895,10896],{"id":5019},[16,10897,5020],{},[12,10899,10900,10901,10904,10905,10908,10909,10913],{},"Oobeya is a leading ",[16,10902,10903],{},"Software Engineering Intelligence Platform"," recognized for its ability to measure and track the most accurate ",[514,10906,3261],{"href":7188,"rel":10907},[518],". The platform differentiates itself with its innovative \"",[514,10910,10912],{"href":10288,"rel":10911},[518],"Team Health and Symptoms","\" module, which provides actionable suggestions to enhance team performance. With a global presence, Oobeya partners with organizations across six continents and in over ten countries. Headquartered in the United States, Oobeya is committed to delivering solutions that enhance efficiency, quality, and collaboration for development teams worldwide.",{"title":526,"searchDepth":527,"depth":527,"links":10915},[10916,10917,10918,10919,10922],{"id":10813,"depth":527,"text":10816},{"id":10824,"depth":527,"text":10827},{"id":10835,"depth":527,"text":10838},{"id":10849,"depth":527,"text":10852,"children":10920},[10921],{"id":10864,"depth":530,"text":10865},{"id":5019,"depth":527,"text":5020},[4232],"2024-08-16","We are thrilled to announce that Oobeya will be one of the sponsors of the Enterprise Technology Leadership Summit 2024 —an event renowned for bringing...",{},"\u002Fblog\u002Fenterprise-technology-leadership-summit-2024",{"title":10791,"description":10925},"blog\u002Fenterprise-technology-leadership-summit-2024","21jwBD3rO00pT65wsEUioB3B6viBU61yugGHyPor-R8",{"id":10932,"title":10933,"author":4245,"avatar":575,"body":10934,"categories":11207,"createAt":542,"date":11208,"description":11209,"extension":545,"meta":11210,"navigation":547,"path":11211,"position":542,"seo":11212,"spotImage":542,"spotText":542,"stem":11213,"tags":542,"__hash__":11214},"blog\u002Fblog\u002Fwhat-is-the-role-of-observability-in-devops-practices.md","What is the Role of Observability in DevOps Practices?",{"type":9,"value":10935,"toc":11176},[10936,10940,10943,10949,10952,10955,10958,10964,10967,10973,10976,10982,10985,10991,10994,11007,11013,11016,11022,11025,11031,11034,11040,11043,11049,11052,11058,11061,11067,11070,11076,11079,11085,11088,11092,11105,11111,11114,11134,11140,11143,11169,11173],[613,10937,10938,8398],{"id":8114},[16,10939,8115],{},[12,10941,10942],{},"Observability is a crucial component of DevOps practices. It plays a vital role in enhancing system reliability, performance, and overall software quality. By focusing on observability, engineering leaders can ensure their teams are well-equipped to handle the complexities of modern software development. In this blog post, we'll explore the significance of observability in DevOps, how to implement it effectively, and the benefits it brings to engineering teams. ",[613,10944,10946,8398],{"id":10945},"what-is-observability-in-devops",[16,10947,10948],{},"What is Observability in DevOps?",[12,10950,10951],{},"Observability in DevOps refers to the ability to measure the internal state of a system based on the data it produces. This involves collecting and analyzing metrics, logs, and traces to gain insights into system behavior. Unlike traditional monitoring, which only alerts you when something goes wrong, observability allows you to understand why it happened and how to fix it. ",[12,10953,10954],{},"For example, with comprehensive observability, a DevOps team can quickly identify and resolve issues, ensuring continuous delivery and high system availability. Observability tools provide a window into the system's internal workings, enabling teams to detect anomalies, track down root causes, and optimize performance. ",[12,10956,10957],{},"Observability encompasses three main pillars: Metrics, Logs, and Traces. Metrics provide quantitative data on system performance, such as CPU usage and response times. Logs offer detailed records of events within the system, helping teams understand what happened at a specific time. Traces follow the path of a request through the system, identifying bottlenecks and performance issues. Together, these elements create a comprehensive view of the system's health and behavior. ",[613,10959,10961,8398],{"id":10960},"why-is-observability-crucial-for-devops-success",[16,10962,10963],{},"Why is Observability Crucial for DevOps Success?",[12,10965,10966],{},"Observability is essential for DevOps success for several reasons: ",[52,10968,10970],{"id":10969},"enhanced-system-reliability",[791,10971,10972],{},"Enhanced System Reliability",[12,10974,10975],{},"By monitoring and analyzing system metrics, teams can proactively identify and address potential issues before they escalate. This leads to more stable and reliable software systems, reducing the likelihood of downtime and failures. Proactive issue detection and resolution are critical in maintaining high system availability, which is a cornerstone of successful DevOps practices. ",[52,10977,10979],{"id":10978},"improved-user-experience",[791,10980,10981],{},"Improved User Experience",[12,10983,10984],{},"Rapid detection and resolution of issues lead to less downtime and a smoother user experience. Users are less likely to encounter errors or disruptions, resulting in higher satisfaction and retention rates. In a competitive market, delivering a seamless user experience can significantly impact customer loyalty and business success. ",[52,10986,10988],{"id":10987},"data-driven-decision-making",[791,10989,10990],{},"Data-Driven Decision Making",[12,10992,10993],{},"Observability provides actionable insights that help teams make informed decisions about system improvements and optimizations. Engineering leaders can prioritize efforts based on real-time data, leading to more effective and efficient development processes. Data-driven decision-making ensures that resources are allocated to areas that will have the most significant impact on system performance and user satisfaction. ",[12,10995,10996,10997,11002,11003,11006],{},"According to the ",[514,10998,11001],{"href":10999,"rel":11000},"https:\u002F\u002Fcloud.google.com\u002Fdevops\u002Fstate-of-devops",[518],"State of DevOps Report by DORA"," (DevOps Research and Assessment), high-performing IT organizations can achieve up to a 24% improvement in efficiency and a 20% reduction in ",[514,11004,3048],{"href":11005},"\u002Fblog\u002Fimprove-change-failure-rate"," by implementing observability and continuous improvement practices.",[613,11008,11010,8398],{"id":11009},"how-can-you-implement-observability-in-devops-practices",[16,11011,11012],{},"How Can You Implement Observability in DevOps Practices?",[12,11014,11015],{},"Implementing observability in DevOps requires a strategic approach. Here are some steps to get started: ",[52,11017,11019],{"id":11018},"define-key-metrics",[791,11020,11021],{},"Define Key Metrics",[12,11023,11024],{},"Identify the most critical metrics that reflect system health, such as latency, error rates, and request rates. These metrics will provide a clear picture of the system's performance and help teams focus on the most important areas. Establishing key performance indicators (KPIs) ensures that teams can measure and track the effectiveness of their observability efforts. ",[52,11026,11028],{"id":11027},"set-up-logging-and-tracing",[791,11029,11030],{},"Set Up Logging and Tracing",[12,11032,11033],{},"Implement comprehensive logging and distributed tracing to capture detailed information about system operations. This will enable teams to track down issues and understand how different components interact. Effective logging and tracing practices are essential for diagnosing complex issues and ensuring system reliability. ",[52,11035,11037],{"id":11036},"use-observability-tools",[791,11038,11039],{},"Use Observability Tools",[12,11041,11042],{},"Leverage tools like Prometheus, Grafana, and Jaeger to collect, visualize, and analyze observability data. These tools provide powerful capabilities for monitoring and troubleshooting. Prometheus, for example, is widely used for collecting and storing metrics, while Grafana offers robust visualization options. Jaeger is essential for distributed tracing, allowing teams to track requests across microservices. ",[52,11044,11046],{"id":11045},"integrate-with-cicd-pipelines",[791,11047,11048],{},"Integrate with CI\u002FCD Pipelines",[12,11050,11051],{},"Ensure that observability is integrated into your continuous integration and continuous deployment (CI\u002FCD) pipelines for real-time monitoring. This allows teams to detect and address issues early in the development cycle. By incorporating observability into CI\u002FCD processes, teams can maintain high standards of quality and reliability throughout the software development lifecycle. ",[613,11053,11055,8398],{"id":11054},"what-tools-and-technologies-enhance-observability-in-devops",[16,11056,11057],{},"What Tools and Technologies Enhance Observability in DevOps?",[12,11059,11060],{},"Several tools and technologies can significantly enhance observability in DevOps: ",[52,11062,11064],{"id":11063},"prometheus",[791,11065,11066],{},"Prometheus",[12,11068,11069],{},"A powerful monitoring system that collects and stores metrics as time series data. Prometheus is widely used for monitoring and alerting, providing detailed insights into system performance. Its robust querying capabilities and flexible data model make it a popular choice for DevOps teams. ",[52,11071,11073,8398],{"id":11072},"grafana",[791,11074,11075],{},"Grafana",[12,11077,11078],{},"An open-source platform for monitoring and observability, providing rich visualization capabilities. Grafana allows teams to create custom dashboards and visualize metrics in real-time. Its extensive plugin ecosystem enables integration with a variety of data sources, enhancing its versatility. ",[52,11080,11082],{"id":11081},"jaeger",[791,11083,11084],{},"Jaeger",[12,11086,11087],{},"A popular tool for distributed tracing, helping teams track requests across microservices. Jaeger is essential for understanding the flow of requests and identifying bottlenecks. It provides detailed visualizations of request traces, making it easier to pinpoint performance issues and optimize system behavior. ",[52,11089,11090,8398],{"id":9660},[791,11091,469],{},[12,11093,11094,11095,11099,11100,11104],{},"An all-in-one platform offering visualization, monitoring, workflow optimization, and ",[514,11096,11098],{"href":10719,"rel":11097},[518],"data-driven insights",". Oobeya provides comprehensive observability solutions, making it an excellent choice for engineering leaders looking to enhance their ",[514,11101,11103],{"href":10600,"rel":11102},[518],"DevOps"," practices. With Oobeya, teams can monitor their entire system from a single platform, reducing the complexity and overhead of managing multiple tools. The platform's integrated approach simplifies observability, enabling teams to focus on improving engineering performance and reliability. ",[613,11106,11108,8398],{"id":11107},"what-challenges-might-you-encounter-with-observability",[16,11109,11110],{},"What Challenges Might You Encounter with Observability?",[12,11112,11113],{},"Implementing observability comes with its own set of challenges: ",[1520,11115,11116,11122,11128],{},[73,11117,11118,11121],{},[16,11119,11120],{},"Data Overload",": Collecting vast amounts of data can be overwhelming. It's crucial to focus on the most relevant metrics and avoid being swamped by unnecessary information. Effective data management practices, such as filtering and aggregating data, can help teams manage the volume of observability data. ",[73,11123,11124,11127],{},[16,11125,11126],{},"Tool Integration",": Integrating multiple observability tools can be complex and time-consuming. Ensuring seamless integration and compatibility is essential for effective observability. Adopting a standardized approach to tool integration and leveraging platforms that offer built-in integrations can streamline this process. ",[73,11129,11130,11133],{},[16,11131,11132],{},"Skill Gaps",": Teams may require training to effectively use observability tools and interpret the data. Providing adequate training and resources is important for successful implementation. Investing in skill development ensures that team members can leverage observability data to drive improvements in system performance and reliability. ",[613,11135,11137,8398],{"id":11136},"how-does-observability-benefit-devops-teams",[16,11138,11139],{},"How Does Observability Benefit DevOps Teams?",[12,11141,11142],{},"Observability offers numerous benefits to DevOps teams, including: ",[1520,11144,11145,11151,11157,11163],{},[73,11146,11147,11150],{},[16,11148,11149],{},"Faster Issue Resolution",": Teams can quickly pinpoint the root cause of issues and resolve them, reducing downtime. This leads to more stable and reliable software systems. Rapid issue resolution is critical in maintaining high system availability and ensuring a positive user experience.",[73,11152,11153,11156],{},[16,11154,11155],{},"Proactive Maintenance",": With real-time insights, teams can perform proactive maintenance, preventing potential problems. This helps in maintaining high system availability and performance. Proactive maintenance practices reduce the risk of unexpected failures and minimize the impact of issues on users.",[73,11158,11159,11162],{},[16,11160,11161],{},"Enhanced Collaboration",": Observability data fosters better communication and collaboration among team members, leading to more efficient workflows. Teams can work together more effectively, sharing insights and coordinating efforts. Improved collaboration enhances the overall effectiveness of DevOps practices and drives better outcomes for the organization.",[73,11164,11165,11168],{},[16,11166,11167],{},"Continuous Improvement",": By analyzing observability metrics, teams can continuously improve their processes and systems. This leads to higher software quality and better user experiences. Continuous improvement practices ensure that teams can adapt to changing requirements and maintain high standards of quality and reliability.",[613,11170,11171,8398],{"id":477},[16,11172,1159],{},[12,11174,11175],{},"Incorporating observability into DevOps practices is essential for enhancing system reliability, performance, and overall software quality. By leveraging the right tools and strategies, engineering leaders can ensure their teams are well-equipped to handle the complexities of modern software development. Investing in observability not only leads to quicker issue resolution and improved user experiences but also fosters a culture of continuous improvement and data-driven decision-making.",{"title":526,"searchDepth":527,"depth":527,"links":11177},[11178,11179,11181,11187,11194,11202,11204,11206],{"id":8114,"depth":527,"text":8449},{"id":10945,"depth":527,"text":11180},"What is Observability in DevOps? ",{"id":10960,"depth":527,"text":11182,"children":11183},"Why is Observability Crucial for DevOps Success? ",[11184,11185,11186],{"id":10969,"depth":530,"text":10972},{"id":10978,"depth":530,"text":10981},{"id":10987,"depth":530,"text":10990},{"id":11009,"depth":527,"text":11188,"children":11189},"How Can You Implement Observability in DevOps Practices? ",[11190,11191,11192,11193],{"id":11018,"depth":530,"text":11021},{"id":11027,"depth":530,"text":11030},{"id":11036,"depth":530,"text":11039},{"id":11045,"depth":530,"text":11048},{"id":11054,"depth":527,"text":11195,"children":11196},"What Tools and Technologies Enhance Observability in DevOps? ",[11197,11198,11200,11201],{"id":11063,"depth":530,"text":11066},{"id":11072,"depth":530,"text":11199},"Grafana ",{"id":11081,"depth":530,"text":11084},{"id":9660,"depth":530,"text":10765},{"id":11107,"depth":527,"text":11203},"What Challenges Might You Encounter with Observability? ",{"id":11136,"depth":527,"text":11205},"How Does Observability Benefit DevOps Teams? ",{"id":477,"depth":527,"text":478},[541],"2024-08-05","Observability is a crucial component of DevOps practices. It plays a vital role in enhancing system reliability, performance, and overall software...",{},"\u002Fblog\u002Fwhat-is-the-role-of-observability-in-devops-practices",{"title":10933,"description":11209},"blog\u002Fwhat-is-the-role-of-observability-in-devops-practices","xws80v4hHwLPeCIdCTp95bJEu-h8frESQfHc167vFfI",{"id":11216,"title":10749,"author":4245,"avatar":575,"body":11217,"categories":11523,"createAt":542,"date":11524,"description":11525,"extension":545,"meta":11526,"navigation":547,"path":11527,"position":542,"seo":11528,"spotImage":542,"spotText":542,"stem":11529,"tags":542,"__hash__":11530},"blog\u002Fblog\u002Fwhat-is-the-impact-of-mttr-mean-time-to-recovery-on-software-quality.md",{"type":9,"value":11218,"toc":11511},[11219,11223,11248,11251,11253,11259,11262,11269,11275,11278,11281,11284,11286,11292,11295,11298,11301,11307,11309,11315,11335,11338,11357,11360,11362,11368,11382,11385,11387,11393,11433,11435,11439,11442,11444,11450],[613,11220,11221],{"id":8114},[16,11222,8115],{},[12,11224,11225,11226,11228,11229,11233,11234,11237,11238,11241,11242,11247],{},"Understanding the impact of ",[16,11227,4664],{}," on ",[514,11230,11232],{"href":11231},"\u002Fblog\u002F6-steps-to-take-control-of-software-quality","software quality"," is crucial for engineering leaders in DevOps. This metric, which measures the average time taken to restore full functionality after a failure, directly influences software reliability and user experience. ",[16,11235,11236],{},"MTTR"," is one of the four ",[514,11239,848],{"href":7188,"rel":11240},[518]," defined by the ",[514,11243,11246],{"href":11244,"rel":11245},"https:\u002F\u002Fdora.dev\u002F",[518],"DevOps Research and Assessment (DORA) group",", providing a comprehensive framework for measuring the performance of software delivery teams.",[12,11249,11250],{},"High MTTR can lead to prolonged downtimes, frustrating users, and negatively affecting a company’s reputation and bottom line. By the end of this article, you'll learn the significance of MTTR, strategies to reduce it, and how it ties into broader software quality and performance metrics.",[501,11252],{},[613,11254,11256],{"id":11255},"what-is-mttr-and-how-is-it-calculated",[16,11257,11258],{},"What is MTTR and How is it Calculated?",[12,11260,11261],{},"Mean Time to Recovery (MTTR) is a key performance indicator in DevOps and software engineering. It measures the average time required to recover from a failure and restore the system to its normal state. A lower MTTR indicates a more resilient system and a more efficient incident response process.",[12,11263,11264,11268],{},[4866,11265],{"alt":11266,"src":11267},"Time to Restore Service (MTTR) - Oobeya DORA Metrics","\u002Fassets\u002Fblog\u002Fdora-timeline-1024x593.jpg"," Time to Restore Service (MTTR) - Oobeya DORA Metrics",[613,11270,11272],{"id":11271},"why-is-mttr-important-for-software-quality",[16,11273,11274],{},"Why is MTTR Important for Software Quality?",[12,11276,11277],{},"High MTTR is often synonymous with prolonged downtimes, which can severely impact software quality. Frequent and extended outages undermine the reliability of your software, leading to a cascade of negative effects.",[12,11279,11280],{},"Users expect high availability and minimal disruptions. Extended downtime frustrates users and diminishes their trust in the software.",[12,11282,11283],{},"Prolonged downtimes can result in significant revenue loss. For instance, if an e-commerce platform is down, every minute of downtime could mean lost sales. Additionally, frequent outages can damage a company’s reputation, making it difficult to retain existing customers and attract new ones.",[501,11285],{},[613,11287,11289],{"id":11288},"how-does-mttr-affect-user-experience",[16,11290,11291],{},"How Does MTTR Affect User Experience?",[12,11293,11294],{},"In the digital age, users have high expectations for software performance. They expect applications to be available 24\u002F7 with minimal interruptions. When users encounter frequent downtimes or slow recovery times, their experience deteriorates, and they may lose trust in the application and seek alternatives.",[12,11296,11297],{},"Users are likely to lose confidence in the software’s reliability, which can lead to decreased usage or abandonment. This is particularly true for mission-critical applications where downtime can have severe consequences.",[12,11299,11300],{},"Poor user experience due to high MTTR can result in lower engagement levels. Users may spend less time on the application or stop using it altogether, affecting overall user retention and satisfaction.",[12,11302,11303,11306],{},[16,11304,11305],{},"Example",": Consider a financial services company that relies heavily on its online platform. High MTTR in this scenario could lead to clients being unable to access their accounts, perform transactions, or receive timely updates, resulting in a loss of trust and potentially severe financial repercussions. Conversely, a low MTTR ensures that any issues are swiftly resolved, maintaining user confidence and service reliability.",[501,11308],{},[613,11310,11312],{"id":11311},"what-strategies-can-reduce-mttr",[16,11313,11314],{},"What Strategies Can Reduce MTTR?",[70,11316,11317,11323,11329],{},[73,11318,11319,11322],{},[16,11320,11321],{},"Automated Monitoring:"," Implement continuous monitoring tools that provide real-time alerts. This allows teams to detect and respond to issues immediately. Tools like Datadog and New Relic offer comprehensive monitoring solutions that help in early detection and swift resolution of incidents.",[73,11324,11325,11328],{},[16,11326,11327],{},"Incident Response Plans:"," Develop detailed incident response protocols that outline steps to be taken when an incident occurs. Regularly update these plans to incorporate lessons learned from previous incidents. Having a well-documented response plan ensures that team members know exactly what to do, reducing the time spent figuring out the next steps during an incident.",[73,11330,11331,11334],{},[16,11332,11333],{},"Team Training:"," Ensure that all team members are trained in quick incident resolution techniques. Regular drills and simulations can help teams stay prepared for real incidents. Training should also cover the use of monitoring and incident management tools to ensure that everyone is proficient in using the tools available to them.",[12,11336,11337],{},"Several tools are available to help reduce MTTR. These include:",[70,11339,11340,11346,11352],{},[73,11341,11342,11345],{},[16,11343,11344],{},"PagerDuty - OpsGenie - ServiceNow",": For incident management and on-call scheduling.",[73,11347,11348,11351],{},[16,11349,11350],{},"New Relic - Datadog, Appdynamics, Dynatrace",": For application performance monitoring.",[73,11353,11354,11356],{},[16,11355,469],{},": For an all-in-one solution encompassing visualization, monitoring, and workflow optimization.",[12,11358,11359],{},"Using a combination of these tools can help teams effectively monitor, manage, and resolve incidents, thereby reducing MTTR and improving overall system performance.",[501,11361],{},[613,11363,11365],{"id":11364},"how-can-you-monitor-and-improve-mttr",[16,11366,11367],{},"How Can You Monitor and Improve MTTR?",[70,11369,11370,11376],{},[73,11371,11372,11375],{},[16,11373,11374],{},"Data Analytics in Engineering:"," Utilize analytics tools to gain insights into incident patterns and root causes. These insights can help identify and address recurring issues, leading to reduced MTTR. Analyzing data from past incidents can reveal trends and common failure points, allowing teams to proactively address potential issues before they escalate.",[73,11377,11378,11381],{},[16,11379,11380],{},"Continuous Improvement:"," Regularly review and refine incident management processes. Conduct post-incident reviews to learn from each incident and implement improvements. Continuous improvement practices, such as incorporating feedback loops and implementing best practices, can help teams become more efficient in incident resolution.",[12,11383,11384],{},"Continuous improvement involves regularly reviewing incident management processes, conducting post-incident reviews, and incorporating feedback from team members. By fostering a culture of continuous learning and improvement, organizations can ensure that their incident response strategies remain effective and efficient.",[501,11386],{},[613,11388,11390],{"id":11389},"what-are-the-long-term-benefits-of-a-low-mttr-on-software-quality",[16,11391,11392],{},"What are the Long-term Benefits of a Low MTTR on Software Quality?",[70,11394,11395,11401,11407],{},[73,11396,11397,11400],{},[16,11398,11399],{},"Increased Reliability:"," Faster recovery times lead to higher software reliability. Users experience fewer disruptions, which enhances their trust in the software. High reliability is a competitive advantage, especially in markets where users have multiple alternatives.",[73,11402,11403,11406],{},[16,11404,11405],{},"Better User Experience:"," A low MTTR enhances user experience by providing a more stable and dependable application. Users are more likely to continue using and recommending software that they can rely on.",[73,11408,11409,11412,11413],{},[16,11410,11411],{},"Competitive Advantage:"," In the long run, maintaining a low MTTR can have several strategic benefits:\n",[70,11414,11415,11421,11427],{},[73,11416,11417,11420],{},[16,11418,11419],{},"Enhanced Customer Loyalty:"," Users are more likely to remain loyal to reliable software.",[73,11422,11423,11426],{},[16,11424,11425],{},"Market Differentiation:"," Companies that consistently maintain low MTTR can differentiate themselves in the market by emphasizing their reliability and quick recovery times.",[73,11428,11429,11432],{},[16,11430,11431],{},"Cost Savings:"," Reduced downtime directly translates to cost savings by minimizing lost revenue and avoiding penalties related to service level agreements (SLAs).",[501,11434],{},[613,11436,11437],{"id":477},[16,11438,1159],{},[12,11440,11441],{},"In conclusion, Mean Time to Recovery (MTTR) is a critical metric for engineering leaders in DevOps. By understanding and reducing MTTR, organizations can significantly improve software quality, enhance user experience, and achieve long-term benefits. Implementing effective incident management strategies, leveraging data-driven insights, and fostering a culture of continuous improvement are key steps toward achieving these goals. Oobeya provides a comprehensive solution for monitoring, workflow optimization, and data-driven engineering, making it an invaluable tool for any organization aiming to reduce MTTR and improve software performance.",[501,11443],{},[52,11445,11447],{"id":11446},"related-blog-posts",[16,11448,11449],{},"Related Blog Posts",[70,11451,11452,11459,11466,11472,11478,11485,11492,11498,11504],{},[73,11453,11454],{},[514,11455,11458],{"href":11456,"rel":11457},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fhow-to-measure-dora-metrics-accurately\u002F",[518],"How to Measure DORA Metrics Accurately",[73,11460,11461],{},[514,11462,11465],{"href":11463,"rel":11464},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fdora-metrics-delivery-performance\u002F",[518],"DORA Metrics: Key to High-Performing Development Teams",[73,11467,11468],{},[514,11469,11471],{"href":10444,"rel":11470},[518],"How To Reduce Lead Time For Changes (Optimizing DORA Metrics)",[73,11473,11474],{},[514,11475,11477],{"href":10606,"rel":11476},[518],"How To Improve Change Failure Rate: Strategies for Engineering Leaders",[73,11479,11480],{},[514,11481,11484],{"href":11482,"rel":11483},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fdora-metrics-tracking-how-to-effectively-detect-production-failures\u002F",[518],"DORA Metrics Tracking: How to Effectively Detect Production Failures",[73,11486,11487],{},[514,11488,11491],{"href":11489,"rel":11490},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fbeyond-dora-metrics-identifying-symptoms-that-lead-to-poor-dora-metrics\u002F",[518],"Beyond DORA Metrics: Identifying Symptoms That Lead To Poor DORA Metrics",[73,11493,11494],{},[514,11495,11497],{"href":10600,"rel":11496},[518],"What Are The Key DevOps Metrics?",[73,11499,11500],{},[514,11501,11503],{"href":10454,"rel":11502},[518],"How to Calculate Cycle Time?",[73,11505,11506],{},[514,11507,11510],{"href":11508,"rel":11509},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fleveraging-space-framework-and-oobeya-for-enhanced-software-development-productivity\u002F",[518],"Leveraging SPACE Framework and Oobeya for Enhanced Software Development Productivity",{"title":526,"searchDepth":527,"depth":527,"links":11512},[11513,11514,11515,11516,11517,11518,11519,11520],{"id":8114,"depth":527,"text":8115},{"id":11255,"depth":527,"text":11258},{"id":11271,"depth":527,"text":11274},{"id":11288,"depth":527,"text":11291},{"id":11311,"depth":527,"text":11314},{"id":11364,"depth":527,"text":11367},{"id":11389,"depth":527,"text":11392},{"id":477,"depth":527,"text":1159,"children":11521},[11522],{"id":11446,"depth":530,"text":11449},[1232],"2024-07-24","Understanding the impact of Mean Time to Recovery (MTTR) on software quality is crucial for engineering leaders in DevOps. This metric, which measures...",{},"\u002Fblog\u002Fwhat-is-the-impact-of-mttr-mean-time-to-recovery-on-software-quality",{"title":10749,"description":11525},"blog\u002Fwhat-is-the-impact-of-mttr-mean-time-to-recovery-on-software-quality","exhk2M70w-ra6IVC8rC7j5zHCjVidwEPqsNJNCoc5Ig",{"id":11532,"title":11533,"author":4245,"avatar":575,"body":11534,"categories":11950,"createAt":542,"date":11951,"description":11952,"extension":545,"meta":11953,"navigation":547,"path":11954,"position":542,"seo":11955,"spotImage":542,"spotText":542,"stem":11956,"tags":542,"__hash__":11957},"blog\u002Fblog\u002Fstate-of-developer-experience-in-2024-key-findings-and-highlights.md","State of Developer Experience in 2024: Key Findings and Highlights",{"type":9,"value":11535,"toc":11930},[11536,11540,11587,11589,11593,11604,11606,11611,11622,11628,11653,11658,11661,11666,11680,11685,11688,11694,11705,11707,11713,11722,11729,11733,11736,11740,11743,11747,11750,11754,11757,11761,11764,11766,11771,11807,11809,11814,11842,11845,11848,11855,11861,11867,11873,11879,11885,11891,11897,11899,11904,11907,11910,11913,11915,11919,11922],[613,11537,11538],{"id":615},[16,11539,616],{},[1520,11541,11542,11544,11547,11550,11553,11573,11576,11579,11582,11585],{},[73,11543,8115],{},[73,11545,11546],{},"The Disconnect Between Developers and Leaders",[73,11548,11549],{},"The Importance of Developer Experience",[73,11551,11552],{},"Leveraging AI for Better Developer Experience",[73,11554,11555,11556],{},"Top 5 Inefficiencies According To Developers\n",[1520,11557,11558,11561,11564,11567,11570],{},[73,11559,11560],{},"Technical Debt",[73,11562,11563],{},"Insufficient Documentation",[73,11565,11566],{},"Build Processes",[73,11568,11569],{},"Lack of Time for Deep Work",[73,11571,11572],{},"Lack of Clear Direction",[73,11574,11575],{},"State of Developer Experience 2024 Key Findings",[73,11577,11578],{},"How Oobeya Can Help Improve Developer Experience",[73,11580,11581],{},"Oobeya’s Team Symptoms Related To Developer Experience",[73,11583,11584],{},"How to Measure Developer Experience",[73,11586,1159],{},[501,11588],{},[613,11590,11591],{"id":8114},[16,11592,8115],{},[12,11594,11595,11596,11599,11600,611],{},"In the dynamic world of software development, ensuring a seamless developer experience is more crucial than ever. Recent research \"State of developer experience report 2024\" by ",[16,11597,11598],{},"Atlassian",", in collaboration with DX and Wakefield Research, sheds light on the current state of developer experience and offers actionable insights for improvement. This blog post explores the key findings and how Oobeya can help organizations enhance their ",[514,11601,2151],{"href":11602,"rel":11603},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fwhy-developer-experience-matters\u002F",[518],[501,11605],{},[613,11607,11609],{"id":11608},"the-disconnect-between-developers-and-leaders",[16,11610,11546],{},[12,11612,11613,11614,11617,11618,11621],{},"The report highlights a significant gap between developers and their leaders. While ",[16,11615,11616],{},"69% of developers"," lose ",[16,11619,11620],{},"8+ hours weekly"," to inefficiencies, less than half believe their leaders are aware of these issues. This disconnect often leads to misaligned priorities and ineffective solutions.",[4331,11623,11625],{"id":11624},"key-stats",[16,11626,11627],{},"Key Stats:",[70,11629,11630,11640,11647],{},[73,11631,11632,11635,11636,11639],{},[16,11633,11634],{},"69%"," of developers ",[16,11637,11638],{},"lose 8+ hours weekly"," to inefficiencies.",[73,11641,11642,11643,11646],{},"Only ",[16,11644,11645],{},"44%"," believe their leaders are aware of these issues.",[73,11648,11649,11652],{},[16,11650,11651],{},"48%"," of leaders believe their dev team is understaffed.",[613,11654,11656],{"id":11655},"the-importance-of-developer-experience",[16,11657,11549],{},[12,11659,11660],{},"A positive developer experience is essential for productivity and retention. However, traditional productivity metrics often fall short. Atlassian's research found that improving developer experience directly correlates with higher satisfaction and reduced time lost to inefficiencies.",[4331,11662,11664],{"id":11663},"key-stats-1",[16,11665,11627],{},[70,11667,11668,11674],{},[73,11669,11670,11673],{},[16,11671,11672],{},"63%"," of developers consider developer experience important when deciding to stay in a job.",[73,11675,11676,11679],{},[16,11677,11678],{},"76%"," of organizations plan to invest more in improving developer experience.",[613,11681,11683],{"id":11682},"leveraging-ai-for-better-developer-experience",[16,11684,11552],{},[12,11686,11687],{},"Leaders see AI as a key driver for enhancing productivity and satisfaction. However, developers remain skeptical, with many not experiencing significant gains from AI tools yet. Effective implementation requires understanding specific developer needs and creating tailored solutions.",[4331,11689,11691],{"id":11690},"key-insights",[16,11692,11693],{},"Key Insights:",[70,11695,11696,11702],{},[73,11697,11698,11701],{},[16,11699,11700],{},"62%"," of developers say that AI tools are not improving or slightly improving their productivity today.",[73,11703,11704],{},"The same number of developers believe this will change in the next two years.",[501,11706],{},[613,11708,11710],{"id":11709},"top-5-inefficiencies-according-to-developers",[16,11711,11712],{},"Top 5 Inefficiencies According To Developers",[12,11714,11715,11716,11721],{},"Based on ",[514,11717,11720],{"href":11718,"rel":11719},"https:\u002F\u002Fsurvey.stackoverflow.co\u002F2023\u002F",[518],"Stack Overflow’s 2023 Developer Survey",", the global average salary for developers in 2023 was $69,767. If a developer loses an average of 8 hours per week due to inefficiencies, this translates to an annual cost of $13,954.40 per engineer. As organizations grow, the financial impact of these inefficiencies increases. Therefore, engineering leaders must identify their organization's inefficiencies and take action to eliminate them.",[12,11723,11724,11728],{},[4866,11725],{"alt":11726,"src":11727},"State of Developer Experience Report 2024, Atlassian DX","\u002Fassets\u002Fblog\u002Ftop-5-inefficiencies-1024x496.png"," State of Developer Experience Report 2024, Atlassian DX",[52,11730,11732],{"id":11731},"_1-technical-debt-59","1. Technical Debt (59%)",[12,11734,11735],{},"Technical debt is the most significant inefficiency affecting developers. It refers to the future work required to fix or improve code that was rushed or poorly designed. High technical debt leads to increased bugs, slower feature development, and higher maintenance costs.",[52,11737,11739],{"id":11738},"_2-insufficient-documentation-41","2. Insufficient Documentation (41%)",[12,11741,11742],{},"Developers often struggle with inadequate documentation. When documentation is lacking or outdated, it hinders the onboarding process, slows down development, and increases dependency on more experienced team members.",[52,11744,11746],{"id":11745},"_3-build-processes-27","3. Build Processes (27%)",[12,11748,11749],{},"Inefficient processes are another major bottleneck. This includes cumbersome workflows, redundant tasks, and a lack of automation. Streamlining processes and reducing unnecessary steps can significantly enhance productivity.",[52,11751,11753],{"id":11752},"_4-lack-of-time-for-deep-work-27","4. Lack of Time for Deep Work (27%)",[12,11755,11756],{},"Developers need large blocks of uninterrupted time to focus on complex problem-solving and coding tasks. Frequent interruptions and meetings disrupt this deep work, leading to decreased productivity and increased frustration.",[52,11758,11760],{"id":11759},"_5-lack-of-clear-direction-25","5. Lack of Clear Direction (25%)",[12,11762,11763],{},"Unclear or constantly changing goals and priorities can cause significant delays and frustrations. Ensuring clear communication of project goals and regular updates can mitigate this issue.",[501,11765],{},[613,11767,11769],{"id":11768},"state-of-developer-experience-2024-key-findings",[16,11770,11575],{},[70,11772,11773,11779,11784,11791,11797,11802],{},[73,11774,11775,11778],{},[16,11776,11777],{},"86%"," of leaders believe attracting and retaining the best developer talent will be almost impossible without improving developer experience.",[73,11780,11781,11783],{},[16,11782,11672],{}," of developers consider developer experience important or very important when deciding to stay in their current job.",[73,11785,11786,11787,11790],{},"Less than ",[16,11788,11789],{},"50%"," of developers think their organization prioritizes developer experience.",[73,11792,11793,11796],{},[16,11794,11795],{},"2 out of 3"," developers aren’t seeing significant productivity gains from using AI tools yet.",[73,11798,11799,11801],{},[16,11800,11634],{}," of developers lose 8 hours or more of their working week to inefficiencies.",[73,11803,11642,11804,11806],{},[16,11805,11645],{}," of developers believe leaders are aware of these issues.",[501,11808],{},[613,11810,11812],{"id":11811},"how-oobeya-can-help-improve-developer-experience",[16,11813,11578],{},[12,11815,11816,11818,11819,11822,11823,247,11826,11829,11830,11833,11834,27,11837,11841],{},[16,11817,469],{}," stands out with its ",[16,11820,11821],{},"innovative approach"," to detecting and addressing ",[16,11824,11825],{},"development",[16,11827,11828],{},"delivery symptom","s automatically. By leveraging key engineering metrics (like ",[514,11831,848],{"href":7188,"rel":11832},[518],", Agile metrics, ",[514,11835,3551],{"href":10454,"rel":11836},[518],[514,11838,11840],{"href":10106,"rel":11839},[518],"quality metrics",") and hundreds of data points, Oobeya enables software organizations to effortlessly identify recurring anti-patterns, bottlenecks, and roadblocks.",[12,11843,11844],{},"With actionable insights derived from in-depth metric analysis, Oobeya empowers teams to take proactive steps toward optimizing their processes and cultivating healthy, effective teams.",[52,11846,11581],{"id":11847},"oobeyas-team-symptoms-related-to-developer-experience",[12,11849,11850,11854],{},[4866,11851],{"alt":11852,"src":11853},"Oobeya Engineering Insights - State of Developer Experience","\u002Fassets\u002Fblog\u002Fsymptom1-1024x576.jpg"," Oobeya Engineering Insights - State of Developer Experience",[12,11856,11857,11860],{},[16,11858,11859],{},"Recurring High Cognitive Load (S2)"," Developers overwhelmed by complex tasks can experience stress and reduced productivity. High cognitive load often results from poor documentation, complex codebases, or inadequate tooling.",[12,11862,11863,11866],{},[16,11864,11865],{},"High Weekend Activity (S3)"," Excessive weekend work can lead to burnout and decreased job satisfaction, often due to unrealistic deadlines or poor project management.",[12,11868,11869,11872],{},[16,11870,11871],{},"High Code Review Time (S4)"," Extended code review periods can frustrate developers, delay progress, and reduce efficiency, typically due to a lack of reviewer availability or inefficient processes.",[12,11874,11875,11878],{},[16,11876,11877],{},"Unreviewed Pull Requests (S9)"," When pull requests are left without review for too long, it causes bottlenecks and frustration among developers eager to integrate their changes.",[12,11880,11881,11884],{},[16,11882,11883],{},"Lightning Pull Requests (S10)"," Extremely fast pull request reviews may indicate superficial reviews, potentially compromising code quality and leading to technical debt.",[12,11886,11887,11890],{},[16,11888,11889],{},"Oversize Pull Requests (S11)"," Large pull requests are time-consuming to review, leading to prolonged feedback cycles and increased cognitive load on developers.",[12,11892,11893,11894,611],{},"To learn more, visit Oobeya’s ",[514,11895,8353],{"href":10288,"rel":11896},[518],[501,11898],{},[613,11900,11902],{"id":11901},"how-to-measure-developer-experience",[16,11903,11584],{},[12,11905,11906],{},"Is it possible to measure developer experience? Absolutely. However, the key is not to overcomplicate it. Focusing too much on the problem can obscure the solution. You need to look beyond the problem. For Oobeya's partners, assessing developer experience (DX) is straightforward:",[12,11908,11909],{},"If Oobeya detects symptoms, your developer experience isn't optimal. Addressing these symptoms is crucial to improving your team's developer experience.",[12,11911,11912],{},"In essence, Oobeya helps you look beyond the problem to identify the solution.",[501,11914],{},[613,11916,11917],{"id":477},[16,11918,1159],{},[12,11920,11921],{},"Improving developer experience is an ongoing journey that requires continuous effort and alignment between developers and their leaders. By leveraging insights from Atlassian’s research and integrating Oobeya’s powerful tools, organizations can create a more satisfying and productive environment for their developers.",[12,11923,11924,11925,611],{},"For more detailed insights, read the full ",[514,11926,11929],{"href":11927,"rel":11928},"https:\u002F\u002Fwww.atlassian.com\u002Fblog\u002Fdeveloper\u002Fdeveloper-experience-report-2024",[518],"Atlassian Developer Experience Report 2024",{"title":526,"searchDepth":527,"depth":527,"links":11931},[11932,11933,11934,11935,11936,11937,11944,11945,11948,11949],{"id":615,"depth":527,"text":616},{"id":8114,"depth":527,"text":8115},{"id":11608,"depth":527,"text":11546},{"id":11655,"depth":527,"text":11549},{"id":11682,"depth":527,"text":11552},{"id":11709,"depth":527,"text":11712,"children":11938},[11939,11940,11941,11942,11943],{"id":11731,"depth":530,"text":11732},{"id":11738,"depth":530,"text":11739},{"id":11745,"depth":530,"text":11746},{"id":11752,"depth":530,"text":11753},{"id":11759,"depth":530,"text":11760},{"id":11768,"depth":527,"text":11575},{"id":11811,"depth":527,"text":11578,"children":11946},[11947],{"id":11847,"depth":530,"text":11581},{"id":11901,"depth":527,"text":11584},{"id":477,"depth":527,"text":1159},[2620],"2024-07-18","Explore key findings on developer experience in 2024, including leadership alignment, AI adoption, productivity, and software team effectiveness.",{},"\u002Fblog\u002Fstate-of-developer-experience-in-2024-key-findings-and-highlights",{"title":11533,"description":11952},"blog\u002Fstate-of-developer-experience-in-2024-key-findings-and-highlights","3EgbKNOdMtcPYFiWpdWkrXUzHLvcIQ1b348CLk7Xoc0",{"id":11959,"title":11960,"author":4245,"avatar":575,"body":11961,"categories":12281,"createAt":542,"date":12282,"description":12283,"extension":545,"meta":12284,"navigation":547,"path":12285,"position":542,"seo":12286,"spotImage":542,"spotText":542,"stem":12287,"tags":542,"__hash__":12288},"blog\u002Fblog\u002Fdata-driven-insights-optimize-engineering-workflow.md","How to Optimize Engineering Workflow with Data-Driven Insights?",{"type":9,"value":11962,"toc":12264},[11963,11967,11995,11997,12001,12004,12006,12011,12020,12034,12036,12041,12044,12047,12051,12062,12064,12069,12077,12080,12083,12098,12103,12125,12135,12137,12142,12145,12148,12151,12156,12182,12184,12189,12192,12195,12198,12203,12214,12216,12221,12224,12227,12230,12235,12255,12257,12261],[613,11964,11965],{"id":615},[16,11966,616],{},[1520,11968,11969],{},[73,11970,11971],{},[1520,11972,11973,11975,11978,11981,11984,11987,11990,11993],{},[73,11974,8115],{},[73,11976,11977],{},"What Are Data-Driven Insights in Engineering?",[73,11979,11980],{},"How Can Data-Driven Insights Improve Engineering Workflow?",[73,11982,11983],{},"What Tools and Technologies Are Used for Data-Driven Engineering?",[73,11985,11986],{},"How Do You Implement Data-Driven Practices in Your Workflow?",[73,11988,11989],{},"What Challenges Might You Face When Using Data-Driven Insights?",[73,11991,11992],{},"What Are the Best Practices for Leveraging Data-Driven Insights?",[73,11994,1159],{},[501,11996],{},[613,11998,11999,8398],{"id":8114},[16,12000,8115],{},[12,12002,12003],{},"In today's fast-paced engineering environment, optimizing workflows is crucial for success. However, many teams struggle with inefficiencies and bottlenecks that hinder performance. By leveraging data-driven insights, you can streamline your processes and achieve remarkable results. This article will guide you on how to harness the power of data to enhance your engineering workflow, improve efficiency, and drive better outcomes. ",[501,12005],{},[613,12007,12009,8398],{"id":12008},"what-are-data-driven-insights-in-engineering",[16,12010,11977],{},[12,12012,12013,12014,12019],{},"Data-driven insights refer to actionable knowledge derived from the systematic analysis of data. In engineering, this means using data to inform decisions, ",[514,12015,12018],{"href":12016,"rel":12017},"https:\u002F\u002Foobeya.io\u002Foptimize-software-engineering\u002F",[518],"optimize processes",", and solve problems more effectively. With the right data, engineering leaders can gain a clearer understanding of their workflow, identify areas for improvement, and make informed decisions that drive success. ",[3354,12021,12022],{},[12,12023,12024,12025,23,12028,12033],{},"Organizations utilizing data-driven strategies see up to a 30% increase in operational efficiency (source: ",[791,12026,12027],{},"Data Delivery and Transformation",[514,12029,12032],{"href":12030,"rel":12031},"https:\u002F\u002Fwww.mckinsey.com\u002Fcapabilities\u002Fmckinsey-digital\u002Fmckinsey-technology\u002Foverview\u002Fdata-delivery-transformation",[518],"McKinsey","). ",[501,12035],{},[613,12037,12039,8398],{"id":12038},"how-can-data-driven-insights-improve-engineering-workflow",[16,12040,11980],{},[12,12042,12043],{},"Data-driven insights offer numerous benefits that can significantly improve your engineering workflow. Improved decision-making is one of the primary advantages. By analyzing data, you can gain a deeper understanding of your processes, identify trends, and make informed choices that enhance project outcomes. ",[12,12045,12046],{},"Another benefit is enhanced efficiency. Data helps you identify bottlenecks and inefficiencies within your workflow, allowing you to address them proactively. This leads to smoother operations and faster project completion. Additionally, data-driven insights contribute to better project outcomes by enabling you to allocate resources more effectively and ensure that projects are completed on time and within budget. ",[12,12048,12049,8398],{},[16,12050,7452],{},[70,12052,12053,12056,12059],{},[73,12054,12055],{},"Reduced time spent on repetitive tasks.",[73,12057,12058],{},"Faster identification of bottlenecks.",[73,12060,12061],{},"Improved resource allocation.",[501,12063],{},[613,12065,12067,8398],{"id":12066},"what-tools-and-technologies-are-used-for-data-driven-engineering",[16,12068,11983],{},[12,12070,12071,12072,12076],{},"To implement data-driven practices, you'll need the right tools and technologies. Data analytics platforms are essential for visualizing data and uncovering insights. Tools like Tableau and ",[514,12073,12075],{"href":12074},"\u002Fglossary\u002Fpower-bi-embedded","Power BI Embedded"," enable you to create interactive dashboards and reports, making it easier to interpret data and share findings with your team. ",[12,12078,12079],{},"Monitoring and logging tools are also crucial. Solutions like Grafana and Prometheus help you monitor system performance, track key metrics, and log data for analysis. These tools provide real-time insights into your systems, allowing you to detect issues early and take corrective actions promptly. ",[12,12081,12082],{},"Machine learning models play a significant role in data-driven engineering. Frameworks like TensorFlow and PyTorch enable predictive analytics and automation. By leveraging machine learning, you can develop models that predict future trends, identify anomalies, and optimize processes. ",[12,12084,12085,12086,12091,12092,12097],{},"For software engineering, one of the best tools available is ",[514,12087,12089],{"href":10160,"rel":12088},[518],[16,12090,469],{},". Oobeya is a leading software engineering intelligence platform (featured as a Representative Vendor in the ",[514,12093,12096],{"href":12094,"rel":12095},"https:\u002F\u002Fwww.gartner.com\u002Fen\u002Fdocuments\u002F4214399",[518],"Gartner Report",") offering comprehensive capabilities, including data visualization, advanced analytics, workflow optimization, and data-driven insights. It enables engineering teams to streamline their processes and improve efficiency by providing everything needed in one place. ",[12,12099,12100,8398],{},[16,12101,12102],{},"Essential Tools:",[70,12104,12105,12113,12119],{},[73,12106,12107,12110,12111,50],{},[16,12108,12109],{},"Data Visualization & Reporting:"," Tableau, ",[514,12112,12075],{"href":12074},[73,12114,12115,12118],{},[16,12116,12117],{},"Monitoring:"," Grafana, Prometheus. ",[73,12120,12121,12124],{},[16,12122,12123],{},"Software Engineering Intelligence Platform:"," Oobeya SEI Platform. ",[12,12126,12127,12134],{},[514,12128,12130],{"href":10288,"rel":12129},[518],[4866,12131],{"alt":12132,"src":12133},"Oobeya Symptoms","\u002Fassets\u002Fblog\u002FScreen-Shot-2024-05-10-at-17.28.44-1024x528.jpg"," Oobeya Symptoms & Data-driven Insights",[501,12136],{},[613,12138,12140,8398],{"id":12139},"how-do-you-implement-data-driven-practices-in-your-workflow",[16,12141,11986],{},[12,12143,12144],{},"Implementing data-driven practices involves several steps. The first step is data collection. Gather relevant data from various sources within your organization. This could include system logs, project management tools, and performance metrics. Ensure that the data you collect is accurate and comprehensive. ",[12,12146,12147],{},"Once you have collected the data, the next step is data analysis. Use analytical tools to interpret the data and uncover insights. This involves identifying patterns, trends, and correlations within the data. The goal is to gain a deeper understanding of your workflow and identify areas for improvement. ",[12,12149,12150],{},"After analyzing the data, translate the findings into actionable insights. This means developing specific strategies and actions based on the data. For example, if the data reveals a bottleneck in your workflow, you can develop a plan to address it and improve efficiency. Finally, focus on continuous improvement. Regularly review and refine your processes based on new data and insights. ",[12,12152,12153,8398],{},[16,12154,12155],{},"Implementation Steps:",[1520,12157,12158,12164,12170,12176],{},[73,12159,12160,12163],{},[16,12161,12162],{},"Start with a Clear Data Strategy:"," Define your goals and the data you need to achieve them. ",[73,12165,12166,12169],{},[16,12167,12168],{},"Invest in the Right Tools:"," Choose tools that fit your team's needs and capabilities. ",[73,12171,12172,12175],{},[16,12173,12174],{},"Train Your Team on Data Literacy:"," Ensure everyone understands how to use data effectively. ",[73,12177,12178,12181],{},[16,12179,12180],{},"Regularly Review and Adjust Processes:"," Keep improving based on the latest data. ",[501,12183],{},[613,12185,12187,8398],{"id":12186},"what-challenges-might-you-face-when-using-data-driven-insights",[16,12188,11989],{},[12,12190,12191],{},"While data-driven insights can transform your workflow, you may encounter some challenges. One common challenge is data quality issues. Inaccurate or incomplete data can lead to misguided decisions. To overcome this, implement robust data collection and validation processes to ensure data accuracy. ",[12,12193,12194],{},"Resistance to change is another challenge. Team members may be reluctant to adopt new data-driven processes. To address this, foster a culture of openness to change and highlight the benefits of data-driven practices. Emphasize how these practices can improve efficiency and lead to better project outcomes. ",[12,12196,12197],{},"A lack of skills can also pose a challenge. Your team might need training to effectively use data tools and techniques. Invest in training programs and consider hiring new team members with data expertise to bridge the skills gap. ",[12,12199,12200,8398],{},[16,12201,12202],{},"Overcoming Challenges:",[70,12204,12205,12208,12211],{},[73,12206,12207],{},"Ensure data accuracy and completeness.",[73,12209,12210],{},"Overcome resistance by fostering a culture of openness to change.",[73,12212,12213],{},"Bridge the skills gap with training and hiring.",[501,12215],{},[613,12217,12219,8398],{"id":12218},"what-are-the-best-practices-for-leveraging-data-driven-insights",[16,12220,11992],{},[12,12222,12223],{},"To fully benefit from data-driven insights, follow these best practices. First, foster a data-driven culture within your team. Encourage your team members to use data in their everyday work and make data-driven decisions. Provide training and resources to enhance their data literacy and skills. ",[12,12225,12226],{},"Regularly update your tools and processes. Stay current with the latest technologies and methodologies. Evaluate new tools and techniques that can improve your data-driven practices and enhance your workflow. By staying updated, you can ensure that your team has access to the best tools and strategies. ",[12,12228,12229],{},"Measure and track key performance metrics. Define and track key performance indicators (KPIs) to monitor progress and measure success. Use KPIs to identify areas for improvement and make data-driven adjustments to your processes. This continuous feedback loop will help you optimize your workflow and achieve better outcomes. ",[12,12231,12232,8398],{},[16,12233,12234],{},"Best Practices:",[70,12236,12237,12243,12249],{},[73,12238,12239,12242],{},[16,12240,12241],{},"Encourage Data Literacy Across the Team:"," Provide training and resources to enhance data skills. ",[73,12244,12245,12248],{},[16,12246,12247],{},"Stay Updated with the Latest Technologies:"," Regularly evaluate and adopt new tools and techniques. ",[73,12250,12251,12254],{},[16,12252,12253],{},"Use KPIs to Measure Success:"," Define and track key metrics to ensure continuous improvement. ",[501,12256],{},[613,12258,12259,8398],{"id":477},[16,12260,1159],{},[12,12262,12263],{},"Optimizing your engineering workflow with data-driven insights is crucial for achieving better efficiency, performance, and project outcomes. By understanding the importance of data, implementing the right tools, and following best practices, you can transform your engineering processes and drive significant results. Oobeya offers powerful capabilities to help you on this journey, providing comprehensive solutions for data-driven engineering optimization.",{"title":526,"searchDepth":527,"depth":527,"links":12265},[12266,12267,12268,12270,12272,12274,12276,12278,12280],{"id":615,"depth":527,"text":616},{"id":8114,"depth":527,"text":8449},{"id":12008,"depth":527,"text":12269},"What Are Data-Driven Insights in Engineering? ",{"id":12038,"depth":527,"text":12271},"How Can Data-Driven Insights Improve Engineering Workflow? ",{"id":12066,"depth":527,"text":12273},"What Tools and Technologies Are Used for Data-Driven Engineering? ",{"id":12139,"depth":527,"text":12275},"How Do You Implement Data-Driven Practices in Your Workflow? ",{"id":12186,"depth":527,"text":12277},"What Challenges Might You Face When Using Data-Driven Insights? ",{"id":12218,"depth":527,"text":12279},"What Are the Best Practices for Leveraging Data-Driven Insights? ",{"id":477,"depth":527,"text":478},[541],"2024-07-17","Learn how data-driven engineering insights improve workflow visibility, team efficiency, delivery planning, and software development decision-making.",{},"\u002Fblog\u002Fdata-driven-insights-optimize-engineering-workflow",{"title":11960,"description":12283},"blog\u002Fdata-driven-insights-optimize-engineering-workflow","2SuQ1PxAV969pNTdi9YNJqehYOSQGjbKtwk72WaIcWo",{"id":12290,"title":11477,"author":4245,"avatar":575,"body":12291,"categories":12561,"createAt":542,"date":12562,"description":12563,"extension":545,"meta":12564,"navigation":547,"path":11005,"position":4134,"seo":12565,"spotImage":542,"spotText":542,"stem":12566,"tags":12567,"__hash__":12568},"blog\u002Fblog\u002Fimprove-change-failure-rate.md",{"type":9,"value":12292,"toc":12544},[12293,12304,12310,12316,12319,12326,12333,12339,12342,12362,12368,12371,12397,12403,12406,12426,12432,12435,12461,12467,12476,12496,12503,12507,12510,12515],[12,12294,12295,12296,8398],{},"Change failure rate is a critical metric for engineering leaders, especially in software development and DevOps. Monitoring and reducing change failure rate can significantly impact your team's efficiency and the overall success of your projects. In this article, we’ll explore what change failure rate is from the DORA Metrics perspective, its impact on organizations, common causes, detection methods, strategies to reduce it, and ",[16,12297,12298,12299,12303],{},"how ",[514,12300,12302],{"href":7188,"rel":12301},[518],"Oobeya's unique approach"," can help.",[613,12305,12307,8398],{"id":12306},"what-is-change-failure-rate",[16,12308,12309],{},"What is Change Failure Rate?",[12,12311,12312,12315],{},[16,12313,12314],{},"Change failure rate (CFR)"," measures the percentage of changes or deployments that result in failures in production. This includes bugs, errors, or any issues that require a rollback or a hotfix. Understanding and tracking change failure rate is crucial for maintaining high-quality software delivery and improving your team's performance. ",[12,12317,12318],{},"At its core, change failure rate reflects the reliability and stability of your development and deployment processes. A high change failure rate indicates frequent issues that disrupt operations, while a low change failure rate suggests a well-designed process with fewer interruptions.",[12,12320,12321,12322,12325],{},"Moreover, change failure rate is one of the four key metrics defined by the ",[514,12323,11246],{"href":11244,"rel":12324},[518],", providing a comprehensive framework for measuring the performance of software delivery teams. By focusing on change failure rate, organizations can gain insights into the effectiveness of their DevOps practices. ",[12,12327,12328,12332],{},[4866,12329],{"alt":12330,"src":12331,"title":12330},"DORA Metrics - Change Failure Rate","\u002Fassets\u002Fblog\u002Fdora-cfr-1024x704.png"," DORA Metrics - Change Failure Rate",[613,12334,12336,8398],{"id":12335},"the-impact-of-change-failure-rate-on-organizations",[16,12337,12338],{},"The Impact of Change Failure Rate on Organizations",[12,12340,12341],{},"High change failure rates can have several negative effects on a software organization, including: ",[70,12343,12344,12350,12356],{},[73,12345,12346,12349],{},[16,12347,12348],{},"Increased Downtime",": When changes fail, systems can become unstable or completely inoperative, leading to downtime that affects both internal operations and customer-facing services. This downtime can result in significant financial losses and damage to the organization's reputation.",[73,12351,12352,12355],{},[16,12353,12354],{},"Higher Costs",": Fixing failed changes consumes resources and time, diverting your team from working on new features or improvements. The costs associated with addressing these failures include not only the time spent by developers but also potential lost revenue from service interruptions.",[73,12357,12358,12361],{},[16,12359,12360],{},"Lower Team Morale",": Persistent failures can demotivate your team, leading to lower productivity and higher turnover rates. A high CFR often signals underlying issues in the development process that need to be addressed to maintain a positive and productive work environment. ",[613,12363,12365,8398],{"id":12364},"common-causes-of-high-change-failure-rates",[16,12366,12367],{},"Common Causes of High Change Failure Rates",[12,12369,12370],{},"Several factors can contribute to a high change failure rate: ",[70,12372,12373,12379,12385,12391],{},[73,12374,12375,12378],{},[16,12376,12377],{},"Inadequate Testing",": Without comprehensive testing, bugs, and errors can easily slip into production. Automated testing, though highly effective, is not always utilized to its full potential, leaving gaps that manual testing cannot always cover. Comprehensive test coverage is essential to ensure that all possible scenarios are considered before changes are deployed.",[73,12380,12381,12384],{},[16,12382,12383],{},"Complex Deployments",": When deployment processes are overly complicated, the risk of errors increases. Simplifying these processes can help reduce the likelihood of failures. This often involves streamlining deployment pipelines and automating repetitive tasks to minimize human error.",[73,12386,12387,12390],{},[16,12388,12389],{},"Poor Communication",": Miscommunication about changes, requirements, or deployment procedures can result in avoidable errors. Establishing clear communication channels and protocols is essential to reducing these risks.",[73,12392,12393,12396],{},[16,12394,12395],{},"Lack of Automation",": Manual processes are inherently more error-prone compared to automated ones. Automation not only reduces the risk of human error but also ensures consistency and reliability in deployments. ",[613,12398,12400,8398],{"id":12399},"methods-to-detect-change-failures",[16,12401,12402],{},"Methods to Detect Change Failures",[12,12404,12405],{},"Detecting production failures or incidents promptly is essential for minimizing their impact. Effective detection methods include: ",[70,12407,12408,12414,12420],{},[73,12409,12410,12413],{},[16,12411,12412],{},"Automated Testing",": Implementing continuous integration and automated testing to catch issues early. Automated testing ensures that each change is thoroughly vetted before it reaches production, helping in identifying potential failures and addressing them promptly.",[73,12415,12416,12419],{},[16,12417,12418],{},"Monitoring and Alerts",": Using monitoring tools (e.g., New Relic, Datadog) to track performance and set up alerts for anomalies. Real-time monitoring allows for quick detection and resolution of problems, minimizing downtime and its associated impacts.",[73,12421,12422,12425],{},[16,12423,12424],{},"User Feedback",": Collecting and analyzing user feedback to highlight issues that escaped initial detection. User feedback can highlight problems that were not identified during testing or code reviews, helping to refine and improve the development process. ",[613,12427,12429,8398],{"id":12428},"how-to-reduce-change-failure-rates",[16,12430,12431],{},"How to Reduce Change Failure Rates",[12,12433,12434],{},"Improving your change failure rate involves several strategies: ",[70,12436,12437,12443,12449,12455],{},[73,12438,12439,12442],{},[16,12440,12441],{},"Enhance Testing Protocols",": Strengthen your testing processes with comprehensive test coverage and automated tests. Automated testing ensures that each change is thoroughly vetted before it reaches production, reducing the number of failures.",[73,12444,12445,12448],{},[16,12446,12447],{},"Simplify Deployments",": Streamline your deployment procedures to reduce complexity and errors. Simplifying these processes helps in minimizing the risk of failures and often involves automating deployment processes and reducing the number of steps required for a deployment.",[73,12450,12451,12454],{},[16,12452,12453],{},"Foster Communication",": Encourage open communication and collaboration among team members. Clear documentation and regular meetings can significantly improve team coordination and reduce the risk of failures.",[73,12456,12457,12460],{},[16,12458,12459],{},"Implement Continuous Delivery",": Adopt continuous delivery practices to ensure small, incremental changes that are easier to manage. Continuous delivery involves making frequent, small changes that are less likely to cause major disruptions, reducing the overall risk of failures. ",[613,12462,12464,8398],{"id":12463},"change-failure-rate-detection-with-oobeya",[16,12465,12466],{},"Change Failure Rate Detection with Oobeya",[12,12468,12469,12470,12475],{},"Oobeya offers a unique solution for tracking and improving change failure rates. By leveraging DORA metrics and ",[514,12471,12474],{"href":12472,"rel":12473},"https:\u002F\u002Foobeya.io\u002Fintegrations\u002F",[518],"advanced monitoring tools",", Oobeya provides accurate detection and actionable insights to help you reduce your change failure rate. Our approach includes: ",[70,12477,12478,12484,12490],{},[73,12479,12480,12483],{},[16,12481,12482],{},"Manual and Automatic Detection:"," Oobeya combines manual checks and automated processes, including Oobeya’s own API for setting deployment health statuses and detecting hotfix deployments by analyzing branch naming patterns.  ",[73,12485,12486,12489],{},[16,12487,12488],{},"Tracking Incident Management Tools:"," Oobeya integrates with Application Performance Management (APM) and Incident Management tools to actively monitor production incidents and calculate CFR. ",[73,12491,12492,12495],{},[16,12493,12494],{},"Comprehensive Reports",": Detailed analytics to identify trends and areas for improvement, helping to address the root causes of failures effectively.",[12,12497,12498,12499,50],{},"For a more in-depth look at how Oobeya can help you manage change failure rates, check out our ",[514,12500,12502],{"href":9201,"rel":12501},[518],"guide on DORA metrics and production failure detection",[613,12504,12505,8398],{"id":477},[16,12506,1159],{},[12,12508,12509],{},"Monitoring and reducing change failure rates are crucial for maintaining high standards in software development and DevOps. By understanding its impact, identifying causes, and implementing effective detection and reduction strategies, you can enhance your team's performance and the quality of your deployments. Oobeya's unique approach to change failure rate detection offers an invaluable tool for engineering leaders committed to continuous improvement.  ",[52,12511,12513],{"id":12512},"read-more",[791,12514,10742],{},[70,12516,12517,12523,12528,12534,12539],{},[73,12518,12519,8398],{},[514,12520,12522],{"href":9201,"rel":12521},[518],"Understanding DORA Metrics",[73,12524,12525,8398],{},[514,12526,11465],{"href":11463,"rel":12527},[518],[73,12529,12530],{},[514,12531,12533],{"href":10600,"rel":12532},[518],"Key DevOps Metrics",[73,12535,12536],{},[514,12537,11491],{"href":11489,"rel":12538},[518],[73,12540,12541],{},[514,12542,11471],{"href":10444,"rel":12543},[518],{"title":526,"searchDepth":527,"depth":527,"links":12545},[12546,12548,12550,12552,12554,12556,12558],{"id":12306,"depth":527,"text":12547},"What is Change Failure Rate? ",{"id":12335,"depth":527,"text":12549},"The Impact of Change Failure Rate on Organizations ",{"id":12364,"depth":527,"text":12551},"Common Causes of High Change Failure Rates ",{"id":12399,"depth":527,"text":12553},"Methods to Detect Change Failures ",{"id":12428,"depth":527,"text":12555},"How to Reduce Change Failure Rates ",{"id":12463,"depth":527,"text":12557},"Change Failure Rate Detection with Oobeya ",{"id":477,"depth":527,"text":478,"children":12559},[12560],{"id":12512,"depth":530,"text":10742},[1232,540],"2024-07-09","Change failure rate is a critical metric for engineering leaders, especially in software development and DevOps. Monitoring and reducing change failure...",{},{"title":11477,"description":12563},"blog\u002Fimprove-change-failure-rate",[8440,696,1231],"WfzGF0-jteugtRN0veLfRlZ2Ja1knto3nb0H-pWJMuM",{"id":12570,"title":12571,"author":4245,"avatar":575,"body":12572,"categories":12983,"createAt":542,"date":12985,"description":12986,"extension":545,"meta":12987,"navigation":547,"path":12988,"position":542,"seo":12989,"spotImage":542,"spotText":542,"stem":12990,"tags":542,"__hash__":12991},"blog\u002Fblog\u002Fwhy-developer-experience-matters.md","Why Code Reviews Should Be Your Favorite Activity - Blog",{"type":9,"value":12573,"toc":12961},[12574,12576,12598,12600,12602,12605,12608,12611,12614,12640,12643,12646,12649,12669,12674,12677,12680,12684,12704,12708,12728,12732,12752,12756,12776,12780,12800,12803,12806,12810,12830,12834,12854,12858,12878,12881,12884,12886,12888,12897,12902,12907,12912,12917,12922,12930,12938,12940,12942,12951,12954],[613,12575,616],{"id":615},[1520,12577,12578,12580,12583,12586,12589,12592,12595],{},[73,12579,8115],{},[73,12581,12582],{},"What is Developer Experience?",[73,12584,12585],{},"The Impact of Good Developer Experience",[73,12587,12588],{},"Strategies to Improve Developer Experience",[73,12590,12591],{},"Measuring Developer Experience",[73,12593,12594],{},"How Can Oobeya Help You To Improve Developer Experience?",[73,12596,12597],{},"Oobeya's Team Symptoms Related to Developer Experience",[501,12599],{},[613,12601,8115],{"id":8114},[12,12603,12604],{},"The term 'developer experience' (DX or DevEx) has gained significant traction in the software development industry. For software development team leaders, engineering leaders, and VPs of Software Engineering, understanding and prioritizing DX is crucial to building high-performing, satisfied, and efficient teams. A positive developer experience boosts developer productivity and enhances job satisfaction, leading to better retention rates and faster onboarding of new team members.",[613,12606,12582],{"id":12607},"what-is-developer-experience",[12,12609,12610],{},"Developer experience, or DX, refers to the overall experience that developers have while working within an organization. It encompasses everything from the tools and technologies they use to the work environment and the support they receive. A positive DX ensures that developers can work efficiently, feel valued, and continue to grow professionally.",[12,12612,12613],{},"Key elements that contribute to a positive DX include:",[1520,12615,12616,12622,12628,12634],{},[73,12617,12618,12621],{},[16,12619,12620],{},"Effective Tools and Technologies",": Access to modern, efficient tools that streamline development processes, including integrated development environments (IDEs), version control systems, coding copilots like GitHub Copilot, CI\u002FCD, and project management tools.",[73,12623,12624,12627],{},[16,12625,12626],{},"Collaborative Environment",": A culture that promotes teamwork and open communication, encouraging collaboration through regular team meetings, code reviews, and knowledge-sharing sessions.",[73,12629,12630,12633],{},[16,12631,12632],{},"Learning and Development",": Opportunities for continuous learning and career advancement, such as courses, certifications, and conference attendance.",[73,12635,12636,12639],{},[16,12637,12638],{},"Supportive Infrastructure",": Reliable systems and resources that minimize disruptions and downtime, including robust hardware, fast internet connections, and efficient technical support.",[12,12641,12642],{},"By focusing on these elements, organizations can create an environment where developers thrive, leading to better software products and services.",[613,12644,12585],{"id":12645},"the-impact-of-good-developer-experience",[12,12647,12648],{},"A good developer experience can significantly impact an organization in several ways:",[1520,12650,12651,12657,12663],{},[73,12652,12653,12656],{},[16,12654,12655],{},"Enhanced Productivity and Efficiency",": When developers have access to the right tools and a supportive environment, they can work more efficiently. This leads to faster software delivery and higher-quality code.",[73,12658,12659,12662],{},[16,12660,12661],{},"Improved Job Satisfaction and Retention Rates",": Developers who feel valued and supported are more likely to stay with an organization, reducing turnover rates and retaining valuable knowledge and skills within the company.",[73,12664,12665,12668],{},[16,12666,12667],{},"Faster Onboarding for New Team Members",": A positive DevEx helps new developers get up to speed quickly with clear documentation, streamlined onboarding processes, and a welcoming team culture.",[3354,12670,12671],{},[12,12672,12673],{},"A study by Stripe revealed that developers spend almost half of their time maintaining legacy systems and bad code. By improving developer experience (DX), organizations can reduce this unproductive time, allowing developers to focus more on innovation and less on maintenance.",[613,12675,12588],{"id":12676},"strategies-to-improve-developer-experience",[12,12678,12679],{},"Improving developer experience requires a multifaceted approach. Here are some strategies to consider:",[52,12681,12683],{"id":12682},"_1-provide-the-right-tools-and-technologies","1. Provide the Right Tools and Technologies",[70,12685,12686,12692,12698],{},[73,12687,12688,12691],{},[16,12689,12690],{},"Invest in Modern Development Tools",": Tools like JetBrains IntelliJ IDEA for Java development, GitHub for version control, Microsoft Copilot and GitHub Copilot to empower developers, and Docker for containerization can significantly streamline workflows. Regularly assess and update these tools to keep pace with industry standards.",[73,12693,12694,12697],{},[16,12695,12696],{},"Ensure Tools are Well-Integrated",": Tools should work seamlessly together. For example, integrating your IDE with your version control system can reduce context switching and save time.",[73,12699,12700,12703],{},[16,12701,12702],{},"Maintain Tools to Prevent Disruptions",": Regular maintenance and updates are crucial to prevent bugs and compatibility issues. Ensure that your development environment is stable and reliable.",[52,12705,12707],{"id":12706},"_2-foster-a-collaborative-environment","2. Foster a Collaborative Environment",[70,12709,12710,12716,12722],{},[73,12711,12712,12715],{},[16,12713,12714],{},"Encourage Open Communication",": Use collaboration platforms like Slack, Discord, or Microsoft Teams to facilitate communication. Encourage developers to share their thoughts, ideas, and challenges.",[73,12717,12718,12721],{},[16,12719,12720],{},"Implement Agile Methodologies",": Agile practices such as daily stand-ups, sprint planning, and retrospectives can enhance teamwork and ensure that everyone is aligned with project goals.",[73,12723,12724,12727],{},[16,12725,12726],{},"Create Opportunities for Cross-Functional Collaboration",": Encourage developers to work with other roles and teams, such as product management, design, and QA, to gain different perspectives and build better products.",[52,12729,12731],{"id":12730},"_3-continuous-learning-and-development-opportunities","3. Continuous Learning and Development Opportunities",[70,12733,12734,12740,12746],{},[73,12735,12736,12739],{},[16,12737,12738],{},"Offer Regular Training Sessions and Workshops",": Bring in experts to provide training on new technologies and best practices. Organize internal workshops where team members can share their knowledge.",[73,12741,12742,12745],{},[16,12743,12744],{},"Provide Access to Online Courses and Certifications",": Platforms like Coursera, Udemy, and Pluralsight offer a wide range of courses. Support developers in pursuing certifications relevant to their roles.",[73,12747,12748,12751],{},[16,12749,12750],{},"Encourage Participation in Conferences and Industry Events",": Encourage developers to attend conferences and events to inspire new ideas and foster professional growth.",[52,12753,12755],{"id":12754},"_4-recognize-and-reward-contributions","4. Recognize and Reward Contributions",[70,12757,12758,12764,12770],{},[73,12759,12760,12763],{},[16,12761,12762],{},"Implement a Recognition Program",": Celebrate achievements publicly through team meetings, company-wide emails, or internal social networks.",[73,12765,12766,12769],{},[16,12767,12768],{},"Offer Incentives for Innovative Solutions",": Reward developers who come up with innovative solutions or improvements with bonuses, promotions, or other incentives.",[73,12771,12772,12775],{},[16,12773,12774],{},"Provide Regular Feedback and Support Career Progression",": Conduct regular one-on-one meetings to discuss performance, provide constructive feedback, and plan career development paths.",[52,12777,12779],{"id":12778},"_5-prioritize-mental-and-physical-well-being","5. Prioritize Mental and Physical Well-being",[70,12781,12782,12788,12794],{},[73,12783,12784,12787],{},[16,12785,12786],{},"Promote Work-Life Balance",": Encourage a healthy work-life balance by setting realistic deadlines, promoting flexible working hours, and discouraging overtime.",[73,12789,12790,12793],{},[16,12791,12792],{},"Offer Health and Wellness Programs",": Provide access to health and wellness programs, such as gym memberships, mental health support, and wellness workshops.",[73,12795,12796,12799],{},[16,12797,12798],{},"Create a Comfortable Work Environment",": Ensure the physical workspace is comfortable and conducive to productivity, with ergonomic furniture, adequate lighting, and a pleasant office ambiance.",[613,12801,12591],{"id":12802},"measuring-developer-experience",[12,12804,12805],{},"To ensure continuous improvement in developer experience, it's essential to measure and track key metrics. Here are some methods to consider:",[52,12807,12809],{"id":12808},"_1-key-metrics-to-track","1. Key Metrics to Track",[70,12811,12812,12818,12824],{},[73,12813,12814,12817],{},[16,12815,12816],{},"Developer Satisfaction Scores",": Regular surveys to gauge overall satisfaction with the work environment, tools, and processes.",[73,12819,12820,12823],{},[16,12821,12822],{},"Flow Metrics",": Identify bottlenecks, and problematic areas to reduce friction in the value delivery flow.",[73,12825,12826,12829],{},[16,12827,12828],{},"Onboarding Time",": Track the time taken for new developers to become fully productive.",[52,12831,12833],{"id":12832},"_2-methods-to-gather-feedback","2. Methods to Gather Feedback",[70,12835,12836,12842,12848],{},[73,12837,12838,12841],{},[16,12839,12840],{},"Conduct Regular One-on-One Meetings and Team Retrospectives",": These meetings provide a platform for developers to share their thoughts and feedback.",[73,12843,12844,12847],{},[16,12845,12846],{},"Use Anonymous Surveys to Collect Honest Feedback",": Anonymous feedback can sometimes be more candid and provide insights that might not come out in face-to-face meetings.",[73,12849,12850,12853],{},[16,12851,12852],{},"Create a Feedback Loop Where Developers Can Suggest Improvements",": Encourage developers to suggest improvements to tools, processes, and the work environment. Implement a system where suggestions are reviewed and acted upon.",[52,12855,12857],{"id":12856},"_3-importance-of-regular-assessment-and-iteration","3. Importance of Regular Assessment and Iteration",[70,12859,12860,12866,12872],{},[73,12861,12862,12865],{},[16,12863,12864],{},"Continuously Monitor and Assess Developer Experience Metrics",": Regular monitoring helps identify trends and areas that need improvement.",[73,12867,12868,12871],{},[16,12869,12870],{},"Iterate on Feedback and Implement Changes to Improve Developer Experience",": Act on the feedback received and continuously seek new feedback to ensure ongoing improvement.",[73,12873,12874,12877],{},[16,12875,12876],{},"Regularly Update Tools, Processes, and Training Programs to Keep Up with Industry Trends",": The tech industry evolves rapidly. Regular updates ensure that your development environment remains competitive and efficient.",[613,12879,12594],{"id":12880},"how-can-oobeya-help-you-to-improve-developer-experience",[12,12882,12883],{},"Oobeya stands out with its innovative approach to automatically detecting and addressing development and delivery symptoms. By leveraging key engineering metrics (like DORA metrics, Agile metrics, cycle time, and quality metrics) and hundreds of data points, this unique capability enables software organizations to effortlessly identify recurring anti-patterns, bottlenecks, and roadblocks.",[12,12885,11844],{},[52,12887,12597],{"id":11847},[12,12889,12890,12896],{},[514,12891,12893],{"href":10160,"rel":12892},[518],[4866,12894],{"alt":12895,"src":12133,"title":12895},"Oobeya Symptoms - Developer Experience"," Oobeya Symptoms - Developer Experience",[12,12898,12899,12901],{},[16,12900,11859],{},": This symptom indicates that developers are frequently overwhelmed by complex tasks, leading to stress and reduced productivity. High cognitive load can stem from poor documentation, complex codebases, or inadequate tooling.",[12,12903,12904,12906],{},[16,12905,11865],{},": This suggests that developers are working excessively during weekends, which can lead to burnout and decreased job satisfaction. It often results from unrealistic deadlines or poor project management.",[12,12908,12909,12911],{},[16,12910,11871],{},": Extended periods for code reviews can frustrate developers, delaying progress and reducing efficiency. It may be due to a lack of reviewer availability or inefficient review processes.",[12,12913,12914,12916],{},[16,12915,11877],{},": This occurs when pull requests are left without review for too long, causing bottlenecks and frustration among developers eager to integrate their changes.",[12,12918,12919,12921],{},[16,12920,11883],{},": Extremely fast pull request reviews may indicate superficial reviews, potentially compromising code quality and leading to technical debt.",[12,12923,12924,12926,12927,611],{},[16,12925,11889],{},": Large pull requests can be difficult and time-consuming to review, often leading to prolonged feedback cycles and increased cognitive load on developers. View Oobeya's Symptoms Catalog ",[514,12928,4354],{"href":10288,"rel":12929},[518],[12,12931,12932,12933,12937],{},"For more details, you can read our blog post on the ",[514,12934,12132],{"href":12935,"rel":12936},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fharness-advanced-insights-with-oobeyas-symptoms-module-now-ga\u002F",[518]," module.",[501,12939],{},[613,12941,4893],{"id":4892},[12,12943,12944,12945,12950],{},"The Oobeya platform, featured in the ",[514,12946,12949],{"href":12947,"rel":12948},"https:\u002F\u002Fwww.gartner.com\u002Fen\u002Fdocuments\u002F5276563",[518],"Gartner Market Guide"," for Software Engineering Intelligence Platforms, provides comprehensive insights into software development processes. It serves as a single source of truth for engineering data, offering a unified, comprehensive, and transparent view of engineering processes. By using Oobeya, teams can better understand how software solutions are built and delivered, see where they are spending time, and improve team flow through key metrics like DORA metrics and cycle time.",[12,12952,12953],{},"By leveraging these engineering insights, you can optimize software development processes, boost developer experience, improve team well-being, and deliver higher-quality software faster.",[12,12955,12956,12960],{},[514,12957,12959],{"href":10160,"rel":12958},[518],"Start your integration today"," and unlock the full potential of your software organization.",{"title":526,"searchDepth":527,"depth":527,"links":12962},[12963,12964,12965,12966,12967,12974,12979,12982],{"id":615,"depth":527,"text":616},{"id":8114,"depth":527,"text":8115},{"id":12607,"depth":527,"text":12582},{"id":12645,"depth":527,"text":12585},{"id":12676,"depth":527,"text":12588,"children":12968},[12969,12970,12971,12972,12973],{"id":12682,"depth":530,"text":12683},{"id":12706,"depth":530,"text":12707},{"id":12730,"depth":530,"text":12731},{"id":12754,"depth":530,"text":12755},{"id":12778,"depth":530,"text":12779},{"id":12802,"depth":527,"text":12591,"children":12975},[12976,12977,12978],{"id":12808,"depth":530,"text":12809},{"id":12832,"depth":530,"text":12833},{"id":12856,"depth":530,"text":12857},{"id":12880,"depth":527,"text":12594,"children":12980},[12981],{"id":11847,"depth":530,"text":12597},{"id":4892,"depth":527,"text":4893},[2620,12984],"dx","2024-07-05","Tips for being a better code reviewer, creating better pull requests, and accelerating the delivery cycle with pull request analytics.",{},"\u002Fblog\u002Fwhy-developer-experience-matters",{"title":12571,"description":12986},"blog\u002Fwhy-developer-experience-matters","hN63v1ScqnIYevRq6WhMq6Kh6dannEhgcSOn2maeJi4",{"id":12993,"title":12994,"author":4245,"avatar":575,"body":12995,"categories":13224,"createAt":542,"date":13225,"description":13226,"extension":545,"meta":13227,"navigation":547,"path":13228,"position":542,"seo":13229,"spotImage":542,"spotText":542,"stem":13230,"tags":542,"__hash__":13231},"blog\u002Fblog\u002Fdatadog-dash-2024-key-conference-highlights-new-features-and-event-recap.md","Datadog DASH 2024: Key Conference Highlights, New Features, and Event Recap",{"type":9,"value":12996,"toc":13213},[12997,13001,13004,13010,13014,13020,13026,13032,13039,13045,13050,13056,13059,13065,13071,13075,13081,13084,13090,13096,13102,13107,13113,13116,13122,13125,13129,13135,13141,13147,13150,13156,13162,13168,13171,13177,13184,13190,13198,13202,13205],[613,12998,12999],{"id":8114},[16,13000,8115],{},[12,13002,13003],{},"Imagine a world where your software engineering team can detect and resolve issues before they impact your users. At the Datadog DASH 2024 conference, Datadog unveiled groundbreaking features that make this a reality. In this article, you'll discover how these innovations can transform your observability, security, and operational efficiency.",[613,13005,13007],{"id":13006},"key-takeaways-from-datadog-dash-2024",[16,13008,13009],{},"Key Takeaways from Datadog DASH 2024",[52,13011,13013],{"id":13012},"new-features-and-enhancements","New Features and Enhancements",[4331,13015,13017],{"id":13016},"llm-observability",[16,13018,13019],{},"LLM Observability",[12,13021,13022,13023,13025],{},"Datadog introduced ",[16,13024,13019],{},", a feature providing deep visibility into generative AI applications. This tool allows you to trace errors, evaluate performance, and ensure security for your AI models, making it easier to optimize and secure your AI-driven projects.",[4331,13027,13029],{"id":13028},"datadog-opentelemetry-integration",[16,13030,13031],{},"Datadog OpenTelemetry Integration",[12,13033,13034,13035,13038],{},"The integration of an embedded ",[16,13036,13037],{},"OTel Collector"," in the Datadog Agent enhances observability. This seamless integration simplifies data collection and analysis, offering a unified view of your system’s performance.",[4331,13040,13042],{"id":13041},"log-workspaces",[16,13043,13044],{},"Log Workspaces",[12,13046,346,13047,13049],{},[16,13048,13044],{},", teams can parse, enrich, and analyze log data using SQL, natural language, and Datadog’s visualizations. This feature simplifies log management and makes data analysis more intuitive and accessible.",[4331,13051,13053],{"id":13052},"live-debugging",[16,13054,13055],{},"Live Debugging",[12,13057,13058],{},"Live Debugging enables developers to debug production issues directly from their Integrated Development Environment (IDE). This streamlines the debugging process, reduces downtime, and increases development efficiency.",[4331,13060,13062],{"id":13061},"product-analytics",[16,13063,13064],{},"Product Analytics",[12,13066,13067,13068,13070],{},"The new ",[16,13069,13064],{}," tool helps teams make data-driven UX decisions. By visualizing user engagement and interaction data, you can optimize user experiences and improve product performance.",[52,13072,13074],{"id":13073},"security-enhancements","Security Enhancements",[4331,13076,13078],{"id":13077},"agentless-scanning",[16,13079,13080],{},"Agentless Scanning",[12,13082,13083],{},"Agentless Scanning allows teams to detect and remediate vulnerabilities across cloud infrastructure without deploying agents. This enhances security posture and reduces the complexity of vulnerability management.",[4331,13085,13087],{"id":13086},"data-security",[16,13088,13089],{},"Data Security",[12,13091,13092,13093,13095],{},"Datadog now offers tools to identify and protect sensitive data in cloud storage, ensuring compliance and enhancing security. ",[16,13094,13089],{}," features help safeguard your data against unauthorized access and breaches.",[4331,13097,13099],{"id":13098},"infrastructure-as-code-remediation",[16,13100,13101],{},"Infrastructure-as-Code Remediation",[12,13103,346,13104,13106],{},[16,13105,13101],{},", teams can fix misconfigured cloud resources directly from Datadog’s platform. This reduces drift and improves security posture by ensuring consistent and secure configurations.",[4331,13108,13110],{"id":13109},"code-security",[16,13111,13112],{},"Code Security",[12,13114,13115],{},"Code Security detects code-level vulnerabilities in production environments, providing actionable insights and recommended fixes. This feature helps maintain secure and robust codebases.",[4331,13117,13119],{"id":13118},"software-composition-analysis-sca",[16,13120,13121],{},"Software Composition Analysis (SCA)",[12,13123,13124],{},"Software Composition Analysis (SCA) automates the detection of vulnerabilities and risks in open-source software components, improving overall software supply chain security.",[52,13126,13128],{"id":13127},"operational-improvements","Operational Improvements",[4331,13130,13132],{"id":13131},"kubernetes-autoscaling",[16,13133,13134],{},"Kubernetes Autoscaling",[12,13136,13137,13138,13140],{},"Datadog’s new ",[16,13139,13134],{}," feature optimizes workloads, balancing cost efficiency and performance. This helps you manage resources effectively and ensure reliable application performance.",[4331,13142,13144],{"id":13143},"change-tracking",[16,13145,13146],{},"Change Tracking",[12,13148,13149],{},"Change Tracking streamlines incident response by surfacing relevant changes and potential remediation steps from within the monitor status page. This feature improves incident management and reduces resolution times.",[4331,13151,13153],{"id":13152},"bits-ai",[16,13154,13155],{},"Bits AI",[12,13157,13158,13159,13161],{},"The latest evolution of ",[16,13160,13155],{}," can now autonomously perform complex operational tasks, such as investigating alerts and coordinating incidents. This AI-powered feature enhances operational efficiency and reduces the burden on your team.",[4331,13163,13165],{"id":13164},"on-call-enhancements",[16,13166,13167],{},"On-Call Enhancements",[12,13169,13170],{},"On-call enhancements improve the on-call experience by integrating observability data, making it easier for engineers to monitor and resolve issues. This reduces the stress of on-call duties and improves incident response times.",[613,13172,13174],{"id":13173},"why-datadog-matters",[16,13175,13176],{},"Why Datadog Matters",[12,13178,13179,13180,13183],{},"Datadog continues to lead the industry in observability and security solutions. According to a recent survey, ",[16,13181,13182],{},"78% of organizations"," reported improved incident management and reduced downtime after adopting Datadog’s tools. By integrating these new features, Datadog helps engineering leaders like you ensure your applications and infrastructure are secure, reliable, and high-performing.",[613,13185,13187],{"id":13186},"additional-resources",[16,13188,13189],{},"Additional Resources",[12,13191,13192,13193,611],{},"For more detailed information on the announcements, visit the ",[514,13194,13197],{"href":13195,"rel":13196},"https:\u002F\u002Fwww.datadoghq.com\u002Fblog\u002Fdash-2024-new-feature-roundup-keynote\u002F",[518],"DASH 2024 Keynote Roundup",[613,13199,13200],{"id":477},[16,13201,1159],{},[12,13203,13204],{},"Datadog’s DASH 2024 conference brought many new features and enhancements designed to provide better observability, security, and operational efficiency. These innovations are set to empower teams to monitor, troubleshoot, and secure their applications and infrastructure more effectively.",[12,13206,13207],{},[791,13208,13209,13210,611],{},"For more insights and the latest updates on engineering tools, visit ",[514,13211,469],{"href":516,"rel":13212},[518],{"title":526,"searchDepth":527,"depth":527,"links":13214},[13215,13216,13221,13222,13223],{"id":8114,"depth":527,"text":8115},{"id":13006,"depth":527,"text":13009,"children":13217},[13218,13219,13220],{"id":13012,"depth":530,"text":13013},{"id":13073,"depth":530,"text":13074},{"id":13127,"depth":530,"text":13128},{"id":13173,"depth":527,"text":13176},{"id":13186,"depth":527,"text":13189},{"id":477,"depth":527,"text":1159},[541],"2024-07-01","Imagine a world where your software engineering team can detect and resolve issues before they impact your users. At the Datadog DASH 2024 conference,...",{},"\u002Fblog\u002Fdatadog-dash-2024-key-conference-highlights-new-features-and-event-recap",{"title":12994,"description":13226},"blog\u002Fdatadog-dash-2024-key-conference-highlights-new-features-and-event-recap","RR9vd8s1zJnW_mUGRx86SQXDDy7eQqbny2mUi8ZhrP8",{"id":13233,"title":11465,"author":4245,"avatar":575,"body":13234,"categories":13521,"createAt":542,"date":13523,"description":13524,"extension":545,"meta":13525,"navigation":547,"path":13526,"position":4134,"seo":13527,"spotImage":542,"spotText":542,"stem":13528,"tags":13529,"__hash__":13531},"blog\u002Fblog\u002Fdora-metrics-delivery-performance.md",{"type":9,"value":13235,"toc":13508},[13236,13239,13245,13253,13259,13262,13268,13271,13274,13279,13286,13289,13292,13297,13306,13312,13315,13318,13327,13332,13342,13350,13353,13356,13358,13364,13367,13370,13376,13382,13385,13411,13417,13420,13439,13445,13459,13464,13488,13490,13493,13499],[12,13237,13238],{},"Imagine deploying new features rapidly while maintaining high reliability. This isn't just a dream for software development teams—it's achievable with the right metrics. DORA metrics are designed to help teams measure their performance and make data-driven improvements. If you're an engineering leader aiming to boost your team's efficiency and quality, this guide to DORA metrics will provide the insights you need.",[613,13240,13242],{"id":13241},"what-are-the-dora-metrics",[16,13243,13244],{},"What are the DORA Metrics?",[12,13246,13247,13248,13252],{},"DORA metrics, developed by the ",[514,13249,13251],{"href":11244,"rel":13250},[518],"DevOps Research and Assessment (DORA)"," team, are essential measurements for software development and delivery performance. These metrics are crucial for engineering leaders aiming to optimize their DevOps processes and achieve continuous improvement. They provide a clear, actionable framework to evaluate the efficiency and effectiveness of software delivery.",[613,13254,13256],{"id":13255},"understanding-dora-metrics-the-four-key-performance-indicators",[16,13257,13258],{},"Understanding DORA Metrics: The Four Key Performance Indicators",[12,13260,13261],{},"To fully grasp the power of DORA metrics, let's break down the four key performance indicators (KPIs) that make them so impactful.",[52,13263,13264],{"id":824},[791,13265,13266],{},[16,13267,825],{},[12,13269,13270],{},"Deployment Frequency measures how often your team releases new code to production. High-performing teams aim for frequent deployments, allowing for faster feedback and quicker iterations. This metric reflects the agility of the development process and is a strong indicator of a team's ability to respond to changing market demands. Frequent deployments are the hallmark of a mature DevOps culture. They reduce risk and improve customer satisfaction.",[12,13272,13273],{},"Frequent deployments help in reducing the size of changes, making it easier to identify issues and mitigate risks. For instance, a team that deploys code daily can quickly fix bugs and roll out new features, enhancing overall product quality and customer satisfaction.",[3354,13275,13276],{},[12,13277,13278],{},"According to the 2023 State of DevOps report, elite performers deploy code 973 times more frequently than low performers.",[52,13280,13281],{"id":834},[791,13282,13283],{},[16,13284,13285],{},"Lead Time For Changes",[12,13287,13288],{},"Lead Time for Changes tracks the time it takes from code commit to deployment. Shorter lead times indicate a more efficient development process and quicker delivery of value to customers. This metric is crucial for understanding the speed at which your team can respond to new requirements or changes in the market.",[12,13290,13291],{},"Reducing lead time for changes involves streamlining the CI\u002FCD pipeline, automating testing, and ensuring that the path from code commit to deployment is as frictionless as possible. This efficiency enables teams to adapt swiftly, enhancing their competitive edge. Reducing lead time for changes is critical for staying competitive. It enables faster innovation and responsiveness.",[12,13293,13294],{},[16,13295,13296],{},"Check out our tips on reducing lead time for changes:",[12,13298,13299,13305],{},[514,13300,13302],{"href":10444,"rel":13301},[518],[4866,13303],{"alt":13285,"src":13304},"\u002Fassets\u002Fblog\u002Foobeya-reduce-lead-time-1024x307.png"," Click on the image: How To Reduce the Lead Time For Changes to optimize DORA Metrics",[52,13307,13308],{"id":858},[791,13309,13310],{},[16,13311,859],{},[12,13313,13314],{},"Change Failure Rate measures the percentage of deployments that cause a failure in production. Lowering this rate is essential for maintaining system reliability and customer trust. This metric highlights the stability and reliability of the deployment process.",[12,13316,13317],{},"A high change failure rate indicates issues with the quality of code being deployed or gaps in testing and review processes. Implementing robust automated testing, peer reviews, and continuous monitoring can help reduce failure rates and improve overall system stability.",[3354,13319,13320],{},[12,13321,13322,13323],{},"The DORA report states that elite teams have a change failure rate of 0-15%, significantly lower than their counterparts. - ",[514,13324,13326],{"href":10999,"rel":13325},[518],"2023 State of DevOps Report",[12,13328,13329],{},[16,13330,13331],{},"Check out our tips on detecting production failures:",[12,13333,13334,13341],{},[514,13335,13337],{"href":11482,"rel":13336},[518],[4866,13338],{"alt":13339,"src":13340},"Detect Production Failures","\u002Fassets\u002Fblog\u002Foobeya-dora-cfr-1024x307.png"," Click on the image: Detecting Production Failures to measure DORA Metrics",[52,13343,13345],{"id":13344},"time-to-restore-service",[791,13346,13347],{},[16,13348,13349],{},"Time to Restore Service",[12,13351,13352],{},"Time to Restore Service indicates how quickly a team can recover from a failure in production. Efficient incident response and recovery processes are vital for minimizing downtime and its associated costs. This metric is crucial for maintaining service reliability and minimizing the impact of outages on users.",[12,13354,13355],{},"Improving this metric involves having well-defined incident management processes, effective communication channels, and rapid deployment capabilities to quickly roll back or fix problematic changes. Teams that excel in this area can maintain high levels of user trust and service availability.",[501,13357],{},[613,13359,13361],{"id":13360},"case-studies-and-real-world-examples-of-leveraging-dora-metrics",[16,13362,13363],{},"Case Studies and Real-World Examples of Leveraging DORA Metrics",[12,13365,13366],{},"Many organizations have successfully implemented DORA metrics to transform their software delivery processes. For example, a leading e-commerce company reduced its lead time for changes from days to minutes by automating its CI\u002FCD pipeline and adopting microservices architecture. This change enabled the company to quickly adapt to market trends and deliver new features at an unprecedented pace.",[12,13368,13369],{},"Another example is a financial services firm that lowered its change failure rate by integrating automated testing and continuous monitoring into its development workflow. This approach not only improved the quality of its deployments but also increased customer satisfaction by ensuring more stable and reliable services.",[12,13371,13372],{},[514,13373,13374],{"href":13374,"rel":13375},"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=2mSRv4DEUik",[518],[613,13377,13379],{"id":13378},"benefits-of-using-dora-metrics",[16,13380,13381],{},"Benefits of Using DORA Metrics",[12,13383,13384],{},"Using DORA metrics provides several benefits for teams and organizations:",[1520,13386,13387,13393,13399,13405],{},[73,13388,13389,13392],{},[16,13390,13391],{},"Improved Efficiency:"," By identifying bottlenecks and inefficiencies in the development process, teams can streamline workflows and enhance productivity.",[73,13394,13395,13398],{},[16,13396,13397],{},"Higher Quality:"," Frequent deployments and shorter lead times lead to smaller, manageable changes, reducing the risk of introducing bugs and improving overall code quality.",[73,13400,13401,13404],{},[16,13402,13403],{},"Better Customer Satisfaction:"," Faster delivery of features and quicker resolution of issues directly contribute to higher customer satisfaction and loyalty.",[73,13406,13407,13410],{},[16,13408,13409],{},"Enhanced Team Morale:"," Clear, measurable goals and visible improvements can boost team morale and motivation, fostering a culture of continuous improvement.",[613,13412,13414],{"id":13413},"challenges-and-solutions",[16,13415,13416],{},"Challenges and Solutions",[12,13418,13419],{},"While DORA metrics offer significant benefits, implementing them can come with challenges:",[1520,13421,13422,13428,13434],{},[73,13423,13424,13427],{},[16,13425,13426],{},"Cultural Resistance:"," Teams accustomed to traditional development practices may resist changes required to adopt DevOps and DORA metrics. Solution: Provide training, clear communication, and involve teams in the change process.",[73,13429,13430,13433],{},[16,13431,13432],{},"Tool Integration:"," Integrating various tools and systems to capture and analyze DORA metrics can be complex. Solution: Use comprehensive platforms like Oobeya Software Engineering Intelligence Platform that provide seamless integration and unified dashboards.",[73,13435,13436,13438],{},[16,13437,11380],{}," Maintaining continuous improvement requires ongoing monitoring and adjustment. Solution: Establish regular reviews and feedback loops to assess performance and make necessary adjustments.",[613,13440,13442],{"id":13441},"how-to-maximize-your-performance-with-oobeya",[16,13443,13444],{},"How to Maximize Your Performance with Oobeya!",[12,13446,13447,13448,13452,13453,13458],{},"Why should you choose Oobeya to optimize your DORA metrics? Our platform offers comprehensive engineering metrics and ",[514,13449,13451],{"href":11489,"rel":13450},[518],"actionable insights",", tailored to help you excel in your DevOps journey. With Oobeya, you can seamlessly ",[514,13454,13457],{"href":13455,"rel":13456},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fachieving-seamless-integration-connecting-your-tools-with-oobeya\u002F",[518],"integrate your SDLC tools",", monitor real-time data, and leverage advanced analytics to drive continuous improvement.",[12,13460,13461],{},[791,13462,13463],{},"Recommended Reading:",[70,13465,13466,13472,13477,13482],{},[73,13467,13468],{},[514,13469,13471],{"href":7188,"rel":13470},[518],"DORA Metrics: Four Key Metrics to Unlock DevOps Success",[73,13473,13474],{},[514,13475,10265],{"href":10263,"rel":13476},[518],[73,13478,13479],{},[514,13480,11484],{"href":11482,"rel":13481},[518],[73,13483,13484],{},[514,13485,13487],{"href":11456,"rel":13486},[518],"How to Measure DORA Metrics Accurately?",[501,13489],{},[12,13491,13492],{},"By focusing on DORA metrics, you can significantly enhance your team's performance and achieve a high level of operational excellence. Start leveraging these insights today and watch your team transform into a high-performing powerhouse.",[12,13494,13495,13498],{},[514,13496,10359],{"href":10357,"rel":13497},[518]," and get started with Oobeya now!",[12,13500,13501,13502,13507],{},"[embed]",[514,13503,13506],{"href":13504,"rel":13505},"https:\u002F\u002Fform.jotform.com\u002Fform\u002F241291821143045%5C%5B\u002Fembed%5C",[518],"https:\u002F\u002Fform.jotform.com\u002Fform\u002F241291821143045\\[\u002Fembed\\","]",{"title":526,"searchDepth":527,"depth":527,"links":13509},[13510,13511,13517,13518,13519,13520],{"id":13241,"depth":527,"text":13244},{"id":13255,"depth":527,"text":13258,"children":13512},[13513,13514,13515,13516],{"id":824,"depth":530,"text":825},{"id":834,"depth":530,"text":13285},{"id":858,"depth":530,"text":859},{"id":13344,"depth":530,"text":13349},{"id":13360,"depth":527,"text":13363},{"id":13378,"depth":527,"text":13381},{"id":13413,"depth":527,"text":13416},{"id":13441,"depth":527,"text":13444},[1232,1259,1231,13522],"space-metrics","2024-06-27","Imagine deploying new features rapidly while maintaining high reliability. This isn't just a dream for software development teams—it's achievable with...",{},"\u002Fblog\u002Fdora-metrics-delivery-performance",{"title":11465,"description":13524},"blog\u002Fdora-metrics-delivery-performance",[1232,1259,1231,13530],"space","g2VFlOvUAo-d-dlmme0n5Tl9useUbE-P34pmmSQ1Zx0",{"id":13533,"title":13534,"author":4245,"avatar":575,"body":13535,"categories":13739,"createAt":542,"date":13740,"description":13741,"extension":545,"meta":13742,"navigation":547,"path":13743,"position":542,"seo":13744,"spotImage":542,"spotText":542,"stem":13745,"tags":542,"__hash__":13746},"blog\u002Fblog\u002Fthe-essential-role-of-version-control-in-modern-development.md","The Essential Role of Version Control in Modern Development",{"type":9,"value":13536,"toc":13729},[13537,13540,13546,13549,13555,13558,13564,13571,13577,13585,13591,13594,13600,13607,13639,13646,13694,13701,13707,13715,13721],[12,13538,13539],{},"Version control is the backbone of modern software development, ensuring seamless collaboration and efficient code management. But why is it so crucial, and how does it support development practices? Let's dive into the world of Version Control Systems (VCS) and discover their indispensable role in the development process.",[613,13541,13543],{"id":13542},"understanding-the-basics-of-version-control-systems-vcs",[16,13544,13545],{},"Understanding the Basics of Version Control Systems (VCS)",[12,13547,13548],{},"Version control systems, such as Git, are essential tools in software development. They track changes in code, allowing multiple developers to work on the same project simultaneously without conflicts. This not only improves collaboration but also ensures that every change is documented and can be reverted if necessary.",[613,13550,13552],{"id":13551},"the-evolution-of-version-control-from-cvs-to-git",[16,13553,13554],{},"The Evolution of Version Control: From CVS to Git",[12,13556,13557],{},"Version control has come a long way since its inception. Early systems like CVS (Concurrent Versions System) paved the way, but modern tools like Git have revolutionized the way we manage code. Git’s distributed nature allows for greater flexibility and efficiency, making it the preferred choice for many development teams.",[613,13559,13561],{"id":13560},"how-version-control-supports-agile-and-devops-practices",[16,13562,13563],{},"How Version Control Supports Agile and DevOps Practices",[12,13565,13566,13567,13570],{},"Agile and ",[514,13568,11103],{"href":13569},"\u002Fglossary\u002Fdevops"," practices thrive on collaboration, continuous integration, and continuous delivery. VCS is at the heart of these methodologies. They enable teams to manage their codebase effectively, facilitate automated testing, and ensure that new features and fixes can be integrated seamlessly into the main codebase.",[613,13572,13574],{"id":13573},"version-control-for-code-quality-branching-and-merging-strategies",[16,13575,13576],{},"Version Control for Code Quality: Branching and Merging Strategies",[12,13578,13579,13580,13584],{},"Effective branching and merging strategies are crucial for maintaining code quality. Branching allows developers to work on new features or fixes in isolation while merging ensures that these changes are integrated smoothly into the main codebase. Techniques like feature branching, release branching, and ",[514,13581,13583],{"href":13582},"\u002Fglossary\u002Ftrunk-based-development","trunk-based development"," help teams manage their workflows efficiently.",[613,13586,13588],{"id":13587},"how-oobeya-works-with-version-control-systems-vcs",[16,13589,13590],{},"How Oobeya Works with Version Control Systems (VCS)",[12,13592,13593],{},"Oobeya integrates seamlessly with popular VCS tools like GitHub, GitLab, Azure DevOps, and Bitbucket, enhancing your development workflow. By connecting your VCS to Oobeya, you gain deeper insights into your development process, enabling you to track metrics, identify bottlenecks, and optimize performance.",[613,13595,13597],{"id":13596},"what-you-gain-from-oobeyas-integration-with-your-vcs",[16,13598,13599],{},"What You Gain from Oobeya’s Integration with Your VCS",[12,13601,13602,13603],{},"Integrating your version control system with Oobeya provides several substantial benefits, each aligned with the ",[514,13604,13606],{"href":11508,"rel":13605},[518],"SPACE framework.",[70,13608,13609,13615,13621,13627,13633],{},[73,13610,13611,13614],{},[16,13612,13613],{},"S","atisfaction and Wellbeing",[73,13616,13617,13620],{},[16,13618,13619],{},"P","erformance",[73,13622,13623,13626],{},[16,13624,13625],{},"A","ctivity",[73,13628,13629,13632],{},[16,13630,13631],{},"C","ommunication and Collaboration",[73,13634,13635,13638],{},[16,13636,13637],{},"E","fficiency and Flow",[12,13640,13641,13645],{},[4866,13642],{"alt":13643,"src":13644},"SPACE Framework","\u002Fassets\u002Fblog\u002Fspace-framework-1024x750.jpeg"," SPACE Framework",[1520,13647,13648,13654,13660,13666,13672,13682,13688],{},[73,13649,13650,13653],{},[16,13651,13652],{},"Enhanced Collaboration (Communication and Collaboration)",": By tracking changes and contributions in real time, Oobeya fosters a collaborative environment where team members can work more effectively.",[73,13655,13656,13659],{},[16,13657,13658],{},"Improved Code Quality (Performance)",": With features like automated code reviews and pull request analytics, Oobeya enhances performance by maintaining high code standards and identifying potential issues early.",[73,13661,13662,13665],{},[16,13663,13664],{},"Increased Productivity (Activity)",": Oobeya’s detailed insights and metrics allow teams to identify inefficiencies and streamline workflows, leading to higher activity levels and productivity.",[73,13667,13668,13671],{},[16,13669,13670],{},"Comprehensive Insights (Efficiency and Flow)",": Gain access to in-depth analytics on your version control activities, enabling data-driven decision-making and improving the efficiency and flow of your projects.",[73,13673,13674,13677,13678,13681],{},[16,13675,13676],{},"Advanced Metrics for Continuous Improvement (Performance)",": Oobeya’s integration provides advanced metrics like cycle time, lead time, and ",[514,13679,13680],{"href":891},"code churn",", which help teams continuously improve by identifying areas for enhancement in the development process.",[73,13683,13684,13687],{},[16,13685,13686],{},"Unified Platform for Value Stream Visibility (Communication and Collaboration)",": Oobeya consolidates various aspects of value delivery into a single platform, ensuring consistent communication and collaboration across projects.",[73,13689,13690,13693],{},[16,13691,13692],{},"Supports Agile and DevOps Practices (Efficiency and Flow)",": Oobeya’s real-time monitoring and reporting capabilities measure Agile and DevOps performance, providing timely feedback and facilitating continuous integration and delivery for better efficiency and flow.",[12,13695,13696,13697,611],{},"For more detailed information on how Oobeya can enhance your development workflow, visit ",[514,13698,13700],{"href":8079,"rel":13699},[518],"Oobeya Docs",[613,13702,13704],{"id":13703},"seamless-integration-with-vcs-tools",[16,13705,13706],{},"Seamless Integration with VCS Tools",[12,13708,13709,13710,13714],{},"Oobeya supports a wide range of ",[514,13711,13713],{"href":12472,"rel":13712},[518],"VCS tools",", making it easy to integrate with your existing setup. Whether you’re using Git, GitHub, or another VCS, Oobeya has you covered.",[613,13716,13718],{"id":13717},"measure-git-metrics",[16,13719,13720],{},"Measure Git Metrics",[12,13722,13723,13724,13728],{},"Ready to take your development process to the next level? Integrate your version control system with ",[514,13725,13727],{"href":10160,"rel":13726},[518],"Oobeya today",", measure Git metrics, and experience the benefits of enhanced collaboration, improved code quality, and increased productivity.",{"title":526,"searchDepth":527,"depth":527,"links":13730},[13731,13732,13733,13734,13735,13736,13737,13738],{"id":13542,"depth":527,"text":13545},{"id":13551,"depth":527,"text":13554},{"id":13560,"depth":527,"text":13563},{"id":13573,"depth":527,"text":13576},{"id":13587,"depth":527,"text":13590},{"id":13596,"depth":527,"text":13599},{"id":13703,"depth":527,"text":13706},{"id":13717,"depth":527,"text":13720},[541],"2024-06-20","Version control is the backbone of modern software development, ensuring seamless collaboration and efficient code management. But why is it so...",{},"\u002Fblog\u002Fthe-essential-role-of-version-control-in-modern-development",{"title":13534,"description":13741},"blog\u002Fthe-essential-role-of-version-control-in-modern-development","kHaX06JlIfnW-C4woq37pAqjD5Ibv0EE1qVnfarCbCY",{"id":13748,"title":13749,"author":4245,"avatar":575,"body":13750,"categories":14047,"createAt":542,"date":14048,"description":14049,"extension":545,"meta":14050,"navigation":547,"path":14051,"position":542,"seo":14052,"spotImage":542,"spotText":542,"stem":14053,"tags":542,"__hash__":14054},"blog\u002Fblog\u002Felevate-your-agile-practices-with-oobeyas-comprehensive-scrum-boards-analytics.md","Elevate Your Agile Practices with Oobeya's Comprehensive Scrum Boards Analytics",{"type":9,"value":13751,"toc":14037},[13752,13759,13765,13772,13778,13788,13795,13801,13812,13822,13828,13831,13875,13878,13882,13888,13894,13920,13927,13933,13941,13948,13954,13959,13965,13973,13979,13987,13993,14001,14007,14010,14016,14026,14029],[12,13753,13754,13755,13758],{},"Agile methodologies are revolutionizing how teams work, but even the best practices can fall short without the right tools. ",[16,13756,13757],{},"Oobeya's Agile Board Analytics module (AgileSpace)"," offers an unparalleled solution to enhance your Agile practices by providing deep insights into your planning, development, and delivery processes.",[613,13760,13762],{"id":13761},"understanding-the-basics-of-oobeyas-scrum-boards-analytics",[16,13763,13764],{},"Understanding the Basics of Oobeya's Scrum Boards Analytics",[12,13766,13767,13768,13771],{},"At its core, ",[16,13769,13770],{},"Oobeya’s AgileSpace"," analyzes all work items and tickets on an Agile board, generating crucial metrics to help teams understand and improve their processes. By leveraging these metrics, teams can detect process symptoms and take proactive measures.",[613,13773,13775],{"id":13774},"integrating-oobeya-scrum-boards-with-your-agile-workflow",[16,13776,13777],{},"Integrating Oobeya Scrum Boards with Your Agile Workflow",[12,13779,13780,13781,5502,13784,13787],{},"Integrating Oobeya Scrum Boards into your Agile workflow is seamless. Whether you're using ",[16,13782,13783],{},"Jira scrum boards",[16,13785,13786],{},"Azure Boards",", Oobeya's comprehensive suite of tools can elevate your Agile practices. Syncing with your existing tools, Oobeya ensures you get the most accurate and relevant insights.",[12,13789,13790,13794],{},[4866,13791],{"alt":13792,"src":13793},"Oobeya Agile Analytics","\u002Fassets\u002Fblog\u002Fagile-analytics-1024x532.png"," Oobeya Agile Analytics",[613,13796,13798],{"id":13797},"customizing-your-scrum-board-analytics-for-maximum-efficiency",[16,13799,13800],{},"Customizing Your Scrum Board Analytics for Maximum Efficiency",[12,13802,13803,13804,13807,13808,13811],{},"Customization is key to accurate Agile metrics. Oobeya allows dynamic state mapping of each scrum board, ensuring precise analysis tailored to your specific workflow. The ",[16,13805,13806],{},"status mapping feature"," lets users adjust workflows on Oobeya, while the ",[16,13809,13810],{},"effort field mapping feature"," allows selecting the proper effort fields like story points, original estimates, or custom fields.",[12,13813,13814,13821],{},[514,13815,13817],{"href":10160,"rel":13816},[518],[4866,13818],{"alt":13819,"src":13820},"Oobeya Scrum Board State Mapping","\u002Fassets\u002Fblog\u002Fboard-state-mapping-1024x738.png"," Oobeya Scrum Board State Mapping",[613,13823,13825],{"id":13824},"advanced-features-of-oobeyas-scrum-boards-to-boost-productivity",[16,13826,13827],{},"Advanced Features of Oobeya's Scrum Boards to Boost Productivity",[12,13829,13830],{},"Oobeya offers several widgets that display various metrics:",[70,13832,13833,13839,13845,13851,13857,13863,13869],{},[73,13834,13835,13838],{},[16,13836,13837],{},"Summary Widget",": Basic view of your board (name, type, average stats, etc.).",[73,13840,13841,13844],{},[16,13842,13843],{},"Time in State Widget",": Average time a task stays in each state. This widget includes Summary, Lead Time Highest 50 & Lowest 50, and Done Issue List views.",[73,13846,13847,13850],{},[16,13848,13849],{},"Sprint Velocity Metrics Widget",": Velocity measurements of work completed in a Sprint.",[73,13852,13853,13856],{},[16,13854,13855],{},"Assignee List Widget",": Activities of all assignees on the board.",[73,13858,13859,13862],{},[16,13860,13861],{},"Work In Progress Widget",": Issues open for more than 5 days.",[73,13864,13865,13868],{},[16,13866,13867],{},"Scope Change Widget",": Changes (removed and added tasks) after the sprint starts (item count and effort).",[73,13870,13871,13874],{},[16,13872,13873],{},"Estimated\u002FActual Effort Widget",": Shows the accuracy of the estimations provided by the team (Estimated Effort\u002FActual Effort). This graph is used to understand the root cause of divergence.",[12,13876,13877],{},"These features not only help in tracking but also in identifying areas for continuous improvement, ensuring that your team is always on the path to enhanced productivity.",[52,13879,13881],{"id":13880},"detailed-overview-of-key-scrum-metrics-and-reports","Detailed Overview of Key Scrum Metrics and Reports",[12,13883,3617,13884,13887],{},[16,13885,13886],{},"Summary Report"," gives an overarching view of completed sprints, average sprint velocity, lead time, and cycle time. It helps teams quickly grasp their overall performance and identify areas for improvement.",[4331,13889,13891,3444],{"id":13890},"time-in-state",[16,13892,13893],{},"Time in State",[70,13895,13896,13899,13902,13908,13914],{},[73,13897,13898],{},"Tracks the average time tasks stay in each state before completion.",[73,13900,13901],{},"Helps teams identify bottlenecks and streamline processes.",[73,13903,13904,13907],{},[16,13905,13906],{},"Reaction Time:"," Reaction time is the measurement of how much time a task stays in 'Not started' (to do, backlog, etc.) states.",[73,13909,13910,13913],{},[16,13911,13912],{},"Cycle Time:"," Cycle time is the measurement of how much time passes between work started on an item (story, task, bug, etc.) until it’s ready for delivery. (Work started -in progress- to work completed.)",[73,13915,13916,13919],{},[16,13917,13918],{},"Lead Time:"," Lead time is the measurement of how much time passes between task creation and when the work is completed. (Task created to work completed.)",[12,13921,13922,13926],{},[4866,13923],{"alt":13924,"src":13925},"Oobeya Time In State","\u002Fassets\u002Fblog\u002Ftime-in-state-1024x413.png"," Oobeya Time In State",[4331,13928,13930,3444],{"id":13929},"sprint-velocity-metrics",[16,13931,13932],{},"Sprint Velocity Metrics",[70,13934,13935,13938],{},[73,13936,13937],{},"Shows completed issues per sprint, delivery rate by issue count and effort, planning accuracy, and completed effort per sprint.",[73,13939,13940],{},"Provides a visual representation of planned vs. done work items over multiple sprints.",[12,13942,13943,13947],{},[4866,13944],{"alt":13945,"src":13946},"Sprint Velocity","\u002Fassets\u002Fblog\u002Fsprint-velocity-1024x464.png"," Sprint Velocity",[4331,13949,13951,3444],{"id":13950},"assignee-list",[16,13952,13953],{},"Assignee List",[70,13955,13956],{},[73,13957,13958],{},"Displays all team members and their activities, helping to balance workload distribution, identify high performers, and identify red flags for overloading risks.",[4331,13960,13962,3444],{"id":13961},"work-in-progress",[16,13963,13964],{},"Work In Progress",[70,13966,13967,13970],{},[73,13968,13969],{},"Lists open issues that have been in progress for more than five days.",[73,13971,13972],{},"Highlights potential blockers that need attention.",[4331,13974,13976,3444],{"id":13975},"sprint-scope-change",[16,13977,13978],{},"Sprint Scope Change",[70,13980,13981,13984],{},[73,13982,13983],{},"Tracks changes during the sprint, showing added and removed issues after the sprint starts.",[73,13985,13986],{},"Provides insights into how scope changes impact sprint performance.",[4331,13988,13990,3444],{"id":13989},"estimatedactual-effort",[16,13991,13992],{},"Estimated\u002FActual Effort",[70,13994,13995,13998],{},[73,13996,13997],{},"Depicts the time spent on issues versus the estimated effort.",[73,13999,14000],{},"Helps teams improve estimation accuracy and manage capacity better.",[613,14002,14004],{"id":14003},"measuring-success-and-continuous-improvement-with-oobeyas-analytics",[16,14005,14006],{},"Measuring Success and Continuous Improvement with Oobeya's Analytics",[12,14008,14009],{},"Success in Agile is not just about completing sprints but continuously improving with each iteration. Oobeya's comprehensive analytics provide a deep dive into sprint performance, enabling teams to pinpoint strengths and identify areas needing improvement. With detailed metrics like Sprint Velocity, Assignee Statistics, and Issue Distribution, Oobeya empowers teams to make data-driven decisions. These insights foster a culture of continuous improvement, ensuring that every sprint is more efficient and productive than the last. By leveraging Oobeya's analytics, Agile teams can elevate their practices, enhance collaboration, and consistently achieve their goals.",[613,14011,14013],{"id":14012},"ready-to-transform-your-agile-workflow",[16,14014,14015],{},"Ready to transform your Agile workflow?",[12,14017,14018,365,14021,14025],{},[16,14019,14020],{},"Enhance your agile methodology with Oobeya Scrum Boards",[514,14022,14024],{"href":12016,"rel":14023},[518],"Optimize your software engineering"," today and take the first step towards streamlined workflows, improved collaboration, and effortless productivity.",[12,14027,14028],{},"By leveraging Oobeya's agile analytics module, you can elevate your Agile practices to new heights. Whether you're looking to better understand your current processes or seeking ways to optimize for the future, Oobeya provides the tools and insights you need to succeed.",[3354,14030,14031],{},[12,14032,14033,14036],{},[514,14034,10359],{"href":10357,"rel":14035},[518]," and get started with Oobeya now!",{"title":526,"searchDepth":527,"depth":527,"links":14038},[14039,14040,14041,14042,14045,14046],{"id":13761,"depth":527,"text":13764},{"id":13774,"depth":527,"text":13777},{"id":13797,"depth":527,"text":13800},{"id":13824,"depth":527,"text":13827,"children":14043},[14044],{"id":13880,"depth":530,"text":13881},{"id":14003,"depth":527,"text":14006},{"id":14012,"depth":527,"text":14015},[541,6446],"2024-06-17","Agile methodologies are revolutionizing how teams work, but even the best practices can fall short without the right tools. Oobeya's Agile Board...",{},"\u002Fblog\u002Felevate-your-agile-practices-with-oobeyas-comprehensive-scrum-boards-analytics",{"title":13749,"description":14049},"blog\u002Felevate-your-agile-practices-with-oobeyas-comprehensive-scrum-boards-analytics","xULZOd2cP2u3oP5_Ep-EVcZRF2ulpJUeygNcTH3yPgs",{"id":14056,"title":14057,"author":4245,"avatar":575,"body":14058,"categories":14523,"createAt":542,"date":14524,"description":14525,"extension":545,"meta":14526,"navigation":547,"path":14527,"position":542,"seo":14528,"spotImage":542,"spotText":542,"stem":14529,"tags":542,"__hash__":14530},"blog\u002Fblog\u002Fachieving-seamless-integration-connecting-your-tools-with-oobeya.md","Achieving Seamless Integration: Connecting Your Tools with Oobeya",{"type":9,"value":14059,"toc":14494},[14060,14066,14069,14072,14078,14081,14085,14130,14140,14144,14195,14199,14243,14247,14267,14271,14301,14305,14351,14358,14364,14367,14371,14374,14378,14381,14385,14388,14392,14395,14401,14403,14409,14412,14416,14419,14423,14426,14430,14433,14437,14440,14444,14447,14449,14455,14458,14462,14465,14469,14476,14480,14483,14486],[613,14061,14063],{"id":14062},"introduction-to-oobeyas-integration-capabilities",[16,14064,14065],{},"Introduction to Oobeya's Integration Capabilities",[12,14067,14068],{},"Oobeya's integration capabilities are designed to connect your diverse set of tools, providing a unified platform that enhances your Software Development Life Cycle (SDLC) and DevOps process. With Oobeya, you can streamline the value delivery across development, testing, maintenance, and operations, ensuring that your team remains in sync and productive.",[12,14070,14071],{},"Oobeya stands out as a leader in the software engineering intelligence platforms market, offering solutions that simplify the complexities of integrating multiple tools and platforms. By leveraging Oobeya, you can achieve seamless software integration and improve your overall workflow efficiency.",[613,14073,14075],{"id":14074},"oobeya-sdlc-tool-integrations-list",[16,14076,14077],{},"Oobeya SDLC Tool Integrations List",[12,14079,14080],{},"Oobeya offers an extensive range of integrations tailored to meet the needs of various stages of the SDLC. Here is a comprehensive list of Oobeya's integrations, categorized by their primary functions and main use cases:",[52,14082,14084],{"id":14083},"version-control-systems-vcs","Version Control Systems (VCS)",[70,14086,14087,14093,14099,14105,14115,14121],{},[73,14088,14089,14092],{},[16,14090,14091],{},"Azure DevOps (Cloud, Server)",": Manage repositories and track changes, crucial for maintaining a centralized codebase.",[73,14094,14095,14098],{},[16,14096,14097],{},"Bitbucket (Cloud, Server)",": Sync repositories and manage team collaborations, enhancing collaborative development.",[73,14100,14101,14104],{},[16,14102,14103],{},"GitHub.com (All Plans)",": Manage repositories, pull requests, and code reviews, providing a robust platform for open-source and private projects.",[73,14106,14107,14114],{},[16,14108,14109,14113],{},[514,14110,14112],{"href":14111},"\u002Fglossary\u002Fgithub-enterprise","GitHub Enterprise"," (Cloud, On-premise)",": Advanced version control for large teams, ensuring scalability and enterprise-level management.",[73,14116,14117,14120],{},[16,14118,14119],{},"GitLab (Cloud, Enterprise)",": Integrate CI\u002FCD pipelines, issue tracking, and version control, offering a comprehensive development workflow.",[73,14122,14123,14129],{},[16,14124,14125],{},[514,14126,14128],{"href":14127},"\u002Fglossary\u002Fgitea","Gitea",": Lightweight, self-hosted Git service, ideal for teams seeking customizable and independent version control.",[12,14131,14132,14139],{},[514,14133,14135],{"href":10160,"rel":14134},[518],[4866,14136],{"alt":14137,"src":14138},"Oobeya VCS integrations","\u002Fassets\u002Fblog\u002Fgithub-enterprise-oobeya-300x235.webp"," Oobeya VCS integrations",[52,14141,14143],{"id":14142},"cicd-tools","CI\u002FCD Tools",[70,14145,14146,14152,14161,14171,14177,14186],{},[73,14147,14148,14151],{},[16,14149,14150],{},"GitHub Actions",": Streamline CI\u002FCD workflows directly within GitHub, simplifying continuous integration and deployment.",[73,14153,14154,14160],{},[16,14155,14156],{},[514,14157,14159],{"href":14158},"\u002Fglossary\u002Fgitlab-cicd","GitLab CI\u002FCD",": Integrated CI\u002FCD pipelines with GitLab repositories, enhancing automated testing and deployment.",[73,14162,14163,14170],{},[16,14164,14165,14166],{},"Jenkins & ",[514,14167,14169],{"href":14168},"\u002Fglossary\u002Fcloudbees","CloudBees",": Automate build, test, and deployment processes, providing flexibility and extensive plugin support.",[73,14172,14173,14176],{},[16,14174,14175],{},"Azure DevOps Pipelines & Releases",": Build, test, and deploy with Azure DevOps, ensuring seamless integration with other Azure services.",[73,14178,14179,14185],{},[16,14180,14181],{},[514,14182,14184],{"href":14183},"\u002Fglossary\u002Fteamcity","TeamCity",": Powerful CI\u002FCD server for building and deploying projects, offering deep integration with various development tools.",[73,14187,14188,14194],{},[16,14189,14190],{},[514,14191,14193],{"href":14192},"\u002Fglossary\u002Foctopus-deploy","Octopus Deploy",": Automated deployment and release management, simplifying complex deployment workflows.",[52,14196,14198],{"id":14197},"apm-observability","APM & Observability",[70,14200,14201,14210,14216,14222,14228,14234],{},[73,14202,14203,14209],{},[16,14204,14205],{},[514,14206,14208],{"href":14207},"\u002Fglossary\u002Fnew-relic","New Relic",": Monitor application performance and infrastructure, providing detailed insights and real-time analytics.",[73,14211,14212,14215],{},[16,14213,14214],{},"Dynatrace",": Advanced observability and performance monitoring, helping to detect and resolve issues proactively.",[73,14217,14218,14221],{},[16,14219,14220],{},"Sentry (Cloud, Self-hosted)",": Monitor and fix crashes in real-time, enhancing error tracking and debugging processes.",[73,14223,14224,14227],{},[16,14225,14226],{},"AppDynamics",": Application performance management and IT operations analytics, offering comprehensive visibility into performance metrics.",[73,14229,14230,14233],{},[16,14231,14232],{},"ElasticAPM",": Application performance monitoring for the Elastic Stack, integrating seamlessly with your existing ELK stack.",[73,14235,14236,14242],{},[16,14237,14238],{},[514,14239,14241],{"href":14240},"\u002Fglossary\u002Fdatadog","Datadog",": Collect and visualize metrics, logs, and traces, providing a unified view of your entire stack.",[52,14244,14246],{"id":14245},"issue-tracking","Issue Tracking",[70,14248,14249,14255,14261],{},[73,14250,14251,14254],{},[16,14252,14253],{},"Jira Cloud",": Track issues, manage agile projects, and plan sprints, providing robust project management capabilities.",[73,14256,14257,14260],{},[16,14258,14259],{},"Jira (Server, Data Center)",": Advanced issue tracking for enterprise environments, ensuring scalability and performance.",[73,14262,14263,14266],{},[16,14264,14265],{},"Azure DevOps Boards (Cloud, Server)",": Plan, track, and discuss work across teams, integrating deeply with Azure DevOps services.",[52,14268,14270],{"id":14269},"authentication-single-sign-on-sso","Authentication & Single Sign On (SSO)",[70,14272,14273,14279,14285,14291],{},[73,14274,14275,14278],{},[16,14276,14277],{},"LDAP",": Integrate with Lightweight Directory Access Protocol for user authentication, enhancing security and user management.",[73,14280,14281,14284],{},[16,14282,14283],{},"Active Directory",": Manage user identities and secure access, providing robust directory services and authentication.",[73,14286,14287,14290],{},[16,14288,14289],{},"Microsoft Entra (Azure AD)",": Comprehensive identity and access management, simplifying user access control and security.",[73,14292,14293,14300],{},[16,14294,14295,14296,6347],{},"Okta (",[514,14297,14299],{"href":14298},"\u002Fglossary\u002Fsaml","SAML",": Secure identity management and single sign-on, streamlining user authentication and access across multiple applications.",[52,14302,14304],{"id":14303},"quality-security","Quality & Security",[70,14306,14307,14312,14321,14327,14333,14339,14345],{},[73,14308,14309,14311],{},[16,14310,5120],{},": Analyze code quality and security vulnerabilities, helping maintain high code standards and security.",[73,14313,14314,14320],{},[16,14315,14316],{},[514,14317,14319],{"href":14318},"\u002Fglossary\u002Fsonarqube-cloud","SonarQube Cloud",": Cloud-based code quality and security service, offering seamless integration with your CI\u002FCD pipelines.",[73,14322,14323,14326],{},[16,14324,14325],{},"Fortify",": Static and dynamic application security testing, ensuring your applications are secure from vulnerabilities.",[73,14328,14329,14332],{},[16,14330,14331],{},"Veracode",": Application security testing solutions, providing comprehensive security analysis and remediation guidance.",[73,14334,14335,14338],{},[16,14336,14337],{},"TestRail (beta)",": Test case management tool for quality assurance, improving test planning and execution.",[73,14340,14341,14344],{},[16,14342,14343],{},"Testinium",": Cloud-based test automation platform, enhancing automated testing capabilities.",[73,14346,14347,14350],{},[16,14348,14349],{},"Zephyr for Jira (beta)",": Test management solution integrated with Jira, streamlining test case management within your existing workflows.",[12,14352,14353,14354,611],{},"For a comprehensive list of Oobeya's integrations, visit the ",[514,14355,14357],{"href":12472,"rel":14356},[518],"Oobeya Integration Catalog",[613,14359,14361],{"id":14360},"step-by-step-guide-to-integrating-your-development-tools-with-oobeya",[16,14362,14363],{},"Step-by-Step Guide to Integrating Your Development Tools with Oobeya",[12,14365,14366],{},"Integrating your tools with Oobeya is a straightforward process. Follow these general steps to ensure a smooth setup:",[52,14368,14370],{"id":14369},"step-1-access-oobeya-integration-settings","Step 1: Access Oobeya Integration Settings",[12,14372,14373],{},"Navigate to the integrations section in Oobeya to access available integrations.",[52,14375,14377],{"id":14376},"step-2-select-your-tool","Step 2: Select Your Tool",[12,14379,14380],{},"Choose the tool you wish to integrate from the list of supported integrations.",[52,14382,14384],{"id":14383},"step-3-configure-integration-settings","Step 3: Configure Integration Settings",[12,14386,14387],{},"Enter the necessary credentials and configuration details. Ensure that your API tokens have the required permissions.",[52,14389,14391],{"id":14390},"step-4-verify-integration","Step 4: Verify Integration",[12,14393,14394],{},"Test the integration to confirm that data is flowing correctly between Oobeya and your tool.",[12,14396,14397,14398,611],{},"For detailed instructions, refer to the ",[514,14399,14357],{"href":8313,"rel":14400},[518],[501,14402],{},[613,14404,14406],{"id":14405},"best-practices-for-managing-your-tool-ecosystem-through-oobeya",[16,14407,14408],{},"Best Practices for Managing Your Tool Ecosystem through Oobeya",[12,14410,14411],{},"Managing a diverse tool ecosystem can be challenging. Here are some best practices to help you leverage Oobeya effectively:",[52,14413,14415],{"id":14414},"identify-inefficiencies-in-tool-usage","Identify Inefficiencies in Tool Usage",[12,14417,14418],{},"Regularly review your tool usage to identify inefficiencies or redundancies. This helps ensure that all tools are being used effectively and that your team isn't bogged down by unnecessary complexity.",[52,14420,14422],{"id":14421},"make-tools-effectively-used-in-your-organization","Make Tools Effectively Used in Your Organization",[12,14424,14425],{},"Train your team on the effective use of each tool and promote best practices to ensure maximum productivity. Leveraging SaaS integration software can streamline these processes and enhance overall efficiency.",[52,14427,14429],{"id":14428},"centralize-tool-management","Centralize Tool Management",[12,14431,14432],{},"Use Oobeya as a single point of control for all your tools to reduce complexity and enhance visibility. This approach leverages systems integration software to ensure all your development processes are streamlined.",[52,14434,14436],{"id":14435},"monitor-integration-health","Monitor Integration Health",[12,14438,14439],{},"Regularly check the health of your integrations to ensure continuous data flow and minimize disruptions. This is crucial for maintaining effective software continuous integration.",[52,14441,14443],{"id":14442},"optimize-permission-scopes","Optimize Permission Scopes",[12,14445,14446],{},"Ensure that API tokens and permissions are appropriately scoped to balance security and functionality.",[501,14448],{},[613,14450,14452],{"id":14451},"troubleshooting-common-integration-challenges-with-oobeya",[16,14453,14454],{},"Troubleshooting Common Integration Challenges with Oobeya",[12,14456,14457],{},"Even with seamless integration capabilities, you may encounter challenges. Here are some tips for troubleshooting common issues:",[52,14459,14461],{"id":14460},"_1-network-access","1- Network Access",[12,14463,14464],{},"Double-check the network access to your tools. Add Oobeya IP addresses to your whitelist if your tools are behind a firewall.",[52,14466,14468],{"id":14467},"_2-api-permissions","2- API Permissions",[12,14470,14471,14472,611],{},"Verify the permission scopes of your API tokens. Ensure they have the necessary access rights as specified in the ",[514,14473,14475],{"href":8079,"rel":14474},[518],"Oobeya docs",[52,14477,14479],{"id":14478},"_3-data-synchronization","3- Data Synchronization",[12,14481,14482],{},"Ensure that data synchronization settings are correctly configured to avoid discrepancies.",[12,14484,14485],{},"By following these guidelines and leveraging Oobeya's robust integration capabilities, you can achieve a seamless and efficient SDLC.",[3354,14487,14488],{},[12,14489,14490,14493],{},[514,14491,10359],{"href":10357,"rel":14492},[518]," now and get started with Oobeya!",{"title":526,"searchDepth":527,"depth":527,"links":14495},[14496,14497,14505,14511,14518],{"id":14062,"depth":527,"text":14065},{"id":14074,"depth":527,"text":14077,"children":14498},[14499,14500,14501,14502,14503,14504],{"id":14083,"depth":530,"text":14084},{"id":14142,"depth":530,"text":14143},{"id":14197,"depth":530,"text":14198},{"id":14245,"depth":530,"text":14246},{"id":14269,"depth":530,"text":14270},{"id":14303,"depth":530,"text":14304},{"id":14360,"depth":527,"text":14363,"children":14506},[14507,14508,14509,14510],{"id":14369,"depth":530,"text":14370},{"id":14376,"depth":530,"text":14377},{"id":14383,"depth":530,"text":14384},{"id":14390,"depth":530,"text":14391},{"id":14405,"depth":527,"text":14408,"children":14512},[14513,14514,14515,14516,14517],{"id":14414,"depth":530,"text":14415},{"id":14421,"depth":530,"text":14422},{"id":14428,"depth":530,"text":14429},{"id":14435,"depth":530,"text":14436},{"id":14442,"depth":530,"text":14443},{"id":14451,"depth":527,"text":14454,"children":14519},[14520,14521,14522],{"id":14460,"depth":530,"text":14461},{"id":14467,"depth":530,"text":14468},{"id":14478,"depth":530,"text":14479},[541],"2024-06-13","Oobeya's integration capabilities are designed to connect your diverse set of tools, providing a unified platform that enhances your Software...",{},"\u002Fblog\u002Fachieving-seamless-integration-connecting-your-tools-with-oobeya",{"title":14057,"description":14525},"blog\u002Fachieving-seamless-integration-connecting-your-tools-with-oobeya","IbFR12jUVQJhhb2lhIAeSWS3MlKoFQeIom7__a5Sc64",{"id":14532,"title":14533,"author":4245,"avatar":575,"body":14534,"categories":14797,"createAt":542,"date":14798,"description":14799,"extension":545,"meta":14800,"navigation":547,"path":11231,"position":4134,"seo":14801,"spotImage":542,"spotText":542,"stem":14802,"tags":14803,"__hash__":14805},"blog\u002Fblog\u002F6-steps-to-take-control-of-software-quality.md","6 Steps To Take Control of Software Quality - Blog",{"type":9,"value":14535,"toc":14782},[14536,14539,14545,14548,14580,14586,14592,14600,14606,14609,14629,14632,14638,14645,14651,14654,14660,14663,14669,14672,14678,14681,14687,14690,14701,14707,14710,14724,14727,14730,14733,14736,14744,14747,14750,14761,14764,14767,14773,14776],[12,14537,14538],{},"This blog post explores six practical steps to control software quality and introduces the concept of software intelligence for further improvement.",[613,14540,14542],{"id":14541},"why-is-software-quality-important",[16,14543,14544],{},"Why is Software Quality Important?",[12,14546,14547],{},"Delivering high-quality software is crucial for several reasons:",[70,14549,14550,14556,14562,14568,14574],{},[73,14551,14552,14555],{},[16,14553,14554],{},"Enhanced user experience and satisfaction:"," Users are more likely to be satisfied with a product that is functional, reliable, and easy to use.",[73,14557,14558,14561],{},[16,14559,14560],{},"Reduced development and maintenance costs:"," Fixing defects early in the development process is significantly cheaper than fixing them after release.",[73,14563,14564,14567],{},[16,14565,14566],{},"Improved brand reputation and market competitiveness:"," High-quality software helps build trust with customers and gives you an edge over competitors.",[73,14569,14570,14573],{},[16,14571,14572],{},"Minimized security risks and vulnerabilities:"," Secure software protects user data and system resources from unauthorized access.",[73,14575,14576,14579],{},[16,14577,14578],{},"Faster time-to-market for new features and updates:"," Efficient development processes allow you to release new features and updates quickly.",[613,14581,14583],{"id":14582},"_6-steps-to-take-control-of-software-quality-and-meet-software-intelligence-with-oobeya",[16,14584,14585],{},"6 Steps to Take Control of Software Quality and Meet Software Intelligence with Oobeya",[52,14587,14589],{"id":14588},"_1-track-and-visualize-coding-activities",[16,14590,14591],{},"1. Track and Visualize Coding Activities:",[12,14593,14594,14595,14599],{},"Monitor atomic development activities like commits, ",[514,14596,14598],{"href":14597},"\u002Fblog\u002Fwhat-is-a-pull-request-oobeya","pull requests",", and code review cycles. Utilize visualization tools to gain actionable insights into your development process, identify bottlenecks, and improve efficiency. Consider tools like Oobeya, LinearB, Pluralsight Flow, and GitHub Insights.",[52,14601,14603],{"id":14602},"_2-analyze-source-code-quality",[16,14604,14605],{},"2. Analyze Source Code Quality:",[12,14607,14608],{},"Continuous code inspection is essential for maintaining high-quality code. Implement these practices:",[70,14610,14611,14614,14617,14620,14623,14626],{},[73,14612,14613],{},"Enable on-the-fly code analysis with IDE extensions.",[73,14615,14616],{},"Integrate code analysis into your CI\u002FCD pipeline.",[73,14618,14619],{},"Set quality gates and break builds if quality standards are not met.",[73,14621,14622],{},"Track and address all code issues.",[73,14624,14625],{},"Encourage developers to follow clean coding principles and standards.",[73,14627,14628],{},"Plan code quality tasks for each sprint.",[12,14630,14631],{},"Explore code quality analysis software like SonarQube, SonarCloud, CAST, and Fortify.",[52,14633,14635],{"id":14634},"_3-care-about-code-vulnerabilities",[16,14636,14637],{},"3. Care About Code Vulnerabilities:",[12,14639,14640,14641,14644],{},"Proactively identify and address security vulnerabilities in your codebase before they are exploited by attackers. Use quality control software (specifically SAST tools like ",[514,14642,5120],{"href":5118,"rel":14643},[518],", Veracode, Checkmarx, Synk, and Fortify) to analyze your code and detect potential security issues. Integrate these tools into your CI\u002FCD pipelines.",[52,14646,14648],{"id":14647},"_4-test-what-you-code",[16,14649,14650],{},"4. Test What You Code:",[12,14652,14653],{},"Comprehensive testing is vital for ensuring the functionality and reliability of your software. Increase your test coverage by employing various testing types like unit testing, integration testing, API testing, UI testing, and functional testing. Utilize testing frameworks and tools to write and execute tests effectively. Consider test management software like Testinium, Zephyr, and TestRail to track and manage test execution results.",[52,14655,14657],{"id":14656},"_5-monitor-application-performance",[16,14658,14659],{},"5. Monitor Application Performance:",[12,14661,14662],{},"Application performance monitoring (APM) tools provide insights into user experience and application health. Identify and address performance issues that may impact user experience. Use APM tools like New Relic, Dynatrace, Sentry, Elastic APM, and AppDynamics.",[52,14664,14666],{"id":14665},"_6-make-your-issues-visible",[16,14667,14668],{},"6. Make Your Issues Visible:",[12,14670,14671],{},"Effectively capture, assign, and track issues throughout the software development lifecycle. Maintain clear visibility into all issues to ensure they are addressed promptly. Utilize quality management software systems like Jira, Azure DevOps, GitHub, and GitLab.",[613,14673,14675],{"id":14674},"introducing-software-intelligence",[16,14676,14677],{},"Introducing Software Intelligence:",[12,14679,14680],{},"While these steps can significantly improve software quality, managing multiple tools and data sources can become overwhelming. This is where software intelligence comes in.",[613,14682,14684],{"id":14683},"what-is-software-intelligence",[16,14685,14686],{},"What is Software Intelligence?",[12,14688,14689],{},"Software intelligence provides a unified platform that connects your existing DevOps tools and offers:",[70,14691,14692,14695,14698],{},[73,14693,14694],{},"Complete visibility into your software development lifecycle",[73,14696,14697],{},"Identification of bottlenecks across the entire development process",[73,14699,14700],{},"Actionable insights to improve software quality and team performance",[613,14702,14704],{"id":14703},"oobeya-your-software-engineering-intelligence-partner-enables-control-software-quality",[16,14705,14706],{},"Oobeya: Your Software Engineering Intelligence Partner Enables Control Software Quality",[12,14708,14709],{},"Oobeya, a software engineering intelligence platform, helps organizations deliver faster, high-quality software. It connects your existing DevOps tools to provide:",[70,14711,14712,14715,14718,14721],{},[73,14713,14714],{},"Real-time monitoring of the entire software development lifecycle",[73,14716,14717],{},"Visualization of software delivery cycles",[73,14719,14720],{},"Complete visibility into software health and delivery efficiency",[73,14722,14723],{},"Real-time data and insights to empower informed decision-making",[12,14725,14726],{},"By leveraging Oobeya's software engineering intelligence platform, you can take control of your software quality, improve development efficiency, and ultimately deliver exceptional software products.",[12,14728,14729],{},"After these practical steps, we need to talk about a new concept to overcome some difficulties.",[12,14731,14732],{},"The DevOps toolchain of an organization includes many tools to manage, maintain, and operate all the engineering processes.",[12,14734,14735],{},"Therefore, engineering managers should log in to many different tools, find their projects\u002Fteams, get relevant metrics of the projects\u002Fteams, and map them all in their brains to see the health and efficiency of their software and teams.",[12,14737,14738,14743],{},[4866,14739],{"alt":14740,"src":14741,"title":14742},"DevOps tools","\u002Fassets\u002Fblog\u002Fsdlc-tools-1024x421.webp","Control Software Quality"," DevOps tools - Control Software Quality",[12,14745,14746],{},"At this point, software engineering intelligence is here for you. Software engineering intelligence provides a complete platform to take control of software quality, identify bottlenecks of the entire development process, and produce actionable metrics to help you improve your software and team performance.",[12,14748,14749],{},"All the tools you use, and all the analysis you perform in DevOps, help you get a deeper level of software intelligence. And software intelligence helps you get rid of misinformation and disinformation about your product development process.",[12,14751,14752,14755,14756,14760],{},[514,14753,469],{"href":516,"rel":14754},[518]," -a brand-new ",[514,14757,14759],{"href":12016,"rel":14758},[518],"software engineering"," intelligence platform- helps organizations deliver faster, high-quality products by connecting their DevOps tools. Oobeya enables real-time monitoring of the entire software development life cycle and analyzes coding activities to visualize software delivery cycles.",[12,14762,14763],{},"By enabling Oobeya, you get complete visibility into your software health and delivery efficiency in a single platform.",[12,14765,14766],{},"Accessing real-time data and insights on teams and processes makes you more confident in taking action on product development and engineering processes.",[613,14768,14770],{"id":14769},"let-the-power-be-with-you",[16,14771,14772],{},"Let The Power Be With You",[12,14774,14775],{},"If you want to build a high-performing technology organization, it’s time to meet software intelligence with Oobeya.",[12,14777,14778,14779],{},"You can learn more about the product, schedule a demo, or see the live demo by visiting Oobeya’s website: ",[514,14780,5051],{"href":5051,"rel":14781},[518],{"title":526,"searchDepth":527,"depth":527,"links":14783},[14784,14785,14793,14794,14795,14796],{"id":14541,"depth":527,"text":14544},{"id":14582,"depth":527,"text":14585,"children":14786},[14787,14788,14789,14790,14791,14792],{"id":14588,"depth":530,"text":14591},{"id":14602,"depth":530,"text":14605},{"id":14634,"depth":530,"text":14637},{"id":14647,"depth":530,"text":14650},{"id":14656,"depth":530,"text":14659},{"id":14665,"depth":530,"text":14668},{"id":14674,"depth":527,"text":14677},{"id":14683,"depth":527,"text":14686},{"id":14703,"depth":527,"text":14706},{"id":14769,"depth":527,"text":14772},[10390,541],"2024-06-11","Learn 6 practical steps to improve software quality with better visibility, workflows, and engineering intelligence.",{},{"title":14533,"description":14799},"blog\u002F6-steps-to-take-control-of-software-quality",[6715,14804],"software-intelligence","r_3aWi3jIcpxV4P3rMZhKaYpE-4EiACPrWCFFL3qGD4",{"id":14807,"title":14808,"author":4245,"avatar":575,"body":14809,"categories":15125,"createAt":542,"date":15126,"description":15127,"extension":545,"meta":15128,"navigation":547,"path":15129,"position":542,"seo":15130,"spotImage":542,"spotText":542,"stem":15131,"tags":542,"__hash__":15132},"blog\u002Fblog\u002Fwhat-is-software-development-life-cycle-sdlc.md","What is Software Development Life Cycle (SDLC)?",{"type":9,"value":14810,"toc":15104},[14811,14817,14820,14826,14829,14873,14876,14882,14885,14917,14920,14926,14929,14949,14952,14958,14961,14967,14970,14976,14980,14983,14985,14988,14992,14995,14999,15002,15006,15009,15013,15016,15020,15023,15027,15030,15036,15039,15063,15066,15072,15080,15089,15095],[613,14812,14814],{"id":14813},"what-is-sdlc",[16,14815,14816],{},"What is SDLC?",[12,14818,14819],{},"The Software Development Life Cycle (SDLC) is a structured process software developers use to design, develop, test, deliver, and maintain high-quality software. The SDLC meaning is to produce software that meets or exceeds customer expectations, reaches completion within times and cost estimates, and is cost-efficient to produce and maintain. The SDLC process includes planning, creating, developing, testing, and deploying software.",[613,14821,14823],{"id":14822},"what-are-the-stages-of-sdlc",[16,14824,14825],{},"What are the Stages of SDLC?",[12,14827,14828],{},"The stages of the SDLC are crucial to the development of software projects and typically include:",[1520,14830,14831,14837,14843,14849,14855,14861,14867],{},[73,14832,14833,14836],{},[16,14834,14835],{},"Planning:"," Defining objectives, scope, and feasibility.",[73,14838,14839,14842],{},[16,14840,14841],{},"Requirements Analysis:"," Gathering detailed requirements from stakeholders.",[73,14844,14845,14848],{},[16,14846,14847],{},"Design:"," Creating architectural and detailed design plans.",[73,14850,14851,14854],{},[16,14852,14853],{},"Implementation (Coding):"," Writing the actual code.",[73,14856,14857,14860],{},[16,14858,14859],{},"Testing:"," Ensuring the software is defect-free.",[73,14862,14863,14866],{},[16,14864,14865],{},"Deployment:"," Delivering the software to users.",[73,14868,14869,14872],{},[16,14870,14871],{},"Maintenance:"," Ongoing support and refinement.",[12,14874,14875],{},"These software development life cycle phases ensure a comprehensive approach to delivering a successful software project.",[613,14877,14879],{"id":14878},"what-are-sdlc-models",[16,14880,14881],{},"What are SDLC Models?",[12,14883,14884],{},"SDLC models provide a framework for planning and controlling the development and delivery process. These models include:",[1520,14886,14887,14893,14899,14905,14911],{},[73,14888,14889,14892],{},[16,14890,14891],{},"Waterfall Life Cycle Model:"," A linear and sequential approach.",[73,14894,14895,14898],{},[16,14896,14897],{},"V-Model:"," Verification and validation model.",[73,14900,14901,14904],{},[16,14902,14903],{},"Iterative Model:"," Development in repetitive cycles.",[73,14906,14907,14910],{},[16,14908,14909],{},"Spiral Model:"," Combining iterative development with systematic aspects of the waterfall life cycle.",[73,14912,14913,14916],{},[16,14914,14915],{},"Agile Model:"," Promoting adaptive planning and flexible response to changes.",[12,14918,14919],{},"Each of these software development life cycle models offers unique benefits depending on the project's requirements and constraints.",[613,14921,14923],{"id":14922},"popular-sdlc-methodologies",[16,14924,14925],{},"Popular SDLC Methodologies",[12,14927,14928],{},"The most popular SDLC methodologies are:",[70,14930,14931,14937,14943],{},[73,14932,14933,14936],{},[16,14934,14935],{},"Agile SDLC:"," Focuses on iterative development and customer collaboration.",[73,14938,14939,14942],{},[16,14940,14941],{},"Waterfall Life Cycle:"," A sequential design process.",[73,14944,14945,14948],{},[16,14946,14947],{},"Lean Software Development:"," Emphasizes optimizing efficiency and eliminating waste.",[12,14950,14951],{},"Agile SDLC is widely used due to its specific advantages in different project environments.",[613,14953,14955],{"id":14954},"why-is-sdlc-important",[16,14956,14957],{},"Why is SDLC Important?",[12,14959,14960],{},"The SDLC is important because it provides a structured approach to software development, ensuring high quality and efficiency. It helps in managing complexity, minimizing risks, and improving project management and control. By following an SDLC, teams can produce software that is reliable, maintainable and meets the needs of stakeholders.",[613,14962,14964],{"id":14963},"how-the-sdlc-works",[16,14965,14966],{},"How the SDLC Works",[12,14968,14969],{},"The SDLC works by dividing the software development process into distinct phases, each with specific deliverables and objectives. This structured approach ensures that all aspects of development are addressed, from initial requirements to final deployment and maintenance. This leads to improved project outcomes, better-quality software, and greater user satisfaction.",[613,14971,14973],{"id":14972},"sdlc-tools-categories",[16,14974,14975],{},"SDLC Tools & Categories",[52,14977,14979],{"id":14978},"version-control-systems","Version Control Systems",[12,14981,14982],{},"Version control systems like GitHub, Azure DevOps, Bitbucket, and GitLab help manage changes to source code over time, allowing multiple developers to collaborate effectively.",[52,14984,14143],{"id":14142},[12,14986,14987],{},"Continuous Integration and Continuous Deployment (CI\u002FCD) tools like Jenkins, Azure Pipelines, GitLab CI, GitHub Actions, Octopus Deploy, and TeamCity automate the testing and deployment of code, ensuring rapid and reliable delivery.",[52,14989,14991],{"id":14990},"project-management-and-issue-tracking-tools","Project Management and Issue Tracking Tools",[12,14993,14994],{},"Tools like Jira and Azure Boards help teams plan, track, and manage software development projects and issues.",[52,14996,14998],{"id":14997},"code-quality-analysis-tools","Code Quality Analysis Tools",[12,15000,15001],{},"Tools like SonarQube and SonarCloud analyze code for quality and adherence to standards, helping to maintain high-quality codebases.",[52,15003,15005],{"id":15004},"security-analysis-tools","Security Analysis Tools",[12,15007,15008],{},"Security tools like Fortify and Veracode scan software for vulnerabilities, ensuring security is prioritized throughout the development lifecycle.",[52,15010,15012],{"id":15011},"testing-tools","Testing Tools",[12,15014,15015],{},"Automated testing tools like Testinium and Selenium ensure that software is thoroughly tested before release, catching bugs early in the development process.",[52,15017,15019],{"id":15018},"application-performance-monitoring-tools","Application Performance Monitoring Tools",[12,15021,15022],{},"Tools like New Relic, Sentry, Dynatrace, and Datadog monitor application performance in real time, providing insights into performance bottlenecks and user experience issues.",[52,15024,15026],{"id":15025},"incident-management-tools","Incident Management Tools",[12,15028,15029],{},"Tools like PagerDuty, OpsGenie, and ServiceNow help manage and respond to incidents quickly, minimizing downtime and maintaining service reliability.",[613,15031,15033],{"id":15032},"how-to-measure-sdlc-performance",[16,15034,15035],{},"How to Measure SDLC Performance",[12,15037,15038],{},"Measuring the performance of the SDLC involves tracking various metrics, such as:",[70,15040,15041,15046,15051,15057],{},[73,15042,15043,15045],{},[16,15044,13912],{}," The time it takes to complete one development cycle.",[73,15047,15048,15050],{},[16,15049,13918],{}," The time from feature request to delivery.",[73,15052,15053,15056],{},[16,15054,15055],{},"Defect Density:"," The number of defects per unit of code.",[73,15058,15059,15062],{},[16,15060,15061],{},"Customer Satisfaction:"," Feedback from end-users regarding the software.",[12,15064,15065],{},"By analyzing these metrics, organizations can identify areas for improvement and optimize their SDLC processes.",[613,15067,15069],{"id":15068},"oobeya-sdlc-tool-integrations",[16,15070,15071],{},"Oobeya SDLC Tool Integrations",[12,15073,15074,15075,15079],{},"Oobeya offers robust ",[514,15076,15078],{"href":12472,"rel":15077},[518],"SDLC tool integrations"," to streamline and enhance the development process. These integrations connect various tools and systems, providing a comprehensive view of your software development lifecycle.",[12,15081,15082,15088],{},[514,15083,15085],{"href":8313,"rel":15084},[518],[4866,15086],{"alt":15087,"src":14741},"Oobeya SDLC integrations"," Oobeya SDLC integrations",[613,15090,15092],{"id":15091},"optimize-the-sdlc-performance-with-oobeya",[16,15093,15094],{},"Optimize the SDLC Performance with Oobeya",[12,15096,15097,15098,15103],{},"Optimize your SDLC performance with Oobeya's innovative platform. By leveraging advanced analytics and integrations, Oobeya helps you identify bottlenecks, improve efficiency, and deliver high-quality software faster. Learn more about how Oobeya can ",[514,15099,15102],{"href":15100,"rel":15101},"https:\u002F\u002Foobeya.io\u002Foptimize-software-engineering",[518],"optimize your software engineering"," processes.",{"title":526,"searchDepth":527,"depth":527,"links":15105},[15106,15107,15108,15109,15110,15111,15112,15122,15123,15124],{"id":14813,"depth":527,"text":14816},{"id":14822,"depth":527,"text":14825},{"id":14878,"depth":527,"text":14881},{"id":14922,"depth":527,"text":14925},{"id":14954,"depth":527,"text":14957},{"id":14963,"depth":527,"text":14966},{"id":14972,"depth":527,"text":14975,"children":15113},[15114,15115,15116,15117,15118,15119,15120,15121],{"id":14978,"depth":530,"text":14979},{"id":14142,"depth":530,"text":14143},{"id":14990,"depth":530,"text":14991},{"id":14997,"depth":530,"text":14998},{"id":15004,"depth":530,"text":15005},{"id":15011,"depth":530,"text":15012},{"id":15018,"depth":530,"text":15019},{"id":15025,"depth":530,"text":15026},{"id":15032,"depth":527,"text":15035},{"id":15068,"depth":527,"text":15071},{"id":15091,"depth":527,"text":15094},[541],"2024-06-10","The Software Development Life Cycle (SDLC) is a structured process software developers use to design, develop, test, deliver, and maintain high quality...",{},"\u002Fblog\u002Fwhat-is-software-development-life-cycle-sdlc",{"title":14808,"description":15127},"blog\u002Fwhat-is-software-development-life-cycle-sdlc","HXZpujPFSpNsBHMKc1LSCULgbMvQzz03OIvyzhqApe4",{"id":15134,"title":15135,"author":4245,"avatar":575,"body":15136,"categories":15450,"createAt":542,"date":15451,"description":15452,"extension":545,"meta":15453,"navigation":547,"path":14597,"position":542,"seo":15454,"spotImage":542,"spotText":542,"stem":15455,"tags":542,"__hash__":15456},"blog\u002Fblog\u002Fwhat-is-a-pull-request-oobeya.md","What is a Pull Request?",{"type":9,"value":15137,"toc":15436},[15138,15141,15147,15150,15156,15159,15165,15168,15218,15224,15227,15259,15265,15267,15271,15273,15277,15279,15283,15285,15294,15298,15300,15304,15306,15310,15312,15317,15319,15323,15325,15329,15331,15335,15337,15341,15343,15347,15349,15358,15365,15367,15371,15373,15378,15385,15393,15395,15402,15404,15410,15412,15418,15420,15426,15429],[12,15139,15140],{},"In the world of software development, collaboration and code quality are paramount. Pull requests (PRs) are a key mechanism to achieve these goals, allowing developers to collaborate on code and ensure high standards before merging changes into the main codebase. But what exactly is a pull request?",[613,15142,15144],{"id":15143},"why-is-it-called-a-pull-request",[16,15145,15146],{},"Why is it Called a Pull Request?",[12,15148,15149],{},"A pull request is named as such because it involves pulling in changes from one branch to another. Essentially, when a developer finishes working on a feature or bug fix, they create a pull request to merge these changes from their feature branch into the main branch. This process involves code review and discussion, ensuring that the changes are vetted and agreed upon by the team.",[613,15151,15153],{"id":15152},"differences-between-pull-request-and-merge-request",[16,15154,15155],{},"Differences Between Pull Request and Merge Request",[12,15157,15158],{},"While pull request and merge request are often used interchangeably, there are subtle differences. A pull request is a term primarily used in GitHub, whereas a merge request is used in GitLab. Both serve the same purpose: to merge changes from one branch into another. However, the terminology can vary depending on the platform you use.",[613,15160,15162],{"id":15161},"how-to-create-a-pull-request",[16,15163,15164],{},"How to Create a Pull Request?",[12,15166,15167],{},"Creating a pull request involves several steps:",[1520,15169,15170,15176,15182,15188,15194,15200,15206,15212],{},[73,15171,15172,15175],{},[16,15173,15174],{},"Branching",": Start by creating a new branch for your feature or fix.",[73,15177,15178,15181],{},[16,15179,15180],{},"Commit Changes",": Make your changes and commit them to your branch.",[73,15183,15184,15187],{},[16,15185,15186],{},"Push to Remote",": Push your branch to the remote repository.",[73,15189,15190,15193],{},[16,15191,15192],{},"Open Pull Request",": Navigate to the repository on Git provider and open a new pull request.",[73,15195,15196,15199],{},[16,15197,15198],{},"Describe Your Changes",": Provide a clear description of what your pull request does.",[73,15201,15202,15205],{},[16,15203,15204],{},"Request Review",": Assign reviewers to get feedback on your code.",[73,15207,15208,15211],{},[16,15209,15210],{},"Address Feedback",": Make any necessary changes based on the feedback received.",[73,15213,15214,15217],{},[16,15215,15216],{},"Merge",": Once approved, merge the pull request into the main branch.",[613,15219,15221],{"id":15220},"pull-request-best-practices",[16,15222,15223],{},"Pull Request Best Practices",[12,15225,15226],{},"To make the most out of pull requests, follow these best practices:",[70,15228,15229,15235,15241,15247,15253],{},[73,15230,15231,15234],{},[16,15232,15233],{},"Small, Focused Changes",": Keep your pull requests small and focused on a single issue or feature.",[73,15236,15237,15240],{},[16,15238,15239],{},"Clear Descriptions",": Provide clear and detailed descriptions of what your pull request does.",[73,15242,15243,15246],{},[16,15244,15245],{},"Regular Updates",": Keep your branch up-to-date with the main branch to avoid merge conflicts.",[73,15248,15249,15252],{},[16,15250,15251],{},"Thorough Reviews",": Take the time to review the code thoroughly and provide constructive feedback.",[73,15254,15255,15258],{},[16,15256,15257],{},"Automated Checks",": Ensure your changes are covered by automated checks to catch issues early.",[613,15260,15262],{"id":15261},"pull-request-metrics-in-oobeya",[16,15263,15264],{},"Pull Request Metrics in Oobeya",[12,15266,10128],{},[4331,15268,15269],{"id":10131},[16,15270,10134],{},[12,15272,10137],{},[4331,15274,15275],{"id":10140},[16,15276,10143],{},[12,15278,10146],{},[4331,15280,15281],{"id":10149},[16,15282,10152],{},[12,15284,10155],{},[12,15286,15287,15293],{},[514,15288,15290],{"href":10160,"rel":15289},[518],[4866,15291],{"alt":10164,"src":15292},"\u002Fassets\u002Fblog\u002Foobeya-pull-request-1-1024x590.png"," Oobeya Pull Request Metrics",[4331,15295,15296],{"id":10170},[16,15297,10173],{},[12,15299,10176],{},[4331,15301,15302],{"id":10179},[16,15303,10182],{},[12,15305,10185],{},[4331,15307,15308],{"id":10188},[16,15309,10191],{},[12,15311,10194],{},[4331,15313,15314],{"id":10197},[16,15315,15316],{},"7. Work in Progress - Open PRs",[12,15318,10203],{},[4331,15320,15321],{"id":10206},[16,15322,10209],{},[12,15324,10212],{},[4331,15326,15327],{"id":10215},[16,15328,10218],{},[12,15330,10221],{},[4331,15332,15333],{"id":10224},[16,15334,10227],{},[12,15336,10230],{},[4331,15338,15339],{"id":10233},[16,15340,10236],{},[12,15342,10239],{},[4331,15344,15345],{"id":10242},[16,15346,10245],{},[12,15348,10248],{},[12,15350,15351,15357],{},[514,15352,15354],{"href":10160,"rel":15353},[518],[4866,15355],{"alt":10164,"src":15356},"\u002Fassets\u002Fblog\u002Foobeya-pull-request-2-1024x306.png"," Oobeya Pull Request Metrics - Risky PRs",[12,15359,15360,15361,15364],{},"By leveraging these metrics, Oobeya provides a detailed view of your pull request and code review processes, helping you identify inefficiencies and optimize your development workflow. Learn more about key Oobeya metrics on our ",[514,15362,10265],{"href":10263,"rel":15363},[518]," page.",[501,15366],{},[613,15368,15369],{"id":10271},[16,15370,10274],{},[12,15372,10277],{},[613,15374,15375],{"id":10280},[16,15376,15377],{},"Understanding Oobeya's Symptoms Catalog",[12,15379,15380,15384],{},[514,15381,15383],{"href":10288,"rel":15382},[518],"Oobeya's Symptoms Catalog"," is a powerful tool for diagnosing issues in the code review process. Here are some critical code review process symptoms to watch out for:",[12,15386,15387,10301],{},[514,15388,15390],{"href":10160,"rel":15389},[518],[4866,15391],{"alt":10299,"src":15392},"\u002Fassets\u002Fblog\u002Foobeya-pull-request-3-1024x715.png",[52,15394,10305],{"id":10304},[12,15396,15397,15398,15401],{},"Unreviewed pull requests can indicate bottlenecks in your review process. When pull requests sit unreviewed for extended periods, it can delay the integration of important changes and impact team productivity. This symptom highlights the need for a more streamlined review process, potentially involving more reviewers or better prioritization. ",[514,15399,10313],{"href":10311,"rel":15400},[518]," and learn more about this Symptom.",[52,15403,10318],{"id":10317},[12,15405,15406,15407,15401],{},"Lightning pull requests are those that are reviewed and merged extremely quickly. While speed can be beneficial, overly rapid reviews may suggest superficial reviews, increasing the risk of undetected issues. Ensuring thorough reviews, even for smaller changes, is crucial for maintaining code quality. ",[514,15408,10313],{"href":10324,"rel":15409},[518],[52,15411,10329],{"id":10328},[12,15413,15414,15415,15401],{},"Oversize pull requests involve a large number of changes, making them difficult to review effectively. They can overwhelm reviewers, leading to delays and potentially missed issues. Breaking down large changes into smaller, more manageable pull requests can improve review quality and efficiency. ",[514,15416,10313],{"href":10335,"rel":15417},[518],[52,15419,10340],{"id":10339},[12,15421,15422,15423,15401],{},"High code review times can signal inefficiencies in the review process. Prolonged review times might be due to complex changes, insufficient reviewer availability, or unclear code. Identifying the root causes and addressing them, such as by increasing reviewer availability or improving code documentation, can help reduce review times. ",[514,15424,10313],{"href":10346,"rel":15425},[518],[12,15427,15428],{},"By leveraging these insights from Oobeya's Symptoms Catalog, you can enhance your code review process, ensuring a more efficient and effective workflow.",[3354,15430,15431],{},[12,15432,15433,10360],{},[514,15434,10359],{"href":10357,"rel":15435},[518],{"title":526,"searchDepth":527,"depth":527,"links":15437},[15438,15439,15440,15441,15442,15443,15444],{"id":15143,"depth":527,"text":15146},{"id":15152,"depth":527,"text":15155},{"id":15161,"depth":527,"text":15164},{"id":15220,"depth":527,"text":15223},{"id":15261,"depth":527,"text":15264},{"id":10271,"depth":527,"text":10274},{"id":10280,"depth":527,"text":15377,"children":15445},[15446,15447,15448,15449],{"id":10304,"depth":530,"text":10305},{"id":10317,"depth":530,"text":10318},{"id":10328,"depth":530,"text":10329},{"id":10339,"depth":530,"text":10340},[541,7371],"2024-06-04","In the world of software development, collaboration and code quality are paramount. Pull requests (PRs) are a key mechanism to achieve these goals,...",{},{"title":15135,"description":15452},"blog\u002Fwhat-is-a-pull-request-oobeya","iLiVYMZA47lSzMKNL4bdFnJJ3pQYro8wi8PN9UZi1Ag",{"id":15458,"title":11497,"author":4245,"avatar":575,"body":15459,"categories":15642,"createAt":542,"date":15643,"description":15644,"extension":545,"meta":15645,"navigation":547,"path":15646,"position":542,"seo":15647,"spotImage":542,"spotText":542,"stem":15648,"tags":542,"__hash__":15649},"blog\u002Fblog\u002Fwhat-are-the-key-devops-metrics.md",{"type":9,"value":15460,"toc":15632},[15461,15464,15468,15471,15475,15478,15482,15485,15496,15502,15506,15509,15513,15516,15520,15523,15527,15606,15618,15622,15625],[12,15462,15463],{},"DevOps metrics provide valuable insights into the performance and efficiency of your development, DevOps, and Platform Engineering teams. By leveraging these metrics, organizations can identify areas for improvement, streamline workflows, and deliver high-quality software faster. In this blog post, we will explore the key DevOps metrics that every team should monitor, explain why they are important, and demonstrate how the Oobeya Software Engineering Intelligence Platform can help you elevate your DevOps performance.",[613,15465,15467],{"id":15466},"what-are-devops-metrics","What Are DevOps Metrics?",[12,15469,15470],{},"DevOps metrics are quantitative measures that help teams understand the effectiveness and efficiency of their software development and delivery processes. These metrics provide insights into various aspects of the DevOps lifecycle, enabling teams to make data-driven decisions to improve their workflows.",[613,15472,15474],{"id":15473},"why-are-devops-metrics-important","Why Are DevOps Metrics Important?",[12,15476,15477],{},"DevOps metrics are crucial because they help teams identify bottlenecks, track value delivery performance, and ensure continuous improvement. By monitoring these metrics, organizations can achieve higher efficiency, better quality software, and faster delivery times. Furthermore, DevOps metrics help in aligning development, DevOps, and Platform Engineering teams with business goals, promoting a culture of collaboration and transparency.",[613,15479,15481],{"id":15480},"what-are-the-4-key-metrics-in-devops","What are the 4 Key Metrics in DevOps?",[12,15483,15484],{},"The DevOps Research and Assessment (DORA) team has identified four key metrics that are critical for evaluating DevOps performance. These metrics provide a comprehensive view of the software delivery process and are essential for continuous improvement.",[1520,15486,15487,15489,15491,15493],{},[73,15488,825],{},[73,15490,835],{},[73,15492,859],{},[73,15494,15495],{},"Mean Time to Restore Service (MTTR)",[12,15497,15498,15501],{},[4866,15499],{"alt":15500,"src":11267,"title":15500},"DORA Metrics in Oobeya"," DORA Metrics in Oobeya",[613,15503,15505],{"id":15504},"what-is-deployment-frequency","What is Deployment Frequency?",[12,15507,15508],{},"Deployment Frequency measures how often new releases are deployed to production. It reflects the agility of the development process. High deployment frequency indicates that the team can deliver new features, fixes, and improvements quickly, responding rapidly to market demands and user feedback.",[613,15510,15512],{"id":15511},"what-is-lead-time-for-changes","What is Lead Time for Changes?",[12,15514,15515],{},"Lead Time for Changes is the time it takes from committing a change to deploying it into production. This metric highlights the efficiency of the development and deployment processes. Shorter lead times mean faster delivery of value to customers, allowing the organization to stay competitive.",[613,15517,15518],{"id":12306},[514,15519,12309],{"href":11005},[12,15521,15522],{},"Change Failure Rate measures the percentage of changes that result in a failure in production, such as service outages or degraded service. This metric is crucial for understanding the stability and reliability of the deployment process. A lower change failure rate indicates a more stable and reliable system.",[613,15524,15526],{"id":15525},"key-devops-metrics-for-success","Key DevOps Metrics For Success",[1520,15528,15529,15535,15541,15547,15553,15558,15564,15570,15576,15582,15588,15594,15600],{},[73,15530,15531,15534],{},[16,15532,15533],{},"Deployment Frequency (DORA)",": The number of deployments to production in a given time period. It indicates how often the team deploys code and a measure of development agility.",[73,15536,15537,15540],{},[16,15538,15539],{},"Lead Time for Changes (DORA)",": The amount of time it takes for a code commit to get into production. This metric highlights the efficiency of the deployment pipeline.",[73,15542,15543,15546],{},[16,15544,15545],{},"Mean Time to Restore Service (DORA)",": The average time it takes to restore service after an incident. It reflects the team’s ability to respond to and recover from failures.",[73,15548,15549,15552],{},[16,15550,15551],{},"Change Failure Rate (DORA)",": The percentage of deployments that cause a failure in production. This metric indicates the reliability of the deployment process.",[73,15554,15555,15557],{},[16,15556,807],{},": The total time from the start of development work on a feature or bug fix until it is deployed to production. It includes both lead time for changes and any additional delays.",[73,15559,15560,15563],{},[16,15561,15562],{},"Deployment Time",": The time it takes to deploy a release to production once it is ready for deployment. This can include automated and manual deployment steps.",[73,15565,15566,15569],{},[16,15567,15568],{},"Change Volume \u002F Deployment Size",": The amount of code changes in a single deployment. This metric helps in understanding the scope of changes being made in each deployment.",[73,15571,15572,15575],{},[16,15573,15574],{},"Pipeline Failures",": The number of failures that occur in the CI\u002FCD pipeline. Monitoring pipeline failures helps in identifying and addressing issues in the automation process.",[73,15577,15578,15581],{},[16,15579,15580],{},"Mean Time Between Pipeline Failures",": The average time between successive failures in the CI\u002FCD pipeline. This metric helps in understanding the reliability of the pipeline.",[73,15583,15584,15587],{},[16,15585,15586],{},"Availability",": The percentage of time the system is operational and available for use. High availability is critical for user satisfaction and business continuity.",[73,15589,15590,15593],{},[16,15591,15592],{},"Average Response Time",": The average time it takes for the system to respond to a request. This metric is crucial for understanding the performance and user experience of the application.",[73,15595,15596,15599],{},[16,15597,15598],{},"Apdex Score",": A standardized metric that measures user satisfaction based on response times. It provides a clear view of how users perceive the performance of the application.",[73,15601,15602,15605],{},[16,15603,15604],{},"Error Rates",": The frequency of errors occurring in the system. Monitoring error rates helps in identifying stability issues and areas that need improvement.",[12,15607,15608,15609,15613,15614,611],{},"To learn more about the key DevOps metrics, check out our ",[514,15610,15612],{"href":7188,"rel":15611},[518],"DORA metrics guide",". For a comprehensive understanding of various metrics, visit our ",[514,15615,15617],{"href":10263,"rel":15616},[518],"Oobeya metric definitions",[613,15619,15621],{"id":15620},"how-oobeya-can-level-up-your-devops-performance","How Oobeya Can Level Up Your DevOps Performance",[12,15623,15624],{},"Oobeya provides a comprehensive platform to track and analyze these key DevOps metrics, along with many others. With Oobeya, teams can gain deeper insights into their DevOps processes, identify areas for improvement, and drive continuous improvement. Oobeya's intuitive dashboards and detailed reports make it easy to monitor delivery performance and make data-driven decisions.",[3354,15626,15627],{},[12,15628,15629,14493],{},[514,15630,10359],{"href":10160,"rel":15631},[518],{"title":526,"searchDepth":527,"depth":527,"links":15633},[15634,15635,15636,15637,15638,15639,15640,15641],{"id":15466,"depth":527,"text":15467},{"id":15473,"depth":527,"text":15474},{"id":15480,"depth":527,"text":15481},{"id":15504,"depth":527,"text":15505},{"id":15511,"depth":527,"text":15512},{"id":12306,"depth":527,"text":12309},{"id":15525,"depth":527,"text":15526},{"id":15620,"depth":527,"text":15621},[1232,541],"2024-05-31","DevOps metrics provide valuable insights into the performance and efficiency of your development, DevOps, and Platform Engineering teams. By leveraging...",{},"\u002Fblog\u002Fwhat-are-the-key-devops-metrics",{"title":11497,"description":15644},"blog\u002Fwhat-are-the-key-devops-metrics","snTJwMwb1yHQ49yQfv9p_MpAVHRKaY9BVcIcuaLj5Ew",{"id":15651,"title":11503,"author":4245,"avatar":575,"body":15652,"categories":15855,"createAt":542,"date":15856,"description":15857,"extension":545,"meta":15858,"navigation":547,"path":15859,"position":542,"seo":15860,"spotImage":542,"spotText":542,"stem":15861,"tags":542,"__hash__":15862},"blog\u002Fblog\u002Fhow-to-calculate-cycle-time.md",{"type":9,"value":15653,"toc":15847},[15654,15658,15661,15665,15668,15693,15697,15700,15714,15717,15724,15728,15731,15757,15760,15764,15767,15792,15796,15799,15825,15837,15844],[613,15655,15657],{"id":15656},"what-is-cycle-time","What is Cycle Time?",[12,15659,15660],{},"Cycle time is a crucial metric in software development, measuring the time taken from the start of work on an item (such as a story, task, or bug) until it is ready for delivery. Knowing how to calculate cycle time provides valuable insights into the efficiency and productivity of your development process. By understanding cycle time, teams can gain a better perspective on their workflow, identify areas that need improvement, and ultimately deliver higher quality software faster.",[613,15662,15664],{"id":15663},"why-is-cycle-time-important","Why is Cycle Time Important?",[12,15666,15667],{},"Understanding and optimizing cycle time is vital for several reasons:",[1520,15669,15670,15676,15682,15687],{},[73,15671,15672,15675],{},[16,15673,15674],{},"Efficiency",": It helps identify bottlenecks and inefficiencies in the development process. When you can pinpoint where delays are occurring, you can take targeted actions to streamline your workflow.",[73,15677,15678,15681],{},[16,15679,15680],{},"Predictability",": It improves the predictability of delivery timelines. Accurate cycle time metrics enable teams to forecast delivery dates more reliably, enhancing planning and stakeholder confidence.",[73,15683,15684,15686],{},[16,15685,11167],{},": It supports continuous improvement by highlighting areas for process enhancements. Regularly monitoring cycle time can reveal trends and opportunities for making incremental changes that boost overall productivity.",[73,15688,15689,15692],{},[16,15690,15691],{},"Customer Satisfaction",": Faster delivery of high-quality software leads to increased customer satisfaction. Shorter cycle times mean that customers receive updates and new features more quickly, keeping them engaged and satisfied with the product.",[613,15694,15696],{"id":15695},"how-do-you-calculate-cycle-time","How Do You Calculate Cycle Time?",[12,15698,15699],{},"Cycle time can be calculated using the following steps:",[1520,15701,15702,15708],{},[73,15703,15704,15707],{},[16,15705,15706],{},"Identify the Start and End Points",": Determine when work starts (work in progress) and when it is completed (ready for delivery). This involves clearly defining the status changes that mark these points.",[73,15709,15710,15713],{},[16,15711,15712],{},"Measure the Time Taken",": Calculate the duration between these two points. This can be done manually or using software tools that track and record these times automatically.",[12,15715,15716],{},"In the Oobeya platform, cycle time is calculated within the Agile analytics module (AgileSpace) by connecting to tools like Jira Server, Jira Data Center, Jira Cloud, and Azure Boards. Oobeya calculates cycle time for each task or issue, highlighting the highest and lowest cycle times. Additionally, Oobeya provides comprehensive metrics that include Reaction Time and Lead Time, offering a more detailed view of the overall process efficiency.",[12,15718,15719,15723],{},[4866,15720],{"alt":15721,"src":15722},"Oobeya Cycle Time","\u002Fassets\u002Fblog\u002Foobeya-cycle-time-1024x531.png"," Oobeya Cycle Time",[613,15725,15727],{"id":15726},"what-are-the-key-components-of-cycle-time","What Are the Key Components of Cycle Time?",[12,15729,15730],{},"Understanding the key components of cycle time is essential for accurately measuring and improving your software development process. The primary components include:",[1520,15732,15733,15739,15745,15751],{},[73,15734,15735,15738],{},[16,15736,15737],{},"Coding Time",": This is the period during which developers actively write code for a task or issue. It begins when a developer starts working on the coding task and ends when the code is ready for review. Efficient coding practices and clear requirements can help reduce coding time.",[73,15740,15741,15744],{},[16,15742,15743],{},"Code Review Time",": Once the coding is complete, the code enters the review stage. During this process, team members review the code for quality, adherence to standards, and potential issues. The time taken for reviews can vary depending on the complexity of the code and the thoroughness of the review process. Effective code review practices can help streamline this component.",[73,15746,15747,15750],{},[16,15748,15749],{},"Continuous Integration Process",": After, or as part of, the code review process, the other step is integration into the main code base. Continuous integration (CI) involves automatically building and testing the code to ensure that it integrates smoothly with the existing codebase. The length of this process depends on the efficiency of the CI tools and the complexity of the integration tasks.",[73,15752,15753,15756],{},[16,15754,15755],{},"Testing and Validation Process",": The final component is the testing and validation process, where the integrated code is thoroughly tested to identify and fix any bugs or issues. This includes various testing stages such as unit testing, integration testing, and user acceptance testing. Efficient testing strategies and automation can significantly reduce the time required for this component.",[12,15758,15759],{},"By focusing on these key components and continuously seeking improvements, teams can effectively reduce cycle time and enhance overall productivity.",[613,15761,15763],{"id":15762},"what-are-common-challenges-in-calculating-cycle-time","What Are Common Challenges in Calculating Cycle Time?",[12,15765,15766],{},"Some common challenges include:",[1520,15768,15769,15775,15780,15786],{},[73,15770,15771,15774],{},[16,15772,15773],{},"Data Accuracy",": Ensuring that start and end times are accurately recorded. Inaccurate data can lead to misleading cycle time calculations, affecting decision-making.",[73,15776,15777,15779],{},[16,15778,11126],{},": Seamlessly integrating with various project management tools. Different tools may have different ways of tracking time, making it challenging to consolidate data.",[73,15781,15782,15785],{},[16,15783,15784],{},"Consistent Definitions",": Maintaining consistent definitions of cycle time across teams. Without a shared understanding, comparing metrics between teams can be difficult.",[73,15787,15788,15791],{},[16,15789,15790],{},"Handling Exceptions",": Managing outliers and exceptional cases that can skew average cycle times. Special cases, such as particularly complex tasks, need to be handled separately to avoid distorting overall metrics.",[613,15793,15795],{"id":15794},"how-can-you-reduce-cycle-time","How Can You Reduce Cycle Time?",[12,15797,15798],{},"To reduce cycle time, consider the following strategies:",[1520,15800,15801,15807,15813,15819],{},[73,15802,15803,15806],{},[16,15804,15805],{},"Streamline Processes",": Simplify and automate workflows to eliminate unnecessary steps. Automation can significantly reduce the time spent on repetitive tasks.",[73,15808,15809,15812],{},[16,15810,15811],{},"Improve Communication",": Enhance team communication and collaboration to resolve issues faster. Clear and open communication channels can help prevent misunderstandings and delays.",[73,15814,15815,15818],{},[16,15816,15817],{},"Identify Bottlenecks",": Use data to identify and address bottlenecks in the development process. Regularly reviewing cycle time metrics can help pinpoint specific stages where delays occur.",[73,15820,15821,15824],{},[16,15822,15823],{},"Prioritize Tasks",": Focus on high-priority tasks to reduce waiting times and delays. Prioritizing work based on urgency and importance can help ensure that critical tasks are completed more quickly.",[12,15826,15827,15828,15831,15832,15836],{},"For a deeper understanding of cycle time and other key metrics, refer to our ",[514,15829,10265],{"href":10263,"rel":15830},[518]," and learn how to ",[514,15833,15835],{"href":12016,"rel":15834},[518],"Optimize Software Engineering"," with Oobeya.",[12,15838,15839,15840,15843],{},"The Oobeya platform, featured in the ",[514,15841,12949],{"href":12947,"rel":15842},[518]," for Software Engineering Intelligence Platforms, provides comprehensive insights into software development processes. It serves as a single source of truth for engineering data, offering a unified, comprehensive, and transparent view of engineering processes. By using Oobeya, teams can better understand how software solutions are built and delivered, see where they are spending time, and improve team flow through key metrics like DORA metrics and cycle time.",[12,15845,15846],{},"By leveraging these engineering insights, you can optimize software development processes, improve efficiency, and deliver higher quality software faster.",{"title":526,"searchDepth":527,"depth":527,"links":15848},[15849,15850,15851,15852,15853,15854],{"id":15656,"depth":527,"text":15657},{"id":15663,"depth":527,"text":15664},{"id":15695,"depth":527,"text":15696},{"id":15726,"depth":527,"text":15727},{"id":15762,"depth":527,"text":15763},{"id":15794,"depth":527,"text":15795},[1232,541],"2024-05-29","Cycle time is a crucial metric in software development, measuring the time taken from the start of work on an item (such as a story, task, or bug)...",{},"\u002Fblog\u002Fhow-to-calculate-cycle-time",{"title":11503,"description":15857},"blog\u002Fhow-to-calculate-cycle-time","AHMH8Q1OcAXLG2uHtl0khxxXZwfpmCMvZ1zbN0ouVGU",{"id":15864,"title":15865,"author":4245,"avatar":575,"body":15866,"categories":16221,"createAt":542,"date":16222,"description":16223,"extension":545,"meta":16224,"navigation":547,"path":16225,"position":4134,"seo":16226,"spotImage":542,"spotText":542,"stem":16227,"tags":16228,"__hash__":16229},"blog\u002Fblog\u002Fadvanced-devops-insights-oobeyas-guide-to-azure-devops-dora-metrics.md","Advanced DevOps Insights: Oobeya’s Guide to Azure DevOps DORA Metrics",{"type":9,"value":15867,"toc":16198},[15868,15871,15877,15880,15906,15915,15919,15938,15944,15947,15973,15975,15981,15984,16032,16034,16040,16044,16052,16056,16059,16063,16066,16068,16074,16078,16081,16101,16105,16108,16128,16135,16141,16145,16148,16152,16155,16159,16162,16166,16187,16191],[12,15869,15870],{},"For modern software teams, data-driven decision-making is the cornerstone of achieving engineering excellence. By integrating the Oobeya Software Engineering Intelligence Platform with Microsoft Azure DevOps, you can seamlessly measure DORA metrics and other key engineering metrics, and enhance your team performance and well-being. Whether you are an engineering manager, a DevOps enthusiast, a Platform Engineer, or a development team lead, this integration simplifies tracking and improving your software delivery performance.",[613,15872,15874],{"id":15873},"the-importance-of-tracking-azure-devops-dora-metrics",[16,15875,15876],{},"The Importance of Tracking Azure DevOps DORA Metrics",[12,15878,15879],{},"DORA (DevOps Research and Assessment) metrics are vital indicators of an organization's software delivery performance. They include:",[70,15881,15882,15888,15893,15900],{},[73,15883,15884,15887],{},[16,15885,15886],{},"Deployment Frequency:"," How often an organization successfully releases to production.",[73,15889,15890,15892],{},[16,15891,5819],{}," The time it takes for a commit to get into production.",[73,15894,15895,15899],{},[16,15896,15897,3444],{},[514,15898,900],{"href":11527}," The time it takes to recover from a failure in production.",[73,15901,15902,15905],{},[16,15903,15904],{},"Change Failure Rate:"," The percentage of deployments causing a failure in production.",[12,15907,15908,15914],{},[514,15909,15911],{"href":10160,"rel":15910},[518],[4866,15912],{"alt":15913,"src":11267},"Oobeya Azure DevOps DORA Metrics"," Oobeya Azure DevOps DORA Metrics",[52,15916,15918],{"id":15917},"why-dora-metrics-matter","Why DORA Metrics Matter",[1520,15920,15921,15926,15932],{},[73,15922,15923,15925],{},[16,15924,11380],{}," By tracking these metrics, teams can identify bottlenecks, streamline processes, and continuously improve their delivery cycles.",[73,15927,15928,15931],{},[16,15929,15930],{},"Business Impact:"," Faster and more reliable delivery can lead to a competitive advantage, improved customer satisfaction, and higher business agility.",[73,15933,15934,15937],{},[16,15935,15936],{},"Team Performance:"," Understanding these metrics helps in gauging team performance and providing actionable insights to enhance productivity and efficiency.",[613,15939,15941],{"id":15940},"visibility-into-engineering-flow-why-it-matters",[16,15942,15943],{},"Visibility into Engineering Flow: Why It Matters",[12,15945,15946],{},"Engineering teams need visibility into their flow to ensure smooth operations and high-quality outcomes. Here’s why visibility is crucial:",[1520,15948,15949,15955,15961,15967],{},[73,15950,15951,15954],{},[16,15952,15953],{},"Identify Bottlenecks:"," Clear visibility helps in pinpointing stages where delays occur, enabling teams to address and resolve issues promptly.",[73,15956,15957,15960],{},[16,15958,15959],{},"Optimize Processes:"," With a transparent view of workflows, teams can optimize processes for better efficiency and reduced waste.",[73,15962,15963,15966],{},[16,15964,15965],{},"Enhance Collaboration:"," Visibility fosters better communication and collaboration among team members, ensuring everyone is on the same page.",[73,15968,15969,15972],{},[16,15970,15971],{},"Boost Morale:"," When teams see the direct impact of their work on project success, it boosts morale and motivation.",[501,15974],{},[613,15976,15978],{"id":15977},"oobeya-a-strong-partner-of-the-azure-devops-ecosystem",[16,15979,15980],{},"Oobeya: A Strong Partner of the Azure DevOps Ecosystem",[12,15982,15983],{},"Oobeya is a powerful ally for organizations using Azure DevOps. By integrating with Azure DevOps, Oobeya enhances your ability to track and improve engineering performance through comprehensive metrics and insights. Here’s why Oobeya stands out:",[1520,15985,15986,15992,15998,16014,16020,16026],{},[73,15987,15988,15991],{},[16,15989,15990],{},"Seamless Integration:"," Oobeya connects effortlessly with Azure DevOps, allowing you to integrate your repositories, pipelines, releases, and boards in minutes by generating one access token (only read permissions for selected scopes are required).",[73,15993,15994,15997],{},[16,15995,15996],{},"Robust Metrics:"," Oobeya provides accurate DORA metrics and other key metrics, helping you make data-driven decisions.",[73,15999,16000,16003,16004,16008,16009,16011,16013],{},[16,16001,16002],{},"Aligning with the SPACE Framework:"," Oobeya automatically detects the symptoms of inefficiencies and bottlenecks within the software development and delivery processes, offering a detailed ",[514,16005,16007],{"href":10288,"rel":16006},[518],"symptoms catalog"," that resonates with SPACE dimensions. Oobeya provides actionable insights into Satisfaction and well-being, Performance, Activity, Communication and collaboration, Efficiency and flow.",[4531,16010],{},[4866,16012],{"alt":12132,"src":11853}," Oobeya Symptoms",[73,16015,16016,16019],{},[16,16017,16018],{},"Customization:"," Tailor your integration by selecting specific pipelines, stages, environments, release strategies (git-flow, long-lived branches, git tags), and development practices (trunk-based or pull-request-based) to suit your organization’s needs.",[73,16021,16022,16025],{},[16,16023,16024],{},"Comprehensive Reporting:"," Gain deep insights through advanced reporting features, helping you analyze and improve every aspect of your development process on a multi-dimensional level.",[73,16027,16028,16031],{},[16,16029,16030],{},"ADO Version Support:"," Oobeya supports both Azure DevOps Cloud and Server environments, ensuring compatibility across different setups.",[501,16033],{},[613,16035,16037],{"id":16036},"getting-started-a-comprehensive-guide",[16,16038,16039],{},"Getting Started: A Comprehensive Guide",[52,16041,16043],{"id":16042},"step-1-provide-an-azure-devops-token","Step 1: Provide an Azure DevOps Token",[12,16045,16046,16047],{},"To begin, generate an Azure DevOps (ADO) personal access token. This token allows Oobeya to access your repositories, pipelines, pull requests, and work items. Oobeya integration requires only read permissions for the selected scopes. ",[514,16048,16051],{"href":16049,"rel":16050},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fall-integrations\u002Fscm-addons\u002Fazure-devops-integration",[518],"Learn more about Azure DevOps & Oobeya Integration",[52,16053,16055],{"id":16054},"step-2-connect-your-accounts","Step 2: Connect Your Accounts",[12,16057,16058],{},"Link your Oobeya account to your Azure DevOps environment. This process is straightforward and can be completed in minutes.",[52,16060,16062],{"id":16061},"step-3-start-analyzing-your-data","Step 3: Start Analyzing Your Data",[12,16064,16065],{},"Choose your repositories and pipelines to analyze. Specify your release strategy and development practices to ensure accurate metrics.",[501,16067],{},[613,16069,16071],{"id":16070},"advanced-features-of-oobeya-and-azure-devops-integration",[16,16072,16073],{},"Advanced Features of Oobeya and Azure DevOps Integration",[52,16075,16077],{"id":16076},"_1-comprehensive-azure-devops-dora-metrics-measurement-for-different-workflows-and-practices","1. Comprehensive Azure DevOps DORA Metrics Measurement For Different Workflows And Practices",[12,16079,16080],{},"Oobeya enables you to:",[70,16082,16083,16089,16095],{},[73,16084,16085,16088],{},[16,16086,16087],{},"Add Multiple Deployment Pipelines:"," Aggregate DORA metrics across multiple deployment pipelines within a single repository. (If you have a repository and multiple delivery pipelines linked to it.)",[73,16090,16091,16094],{},[16,16092,16093],{},"Select Pipelines from Different Projects:"," Fine-tune DORA metrics calculation by selecting pipelines and releases from different projects. (If you manage pipeline definitions and runs in a different Azure DevOps project.)",[73,16096,16097,16100],{},[16,16098,16099],{},"Support Various Release and Development Strategies:"," Measure DORA metrics accurately whether you use Gitflow, long-lived branches, or Git tags. Specify whether your team follows a trunk-based or pull-request-driven development practice.",[52,16102,16104],{"id":16103},"_2-advanced-data-analytics-and-reporting","2. Advanced Data Analytics and Reporting",[12,16106,16107],{},"With Oobeya, you can:",[70,16109,16110,16116,16122],{},[73,16111,16112,16115],{},[16,16113,16114],{},"Analyze Coding, Code Review, and Delivery Activities:"," Generate insightful reports by analyzing repositories, commits, pull requests, and delivery pipelines across the Azure DevOps workflow.",[73,16117,16118,16121],{},[16,16119,16120],{},"Analyze Agile Boards:"," Generate insightful reports by analyzing scrum and kanban boards from Azure Boards.",[73,16123,16124,16127],{},[16,16125,16126],{},"Group Analysis Results:"," View all metrics at various levels, including repository, product, team, and organization. (Note that Oobeya is a team-focused platform.)",[12,16129,16130,16134],{},[4866,16131],{"alt":16132,"src":16133},"Oobeya Team Scorecard Metrics","\u002Fassets\u002Fblog\u002Foobeya-team-scorecard-1024x610.jpg"," Oobeya Team Scorecard Metrics",[613,16136,16138],{"id":16137},"additional-integrations-and-features",[16,16139,16140],{},"Additional Integrations and Features",[52,16142,16144],{"id":16143},"azure-devops-cloud-and-server-support","Azure DevOps Cloud and Server Support",[12,16146,16147],{},"Oobeya supports both Azure DevOps Cloud and Server environments, ensuring flexibility for different organizational setups.",[52,16149,16151],{"id":16150},"comprehensive-module-compatibility","Comprehensive Module Compatibility",[12,16153,16154],{},"The platform works seamlessly with Azure DevOps Repos, Azure Boards, Pipelines, and Releases modules.",[52,16156,16158],{"id":16157},"microsoft-entra-azure-ad-integration","Microsoft Entra (Azure AD) Integration",[12,16160,16161],{},"For enhanced security and streamlined user management, Oobeya integrates with Microsoft Entra (Azure AD). This enables single sign-on (SSO) and robust authentication settings.",[52,16163,16165],{"id":16164},"resources-to-get-you-started","Resources to Get You Started",[70,16167,16168,16173,16180],{},[73,16169,16170],{},[514,16171,16051],{"href":16049,"rel":16172},[518],[73,16174,16175],{},[514,16176,16179],{"href":16177,"rel":16178},"https:\u002F\u002Fdocs.oobeya.io\u002Fdeployment-analytics\u002Fhow-to-calculate-dora-metrics-for-azure-devops",[518],"How To Measure DORA Metrics for Azure DevOps",[73,16181,16182],{},[514,16183,16186],{"href":16184,"rel":16185},"https:\u002F\u002Fdocs.oobeya.io\u002Fadministration\u002Fuser-management-single-sign-on-auth-settings\u002Fazure-ad-integration",[518],"Azure AD Integration",[613,16188,16189],{"id":477},[16,16190,1159],{},[12,16192,16193,16194,16197],{},"Integrating Oobeya with Azure DevOps transforms how you measure and improve your software engineering performance. With robust support for DORA metrics, customizable analytics, and comprehensive reporting, Oobeya empowers your team to achieve new levels of efficiency and reliability. ",[514,16195,12959],{"href":10160,"rel":16196},[518]," and unlock the full potential of your software development and delivery process.",{"title":526,"searchDepth":527,"depth":527,"links":16199},[16200,16203,16204,16205,16210,16214,16220],{"id":15873,"depth":527,"text":15876,"children":16201},[16202],{"id":15917,"depth":530,"text":15918},{"id":15940,"depth":527,"text":15943},{"id":15977,"depth":527,"text":15980},{"id":16036,"depth":527,"text":16039,"children":16206},[16207,16208,16209],{"id":16042,"depth":530,"text":16043},{"id":16054,"depth":530,"text":16055},{"id":16061,"depth":530,"text":16062},{"id":16070,"depth":527,"text":16073,"children":16211},[16212,16213],{"id":16076,"depth":530,"text":16077},{"id":16103,"depth":530,"text":16104},{"id":16137,"depth":527,"text":16140,"children":16215},[16216,16217,16218,16219],{"id":16143,"depth":530,"text":16144},{"id":16150,"depth":530,"text":16151},{"id":16157,"depth":530,"text":16158},{"id":16164,"depth":530,"text":16165},{"id":477,"depth":527,"text":1159},[10390,541],"2024-05-21","For modern software teams, data driven decision making is the cornerstone of achieving engineering excellence. By integrating the Oobeya Software...",{},"\u002Fblog\u002Fadvanced-devops-insights-oobeyas-guide-to-azure-devops-dora-metrics",{"title":15865,"description":16223},"blog\u002Fadvanced-devops-insights-oobeyas-guide-to-azure-devops-dora-metrics",[8440,696,9227],"CjifWpko848nAiDsmUAoHCC_03Cyifva0UgqqDc10k8",{"id":16231,"title":16232,"author":542,"avatar":542,"body":16233,"categories":16553,"createAt":542,"date":16554,"description":16555,"extension":545,"meta":16556,"navigation":547,"path":8167,"position":542,"seo":16557,"spotImage":542,"spotText":542,"stem":16558,"tags":542,"__hash__":16559},"blog\u002Fblog\u002Ftop-5-tools-for-engineering-managers-in-2024.md","Identify Productivity Eaters: Top 5 Tools For Engineering Managers In 2024",{"type":9,"value":16234,"toc":16534},[16235,16238,16244,16247,16250,16256,16261,16264,16266,16291,16298,16305,16311,16316,16319,16322,16351,16357,16364,16370,16375,16381,16384,16410,16417,16423,16428,16434,16437,16463,16470,16476,16481,16487,16490,16515,16522,16528,16531],[12,16236,16237],{},"Engineering managers are continually seeking the best tools to enhance team productivity, streamline processes, and maintain code quality. With a myriad of options available, it can be challenging to identify which tools truly stand out. This post highlights five standout tools that every engineering manager should consider integrating into their workflow.",[613,16239,16241],{"id":16240},"why-i-wrote-this-blog-post",[16,16242,16243],{},"Why I Wrote This Blog Post",[12,16245,16246],{},"I often hear the question, “What are tools I can use as an Engineering Manager?” so here is a post answering this question. I frequently talk to engineering managers and listen to their requirements and experiences with tools. I also check the pulse of the market and try new tools as a product leader in this field.",[12,16248,16249],{},"Before diving into the list, I want to clarify a few points about its creation. This list excludes tools commonly used by teams, such as Jira, Linear, Git tools, and Slack. Instead, I've highlighted the most innovative and exceptional tools across various categories like employee experience, engineering intelligence, code quality, security, and team collaboration. This article is not driven by any hype.",[613,16251,16253],{"id":16252},"_1-packmind-collaboration",[16,16254,16255],{},"1. Packmind (Collaboration)",[3354,16257,16258],{},[12,16259,16260],{},"Amplify knowledge improve engineering performance: Accelerate your team skill growth and improve coding standards by intelligently integrating the best coding practices directly within your familiar coding places and tailored to your unique context.",[12,16262,16263],{},"Packmind is a standout tool for enhancing collaboration and knowledge sharing within engineering teams. It offers a comprehensive approach to embedding coding standards and best practices directly into your workflow.",[52,16265,7627],{"id":7626},[70,16267,16268,16274,16279,16285],{},[73,16269,16270,16273],{},[16,16271,16272],{},"Coding Standards:"," Automatically scans your repository to identify good coding standards and problematic patterns.",[73,16275,16276,16278],{},[16,16277,12234],{}," Provides a comprehensive set of best coding practices based on clean code principles.",[73,16280,16281,16284],{},[16,16282,16283],{},"Onboarding:"," Effortlessly onboard new developers on your coding standards.",[73,16286,16287,16290],{},[16,16288,16289],{},"Knowledge Sharing:"," Breaks down knowledge silos within teams, promoting better collaboration.",[12,16292,16293,16294,611],{},"Discover more about Packmind ",[514,16295,4354],{"href":16296,"rel":16297},"https:\u002F\u002Fwww.packmind.com\u002F",[518],[12,16299,16300,16304],{},[4866,16301],{"alt":16302,"src":16303},"Packmind","\u002Fassets\u002Fblog\u002Fpackmind-ss-1024x677.jpg"," Packmind",[613,16306,16308],{"id":16307},"_2-oobeya-engineering-intelligence",[16,16309,16310],{},"2. Oobeya (Engineering Intelligence)",[3354,16312,16313],{},[12,16314,16315],{},"Accurate Metrics. Clear Insights. Data-Driven Decisions: Empowering engineering leaders to identify SDLC bottlenecks, assess team productivity, and improve engineering efficiency with top-notch data-driven insights.",[12,16317,16318],{},"Oobeya stands out with its innovative approach to automatically detecting and addressing software development and delivery symptoms. By leveraging key engineering metrics and hundreds of data points, Oobeya enables software organizations to effortlessly identify recurring anti-patterns, poor practices, bottlenecks, and roadblocks. With actionable insights derived from in-depth metrics and data analytics, Oobeya empowers engineering leaders to take proactive steps toward optimizing their processes and cultivating healthy, effective teams.",[52,16320,7627],{"id":16321},"key-features-1",[70,16323,16324,16333,16339,16345],{},[73,16325,16326,16329,16330,16332],{},[16,16327,16328],{},"Advanced Analytics:"," Provides in-depth analytics for coding repositories, ",[514,16331,14598],{"href":14597},", delivery pipelines, issue tracking, agile boards, etc.",[73,16334,16335,16338],{},[16,16336,16337],{},"Key Metrics:"," Measures and tracks over 50 key engineering metrics effortlessly (DORA, SPACE, agile metrics, cycle time, pull request analytics, etc.).",[73,16340,16341,16344],{},[16,16342,16343],{},"Integration:"," Integrates with over 20 DevOps tools (Git tools, Jira, Azure Boards, CI\u002FCD tools, APM tools, Sonarqube).",[73,16346,16347,16350],{},[16,16348,16349],{},"Team Insights:"," Assesses the current situation of engineering excellence and provides smart suggestions for improvement areas.",[12,16352,16353,16354,611],{},"Explore the benefits of Oobeya ",[514,16355,4354],{"href":516,"rel":16356},[518],[12,16358,16359,16013],{},[514,16360,16362],{"href":10160,"rel":16361},[518],[4866,16363],{"alt":12132,"src":12133},[613,16365,16367],{"id":16366},"_3-deepsource-code-quality",[16,16368,16369],{},"3. DeepSource (Code Quality)",[3354,16371,16372],{},[12,16373,16374],{},"The Code Health Platform: Build maintainable and secure software with the power of static analysis and AI.",[12,16376,16377,16380],{},[16,16378,16379],{},"DeepSource"," stands out with its ability to automate the code review process, catching issues before they become costly problems. Its real-time feedback loop helps developers adhere to best practices, ensuring a high standard of code quality across the team. This tool's extensive language support and integration capabilities make it a versatile addition to any engineering manager's toolkit. You may replace all other tools you use to write clean and secure code with the DeepSource platform.",[52,16382,7627],{"id":16383},"key-features-2",[70,16385,16386,16392,16398,16404],{},[73,16387,16388,16391],{},[16,16389,16390],{},"Automated Code Reviews:"," Analyzes every pull request to find and fix code quality issues before merging to the main branch.",[73,16393,16394,16397],{},[16,16395,16396],{},"Security Detection:"," Identifies and highlights potential security risks.",[73,16399,16400,16403],{},[16,16401,16402],{},"Continuous Integration:"," Integrates seamlessly with your CI\u002FCD pipeline for continuous code analysis.",[73,16405,16406,16409],{},[16,16407,16408],{},"Multi-language Support:"," Supports multiple programming languages including Infrastructure-as-code analysis.",[12,16411,16412,16413,611],{},"Check out DeepSource ",[514,16414,4354],{"href":16415,"rel":16416},"https:\u002F\u002Fdeepsource.com\u002F",[518],[613,16418,16420],{"id":16419},"_4-cultureamp-employee-experience",[16,16421,16422],{},"4. CultureAmp (Employee Experience)",[3354,16424,16425],{},[12,16426,16427],{},"An employee experience that people love: Get the employee engagement, performance and development tools and insights you need to build a category-defining culture.",[12,16429,16430,16433],{},[16,16431,16432],{},"CultureAmp"," is an employee engagement platform that helps engineering managers foster a positive work environment and enhance team morale. By providing insights into employee satisfaction, CultureAmp enables managers to take proactive steps to address concerns and improve overall team dynamics. Its detailed analytics enable engineering managers to pinpoint specific areas for improvement, ensuring targeted and effective interventions.",[52,16435,7627],{"id":16436},"key-features-3",[70,16438,16439,16445,16451,16457],{},[73,16440,16441,16444],{},[16,16442,16443],{},"Employee Surveys:"," Conducts regular surveys to gauge employee satisfaction and gather feedback.",[73,16446,16447,16450],{},[16,16448,16449],{},"Comprehensive Analytics:"," Provides deep data and insights across your entire employee experience.",[73,16452,16453,16456],{},[16,16454,16455],{},"Feedback Tools:"," Customizable feedback tools, goal-tracking features, and ready-to-use surveys.",[73,16458,16459,16462],{},[16,16460,16461],{},"Employee Development:"," Aligns individual development with company goals, driving personal growth and business success.",[12,16464,16465,16466,611],{},"Learn more about CultureAmp ",[514,16467,4354],{"href":16468,"rel":16469},"https:\u002F\u002Fwww.cultureamp.com\u002F",[518],[613,16471,16473],{"id":16472},"_5-invicti-application-security",[16,16474,16475],{},"5. Invicti (Application Security)",[3354,16477,16478],{},[12,16479,16480],{},"Application Security Testing For Tech Companies: Secure every website, web app, and API. Even if you have thousands of them. Only with Invicti.",[12,16482,16483,16486],{},[16,16484,16485],{},"Invicti"," is a leading web application security tool that helps engineering managers ensure the security of their applications. By providing comprehensive security testing and real-time vulnerability detection, Invicti helps teams maintain robust security standards. Its easy-to-use platform and powerful features make it a top choice for managing application security. This tool's detailed reports and actionable insights enable engineering managers to address security issues swiftly and effectively.",[52,16488,7627],{"id":16489},"key-features-4",[70,16491,16492,16498,16504,16510],{},[73,16493,16494,16497],{},[16,16495,16496],{},"Comprehensive Security Analysis:"," Performs automated scans to detect security vulnerabilities.",[73,16499,16500,16503],{},[16,16501,16502],{},"Detailed Reports:"," Provides detailed reports with actionable insights to fix security issues.",[73,16505,16506,16509],{},[16,16507,16508],{},"Continuous Monitoring:"," Continuously monitors applications for new vulnerabilities.",[73,16511,16512,16514],{},[16,16513,16343],{}," Integrates with tools and workflows your developers use daily (50+ integrations).",[12,16516,16517,16518,611],{},"Explore Invicti ",[514,16519,4354],{"href":16520,"rel":16521},"https:\u002F\u002Fwww.invicti.com\u002F",[518],[613,16523,16525],{"id":16524},"the-final-the-productivity-eaters",[16,16526,16527],{},"The Final: The Productivity Eaters",[12,16529,16530],{},"In 2024, engineering managers have access to a range of powerful tools designed to enhance productivity, streamline workflows, and maintain code quality. By integrating these standout tools into your engineering management strategy, you can ensure that your team operates at peak efficiency and delivers high-quality results. From project management and team dynamics to code quality and security, these tools provide comprehensive solutions to the challenges faced by engineering managers today.",[12,16532,16533],{},"I have picked my favorite five for you, but you can research each market and find alternatives to these products. Packmind defines the problem as \"Poor knowledge sharing & coding practices are productivity eaters\". Engineering Managers cannot measure productivity in software development, but they can find all the \"productivity eaters\" for their organizations. These five tools help you identify productivity eaters and build healthy and effective development teams!",{"title":526,"searchDepth":527,"depth":527,"links":16535},[16536,16537,16540,16543,16546,16549,16552],{"id":16240,"depth":527,"text":16243},{"id":16252,"depth":527,"text":16255,"children":16538},[16539],{"id":7626,"depth":530,"text":7627},{"id":16307,"depth":527,"text":16310,"children":16541},[16542],{"id":16321,"depth":530,"text":7627},{"id":16366,"depth":527,"text":16369,"children":16544},[16545],{"id":16383,"depth":530,"text":7627},{"id":16419,"depth":527,"text":16422,"children":16547},[16548],{"id":16436,"depth":530,"text":7627},{"id":16472,"depth":527,"text":16475,"children":16550},[16551],{"id":16489,"depth":530,"text":7627},{"id":16524,"depth":527,"text":16527},[541],"2024-05-20","Engineering managers are continually seeking the best tools to enhance team productivity, streamline processes, and maintain code quality. With a...",{},{"title":16232,"description":16555},"blog\u002Ftop-5-tools-for-engineering-managers-in-2024","-a0z7575BTPIHW3Rh5lRwH6rZDCgINq8kGnEe38elAE",{"id":16561,"title":16562,"author":4245,"avatar":575,"body":16563,"categories":16688,"createAt":542,"date":16689,"description":16690,"extension":545,"meta":16691,"navigation":547,"path":16692,"position":542,"seo":16693,"spotImage":542,"spotText":542,"stem":16694,"tags":542,"__hash__":16695},"blog\u002Fblog\u002Fharness-advanced-insights-with-oobeyas-symptoms-module-now-ga.md","Harness Advanced Insights with Oobeya's Symptoms Module, Now GA",{"type":9,"value":16564,"toc":16679},[16565,16568,16572,16575,16601,16607,16611,16613,16615,16619,16627,16634,16638,16641,16647,16651,16659,16663,16666,16669,16672],[12,16566,16567],{},"We’re thrilled to announce the general availability of Oobeya’s Symptoms module, a groundbreaking tool designed to harness advanced insights and provide clear, data-driven perspectives into your software delivery processes. This module leverages the power of advanced metrics and frameworks like DORA and SPACE to help you identify and address critical symptoms affecting your team’s productivity and well-being.",[613,16569,16571],{"id":16570},"introducing-the-oobeya-symptoms-module","Introducing the Oobeya Symptoms Module",[12,16573,16574],{},"After a successful beta phase with selected customers, the Symptoms module is now ready for widespread use. This powerful feature set is designed to help software organizations detect and address software development, delivery, quality, and project management symptoms automatically. With the latest updates, users can now benefit from:",[70,16576,16577,16583,16589,16595],{},[73,16578,16579,16582],{},[16,16580,16581],{},"Customizable Thresholds",": Tailor the sensitivity of symptom detection to fit your specific needs.",[73,16584,16585,16588],{},[16,16586,16587],{},"Visibility for Teams, Parent Teams, and Organizational Levels",": View symptoms at both the parent\u002Fchild team and organizational levels for better oversight.",[73,16590,16591,16594],{},[16,16592,16593],{},"Improved Symptom Detection Algorithm",": Experience more accurate and efficient symptom capture with our enhanced algorithm.",[73,16596,16597,16600],{},[16,16598,16599],{},"Extensive Symptom Catalog",": Benefit from 13 impactful symptoms across four main categories, with an ever-expanding symptom catalog.",[12,16602,16603,16604,611],{},"Learn more about the specific symptoms in our ",[514,16605,8353],{"href":8351,"rel":16606},[518],[52,16608,16610],{"id":16609},"how-oobeya-works","How Oobeya Works",[12,16612,12883],{},[12,16614,11844],{},[52,16616,16618],{"id":16617},"the-importance-of-addressing-symptoms-in-software-development","The Importance of Addressing Symptoms in Software Development",[12,16620,16621,16622,16626],{},"Symptoms and dysfunctions in software development can often indicate deeper issues that, if left unaddressed, can lead to significant performance declines. For instance, identifying symptoms that lead to poor DORA metrics can be crucial for improving delivery performance. Our recent ",[514,16623,16625],{"href":11489,"rel":16624},[518],"blog post"," delves into how understanding and addressing these symptoms can significantly enhance your team's efficiency and output.",[12,16628,16629,16013],{},[514,16630,16632],{"href":10160,"rel":16631},[518],[4866,16633],{"alt":12132,"src":12133},[52,16635,16637],{"id":16636},"leveraging-dora-and-space-frameworks-for-increased-developer-productivity","Leveraging DORA and SPACE Frameworks For Increased Developer Productivity",[12,16639,16640],{},"Oobeya integrates seamlessly with industry-standard frameworks such as DORA and SPACE to provide comprehensive insights into your development processes. The DORA framework focuses on key metrics like deployment frequency, lead time for changes, time to restore service, and change failure rate. By identifying symptoms that negatively impact these metrics, Oobeya helps teams take corrective actions to improve their performance.",[12,16642,16643,16644,611],{},"The SPACE framework emphasizes five key dimensions of software team performance: Satisfaction and well-being, Performance, Activity, Communication and collaboration, and Efficiency and flow. Oobeya's symptoms are closely related to these dimensions, providing a holistic view of your development environment. Learn more about this integration in our ",[514,16645,16625],{"href":11508,"rel":16646},[518],[52,16648,16650],{"id":16649},"optimizing-team-performance-with-oobeya","Optimizing Team Performance with Oobeya",[12,16652,16653,16654,611],{},"The new Symptoms module is part of our broader vision to help teams optimize their performance and well-being. By providing deep insights into development processes, Oobeya enables teams to spot inefficiencies and areas for improvement early. For more on how you can optimize team performance, check out our blog post on ",[514,16655,16658],{"href":16656,"rel":16657},"https:\u002F\u002Foobeya.io\u002Fblog\u002Foptimizing-team-performance-in-software-development\u002F",[518],"optimizing team performance in software development",[613,16660,16662],{"id":16661},"move-beyond-metrics-and-harness-advanced-insights-with-oobeya","Move Beyond Metrics And Harness Advanced Insights with Oobeya",[12,16664,16665],{},"Oobeya's motto, \"Turn data, metrics, knowledge, and experiences into insights\", reflects our commitment to helping teams leverage their data for better decision-making. The Symptoms module is a testament to this philosophy, offering a powerful tool to transform how organizations understand and improve their software development processes.",[12,16667,16668],{},"With the general availability of the Symptoms module, we are excited to see how our users will harness these new capabilities to drive better outcomes and foster healthier, more effective teams. Thank you for being a part of the Oobeya community, and we look forward to continuing this journey of innovation together.",[12,16670,16671],{},"Stay tuned for more updates and insights from Oobeya. If you have any questions or feedback, feel free to reach out to us!",[3354,16673,16674],{},[12,16675,16676,10360],{},[514,16677,10359],{"href":10160,"rel":16678},[518],{"title":526,"searchDepth":527,"depth":527,"links":16680},[16681,16687],{"id":16570,"depth":527,"text":16571,"children":16682},[16683,16684,16685,16686],{"id":16609,"depth":530,"text":16610},{"id":16617,"depth":530,"text":16618},{"id":16636,"depth":530,"text":16637},{"id":16649,"depth":530,"text":16650},{"id":16661,"depth":527,"text":16662},[4232,1232,3343,7371],"2024-05-16","We’re thrilled to announce the general availability of Oobeya’s Symptoms module, a groundbreaking tool designed to harness advanced insights and...",{},"\u002Fblog\u002Fharness-advanced-insights-with-oobeyas-symptoms-module-now-ga",{"title":16562,"description":16690},"blog\u002Fharness-advanced-insights-with-oobeyas-symptoms-module-now-ga","qalozV6fwrzlmQgrQjH_PsmrKTXYapW4Usf8FyV7_EM",{"id":16697,"title":16698,"author":4245,"avatar":575,"body":16699,"categories":16836,"createAt":542,"date":16838,"description":16839,"extension":545,"meta":16840,"navigation":547,"path":16841,"position":542,"seo":16842,"spotImage":542,"spotText":542,"stem":16843,"tags":542,"__hash__":16844},"blog\u002Fblog\u002Fci-cd-decoded-streamlining-your-development-process.md","CI\u002FCD Decoded: Streamlining Your Development Process",{"type":9,"value":16700,"toc":16829},[16701,16704,16708,16711,16715,16718,16722,16725,16729,16732,16758,16762,16791,16798,16801,16826],[12,16702,16703],{},"In the dynamic world of software development, the need for rapid and reliable delivery of code changes has never been more critical. The CI\u002FCD (Continuous Integration\u002FContinuous Delivery) methodology stands out as a transformative approach, enabling teams to accelerate their development processes while maintaining high-quality standards. This blog post delves into the essence of CI\u002FCD, its key benefits, and how integrating it with Oobeya's tools can elevate your development workflow.",[613,16705,16707],{"id":16706},"what-is-cicd","What is CI\u002FCD?",[12,16709,16710],{},"CI\u002FCD is a methodical approach that combines continuous integration and continuous delivery or continuous deployment practices. It's designed to automate the software delivery process, ensuring that code changes are seamlessly integrated, tested, and deployed to production. This automation streamlines the development lifecycle, reducing manual errors, and increasing deployment frequency.",[613,16712,16714],{"id":16713},"the-foundations-of-cicd-continuous-integration-meanings","The Foundations of CI\u002FCD: Continuous Integration Meanings!",[12,16716,16717],{},"Continuous Integration (CI) is the cornerstone of the CI\u002FCD pipeline. It involves automatically integrating code changes from multiple contributors into a single software project. This process typically includes automated testing to detect and resolve conflicts early, ensuring the software remains in a deployable state.",[613,16719,16721],{"id":16720},"continuous-delivery-vs-continuous-deployment-whats-the-difference","Continuous Delivery vs. Continuous Deployment: What's the Difference?",[12,16723,16724],{},"Though they sound similar, continuous delivery and continuous deployment are two distinct concepts within the CI\u002FCD spectrum. Continuous delivery is about automating further steps of the pipeline to ensure that code can be deployed at any time, extending CI principles to the deployment process. Meanwhile, continuous deployment takes this automation a notch higher by deploying every change that passes through the pipeline straight to production, thereby removing manual gates in the release process.",[613,16726,16728],{"id":16727},"key-benefits-of-implementing-cicd-in-your-development-workflow","Key Benefits of Implementing CI\u002FCD in Your Development Workflow",[12,16730,16731],{},"Embracing CI\u002FCD is not just about adopting new tools or processes; it’s about reaping tangible benefits that touch every aspect of development:",[70,16733,16734,16740,16746,16752],{},[73,16735,16736,16739],{},[16,16737,16738],{},"Accelerated Time to Market",": Automation speeds up the entire software delivery process, enabling faster releases.",[73,16741,16742,16745],{},[16,16743,16744],{},"Heightened Product Quality",": Early and automated testing means issues are spotted and resolved sooner, improving overall product quality.",[73,16747,16748,16751],{},[16,16749,16750],{},"Boosted Developer Morale",": Automation frees developers from mundane tasks, allowing them to concentrate on crafting innovative solutions.",[73,16753,16754,16757],{},[16,16755,16756],{},"Streamlined Error Management",": Immediate feedback mechanisms in CI\u002FCD pipelines facilitate quicker bug fixes and enhancements.",[613,16759,16761],{"id":16760},"best-usage-of-cicd-with-oobeyas-integrations","Best Usage of CI\u002FCD with Oobeya's Integrations!",[12,16763,16764,16765,16770,16771,23,16773,16775,16776,23,16778,27,16782,16786,16787,16790],{},"Oobeya enhances the CI\u002FCD process with its seamless integrations with CI\u002FCD tools such as ",[514,16766,16769],{"href":16767,"rel":16768},"https:\u002F\u002Fazure.microsoft.com\u002Fen-us\u002Fproducts\u002Fdevops\u002Fpipelines",[518],"Azure DevOps Pipelines",", Jenkins, ",[514,16772,14184],{"href":14183},[514,16774,14193],{"href":14192},", GitHub Actions, ",[514,16777,14159],{"href":14158},[514,16779,16781],{"href":16780},"\u002Fglossary\u002Fbitbucket-pipelines","Bitbucket Pipelines",[514,16783,16785],{"href":10106,"rel":16784},[518],"SonarQube for code quality metrics",". These integrations enable you to effortlessly measure ",[514,16788,3261],{"href":7188,"rel":16789},[518],", and provide insights into your development and delivery process, helping you maintain high standards of quality and efficiency.",[12,16792,16793,16797],{},[4866,16794],{"alt":16795,"src":16796},"Oobeya DORA Metrics","\u002Fassets\u002Fblog\u002Fdora-metrics-oobeya-1024x532.png"," Oobeya DORA Metrics",[12,16799,16800],{},"Integrating CI\u002FCD with Oobeya’s suite provides a cohesive platform that enriches the development and delivery cycle:",[70,16802,16803,16809,16820],{},[73,16804,16805,16808],{},[16,16806,16807],{},"Comprehensive Dashboard Insights",": Oobeya brings visibility into your CI\u002FCD pipelines and code quality, presenting a unified view that empowers teams to monitor and adjust swiftly.",[73,16810,16811,16814,16815,16819],{},[16,16812,16813],{},"Efficiency in Workflows",": The seamless integration with ",[514,16816,16818],{"href":12472,"rel":16817},[518],"Oobeya integrations"," ensures that your workflow is not just automated but optimized for peak performance, from code commits to deployment.",[73,16821,16822,16825],{},[16,16823,16824],{},"Assured Code Quality",": Through its Sonarqube integration, Oobeya allows direct tracking of code quality metrics, ensuring that deployments meet the highest standards.",[12,16827,16828],{},"Incorporating CI\u002FCD into your development practices, especially through the capabilities offered by Oobeya, is more than just a technical upgrade—it's a strategic advantage. It accelerates the delivery process and ensures that every release meets the highest quality standards, thus significantly enhancing your team's productivity and product reliability. Dive into Oobeya’s ecosystem and redefine the boundaries of your development process.",{"title":526,"searchDepth":527,"depth":527,"links":16830},[16831,16832,16833,16834,16835],{"id":16706,"depth":527,"text":16707},{"id":16713,"depth":527,"text":16714},{"id":16720,"depth":527,"text":16721},{"id":16727,"depth":527,"text":16728},{"id":16760,"depth":527,"text":16761},[1232,16837,541],"posts","2024-04-01","In the dynamic world of software development, the need for rapid and reliable delivery of code changes has never been more critical. The CI\u002FCD...",{},"\u002Fblog\u002Fci-cd-decoded-streamlining-your-development-process",{"title":16698,"description":16839},"blog\u002Fci-cd-decoded-streamlining-your-development-process","pWwmpeZk-g245CASAwgnDR91NrqAaKjHWhPijekfH4o",{"id":16846,"title":11510,"author":542,"avatar":542,"body":16847,"categories":16994,"createAt":542,"date":16995,"description":16996,"extension":545,"meta":16997,"navigation":547,"path":16998,"position":542,"seo":16999,"spotImage":542,"spotText":542,"stem":17000,"tags":542,"__hash__":17001},"blog\u002Fblog\u002Fleveraging-space-framework-and-oobeya-for-enhanced-software-development-productivity.md",{"type":9,"value":16848,"toc":16985},[16849,16856,16860,16866,16875,16879,16891,16895,16907,16947,16951,16954,16958,16961,16968,16970,16973,16979],[12,16850,16851,16852,16855],{},"Understanding and improving productivity and well-being is more critical than ever in our modern fast-changing software development landscape. The introduction of frameworks like ",[514,16853,3085],{"href":11456,"rel":16854},[518],", SPACE, Developer Experience (DevEx), and the implementation of Software Engineering Intelligence Platforms (SEIPs) such as Oobeya offer groundbreaking ways to enhance how we build, deploy, and continuously improve software products. This blog post delves into the close connection between the SPACE framework and Oobeya SEIP, describing how they work together to optimize software engineering processes and efforts.",[613,16857,16859],{"id":16858},"understanding-the-space-framework","Understanding the SPACE Framework",[12,16861,3617,16862,16865],{},[514,16863,3685],{"href":2872,"rel":16864},[518],", detailed in an insightful article by ACM Queue, stands as a comprehensive model for assessing software development productivity. SPACE is an acronym for Satisfaction and well-being, Performance, Activity, Communication and Collaboration, and Efficiency and Flow. This framework encourages a holistic view of productivity, emphasizing not just the output but also the well-being of engineering teams. It suggests that productivity measurement should extend beyond traditional metrics to include factors that affect the developers' experience and contribution to the overall business success.",[12,16867,16868,13645],{},[514,16869,16871],{"href":2872,"rel":16870},[518],[4866,16872],{"alt":16873,"src":16874},"Oobeya SPACE Framework","\u002Fassets\u002Fblog\u002Fspace-oobeya-1024x571.png",[613,16876,16878],{"id":16877},"the-role-of-software-engineering-intelligence-platforms-seip","The Role of Software Engineering Intelligence Platforms (SEIP)",[12,16880,16881,16885,16886,16890],{},[514,16882,5028],{"href":16883,"rel":16884},"https:\u002F\u002Fwww.gartner.com\u002F",[518]," defines Software Engineering Intelligence Platforms as \"platforms that shine a light on engineering data\" (",[514,16887,16889],{"href":12094,"rel":16888},[518],"Innovation Insight for Software Engineering Intelligence Platforms",", March 2023). They help software engineering leaders and teams understand what engineering data really says about how software products are built and deployed, as well as how software engineering teams perform. SEIPs like Oobeya serve as pivotal resources for software engineering leaders, offering data-driven insights that enable better decision-making, improved developer experiences, and enhanced productivity. They help in making sense of the vast amounts of data generated by development activities, thereby driving better business and customer outcomes.",[613,16892,16894],{"id":16893},"how-oobeya-aligns-with-the-space-framework","How Oobeya Aligns with the SPACE Framework",[12,16896,16897,16898,16902,16903,16906],{},"Oobeya, as a leading Software Engineering Intelligence Platform, seamlessly integrates with the principles of the SPACE framework. Oobeya automatically detects ",[514,16899,16901],{"href":10288,"rel":16900},[518],"symptoms of inefficiencies"," and bottlenecks within the software development and delivery processes, offering a detailed ",[514,16904,16007],{"href":10288,"rel":16905},[518]," that resonates with SPACE dimensions. For instance:",[70,16908,16909,16915,16929,16935,16941],{},[73,16910,16911,16914],{},[16,16912,16913],{},"Satisfaction and Well-being:"," Oobeya provides insights into team morale and satisfaction levels, helping leaders identify areas where improvements can enhance team well-being.",[73,16916,16917,16919,16920,16924,16925,16928],{},[16,16918,9901],{}," Through the analysis of cycle times, ",[514,16921,16923],{"href":4681,"rel":16922},[518],"deployment frequencies",", and other ",[514,16926,3085],{"href":7188,"rel":16927},[518]," and Agile metrics, Oobeya helps teams measure and optimize the performance of their processes.",[73,16930,16931,16934],{},[16,16932,16933],{},"Activity:"," Oobeya tracks and analyses development team activities in detail and correlation, offering visibility into how time and resources are allocated across different tasks.",[73,16936,16937,16940],{},[16,16938,16939],{},"Communication and Collaboration:"," By analyzing communication patterns and collaboration efforts, Oobeya identifies hidden inefficiencies and roadblocks in team interactions.",[73,16942,16943,16946],{},[16,16944,16945],{},"Efficiency and Flow:"," Oobeya highlights inefficiencies in workflows and processes, enabling teams to streamline operations and improve flow.",[613,16948,16950],{"id":16949},"beyond-frameworks-and-tools-addressing-culture-and-strategy","Beyond Frameworks and Tools: Addressing Culture and Strategy",[12,16952,16953],{},"While frameworks like DORA, SPACE, and DevEx offer significant insights and improvements in software development processes, it’s crucial to acknowledge their limitations. They are not panaceas for fixing broken cultures, organizational issues, or flawed strategies. Instead, they should be seen as components of a larger ecosystem that includes robust cultural practices, effective organizational structures, and strategic clarity.",[613,16955,16957],{"id":16956},"embracing-a-holistic-approach-with-oobeya-and-space-framework","Embracing a Holistic Approach with Oobeya and SPACE Framework",[12,16959,16960],{},"Integrating the SPACE framework with Oobeya’s capabilities presents a formidable approach to enhancing software development productivity and well-being. It enables a more nuanced understanding of productivity, one that goes beyond mere output to consider the health and efficiency of the development environment. By leveraging these insights, software engineering leaders can foster a more supportive, effective, and efficient software development culture.",[12,16962,16963,16967],{},[4866,16964],{"alt":16965,"src":16966},"Oobeya Team Insights","\u002Fassets\u002Fblog\u002FOobeya-TeamHealth-Symptoms-1024x530.png"," Oobeya Team Insights",[613,16969,1159],{"id":477},[12,16971,16972],{},"The combination of SPACE and Oobeya offers a powerful lens through which software development teams can view and improve their work and well-being. By focusing on comprehensive metrics and data-driven insights, teams can achieve higher productivity levels, better project outcomes, and improved team satisfaction. As the software development industry continues to evolve, embracing these frameworks and platforms will be key to staying competitive and fulfilling both customer and developer needs effectively.",[613,16974,16976],{"id":16975},"join-us-on-the-path-to-software-engineering-excellence",[16,16977,16978],{},"Join Us on the Path to Software Engineering Excellence",[12,16980,16981,16982,611],{},"We invite you to explore the Oobeya SEIP. For more information, visit us at ",[514,16983,469],{"href":516,"rel":16984},[518],{"title":526,"searchDepth":527,"depth":527,"links":16986},[16987,16988,16989,16990,16991,16992,16993],{"id":16858,"depth":527,"text":16859},{"id":16877,"depth":527,"text":16878},{"id":16893,"depth":527,"text":16894},{"id":16949,"depth":527,"text":16950},{"id":16956,"depth":527,"text":16957},{"id":477,"depth":527,"text":1159},{"id":16975,"depth":527,"text":16978},[1232,541,3343,7371],"2024-02-16","Understanding and improving productivity and well being is more critical than ever in our modern fast changing software development landscape. The...",{},"\u002Fblog\u002Fleveraging-space-framework-and-oobeya-for-enhanced-software-development-productivity",{"title":11510,"description":16996},"blog\u002Fleveraging-space-framework-and-oobeya-for-enhanced-software-development-productivity","JjJUbshbdDM_Vz_3xd7bdlDCGXFzf69ni-OTsI4mDgE",{"id":17003,"title":17004,"author":4245,"avatar":575,"body":17005,"categories":17143,"createAt":542,"date":17144,"description":17145,"extension":545,"meta":17146,"navigation":547,"path":17147,"position":542,"seo":17148,"spotImage":542,"spotText":542,"stem":17149,"tags":542,"__hash__":17150},"blog\u002Fblog\u002Fenhance-your-devops-with-the-oobeya-dora-metrics-github-app.md","DORA Metrics GitHub App: Enhance Your DevOps With Oobeya",{"type":9,"value":17006,"toc":17135},[17007,17014,17020,17023,17029,17036,17042,17045,17068,17074,17085,17105,17111,17114,17118,17124,17127],[12,17008,17009,17010,17013],{},"In the ever-evolving landscape of software development, efficiency and performance are not just goals—they are imperatives. At Oobeya, we understand the challenges developers face in achieving these objectives. That's why we are thrilled to announce the launch of the ",[16,17011,17012],{},"Oobeya DORA Metrics GitHub App",", designed to bring the most precise DORA Metric into your software development workflow, now available in the GitHub Marketplace.",[613,17015,17017],{"id":17016},"the-genesis-of-a-game-changer-dora-metrics-github-app",[16,17018,17019],{},"The Genesis of a Game-Changer: DORA Metrics GitHub App",[12,17021,17022],{},"The journey to developing the Oobeya DORA Metrics GitHub App started with a simple question: how can we make the lives of developers easier while enhancing the quality and efficiency of software delivery? The answer lay in leveraging DORA metrics—Deployment Frequency, Lead Time for Changes, Time to Restore Service, and Change Failure Rate—metrics proven to correlate directly with high-performing software development teams.",[613,17024,17026],{"id":17025},"why-dora-metrics",[16,17027,17028],{},"Why DORA Metrics?",[12,17030,17031,17032,17035],{},"For those unfamiliar, ",[514,17033,848],{"href":7188,"rel":17034},[518]," have emerged as the gold standard for measuring software development and delivery performance. They offer concrete data points to track and improve upon, such as how often you deploy to production, how quickly you can move from code commit to code successfully running in production, how fast you can recover from a failure, and what percentage of your deployments cause a failure in production.",[613,17037,17039],{"id":17038},"seamless-github-integration-for-immediate-impact",[16,17040,17041],{},"Seamless GitHub Integration for Immediate Impact",[12,17043,17044],{},"The Oobeya DORA Metrics GitHub App seamlessly integrates with your GitHub repositories, offering real-time insights without disrupting your existing workflow. Here's how it transforms your development process:",[1520,17046,17047,17052,17057,17063],{},[73,17048,17049,17051],{},[16,17050,15886],{}," A measure of how often your team successfully releases to production, reflecting agility and speed.",[73,17053,17054,17056],{},[16,17055,5819],{}," The time it takes for changes to go from code commit to deployment, indicating efficiency.",[73,17058,17059,17062],{},[16,17060,17061],{},"Time to Restore Service:"," How quickly your team can recover from a failure, highlighting resilience.",[73,17064,17065,17067],{},[16,17066,15904],{}," The percentage of deployments causing failure in production, pointing to quality.",[613,17069,17071],{"id":17070},"streamline-your-workflow-with-easy-integration",[16,17072,17073],{},"Streamline Your Workflow with Easy Integration",[12,17075,17076,17077,17079,17080,17084],{},"Adopting the ",[16,17078,17012],{}," is a breeze, thanks to our straightforward setup process. By following our ",[514,17081,17083],{"href":4627,"rel":17082},[518],"comprehensive guide",", you can quickly integrate these metrics into your workflow, empowering your team to:",[1520,17086,17087,17093,17099],{},[73,17088,17089,17092],{},[16,17090,17091],{},"Identify bottlenecks"," and streamline your development and deployment pipeline.",[73,17094,17095,17098],{},[16,17096,17097],{},"Boost productivity"," by making informed decisions based on real-time data.",[73,17100,17101,17104],{},[16,17102,17103],{},"Enhance software quality"," by pinpointing and addressing areas prone to errors.",[613,17106,17108],{"id":17107},"elevating-your-development-journey-with-dora-metrics-github-integration",[16,17109,17110],{},"Elevating Your Development Journey with DORA Metrics GitHub Integration",[12,17112,17113],{},"With the introduction of the Oobeya DORA Metrics GitHub App, we're not just offering a tool; we're providing a pathway to enhanced performance, efficiency, and ultimately, software excellence. By integrating DORA metrics into your daily practices, you're equipped to make informed decisions that streamline processes, improve quality, and accelerate delivery.",[12,17115,17116,16797],{},[4866,17117],{"alt":16795,"src":16796},[613,17119,17121],{"id":17120},"join-us-on-the-path-to-excellence",[16,17122,17123],{},"Join Us on the Path to Excellence",[12,17125,17126],{},"We invite you to explore the Oobeya DORA Metrics GitHub App and experience the transformative impact of DORA metrics on your development workflow. Install the app today and take the first step towards realizing the full potential of your software development team.",[12,17128,17129,17130,17134],{},"For more information, visit us at ",[514,17131,469],{"href":17132,"rel":17133},"https:\u002F\u002Fdocs.oobeya.io\u002F",[518],". Together, let's build software that not only meets but exceeds expectations.",{"title":526,"searchDepth":527,"depth":527,"links":17136},[17137,17138,17139,17140,17141,17142],{"id":17016,"depth":527,"text":17019},{"id":17025,"depth":527,"text":17028},{"id":17038,"depth":527,"text":17041},{"id":17070,"depth":527,"text":17073},{"id":17107,"depth":527,"text":17110},{"id":17120,"depth":527,"text":17123},[1232,16837,541],"2024-02-15","In the ever evolving landscape of software development, efficiency and performance are not just goals—they are imperatives. At Oobeya, we understand...",{},"\u002Fblog\u002Fenhance-your-devops-with-the-oobeya-dora-metrics-github-app",{"title":17004,"description":17145},"blog\u002Fenhance-your-devops-with-the-oobeya-dora-metrics-github-app","ISqPyAJdyoFS5B_zCpwiRYgvxrdC7PRKr9UJnIwdx7Q",{"id":17152,"title":17153,"author":4245,"avatar":575,"body":17154,"categories":17438,"createAt":542,"date":17439,"description":17440,"extension":545,"meta":17441,"navigation":547,"path":17442,"position":4134,"seo":17443,"spotImage":542,"spotText":542,"stem":17444,"tags":17445,"__hash__":17446},"blog\u002Fblog\u002Fbeyond-dora-metrics-identifying-symptoms-that-lead-to-poor-dora-metrics.md","Identifying Symptoms That Lead To Poor DORA Metrics - Blog",{"type":9,"value":17155,"toc":17426},[17156,17159,17166,17169,17175,17186,17193,17196,17204,17209,17212,17217,17225,17231,17234,17237,17244,17247,17251,17254,17276,17284,17288,17291,17311,17315,17318,17346,17354,17358,17361,17373,17375,17381,17384,17388,17401,17407],[12,17157,17158],{},"We’ll explore the correlation between team symptoms and DORA Metrics and how addressing symptoms can help teams boost their software delivery performance. Take your team's productivity and well-being to the next level with this insightful guide.",[12,17160,17161,17162,17165],{},"Software development is a challenging and constantly evolving field that requires a high level of teamwork, collaboration, and productivity. To measure the effectiveness of their development processes, teams often turn to DORA (DevOps Research and Assessment) metrics, which are industry-standard measures of software delivery performance. However, measuring ",[514,17163,3261],{"href":7188,"rel":17164},[518]," alone is not enough to improve software development processes. To truly thrive, teams need to identify and address the root causes of all issues affecting their metrics.",[12,17167,17168],{},"This is where symptoms come in. Symptoms are indicators of underlying problems in the development process that can lead to poor DORA metrics. By identifying and addressing symptoms, teams can improve their development processes and, in turn, improve their DORA metrics. In this article, we’ll explore the correlation between team symptoms and DORA Metrics and how addressing symptoms can help teams boost their software delivery performance.",[613,17170,17172],{"id":17171},"oobeya-symptoms-overview",[16,17173,17174],{},"Oobeya Symptoms Overview",[12,17176,3617,17177,17181,17182,17185],{},[514,17178,17180],{"href":10288,"rel":17179},[518],"Oobeya Symptoms module"," is a powerful tool for identifying and resolving problems in software development and delivery processes. In ",[514,17183,469],{"href":5051,"rel":17184},[518],", a symptom is a recurring anti-pattern, bad practice, bottleneck, or roadblock in the software development and delivery process.",[12,17187,17188,17192],{},[4866,17189],{"alt":17190,"src":17191},"Oobeya Team Symptoms","\u002Fassets\u002Fblog\u002Foobeya-team-symptoms-1024x626.png"," Oobeya Team Symptoms",[12,17194,17195],{},"Symptoms are automatically detected by Oobeya, leveraging over 50 key engineering metrics, and can be used to identify areas where improvements can be made to the software development and delivery process. By addressing the underlying causes of these symptoms, teams can improve their software development and delivery processes and achieve better outcomes.",[3354,17197,17198],{},[12,17199,17200,17201],{},"Optimizing Team Performance in Software Development with Oobeya Team Health Module: ",[514,17202,16656],{"href":16656,"rel":17203},[518],[613,17205,17207,8398],{"id":17206},"understanding-dora-metrics",[16,17208,12522],{},[12,17210,17211],{},"As software development teams strive to improve their processes and deliver high-quality products quickly, it’s important to have a way to measure progress and identify areas for improvement. DORA metrics are a set of four key performance indicators that can help teams measure their delivery performance.",[12,17213,17214,16797],{},[4866,17215],{"alt":16795,"src":17216},"\u002Fassets\u002Fblog\u002Fdora-metrics-1024x532.png",[3354,17218,17219],{},[12,17220,17221,17222],{},"How to Measure DORA Metrics Accurately: ",[514,17223,11456],{"href":11456,"rel":17224},[518],[613,17226,17228],{"id":17227},"symptoms-that-affect-dora-metrics",[16,17229,17230],{},"Symptoms That Affect DORA Metrics",[12,17232,17233],{},"Symptoms are indicators of problems or inefficiencies in your software development process. Various symptoms can impact DORA metrics. Some of the most common symptoms include a recurring high rework rate, high technical debt on SonarQube, oversize pull requests, a high cognitive load, lightning pull requests, and a high pull request revert rate. These symptoms can slow down team performance and impact DORA metrics in various ways.",[12,17235,17236],{},"Symptoms can have a significant impact on DORA metrics. For example, having high technical debt and complexity can increase lead time for changes, while oversize pull requests can decrease deployment frequency. Lightning pull requests and having high code quality bugs can increase the change failure rate and time to restore service. By understanding the relationship between symptoms and DORA metrics, teams can take proactive measures to improve performance.",[12,17238,17239,17243],{},[4866,17240],{"alt":17241,"src":17242},"Symptoms that affect DORA Metrics","\u002Fassets\u002Fblog\u002Fsymptoms-dora-1024x560.png"," Symptoms that affect DORA Metrics",[12,17245,17246],{},"Here are some examples of how the DORA metrics are correlated with specific symptoms:",[52,17248,17250],{"id":17249},"_1-lead-time-for-changes-ltc","1. Lead Time For Changes (LTC)",[12,17252,17253],{},"This measures the amount of time it takes a commit to get into production. The best thing you can do to reduce Change Lead Time is to identify software development waste and bottlenecks. Lead Time for Changes is correlated with the following symptoms:",[70,17255,17256,17266],{},[73,17257,17258,17261,17262,611],{},[16,17259,17260],{},"Recurring high rework rate:"," A high LTC may indicate that code changes are not being thoroughly reviewed or tested, resulting in the need for frequent rework. Learn more about this symptom here. High technical debt on Sonarqube: A high LTC may indicate that technical debt is accumulating in the codebase, making it more difficult and time-consuming to make changes in the codebase. Learn more about this symptom ",[514,17263,4354],{"href":17264,"rel":17265},"https:\u002F\u002Fdocs.oobeya.io\u002Fsymptoms\u002Fsymptoms-catalog\u002Fs1-recurring-high-rework-rate",[518],[73,17267,17268,17271,17272,611],{},[16,17269,17270],{},"Oversize Pull Requests:"," A high LTC may be a result of large, complex code changes that are difficult to review and test, leading to delays in the delivery process. Learn more about this symptom ",[514,17273,4354],{"href":17274,"rel":17275},"https:\u002F\u002Fdocs.oobeya.io\u002Fsymptoms\u002Fsymptoms-catalog\u002Fs11-oversize-pull-requests",[518],[3354,17277,17278],{},[12,17279,17280,17281,8398],{},"How To Reduce Lead Time for Changes (Optimizing DORA Metrics): ",[514,17282,10444],{"href":10444,"rel":17283},[518],[52,17285,17287],{"id":17286},"_2-deployment-frequency-df","2. Deployment Frequency (DF)",[12,17289,17290],{},"This measures how often code changes are deployed to production. Deployment Frequency is correlated with the following symptoms:",[70,17292,17293,17303],{},[73,17294,17295,17298,17299,611],{},[16,17296,17297],{},"Recurring high cognitive load:"," A low DF may indicate that team members are experiencing a high cognitive load due to a lack of resources or poor planning process, leading to lower productivity, poor developer experience, and increased stress. Learn more about this symptom ",[514,17300,4354],{"href":17301,"rel":17302},"https:\u002F\u002Fdocs.oobeya.io\u002Fsymptoms\u002Fsymptoms-catalog\u002Fs2-recurring-high-cognitive-load",[518],[73,17304,17305,17307,17308,611],{},[16,17306,17270],{}," High-performing software teams release often and in small batches. A low DF may also be a result of large, complex code changes that are difficult to review and test, leading to a reviewer bottleneck in the delivery process. Learn more about this symptom ",[514,17309,4354],{"href":17274,"rel":17310},[518],[52,17312,17314],{"id":17313},"_3-change-failure-rate-cfr","3. Change Failure Rate (CFR)",[12,17316,17317],{},"This measures the percentage of deployments causing a failure in production. The failures can significantly impact the stability and reliability of software systems, making it crucial for organizations to detect and resolve them as quickly as possible. Change Failure Rate is correlated with the following symptoms:",[70,17319,17320,17330,17340],{},[73,17321,17322,17325,17326,611],{},[16,17323,17324],{},"Lightning Pull Requests:"," A high Change Failure Rate may be a sign that the team’s code review procedure is weak, which causes unstable and unreliable code. Pull Requests merged in 1–2 min without sufficient review or testing may introduce bugs or other issues that can lead to production failures. Learn more about this symptom ",[514,17327,4354],{"href":17328,"rel":17329},"https:\u002F\u002Fdocs.oobeya.io\u002Fsymptoms\u002Fsymptoms-catalog\u002Fs10-lightning-pull-requests",[518],[73,17331,17332,17335,17336,611],{},[16,17333,17334],{},"High Technical Debt on Sonarqube:"," High technical debt means that there are a lot of issues that need to be fixed, and this can increase the probability of failures in production. Learn more about this symptom ",[514,17337,4354],{"href":17338,"rel":17339},"https:\u002F\u002Fdocs.oobeya.io\u002Fsymptoms\u002Fsymptoms-catalog\u002Fs6-high-technical-debt-on-sonar",[518],[73,17341,17342,17345],{},[16,17343,17344],{},"High Pull Request Revert Rate:"," Pull Requests that are reverted frequently can indicate issues with the code or the development process. If Pull Requests are reverted frequently, it can lead to delays and decreased confidence in the development process.",[3354,17347,17348],{},[12,17349,17350,17351],{},"DORA Metrics Tracking: How to Effectively Detect Production Failures & Calculate Change Failure Rate: ",[514,17352,11482],{"href":11482,"rel":17353},[518],[52,17355,17357],{"id":17356},"_4-mean-time-to-restore-service-mttr","4. Mean Time to Restore Service (MTTR)",[12,17359,17360],{},"This measures how long it takes to restore service after a production incident. Time to Restore Service is correlated with the following symptoms:",[70,17362,17363,17368],{},[73,17364,17365,17367],{},[16,17366,17334],{}," High technical debt and complexity can slow down the process of restoring service after a failure.",[73,17369,17370,17372],{},[16,17371,17297],{}," A high MTTR may be caused by knowledge silos within the team as a result of a lack of knowledge-sharing culture. The recurring high cognitive load may be a sign of knowledge silos.",[501,17374],{},[613,17376,17378],{"id":17377},"improving-team-health-and-performance-by-leveraging-auto-detected-symptoms-and-dora-metrics",[16,17379,17380],{},"Improving Team Health and Performance By Leveraging Auto-detected Symptoms and DORA Metrics",[12,17382,17383],{},"To optimize team performance, it is crucial to identify and address symptoms that hinder productivity and teamwork. Fortunately, teams can leverage a range of tools and strategies to pinpoint such symptoms, such as Oobeya, which can automatically detect them based on predefined rules. Once identified, teams can take necessary actions to address the symptoms, including improving the code review process, reducing technical debt, and establishing clear knowledge-sharing procedures. By spotting and addressing symptoms, teams can improve DORA Metrics and achieve better business outcomes while fostering a healthier and more productive team.",[4331,17385,17386],{"id":13186},[16,17387,13189],{},[70,17389,17390,17396],{},[73,17391,17392,17393],{},"Oobeya Symptoms Catalog: ",[514,17394,10288],{"href":10288,"rel":17395},[518],[73,17397,17200,17398],{},[514,17399,16656],{"href":16656,"rel":17400},[518],[4331,17402,17404],{"id":17403},"previous-articles",[16,17405,17406],{},"Previous Articles",[70,17408,17409,17414,17420],{},[73,17410,17221,17411],{},[514,17412,11456],{"href":11456,"rel":17413},[518],[73,17415,17416,17417],{},"How To Reduce Lead Time For Changes (Optimizing DORA Metrics): ",[514,17418,10444],{"href":10444,"rel":17419},[518],[73,17421,17422,17423],{},"DORA Metrics Tracking: How to Effectively Detect Production Failures: ",[514,17424,11482],{"href":11482,"rel":17425},[518],{"title":526,"searchDepth":527,"depth":527,"links":17427},[17428,17429,17431,17437],{"id":17171,"depth":527,"text":17174},{"id":17206,"depth":527,"text":17430},"Understanding DORA Metrics ",{"id":17227,"depth":527,"text":17230,"children":17432},[17433,17434,17435,17436],{"id":17249,"depth":530,"text":17250},{"id":17286,"depth":530,"text":17287},{"id":17313,"depth":530,"text":17314},{"id":17356,"depth":530,"text":17357},{"id":17377,"depth":527,"text":17380},[1232,541,7371,6446],"2023-03-17","Discover identifying symptoms beyond DORA metrics. Take your team's productivity and well-being to the next level with this insightful guide.",{},"\u002Fblog\u002Fbeyond-dora-metrics-identifying-symptoms-that-lead-to-poor-dora-metrics",{"title":17153,"description":17440},"blog\u002Fbeyond-dora-metrics-identifying-symptoms-that-lead-to-poor-dora-metrics",[8440,7371,6446],"5c0SAsKQ3UKUZrT8ig2934j-Dcr5zJ3o3i_D19Ctzok",{"id":17448,"title":17449,"author":4245,"avatar":575,"body":17450,"categories":18366,"createAt":542,"date":18367,"description":18368,"extension":545,"meta":18369,"navigation":547,"path":18370,"position":542,"seo":18371,"spotImage":542,"spotText":542,"stem":18372,"tags":18373,"__hash__":18374},"blog\u002Fblog\u002Foptimizing-team-performance-in-software-development.md","Optimizing Team Performance in Software Development - Blog",{"type":9,"value":17451,"toc":18359},[17452,17455,17465,17471,17477,17481,17485,17488,18241,18247,18290,18297,18303,18306,18356],[12,17453,17454],{},"In today's fast-paced digital landscape, software development organizations are under constant pressure to deliver high-quality products in a timely manner. To meet this challenge, organizations need to identify and eliminate inefficiencies in their software development processes. This is where the Oobeya Team Health Module comes in, providing a comprehensive solution to optimize team performance in software development.",[12,17456,17457,17458,247,17461,17464],{},"The Oobeya Team Health Module is comprised of two main components: ",[16,17459,17460],{},"Team Symptoms",[16,17462,17463],{},"Team Scorecard",". These components work together to help organizations improve team well-being, performance, and productivity.",[613,17466,17468],{"id":17467},"team-symptoms-detecting-and-addressing-problems-in-the-development-process",[16,17469,17470],{},"Team Symptoms: Detecting and Addressing Problems in the Development Process",[12,17472,17473,17474,611],{},"The Oobeya Symptoms module is a powerful tool for identifying and resolving problems in software development and delivery processes. The Oobeya Symptoms module collects and analyzes data from various sources to automatically detect recurring issues such as anti-patterns, bad practices, and bottlenecks that may be hindering team performance. Upon identifying these issues, the module alerts teams to potential problems and provides recommendations and solutions to resolve them. This allows teams to take proactive measures to improve their processes and avoid obstacles that could impact their performance and health. See the Oobeya Symptoms Catalog ",[514,17475,4354],{"href":10288,"rel":17476},[518],[12,17478,17479,17192],{},[4866,17480],{"alt":17190,"src":17191},[52,17482,17484],{"id":17483},"available-symptoms-coming-more-soon","Available Symptoms (coming more soon)",[12,17486,17487],{},"The Oobeya Symptoms module currently includes the following symptoms:",[1585,17489,17508,17511],{"className":17490,"style":17506,"width":17507},[17491,17492,17493,17494,17495,17496,17497,17498,17499,17500,17501,17502,17503,17504,17505],"r-1oszu61","r-1xc7w19","r-1phboty","r-1yadl64","r-deolkf","r-6koalj","r-1mlwlqe","r-eqz5dr","r-1q142lx","r-crgep1","r-ifefl9","r-bcqeeo","r-t60dpp","r-bnwqim","r-417010","height: 258px;",743,[1588,17509],{"className":17510},[17491,17492,17493,17494,17495,17496,17497,17498,17499,17500,17501,17502,17503,17504,17505],[1601,17512,17514,17620,17697,17775,17853,17931,18009,18087,18164],{"className":17513},[17491,17492,17493,17494,17495,17496,17497,17498,17499,17500,17501,17502,17503,17504,17505],[1591,17515,17520,17560,17597],{"className":17516,"dataRnwi-5xr8s6Dse9kg-2fw26j-1jcliuFocusVisible":17518,"dataRnwiHandle":17519},[17491,17492,17493,17494,17495,17496,17497,17499,17500,17501,17502,17503,17504,17505,17517],"r-18u37iz","true","table-row",[1606,17521,17525],{"className":17522},[17491,17492,17493,17494,17495,17496,17497,17499,17500,17501,17502,17503,17504,17505,17523,17517,17524],"r-fdjqy7","r-1777fci",[4311,17526,17529],{"className":17527},[17528],"css-175oi2r",[4311,17530,17535],{"className":17531},[17528,17532,17533,17534],"r-1ro0kt6","r-16y2uox","r-1wbh5a2",[4311,17536,17540],{"dataKey":17537,"dataFragment":17518,"dataSlateEditor":17518,"dataDocumentKey":17538,"dataGramm":17539},"f8deeeb0ac8d4e76998f1694be38ad10","a7fb9e482bda4e9e9430e2324dc9b194","false",[4311,17541,17544],{"className":17542,"dataKey":17543},[17491,17492,17493,17494,17495,17496,17497,17498,17499,17500,17501,17502,17503,17504,17505],"15a934ff8f204ff49e244f8a0e11c364",[4311,17545,17555],{"className":17546,"dir":17554},[17547,17548,17549,17550,17551,17552,17523,17553],"css-1rynq56","r-gg6oyi","r-ubezar","r-16dba41","r-135wba7","r-1nf4jbm","r-1xnzce8","auto",[17556,17557,17559],"span",{"dataKey":17558},"b04cd84aeda248e69c4f43258544d808","S1",[1606,17561,17563],{"className":17562},[17491,17492,17493,17494,17495,17496,17497,17499,17500,17501,17502,17503,17504,17505,17523,17517,17524],[4311,17564,17566],{"className":17565},[17528],[4311,17567,17569],{"className":17568},[17528,17532,17533,17534],[4311,17570,17572],{"dataKey":17571,"dataFragment":17518,"dataSlateEditor":17518,"dataDocumentKey":17538,"dataGramm":17539},"c80dfac0f53a48689f58c8b5ea7aac36",[4311,17573,17576],{"className":17574,"dataKey":17575},[17491,17492,17493,17494,17495,17496,17497,17498,17499,17500,17501,17502,17503,17504,17505],"5100cca1a16b480d8e12cbdd3158bac4",[4311,17577,17579],{"className":17578,"dir":17554},[17547,17548,17549,17550,17551,17552,17523,17553],[17556,17580,17582],{"style":17581},"color: #3366ff;",[514,17583,17591],{"className":17584,"style":17581,"href":17264,"dataRnwi-5xr8s6Dse9kg-2fw26j-1jcliuFocusVisible":17518,"dataRnwiHandle":17590},[17528,17585,17586,17587,17588,17589],"r-1i6wzkk","r-lrvibr","r-1loqt21","r-1otgn73","r-1471scf","link",[17556,17592,17596],{"className":17593,"dataKey":17594,"dataRnwilink--1o2rotx-":17518,"dataRnwilink-Qd37px-1ddef8gHover":17518,"dataRnwiHandle":17595},[17500],"13f706ecbfc6417a82a4a78132e654d6","nearest","Recurring high rework 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Progress",[12,18248,18249,18250,18253,18254,23,18258,23,18262,23,18266,23,18271,23,18275,23,18280,18284,18285,18289],{},"The Team Scorecard provides teams with an all-encompassing view of their metrics and progress. 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The Scorecard consists of multiple team-based metrics, which come from different data sources such as ",[514,18255,4528],{"href":18256,"rel":18257},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fscm-addons\u002Fgithub-integrations",[518],[514,18259,6908],{"href":18260,"rel":18261},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fscm-addons\u002Fgitlab-addon",[518],[514,18263,6905],{"href":18264,"rel":18265},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fscm-addons\u002Fazure-devops-integration",[518],[514,18267,18270],{"href":18268,"rel":18269},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fscm-addons\u002Fbitbucket-server-integration",[518],"Bitbucket",[514,18272,6900],{"href":18273,"rel":18274},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fproject-management-addons\u002Fjira-cloud-integration",[518],[514,18276,18279],{"href":18277,"rel":18278},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fscm-addons\u002Fjenkins-integration",[518],"Jenkins",[514,18281,17852],{"href":18282,"rel":18283},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fcode-quality-addons\u002Fsonarqube-integration",[518],", Veracode, ",[514,18286,14208],{"href":18287,"rel":18288},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fapm-monitoring-addons\u002Fnew-relic-integration",[518],", DataDog, Dynatrace, and more. The historical data and team-based summaries provided by the Scorecard give teams deep visibility into their progress, bottlenecks, and areas for improvement, enabling them to make data-driven decisions and track the overall health of their teams.",[12,18291,18292,18296],{},[4866,18293],{"alt":18294,"src":18295},"Oobeya Team Scorecard","\u002Fassets\u002Fblog\u002Foobeya-team-scorecard-1024x609.png"," Oobeya Team Scorecard",[613,18298,18300],{"id":18299},"optimizing-team-performance-in-software-development",[16,18301,18302],{},"Optimizing Team Performance in Software Development",[12,18304,18305],{},"Optimizing team performance in software development requires a comprehensive approach that addresses both technical and cultural aspects of the development process. Here are some strategies to help optimize team performance:",[1520,18307,18308,18314,18320,18326,18332,18338,18344,18350],{},[73,18309,18310,18313],{},[16,18311,18312],{},"Clear Communication:"," Ensure that team members have a clear understanding of their roles, responsibilities, and expectations. Encourage open communication channels and foster an environment where team members can freely share ideas, concerns, and feedback.",[73,18315,18316,18319],{},[16,18317,18318],{},"Process Optimization:"," Evaluate and streamline development processes to eliminate bottlenecks and inefficiencies. Encourage teams to continuously improve processes through regular retrospectives and process improvement initiatives.",[73,18321,18322,18325],{},[16,18323,18324],{},"Collaboration Tools:"," Utilize collaboration tools such as code review, version control systems, and project management software to increase transparency, efficiency, and accountability.",[73,18327,18328,18331],{},[16,18329,18330],{},"Agile Methodology:"," Adopt an agile methodology such as Scrum or Kanban to better manage work and continuously improve.",[73,18333,18334,18337],{},[16,18335,18336],{},"Team Metrics:"," Track and measure team progress using metrics such as cycle time, code review, DORA metrics, and code quality metrics. Use these metrics to identify areas for improvement and track progress over time.",[73,18339,18340,18343],{},[16,18341,18342],{},"Continuous Learning:"," Encourage continuous learning through training, mentorship programs, and skill-building activities. This helps team members stay up-to-date on the latest technologies and best practices.",[73,18345,18346,18349],{},[16,18347,18348],{},"Employee Engagement:"," Foster a positive work environment that values employee engagement and well-being. Regularly check in with team members to understand their needs, and provide support to help them achieve their personal and professional goals.",[73,18351,18352,18355],{},[16,18353,18354],{},"Data-Driven Insights:"," Utilize data-driven insights to make informed decisions and track progress. Tools like Oobeya's Team Health module, which includes Team Symptoms and Team Scorecard components, can help teams gather and analyze data from various sources to identify issues and track progress over time.",[12,18357,18358],{},"Optimizing team performance in software development requires a holistic approach that addresses both technical and cultural aspects of the development process. By implementing these strategies, organizations can improve the overall performance and productivity of their software development teams, delivering high-quality products in a timely and efficient manner.",{"title":526,"searchDepth":527,"depth":527,"links":18360},[18361,18364,18365],{"id":17467,"depth":527,"text":17470,"children":18362},[18363],{"id":17483,"depth":530,"text":17484},{"id":18243,"depth":527,"text":18246},{"id":18299,"depth":527,"text":18302},[1232,541,7371,6446],"2023-02-13","Maximize the performance of your software development teams with Oobeya's Team Health Module. Get real-time insights, and track team metrics.",{},"\u002Fblog\u002Foptimizing-team-performance-in-software-development",{"title":17449,"description":18368},"blog\u002Foptimizing-team-performance-in-software-development",[2620,540,696,541,7371,6446],"6RIUfyr669ROeorqdr_dz_DI_l2hPkpKfoqGzKamemM",{"id":18376,"title":18377,"author":4245,"avatar":575,"body":18378,"categories":18607,"createAt":542,"date":18608,"description":18609,"extension":545,"meta":18610,"navigation":547,"path":18611,"position":4134,"seo":18612,"spotImage":542,"spotText":542,"stem":18613,"tags":18614,"__hash__":18615},"blog\u002Fblog\u002Fdora-metrics-tracking-how-to-effectively-detect-production-failures.md","How to Effectively Detect Production Failures - Blog",{"type":9,"value":18379,"toc":18596},[18380,18385,18389,18408,18410,18414,18421,18425,18428,18431,18434,18436,18440,18446,18457,18469,18472,18478,18488,18498,18502,18505,18514,18518,18521,18525,18528,18537,18546,18550,18558,18567,18579,18590,18593],[3354,18381,18382],{},[12,18383,18384],{},"Detecting production failures is the most critical and challenging component of tracking DORA metrics. While it can be challenging, organizations can overcome these challenges by using the right tools and following best practices.",[613,18386,18388],{"id":18387},"quick-intro-what-are-dorametrics","Quick Intro: What Are DORA Metrics?",[12,18390,18391,1044,18396,18399,18400,18404,18405],{},[514,18392,18395],{"href":18393,"rel":18394},"https:\u002F\u002Fdevops-research.com\u002F",[518],"DORA (DevOps Research and Assessment)",[514,18397,696],{"href":7188,"rel":18398},[518]," are a set of metrics that measure the performance of DevOps practices and processes in organizations. The metrics include ",[514,18401,18403],{"href":7188,"rel":18402},[518],"lead time, deployment frequency, mean time to restore, change failure rate",", and they aim to provide a comprehensive view of an organization’s ability to deliver value to customers. Learn more about DORA Metrics here: ",[514,18406,11456],{"href":11456,"rel":18407},[518],[501,18409],{},[613,18411,18413],{"id":18412},"what-is-a-production-failure","What Is A Production Failure?",[12,18415,18416,18417,18420],{},"One critical component of tracking ",[514,18418,848],{"href":7188,"rel":18419},[518]," is detecting production failures. Production failures occur when a change to the software system results in an unintended outcome, causing the system to malfunction or become unavailable. These failures can significantly impact the stability and reliability of software systems, making it crucial for organizations to detect and resolve them as quickly as possible.",[613,18422,18424],{"id":18423},"the-most-challenging-part-of-dora-metrics-tracking-detecting-production-failures","The Most Challenging Part of DORA Metrics Tracking: Detecting Production Failures",[12,18426,18427],{},"However, detecting production failures can be a challenging task for organizations. One of the biggest challenges is automatically detecting production failures, which can be difficult due to the complexity of software systems and the limited visibility into production systems. Additionally, organizations are often overwhelmed by the sheer volume of data to be analyzed, making it difficult to identify and resolve failures quickly.",[12,18429,18430],{},"To overcome these challenges, organizations can use a variety of solutions and tools to detect production failures, including monitoring, log analysis, error tracking, user feedback, performance testing, change, and incident management. These tools can provide organizations with real-time insights into the performance and stability of their systems, allowing them to quickly detect and resolve failures.",[12,18432,18433],{},"In addition to using the right tools, organizations can also follow best practices for detecting production failures. These best practices include conducting regular health checks and setting up real-time alerts. By following these best practices, organizations can improve their ability to detect production failures and improve the stability and reliability of their software systems.",[501,18435],{},[613,18437,18439],{"id":18438},"how-oobeya-detects-production-failures-and-calculates-change-failure-rate-mttr","How Oobeya Detects Production Failures and Calculates Change Failure Rate + MTTR",[12,18441,18442,18445],{},[514,18443,469],{"href":5051,"rel":18444},[518]," is a software engineering intelligence platform that allows software development organizations to gather and analyze data from various sources to make informed decisions and optimize their development and delivery processes.",[12,18447,18448,18451,18452,18456],{},[514,18449,469],{"href":516,"rel":18450},[518]," is also a ",[514,18453,18455],{"href":7188,"rel":18454},[518],"DORA Metrics Tracking tool"," that provides valuable insights into the effectiveness of software development and delivery.",[12,18458,18459,18460,18463,18464,16775,18466,18468],{},"Oobeya has a unique mechanism for calculating ",[514,18461,3261],{"href":7188,"rel":18462},[518]," across platforms\u002Ftools (VCS, CICD, and APM-Incident Management tools) so that any organization can accurately and effortlessly track the journey of a commit from development to production deployment. Furthermore, no changes to workflows or pipelines are required; Oobeya seamlessly integrates with existing tools (GitHub, GitLab, Azure DevOps, Bitbucket, Jenkins, ",[514,18465,14184],{"href":14183},[514,18467,14159],{"href":14158},", Azure Pipelines, Releases, and more) to calculate DORA metrics.",[12,18470,18471],{},"Oobeya analyzes all deployments, detects production failures, and ties them back to production deployments.",[12,18473,18474,18475,18477],{},"Oobeya calculates all four key DORA Metrics. The ",[16,18476,859],{}," (CFR) is the percentage of deployments causing a failure in production. This metric provides a clear and concise representation of the stability and reliability of software systems. Oobeya uses the health status of each deployment to calculate the CFR metric.",[18479,18480,18481],"figure",{},[12,18482,18483,18487],{},[4866,18484],{"alt":18485,"src":18486},"Oobeya DORA Metrics — Change Failure Rate CFR","\u002Fassets\u002Fblog\u002F1_FIq4QEUhXQ6vtVllmaMIfQ.png"," Oobeya DORA Metrics — Change Failure Rate CFR",[12,18489,18490,18491,5502,18494,18497],{},"In Oobeya, each analyzed production deployment has a health status, which is either ",[16,18492,18493],{},"Success",[16,18495,18496],{},"Failure",". Oobeya sets the health status of each deployment by using four methods: manual health status setting, API call, hotfix pattern detection, and tracking incidents from APM\u002FIncident Management tools.",[52,18499,18501],{"id":18500},"_1-setting-health-statusmanually","1- Setting health status manually",[12,18503,18504],{},"In this method, the health status of each deployment is set manually by a user. This method is useful when there is a need for verification, for example, when there is a complex deployment that involves multiple systems and applications or where you don’t have any mechanism to detect and track failures automatically by the tools.",[18479,18506,18507],{},[12,18508,18509,18513],{},[4866,18510],{"alt":18511,"src":18512},"Setting deployment health status manually","\u002Fassets\u002Fblog\u002F1_hdjzQWRcLk1aGbmA8W_-mQ.png"," Setting deployment health status manually",[52,18515,18517],{"id":18516},"_2-setting-health-status-via-an-apicall","2- Setting health status via an API call",[12,18519,18520],{},"Oobeya provides an API that can be used to set the health status of each deployment.",[52,18522,18524],{"id":18523},"_3-detecting-hotfix-naming-patterns-in-the-branch-name-pr-and-deployment-title","3- Detecting hotfix naming patterns in the branch name, PR, and deployment title",[12,18526,18527],{},"To identify hotfix deployments, Oobeya looks for naming patterns in the branch name, Pull Request title, and deployment title. Because hotfix deployments are used to fix critical production issues, Oobeya sets the health status of previous deployments to Failure.",[18479,18529,18530],{},[12,18531,18532,18536],{},[4866,18533],{"alt":18534,"src":18535},"Setting naming patterns","\u002Fassets\u002Fblog\u002F1_xsxLsIYniQwdFEBrwYLvpg.png"," Setting naming patterns",[18479,18538,18539],{},[12,18540,18541,18545],{},[4866,18542],{"alt":18543,"src":18544},"Automatically detected Failure","\u002Fassets\u002Fblog\u002F1_0IA_EDbMCR6B_FGfsoSHaw.png"," Automatically detected Failure",[52,18547,18549],{"id":18548},"_4-tracking-incidents-from-application-performance-incident-management-tools","4- Tracking incidents from Application Performance \u002F Incident Management tools",[12,18551,18552,18553,18557],{},"Oobeya integrates with ",[514,18554,18556],{"href":12472,"rel":18555},[518],"Application Performance Management (APM) and Incident Management tools"," to track incidents in production. If these tools detect an incident in production, Oobeya sets the health status of the most recent deployment prior to the incident to Failure.",[18479,18559,18560],{},[12,18561,18562,18566],{},[4866,18563],{"alt":18564,"src":18565},"Oobeya — DORA Metrics Incident Source","\u002Fassets\u002Fblog\u002F1_lpUoOXNdUjzQWdaI1oSfZQ.png"," Oobeya — DORA Metrics Incident Source",[18479,18568,18569],{},[12,18570,18571,18575,18576,18578],{},[4866,18572],{"alt":18573,"src":18574},"Automatically detected by tracking New Relic Incidents and Alerts","\u002Fassets\u002Fblog\u002F1_R74N6qJBZKPK3OqZnOV3xQ.png"," Automatically detected by tracking ",[514,18577,14208],{"href":14207}," incidents and alerts",[12,18580,18581],{},[791,18582,18583,18584,18586,18587,18589],{},"P.S. ",[514,18585,14208],{"href":14207}," is ready to use, and ",[514,18588,14241],{"href":14240},", Sentry, Dynatrace, PagerDuty, OpsGenie, ServiceNow, and more are coming soon.",[12,18591,18592],{},"In addition to automatically and manually setting the health status of deployments and calculating the CFR, Oobeya also provides other three key DORA Metrics and detailed insights into each deployment. This includes information about the deployment time, deployment size (small, medium, large, and gigantic), contributors, and the link to the deployment pipeline. You can group multiple analyses to get a holistic view of DORA Metrics across your organization in the Oobeya Engineering Intelligence Platform.",[12,18594,18595],{},"In conclusion, detecting production failures is the most critical and challenging component of tracking DORA metrics. While it can be challenging, organizations can overcome these challenges by using the right tools and following best practices. By improving their ability to detect and resolve production failures, organizations can deliver value to customers more effectively and improve the overall performance of their DevOps practices.",{"title":526,"searchDepth":527,"depth":527,"links":18597},[18598,18599,18600,18601],{"id":18387,"depth":527,"text":18388},{"id":18412,"depth":527,"text":18413},{"id":18423,"depth":527,"text":18424},{"id":18438,"depth":527,"text":18439,"children":18602},[18603,18604,18605,18606],{"id":18500,"depth":530,"text":18501},{"id":18516,"depth":530,"text":18517},{"id":18523,"depth":530,"text":18524},{"id":18548,"depth":530,"text":18549},[1232,541],"2023-01-30","Discover how Oobeya, the DORA Metrics Tracking tool, effectively detects production failures by using manual and automated methods.",{},"\u002Fblog\u002Fdora-metrics-tracking-how-to-effectively-detect-production-failures",{"title":18377,"description":18609},"blog\u002Fdora-metrics-tracking-how-to-effectively-detect-production-failures",[8440,696],"Y8yy7-hUabzCdb1y5gQdmNaOgPvae_BP3SKJRmoVU-A",{"id":18617,"title":18618,"author":4245,"avatar":575,"body":18619,"categories":18654,"createAt":542,"date":18655,"description":18625,"extension":545,"meta":18656,"navigation":547,"path":18657,"position":542,"seo":18658,"spotImage":542,"spotText":542,"stem":18659,"tags":18660,"__hash__":18661},"blog\u002Fblog\u002Foobeya-2022-recap.md","Oobeya 2022 Recap - Blog",{"type":9,"value":18620,"toc":18652},[18621,18626,18629,18632,18639,18646],[3354,18622,18623],{},[12,18624,18625],{},"It's been a whirlwind of a year for Oobeya, and we're excited to share with you all of the amazing achievements and milestones we've hit in 2022.",[12,18627,18628],{},"One of the biggest highlights for us this year was the significant expansion of our customer base, with Oobeya now being used in 6 continents (it was only two in 2021). This demonstrates our desire to create a global solution for any software dev organization across the world. We've acquired new customers from various countries, further showcasing the effectiveness of what we offer.",[12,18630,18631],{},"The Oobeya Engineering Team has also made significant progress this year by developing a new approach for accurately calculating DORA metrics (VCS x CICD x APM). As a result, Oobeya is now the most accurate DORA metrics tracking tool on the market.",[12,18633,18634,18638],{},[4866,18635],{"alt":18636,"src":18637},"Oobeya engineering metrics and DORA analytics view","\u002Fassets\u002Fblog\u002Foobeya-dora-2-1024x539.png","In addition to DORA metrics, we've also expanded our capabilities to track over 50 engineering metrics across software development and delivery processes. But we didn't stop there – we've also implemented a new feature (which will be released in January) that detects the symptoms of software development and delivery automatically by leveraging these metrics. It'll be a game-changer in the industry and we're thrilled to see the impact it's having.",[12,18640,18641,18645],{},[4866,18642],{"alt":18643,"src":18644},"Oobeya symptoms and engineering signals view","\u002Fassets\u002Fblog\u002Fsypmtoms-oobeya-1024x472.png","Overall, 2022 has been a fantastic year for Oobeya, and we're grateful for the support of our customers. We can't wait to see what the future holds and we hope you'll join us on this journey. Thank you for your continued support!",[12,18647,18648],{},[4866,18649],{"alt":18650,"src":18651},"Oobeya 2023 recap visual","\u002Fassets\u002Fblog\u002Foobeya-2023-1024x700.jpeg",{"title":526,"searchDepth":527,"depth":527,"links":18653},[],[4232],"2022-12-30",{},"\u002Fblog\u002Foobeya-2022-recap",{"title":18618,"description":18625},"blog\u002Foobeya-2022-recap",[8440,540,9660,541],"RRsBmKeSMrZdbEEOZULZyj0d-wyjtJegL5ylj5Tnv6w",{"id":18663,"title":18664,"author":4245,"avatar":575,"body":18665,"categories":18873,"createAt":542,"date":18875,"description":18876,"extension":545,"meta":18877,"navigation":547,"path":18878,"position":542,"seo":18879,"spotImage":542,"spotText":542,"stem":18880,"tags":18881,"__hash__":18883},"blog\u002Fblog\u002Foobeya-monthly-digest-december-2022.md","Oobeya December 2022 Monthly Digest - Blog",{"type":9,"value":18666,"toc":18861},[18667,18674,18678,18684,18687,18690,18692,18701,18705,18708,18711,18714,18716,18722,18778,18780,18784,18791,18799,18803,18810,18813,18822,18826,18833,18835,18841,18844],[18668,18669,18671],"h1",{"id":18670},"oobeya-monthly-digest",[16,18672,18673],{},"OOBEYA MONTHLY DIGEST",[52,18675,18677],{"id":18676},"december-2022","DECEMBER 2022",[613,18679,18681],{"id":18680},"happy-new-year",[16,18682,18683],{},"🎄 Happy New Year!",[12,18685,18686],{},"As we turn the page on another year, we wanted to take a moment to express our heartfelt gratitude to our valued customers. Thank you for your ongoing support and trust in our company. We are excited to see what the new year has in store and are looking forward to continuing to grow alongside you and help you achieve your goals in the coming year.",[12,18688,18689],{},"We wish you all the best in the coming year!",[501,18691],{},[613,18693,18695,1044,18698],{"id":18694},"were-committed-to-building-the-best-dora-tracking-tool",[16,18696,18697],{},"🎁 We're committed to building the best DORA Tracking tool!",[16,18699,18700],{},"🤶🎅",[12,18702,18703],{},[4866,18704],{"alt":18636,"src":18637},[12,18706,18707],{},"In 2022, Oobeya revolutionized the way DORA Metrics are calculated by creating a mechanism that utilizes VCS and CICD tools to trace the journey of a code change (commit) from development to production deployment for any organization or use case. This innovative feature positions Oobeya as a leading DORA tracking tool.",[12,18709,18710],{},"👩‍🍳 We're in the process of developing new capabilities that will allow Oobeya to seamlessly detect production failures by aggregating data from multiple incident tracking sources including APM tools (e.g. NewRelic, Sentry, DataDog, Dynatrace) and incident management tools (e.g. PagerDuty, OpsGenie, ServiceNow).",[12,18712,18713],{},"💎 In 2023, we're committed to building the most accurate, flexible, and effortless way of tracking DORA Metrics!",[501,18715],{},[613,18717,18719],{"id":18718},"dec-22-new-feature-highlights",[16,18720,18721],{},"Dec '22 - New Feature Highlights ✨",[70,18723,18724,18738,18751,18765,18773],{},[73,18725,18726,1044,18729,18737],{},[16,18727,18728],{},"DORA:",[16,18730,18731,18732],{},"Azure DevOps ",[514,18733,18736],{"href":18734,"rel":18735},"https:\u002F\u002Fazure.microsoft.com\u002Fen-us\u002Fproducts\u002Fdevops\u002Fpipelines\u002F",[518],"Pipelines"," integration is now ready to use! With this feature, Oobeya now supports both Azure Pipelines and Releases!",[73,18739,18740,18742,18743,18746,18747,18750],{},[16,18741,18728],{}," We launched a new ",[16,18744,18745],{},"failure detection"," feature that allows you to ",[16,18748,18749],{},"automatically detect failures by Git branch and Deployment title naming patterns","!",[73,18752,18753,18742,18755,18746,18757,18764],{},[16,18754,18728],{},[16,18756,18745],{},[16,18758,18759,18760],{},"automatically detect failures by ",[514,18761,14208],{"href":18762,"rel":18763},"https:\u002F\u002Fnewrelic.com\u002Fplatform\u002Falerts",[518]," Incidents & Alerts!",[73,18766,18767,18769,18770,611],{},[16,18768,18336],{}," Oobeya now displays the historical timeline of the ",[16,18771,18772],{},"Efficient Development Ratio",[73,18774,18775],{},[791,18776,18777],{},"and more...",[501,18779],{},[52,18781,18783],{"id":18782},"new-blog-post-how-to-reduce-lead-time-for-changes-optimizing-dora-metrics-1","📗 NEW BLOG POST | How To Reduce Lead Time For Changes | Optimizing DORA Metrics -1",[12,18785,18786,18790],{},[4866,18787],{"alt":18788,"src":18789},"Lead time improvement guide cover","\u002Fassets\u002Fblog\u002Foobeya-reduce-lead-time-linkedin-300x300.png","A guide to help teams reduce the Lead Time For Changes (DORA Metrics) metric to optimize software development and delivery processes. * Optimizing Coding Time * Optimizing Code Review Time * Optimizing Waiting For Deploy Time * Optimizing Deployment Time",[12,18792,18793,8398],{},[16,18794,18795],{},[514,18796,18798],{"href":10444,"rel":18797},[518],"READ THE FULL ARTICLE >",[52,18800,18802],{"id":18801},"oobeya-cto-craft-conf-identifying-waste-symptoms-of-software-development-delivery","💬 OOBEYA @ CTO CRAFT CONF | Identifying Waste: Symptoms of Software Development & Delivery",[12,18804,18805,18809],{},[4866,18806],{"alt":18807,"src":18808},"Oobeya CTO Craft Winter 2022 talk visual","\u002Fassets\u002Fblog\u002Foobeya-ctocraft-300x300.png","We gave a talk at the CTO Craft Winter 2022 Conference on \"Identifying Waste: Symptoms of Software Development and Delivery\".",[12,18811,18812],{},"We are honored to be a part of this great event and share the vision behind our product with 500+ CTOs all around the world.",[12,18814,18815,8398],{},[16,18816,18817],{},[514,18818,18821],{"href":18819,"rel":18820},"https:\u002F\u002Fctocraft.com\u002Fblog\u002Fa-recap-of-cto-craft-con-winter-2022\u002F",[518],"READ THE RECAP OF CTO CONF >",[52,18823,18825],{"id":18824},"meetup-dora-metrics-moving-beyond-metrics","💬 MEETUP | DORA Metrics & Moving Beyond Metrics",[12,18827,18828,18832],{},[4866,18829],{"alt":18830,"src":18831},"Talk visual about using engineering metrics wisely","\u002Fassets\u002Fblog\u002F222-300x199.png","Everybody is talking about DORA metrics, Pull Request metrics, Agile metrics, and more. Metrics were measured first. And we began tracking them. What comes next? In our talk, we briefly discussed the following question: How can we build a comprehensive approach to use metrics wisely?",[501,18834],{},[613,18836,18838],{"id":18837},"lets-get-the-show-on-the-road",[16,18839,18840],{},"LET'S GET THE SHOW ON THE ROAD !",[12,18842,18843],{},"If you’re interested in learning more about Oobeya, you can reach out to us for a 21-day free trial and get started today!",[12,18845,18846,18847,1044,18854],{},"And as always, if you have any thoughts or feedback about Oobeya, please don’t hesitate to reach out to us. ",[16,18848,18849],{},[514,18850,18853],{"href":18851,"rel":18852},"https:\u002F\u002Foobeya.io\u002Fcontact\u002F",[518],"TALK TO US",[16,18855,18856],{},[514,18857,18860],{"href":18858,"rel":18859},"https:\u002F\u002Foobeya.io\u002Fschedule-a-new-demo\u002F?utm_source=email&utm_medium=button",[518],"BOOK A DEMO",{"title":526,"searchDepth":527,"depth":527,"links":18862},[18863,18864,18865,18867,18872],{"id":18676,"depth":530,"text":18677},{"id":18680,"depth":527,"text":18683},{"id":18694,"depth":527,"text":18866},"🎁 We're committed to building the best DORA Tracking tool! 🤶🎅",{"id":18718,"depth":527,"text":18721,"children":18868},[18869,18870,18871],{"id":18782,"depth":530,"text":18783},{"id":18801,"depth":530,"text":18802},{"id":18824,"depth":530,"text":18825},{"id":18837,"depth":527,"text":18840},[4232,1232,18874],"product-updates","2022-12-23","We're committed to building the most accurate, flexible, and effortless way of tracking DORA Metrics! Automated Failure Detection...",{},"\u002Fblog\u002Foobeya-monthly-digest-december-2022",{"title":18664,"description":18876},"blog\u002Foobeya-monthly-digest-december-2022",[18882,2620,8865,8440,9660,18874,541],"azure-devops","Y4HAvFjFAzCz2eGlGXz8EK-B4Gtqh7CfDuCFe4mG220",{"id":18885,"title":18886,"author":4245,"avatar":575,"body":18887,"categories":19351,"createAt":542,"date":19352,"description":19353,"extension":545,"meta":19354,"navigation":547,"path":19355,"position":542,"seo":19356,"spotImage":542,"spotText":542,"stem":19357,"tags":19358,"__hash__":19362},"blog\u002Fblog\u002Fhow-to-reduce-lead-time-for-changes-dora-metrics.md","How To Reduce Lead Time For Changes? - Blog",{"type":9,"value":18888,"toc":19333},[18889,18894,18903,18910,18913,18916,18922,18929,18932,18941,18950,18954,18976,18983,18985,18988,18991,18994,19003,19005,19011,19016,19025,19029,19035,19044,19047,19051,19054,19080,19092,19094,19098,19107,19115,19118,19122,19142,19146,19166,19182,19191,19195,19212,19216,19239,19241,19245,19248,19251,19254,19264,19270,19273,19304,19313,19320,19323],[3354,18890,18891],{},[12,18892,18893],{},"A guide to help teams reduce the Lead Time For Changes (DORA Metrics) metric.",[12,18895,18896,18897,23,18900,18902],{},"In this article, we will take a closer look at one of ",[514,18898,3261],{"href":7188,"rel":18899},[518],[16,18901,13285],{}," (Change Lead Time), and how it can be reduced to optimize software development and delivery processes.",[12,18904,18905,18909],{},[4866,18906],{"alt":18907,"src":18908,"title":18907},"Optimizing Software Engineering Processes","\u002Fassets\u002Fblog\u002F1_S7oM30zQyCw5s5F_w7L2lQ.png"," Optimizing Software Engineering Processes",[12,18911,18912],{},"Metrics are a way of measuring something. They are used to understand the current situation, identify trends, predict future outcomes and make better decisions.",[12,18914,18915],{},"DORA metrics are the best way to measure and improve the health of the software delivery process.",[613,18917,18919],{"id":18918},"what-are-dorametrics",[16,18920,18921],{},"What Are DORA Metrics?",[12,18923,18924,18928],{},[514,18925,848],{"href":18926,"rel":18927},"https:\u002F\u002Foobeya.io\u002Fdora-metrics-four-key\u002F?utm_source=medium&utm_content=lead-time",[518]," have been widely adopted by organizations across the world. They are now the standard for measuring software value delivery.",[12,18930,18931],{},"DORA metrics are the way to go if you want to measure overall software delivery performance. But what are they basically?",[12,18933,18934,18937,18938,3444],{},[16,18935,18936],{},"Read my article"," on ‘How To Measure DORA Metrics Accurately’ ",[514,18939,4354],{"href":11456,"rel":18940},[518],[12,18942,18943],{},[514,18944,18946,18949],{"href":11456,"rel":18945,"title":11456},[518],[16,18947,18948],{},"How to Measure DORA Metrics Accurately? | Oobeya Software Engineering Intelligence"," _DORA metrics are quite popular in the industry. However, working with them is extremely difficult. Let's take a look at…_oobeya.io",[52,18951,18953],{"id":18952},"dora-metrics-aka-accelerate-metrics-four-keymetrics","DORA Metrics (a.k.a. Accelerate Metrics & Four Key Metrics)",[1520,18955,18956,18962,18967,18971],{},[73,18957,18958,18961],{},[16,18959,18960],{},"Lead Time For Changes:"," The amount of time it takes a commit to get into production.",[73,18963,18964,18966],{},[16,18965,15886],{}," How often an organization successfully releases to production. High-performing software teams release often and in small batches.",[73,18968,18969,15905],{},[16,18970,15904],{},[73,18972,18973,18975],{},[16,18974,17061],{}," How long it takes an organization to recover from a failure in production.",[12,18977,18978,18979],{},"Learn more from Google Cloud’s DORA research page: ",[514,18980,18981],{"href":18981,"rel":18982},"https:\u002F\u002Fwww.devops-research.com\u002Fresearch.html",[518],[501,18984],{},[12,18986,18987],{},"Organizations should measure and track all these four key metrics together to make better decisions and accelerate their value delivery performance.",[12,18989,18990],{},"If you only focus on one or two of these metrics, you will probably make poor decisions. Assume you focused on increasing deployment frequency and decided to reduce testing efforts in order to make more production deployments in a shorter period of time. Your organization\u002Fproduct will most likely lose stability and reliability as a result of your decision.",[12,18992,18993],{},"Focusing on four DORA Metrics is the best and only thing you can do to create a high-performing organization.",[12,18995,18996,18997,1044,19000,19002],{},"But now we will talk about ",[16,18998,18999],{},"reducing the",[16,19001,13285],{}," (while taking care of all DORA Metrics as well).",[501,19004],{},[18668,19006,19008],{"id":19007},"what-is-the-lead-time-forchanges",[16,19009,19010],{},"What is the Lead Time For Changes?",[12,19012,19013,19014,611],{},"The interval between a code change and its release to the end users is considered ",[16,19015,13285],{},[19017,19018,19023],"pre",{"className":19019,"code":19021,"language":19022},[19020],"language-text","Lead Time For Changes = [Production Deployment Time] - [First Commit Time of all changes]\n","text",[739,19024,19021],{"__ignoreMap":526},[613,19026,19028],{"id":19027},"the-anatomy-of-the-leadtime","The Anatomy of the Lead Time",[12,19030,19031,19032,19034],{},"The image below represents the anatomy of the ",[16,19033,4919],{}," metric.",[18479,19036,19037],{},[12,19038,19039,19043],{},[4866,19040],{"alt":19041,"src":19042},"Lead Time Breakdown","\u002Fassets\u002Fblog\u002F1_7r-mZIZvJu4hzIx9LVfKMw.png"," Lead Time Breakdown",[12,19045,19046],{},"Let’s dive into this breakdown to understand how we can reduce Lead Time For Changes.",[613,19048,19050],{"id":19049},"the-stages-of-lead-time-forchanges","The Stages of Lead Time For Changes",[12,19052,19053],{},"Lead Time For Changes mostly measures friction in the coding, code review, and CI\u002FCD processes.",[1520,19055,19056,19062,19068,19074],{},[73,19057,19058,19061],{},[16,19059,19060],{},"Coding Time:"," The time elapsed between the First commit and PR opened.",[73,19063,19064,19067],{},[16,19065,19066],{},"Code Review Time:"," The time elapsed between the PR opened and PR merged.",[73,19069,19070,19073],{},[16,19071,19072],{},"Waiting For Deploy:"," The time elapsed between the PR merged and Deployment pipeline started.",[73,19075,19076,19079],{},[16,19077,19078],{},"Deployment Time:"," The time elapsed between the Deployment started and Deployment finished successfully.",[18479,19081,19082],{},[12,19083,19084,1044,19088,19091],{},[4866,19085],{"alt":19086,"src":19087},"https:\u002F\u002Foobeya.io — DORA Metrics Tracking","\u002Fassets\u002Fblog\u002F1_vdAsf0iEGB9EHO2lal4Ytw.png",[514,19089,5051],{"href":5051,"rel":19090},[518]," — DORA Metrics Tracking",[501,19093],{},[613,19095,19097],{"id":19096},"how-to-reduce-the-lead-time-forchanges","How To Reduce the Lead Time For Changes",[12,19099,19100,19101,247,19104,611],{},"The best thing you can do to reduce Change Lead Time is to ",[16,19102,19103],{},"identify software development waste",[16,19105,19106],{},"bottlenecks",[12,19108,19109,19110,18750],{},"Identifying waste and working on reducing it will automatically reduce the lead time and ",[514,19111,19114],{"href":19112,"rel":19113},"https:\u002F\u002Foobeya.io\u002Foptimize-software-engineering\u002F?utm_source=medium&utm_content=lead-time",[518],"increase the development teams’ productivity",[12,19116,19117],{},"Let’s see how we can optimize the stages of Lead Time for changes:",[52,19119,19121],{"id":19120},"optimize-codingtime","Optimize Coding Time",[70,19123,19124,19127,19130,19133,19136,19139],{},[73,19125,19126],{},"Reduce rework in the coding cycles (but first measure Rework)",[73,19128,19129],{},"Work with small batches",[73,19131,19132],{},"Avoid unnecessarily complex solutions (needs technical and domain knowledge)",[73,19134,19135],{},"Avoid multitasking and context switching",[73,19137,19138],{},"Write clear requirements",[73,19140,19141],{},"Fasten the feedback cycle (always the most critical one)",[52,19143,19145],{"id":19144},"optimize-code-reviewtime","Optimize Code Review Time",[70,19147,19148,19151,19154,19157,19160,19163],{},[73,19149,19150],{},"Keep it small. If reviewers decide to battle with your changes, it will take too much time to review the PR.",[73,19152,19153],{},"Code faster. Break large features into small pieces and keep the coding time short for each pull request. See the problems earlier.",[73,19155,19156],{},"Review faster. Don’t let your code changes stale to prevent potential merge conflicts.",[73,19158,19159],{},"Create a Code Review Checklist",[73,19161,19162],{},"Automate what can be automated in the code review process. Automation is the first gatekeeper of code reviews.",[73,19164,19165],{},"Be ready to be reviewed. Review yourself before submitting. Give it a clear and descriptive title and write the best description.",[12,19167,19168,11228,19171,1044,19174,19180],{},[16,19169,19170],{},"Check out my article",[791,19172,19173],{},"Code Reviews",[514,19175,19178],{"href":19176,"rel":19177},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fwhy-code-reviews-should-be-your-favorite-activity\u002F",[518],[16,19179,4354],{},[16,19181,3444],{},[12,19183,19184],{},[514,19185,19187,19190],{"href":19176,"rel":19186,"title":19176},[518],[16,19188,19189],{},"Why Code Reviews Should Be Your Favorite Activity | Oobeya Software Engineering Intelligence"," _Tips for being a better code reviewer, creating better pull requests, and accelerating with pull request analytics…_oobeya.io",[52,19192,19194],{"id":19193},"optimize-waiting-for-deploytime","Optimize Waiting For Deploy Time",[70,19196,19197,19200,19203,19206,19209],{},[73,19198,19199],{},"Automate your CI\u002FCD process.",[73,19201,19202],{},"Increase your test automation coverage.",[73,19204,19205],{},"Create a strong set of smoke tests, regression tests, etc.",[73,19207,19208],{},"Eliminate manual approval processes.",[73,19210,19211],{},"Reduce pipeline queue time. Improve your CI\u002FCD tooling performance and capability.",[52,19213,19215],{"id":19214},"optimize-deployment-time","Optimize Deployment Time",[70,19217,19218,19221,19224,19227,19230,19233,19236],{},[73,19219,19220],{},"Identify friction in the CI\u002FCD process.",[73,19222,19223],{},"Reduce CI\u002FCD pipeline duration.",[73,19225,19226],{},"Cache build dependencies.",[73,19228,19229],{},"Optimize container image size.",[73,19231,19232],{},"Check the network latency.",[73,19234,19235],{},"Optimize resources.",[73,19237,19238],{},"Review pipeline architecture.",[501,19240],{},[613,19242,19244],{"id":19243},"yes-i-know-where-i-need-to-improve","“Yes, I know where I need to improve!”",[12,19246,19247],{},"These are the magic words that open the doors for effective and sustainable improvement.",[12,19249,19250],{},"If you want to improve the health and performance of your team, you should start by measuring metrics first. Then you’ll gain insights into what’s going on in your development and delivery cycles (by utilizing trends, benchmarks, patterns, anti-patterns, friction, risks, symptoms, and so on).",[12,19252,19253],{},"You will have the keys to optimizing system performance, team health, developer happiness, productivity, and organizational success once you start saying, ‘yes, I know where I need to improve’.",[12,19255,19256,19260,19261],{},[4866,19257],{"alt":19258,"src":19259},"Yes, I know where I need to improve! — https:\u002F\u002Foobeya.io ","\u002Fassets\u002Fblog\u002F1_P9Dip6Dc4Bg-yA3MU_av-g.png"," Yes, I know where I need to improve! — ",[514,19262,5051],{"href":5051,"rel":19263},[518],[52,19265,19267],{"id":19266},"ready-to-get-started-now",[16,19268,19269],{},"🏃 READY TO GET STARTED NOW?",[12,19271,19272],{},"If you’re not familiar with Oobeya, it’s a software engineering intelligence platform that helps software development teams and leaders track and visualize their entire development and delivery processes.",[12,19274,19275,19276,19279,19280,19283,19284,19287,19288,19291,19292,19295,19296,19299,19300,611],{},"Rather than ",[791,19277,19278],{},"just metric tracking",", ",[514,19281,469],{"href":516,"rel":19282},[518]," (",[791,19285,19286],{},"means large room in Japanese",") offers various features and modules (",[791,19289,19290],{},"team health\u002Fsymptoms, dashboards, gamification, git analytics, PR analytics…",") that aim to provide complete ",[16,19293,19294],{},"visibility into software development"," and ",[16,19297,19298],{},"delivery"," processes with more than 20 SDLC tool integrations. Learn more about ",[514,19301,19303],{"href":516,"rel":19302},[518],"Oobeya Engineering Intelligence Platform",[4331,19305,19307,19308,19312],{"id":19306},"if-youre-interested-in-learning-more-about-oobeya-you-canreach-out-to-usfor-a-free-trial-and-get-started-today","If you’re interested in learning more about Oobeya, you can ",[514,19309,19311],{"href":18851,"rel":19310},[518],"Reach Out To Us"," for a free trial and get started today!",[52,19314,19316,19317],{"id":19315},"ready-to-learn-more","🏃 ",[16,19318,19319],{},"READY TO LEARN MORE?",[12,19321,19322],{},"Do you want to see all features in action with a Product Demo and talk about the product roadmap?",[12,19324,19325,19326,19332],{},"Click and ",[514,19327,19330],{"href":19328,"rel":19329},"https:\u002F\u002Foobeya.io\u002Fschedule-a-new-demo\u002F?utm_source=releasenotes&utm_medium=june2022",[518],[16,19331,4824],{}," now.",{"title":526,"searchDepth":527,"depth":527,"links":19334},[19335,19338,19339,19340,19346],{"id":18918,"depth":527,"text":18921,"children":19336},[19337],{"id":18952,"depth":530,"text":18953},{"id":19027,"depth":527,"text":19028},{"id":19049,"depth":527,"text":19050},{"id":19096,"depth":527,"text":19097,"children":19341},[19342,19343,19344,19345],{"id":19120,"depth":530,"text":19121},{"id":19144,"depth":530,"text":19145},{"id":19193,"depth":530,"text":19194},{"id":19214,"depth":530,"text":19215},{"id":19243,"depth":527,"text":19244,"children":19347},[19348,19349],{"id":19266,"depth":530,"text":19269},{"id":19315,"depth":530,"text":19350},"🏃 READY TO LEARN MORE?",[1232,16837,541],"2022-11-15","Learn how to reduce lead time for changes and improve software delivery flow with practical DORA guidance.",{},"\u002Fblog\u002Fhow-to-reduce-lead-time-for-changes-dora-metrics",{"title":18886,"description":19353},"blog\u002Fhow-to-reduce-lead-time-for-changes-dora-metrics",[19359,11825,8865,8440,19360,19361,9660,541],"continuous-delivery","four-key-metrics","lead-time","c2PLDndKhATA9scjVRLrzwAWkGQvLCuZep-3a-PihWs",{"id":19364,"title":19365,"author":4245,"avatar":575,"body":19366,"categories":19449,"createAt":542,"date":19450,"description":19451,"extension":545,"meta":19452,"navigation":547,"path":19453,"position":542,"seo":19454,"spotImage":542,"spotText":542,"stem":19455,"tags":19456,"__hash__":19463},"blog\u002Fblog\u002Ffaqs-2-can-we-have-gitlab-and-github-as-data-sources-together.md","Can We Have GitLab And GitHub As Data Sources At The Same Time In Oobeya? - Blog",{"type":9,"value":19367,"toc":19443},[19368,19371,19378,19382,19385,19389,19409,19416,19421,19423,19430,19434,19436],[12,19369,19370],{},"Yes! You can add and connect multiple data sources such as GitHub and GitLab to Oobeya. Then, you can use all data sources together and analyze your Git repositories.",[12,19372,19373,19377],{},[4866,19374],{"alt":19375,"src":19376},"Oobeya Gitwiser Multiple Data Sources","\u002Fassets\u002Fblog\u002Foobeya-git-1024x528.png"," Oobeya Gitwiser Multiple Data Sources",[613,19379,19381],{"id":19380},"how-it-works-oobeya-github-and-gitlab-integrations","How It Works: Oobeya GitHub and GitLab integrations",[12,19383,19384],{},"Oobeya’s Development Analytics module collects and transforms data (commits, pull requests, branches, repositories, contributors) from various VCS tools into a common modal.",[613,19386,19388],{"id":19387},"supported-version-control-system-vcs-tools-github-gitlab-and-more","Supported Version Control System (VCS) Tools: GitHub, GitLab, and more",[12,19390,19391,19392,19396,19397,27,19401,19405,19406,611],{},"GitHub, ",[514,19393,6908],{"href":19394,"rel":19395},"http:\u002F\u002Fgitlab.com",[518],", Atlassian ",[514,19398,18270],{"href":19399,"rel":19400},"https:\u002F\u002Fbitbucket.org\u002Fproduct",[518],[514,19402,6905],{"href":19403,"rel":19404},"https:\u002F\u002Fazure.microsoft.com\u002Fen-us\u002Fproducts\u002Fdevops\u002F",[518]," (including all enterprise, server, and cloud services\u002Fplans). See all integrations ",[514,19407,4354],{"href":8313,"rel":19408},[518],[12,19410,19411,19415],{},[4866,19412],{"alt":19413,"src":19414},"Oobeya VCS Addons","\u002Fassets\u002Fblog\u002Fgit-vcs-addons-1024x442.png"," Oobeya VCS Addons",[613,19417,19418],{"id":19266},[16,19419,19420],{},"🏃 READY TO GET STARTED NOW?",[12,19422,19272],{},[4331,19424,19307,19426,19429],{"id":19425},"if-youre-interested-in-learning-more-about-oobeya-you-canreach-out-to-us-for-a-free-trial-and-get-started-today",[514,19427,19311],{"href":18851,"rel":19428},[518]," for a free trial and get started today!",[613,19431,19316,19432],{"id":19315},[16,19433,19319],{},[12,19435,19322],{},[12,19437,19325,19438,19332],{},[514,19439,19441],{"href":19328,"rel":19440},[518],[16,19442,4824],{},{"title":526,"searchDepth":527,"depth":527,"links":19444},[19445,19446,19447,19448],{"id":19380,"depth":527,"text":19381},{"id":19387,"depth":527,"text":19388},{"id":19266,"depth":527,"text":19420},{"id":19315,"depth":527,"text":19350},[4008,16837],"2022-10-31","We use both GitLab and GitHub in our SDLC. Can we have GitLab and GitHub as data sources at the same time in Oobeya?",{},"\u002Fblog\u002Ffaqs-2-can-we-have-gitlab-and-github-as-data-sources-together",{"title":19365,"description":19451},"blog\u002Ffaqs-2-can-we-have-gitlab-and-github-as-data-sources-together",[18882,8865,540,19457,19458,19459,19460,19461,9660,19462],"git-analytics","github","github-enterprise","gitlab","gitwiser","pull-request","VcKMTsmuFW0zDsKYaLNTxLEqSdAj1YUCYHb8p7JIuV0",{"id":19465,"title":19466,"author":4245,"avatar":575,"body":19467,"categories":19579,"createAt":542,"date":19580,"description":19581,"extension":545,"meta":19582,"navigation":547,"path":19583,"position":542,"seo":19584,"spotImage":542,"spotText":542,"stem":19585,"tags":542,"__hash__":19586},"blog\u002Fblog\u002Ffaqs-1-does-oobeya-have-pull-request-statistics.md","Does Oobeya Have Pull Request Statistics? - Blog",{"type":9,"value":19468,"toc":19573},[19469,19475,19499,19506,19522,19529,19542,19549,19553,19555,19560,19564,19566],[613,19470,19472],{"id":19471},"faqs-1-does-oobeya-have-pull-request-stats",[16,19473,19474],{},"FAQs -1: Does Oobeya have Pull Request stats?",[12,19476,19477,19478,23,19481,23,19483,23,19486,23,19489,23,19492,23,19495,19498],{},"Yes! Oobeya analyzes all Pull Requests in the specified branches and generates metrics such as ",[16,19479,19480],{},"PR Review Time",[16,19482,15737],{},[16,19484,19485],{},"Merge Time",[16,19487,19488],{},"PR Size",[16,19490,19491],{},"Authors",[16,19493,19494],{},"Comments",[16,19496,19497],{},"% of PRs Merged Within Goal",", etc.",[12,19500,19501,19505],{},[4866,19502],{"alt":19503,"src":19504},"Oobeya Pull Request Analytics","\u002Fassets\u002Fblog\u002Foobeya-pr-metrics-1024x526.png"," Oobeya Pull Request Analytics",[12,19507,19508,19509,19512,19513,23,19516,27,19519,611],{},"Oobeya also automatically detects the following ",[16,19510,19511],{},"risk labels"," for open Pull Requests: ",[16,19514,19515],{},"oversized",[16,19517,19518],{},"overdue",[16,19520,19521],{},"stale",[12,19523,19524,19528],{},[4866,19525],{"alt":19526,"src":19527},"Oobeya Pull Requests Risks","\u002Fassets\u002Fblog\u002Foobeya-pr-risks-1024x150.png"," Oobeya Pull Requests Risks",[12,19530,19531,19532,1044,19535,247,19538,19541],{},"You can ",[16,19533,19534],{},"make a",[16,19536,19537],{},"team agreement",[16,19539,19540],{},"set goals"," for your pull request metrics at the repository and team levels.",[12,19543,19544,19548],{},[4866,19545],{"alt":19546,"src":19547},"Oobeya Pull Request Team Agreements","\u002Fassets\u002Fblog\u002Foobeya-pr-goals-1024x521.png"," Oobeya Pull Request Team Agreements",[52,19550,19551],{"id":19266},[16,19552,19420],{},[12,19554,19272],{},[4331,19556,19307,19557,19312],{"id":19306},[514,19558,19311],{"href":18851,"rel":19559},[518],[52,19561,19316,19562],{"id":19315},[16,19563,19319],{},[12,19565,19322],{},[12,19567,19325,19568,19332],{},[514,19569,19571],{"href":19328,"rel":19570},[518],[16,19572,4824],{},{"title":526,"searchDepth":527,"depth":527,"links":19574},[19575],{"id":19471,"depth":527,"text":19474,"children":19576},[19577,19578],{"id":19266,"depth":530,"text":19420},{"id":19315,"depth":530,"text":19350},[4008,16837],"2022-10-26","Does Oobeya have Pull Request stats? Yes! Oobeya analyzes all Pull Requests in the specified branches and generates metrics such as...",{},"\u002Fblog\u002Ffaqs-1-does-oobeya-have-pull-request-statistics",{"title":19466,"description":19581},"blog\u002Ffaqs-1-does-oobeya-have-pull-request-statistics","0o1AW9j8hFmWQWXN3O7Sl7GFKFuHE0baMSVimlXaHw0",{"id":19588,"title":19589,"author":4245,"avatar":575,"body":19590,"categories":19922,"createAt":542,"date":19923,"description":19924,"extension":545,"meta":19925,"navigation":547,"path":19926,"position":542,"seo":19927,"spotImage":542,"spotText":542,"stem":19928,"tags":19929,"__hash__":19933},"blog\u002Fblog\u002Foobeya-august-2022-updates.md","Oobeya August 2022 Product Updates - Blog",{"type":9,"value":19591,"toc":19914},[19592,19598,19602,19633,19635,19641,19647,19650,19657,19664,19684,19704,19718,19720,19726,19738,19745,19762,19764,19769,19776,19779,19782,19789,19791,19797,19804,19807,19813,19820,19823,19831,19833,19838,19841,19843,19849,19852,19866,19869,19876,19882,19896,19898],[18668,19593,19595],{"id":19594},"oobeya-august-2022-updates-summary",[16,19596,19597],{},"Oobeya August 2022 Updates Summary",[4331,19599,19601],{"id":19600},"we-are-super-excited-to-share-our-new-features-and-improvements-with-you","🎉  We are super excited to share our new features and improvements with you!",[70,19603,19604,19607,19613,19616,19619,19627,19630],{},[73,19605,19606],{},"TeamCity integration is ready!",[73,19608,19609,19610,19612],{},"Calculate and track ",[514,19611,14184],{"href":14183}," DORA metrics!",[73,19614,19615],{},"Oobeya Dashboard DORA Metrics Widget now displays all DORA Metrics!",[73,19617,19618],{},"Exclude deployments to calculate DORA Metrics more accurately!",[73,19620,19621,19622,19626],{},"Select ",[514,19623,19625],{"href":19624},"\u002Fglossary\u002Fgitwiser","Gitwiser"," analysis period to optimize analysis performance",[73,19628,19629],{},"New Pull Request metrics are ready to use! Improve your teams' code review cycles!",[73,19631,19632],{},"Manage Team Members easily!",[501,19634],{},[18668,19636,19638],{"id":19637},"new-features",[16,19639,19640],{},"​🎁 NEW FEATURES",[613,19642,19644],{"id":19643},"oobeya-teamcity-integration-is-ready",[16,19645,19646],{},"Oobeya TeamCity integration is ready!",[12,19648,19649],{},"If you're using TeamCity for your CI\u002FCD needs, we have some great news for you - the Oobeya TeamCity integration is now available!",[12,19651,19652,19653,19656],{},"You can now calculate and track your TeamCity ",[514,19654,848],{"href":7188,"rel":19655},[518]," seamlessly; we think it's a great way to improve your CI\u002FCD process.",[12,19658,19659,19663],{},[4866,19660],{"alt":19661,"src":19662},"Oobeya TeamCity addon dashboard","\u002Fassets\u002Fblog\u002Foobeya-teamcity-dora.png"," Oobeya TeamCity Addon",[12,19665,19666,19667,19672,19673,19678,19679,19683],{},"To get started, simply head over to our ",[514,19668,19671],{"href":19669,"rel":19670},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Finstalling-an-addon",[518],"Marketplace"," page and activate the TeamCity addon. Then, ",[514,19674,19677],{"href":19675,"rel":19676},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fall-integrations\u002Fscm-addons\u002Fteamcity-integration",[518],"add your TeamCity data source",". Once you have it set up and started ",[514,19680,19682],{"href":4681,"rel":19681},[518],"Oobeya Deployment Analytics",", you'll be able to see your DORA metrics in Oobeya.",[12,19685,19686,19688,19689,23,19693,23,19697,23,19700,19703],{},[16,19687,19682],{}," works with ",[514,19690,19692],{"href":18260,"rel":19691},[518],"GitLab CI",[514,19694,19696],{"href":18264,"rel":19695},[518],"AzureDevOps",[514,19698,18279],{"href":18277,"rel":19699},[518],[514,19701,14150],{"href":18256,"rel":19702},[518],", and TeamCity for now.",[12,19705,19706,1044,19709,19717],{},[16,19707,19708],{},"Coming soon:",[791,19710,19711,19712,23,19714,19716],{},"Spinnaker, ",[514,19713,16781],{"href":16780},[514,19715,14193],{"href":14192},", PagerDuty, OpsGenie, ServiceNow,"," and more...",[501,19719],{},[613,19721,19723],{"id":19722},"oobeya-dashboard-dora-metrics-widget-now-displays-all-four-dora-metrics",[16,19724,19725],{},"Oobeya Dashboard DORA Metrics Widget now displays all Four DORA Metrics!",[12,19727,19728,19729,19732,19733,19737],{},"We are excited to announce that the Oobeya Dashboard \"",[16,19730,19731],{},"DORA Metrics Widget","\" now displays all ",[514,19734,19736],{"href":7188,"rel":19735},[518],"four DORA Metrics","! This improvement makes it easy to track your progress against the four key indicators of the DevOps Performance Framework: Lead Time For Changes, Deployment Frequency, Change Failure Rate, and Mean Time to Restore Service.",[12,19739,19740,19744],{},[4866,19741],{"alt":19742,"src":19743},"Oobeya DORA metrics dashboard widget","\u002Fassets\u002Fblog\u002Foobeya-dora-dashboard-widget.png"," Oobeya DORA Metrics Widget",[12,19746,19747,19748,247,19753,19758,19759,19761],{},"To access the DORA Metrics Widget, simply go to your ",[514,19749,19752],{"href":19750,"rel":19751},"https:\u002F\u002Fdocs.oobeya.io\u002Fdashboards\u002Fcreating-a-new-dashboard",[518],"Dashboard",[514,19754,19757],{"href":19755,"rel":19756},"https:\u002F\u002Fdocs.oobeya.io\u002Fdashboards\u002Fadding-a-new-widget",[518],"click on the \"Widgets\""," button in the top right corner. From ",[514,19760,19625],{"href":19624}," > Deployment Analytics, you can add the DORA Metrics Widget to your Dashboard. We hope you find this new feature helpful in tracking your DORA Metrics!",[501,19763],{},[613,19765,19767],{"id":19766},"exclude-deployments-to-calculate-dora-metrics-more-accurately",[16,19768,19618],{},[12,19770,19771,19772,19775],{},"We're excited to announce a new feature for Oobeya Deployment Analytics - the ability to exclude deployments from your ",[514,19773,3261],{"href":7188,"rel":19774},[518]," calculations!",[12,19777,19778],{},"Previously, when calculating your Lead Time For Changes, any deployments that were considered anomalies would be included in the calculation. This could lead to inaccurate results and made it difficult to get an accurate picture of your development and delivery process.",[12,19780,19781],{},"Now, with the new deployment exclusion feature, Oobeya automatically excludes any deployments that are considered anomalies. Oobeya users are also able to exclude any deployment manually. This will give you a more accurate picture of your delivery process and help you identify and fix any issues more effectively.",[12,19783,19784,19788],{},[4866,19785],{"alt":19786,"src":19787},"Oobeya deployment exclusions settings for DORA metrics","\u002Fassets\u002Fblog\u002Foobeya-dora-deployment-exclusion.png"," Oobeya DORA Deployment Exclusions",[501,19790],{},[613,19792,19794],{"id":19793},"select-gitwiser-analysis-period-to-optimize-analysis-performance",[16,19795,19796],{},"Select Gitwiser analysis period to optimize analysis performance",[12,19798,19799,19800,19803],{},"We are excited to announce a new feature for ",[514,19801,469],{"href":516,"rel":19802},[518]," - the ability to select the analysis period to optimize performance.",[12,19805,19806],{},"Gitwiser is a powerful git analytics tool that lets development teams see the impact and cognitive load of commits on the team average. It's been a valuable tool for development teams and leaders looking to improve their workflow and optimize their working practices.",[12,19808,19809,19810,611],{},"With this new feature, you can select the period of time you want to analyze to get the most accurate results. This is especially ",[16,19811,19812],{},"helpful for large projects with a lot of history",[12,19814,19815,19819],{},[4866,19816],{"alt":19817,"src":19818},"Oobeya Git analytics date range view","\u002Fassets\u002Fblog\u002Foobeya-git-analytics-date.png"," Oobeya Git Analytics Date Range",[12,19821,19822],{},"See the other features below to optimize Gitwiser analysis performance:",[70,19824,19825,19828],{},[73,19826,19827],{},"Commit Exclusions",[73,19829,19830],{},"Source Code File and Folder Exclusions (exclusion patterns)",[501,19832],{},[613,19834,19836],{"id":19835},"manage-team-members-easily",[16,19837,19632],{},[12,19839,19840],{},"Oobeya is excited to announce this new feature to help team leads manage their team members easily! With this new feature, team leads can add and remove members with ease, as well as receive smart suggestions on who to add or remove to their team. This new feature is designed to make managing teams easier and more efficient for Oobeya users.",[501,19842],{},[613,19844,19846],{"id":19845},"new-key-pull-request-metrics-are-ready-to-use-improve-your-teams-code-review-cycles",[16,19847,19848],{},"New Key Pull Request metrics are ready to use! Improve your teams' code review cycles!",[12,19850,19851],{},"We've just released a new set of metrics for the Oobeya Pull Request Analytics module:",[70,19853,19854,19860],{},[73,19855,19856,19859],{},[16,19857,19858],{},"Avg Time To Merge:"," The time elapsed between the first commit and merge time.",[73,19861,19862,19865],{},[16,19863,19864],{},"% PRs Merged Within Goal:"," The percentage of merged pull requests within the specified team goal.",[12,19867,19868],{},"These key metrics will help you improve your team's code review cycles and performance.",[12,19870,19871,19875],{},[4866,19872],{"alt":19873,"src":19874},"Oobeya pull request metrics dashboard","\u002Fassets\u002Fblog\u002Fpr-metrics.png"," Key pull request metrics",[18668,19877,19879],{"id":19878},"improvements",[16,19880,19881],{},"💪 IMPROVEMENTS",[70,19883,19884,19887,19890,19893],{},[73,19885,19886],{},"[Gitwiser] GitHub API Rate Limit improvements",[73,19888,19889],{},"[Gitwiser] Bitbucket API Rate Limit improvements",[73,19891,19892],{},"Performance improvements",[73,19894,19895],{},"UI\u002FUX improvements (on time in state widget, team search, date filter, and more...)",[501,19897],{},[3354,19899,19900,19904,19907],{},[12,19901,19902],{},[16,19903,19350],{},[12,19905,19906],{},"Do you want to see all the new features in action and talk about the product roadmap?",[12,19908,19325,19909,19332],{},[514,19910,19912],{"href":19328,"rel":19911},[518],[16,19913,4824],{},{"title":526,"searchDepth":527,"depth":527,"links":19915},[19916,19917,19918,19919,19920,19921],{"id":19643,"depth":527,"text":19646},{"id":19722,"depth":527,"text":19725},{"id":19766,"depth":527,"text":19618},{"id":19793,"depth":527,"text":19796},{"id":19835,"depth":527,"text":19632},{"id":19845,"depth":527,"text":19848},[4232,1232,18874,541],"2022-09-06","Oobeya August 2022 Product Updates - TeamCity Integration, DORA Metrics Widget Enhancements, Exclude Deployments, New PR Metrics, and more…",{},"\u002Fblog\u002Foobeya-august-2022-updates",{"title":19589,"description":19924},"blog\u002Foobeya-august-2022-updates",[19930,8865,8440,540,19457,19461,696,9660,18874,19462,19931,19932],"code-review","release-notes","teamcity","S6uXq6pqjPEk5l8pL-8ESwUjpX_T4BuPZPaPmf5AKWE",{"id":19935,"title":19936,"author":4245,"avatar":575,"body":19937,"categories":20187,"createAt":542,"date":20188,"description":20189,"extension":545,"meta":20190,"navigation":547,"path":20191,"position":542,"seo":20192,"spotImage":542,"spotText":542,"stem":20193,"tags":20194,"__hash__":20196},"blog\u002Fblog\u002Foobeya-july-2022-updates.md","Oobeya July 2022 Product Updates - Blog",{"type":9,"value":19938,"toc":20180},[19939,19945,19948,19968,19970,19974,19979,19982,19989,20000,20016,20026,20032,20035,20056,20064,20066,20071,20079,20082,20085,20092,20095,20097,20103,20106,20109,20111,20116,20119,20126,20132,20135,20138,20145,20150,20163,20165],[18668,19940,19942],{"id":19941},"oobeya-july-2022-updates-summary",[16,19943,19944],{},"Oobeya July 2022 Updates Summary",[4331,19946,19947],{"id":19600},"🎉 We are super excited to share our new features and improvements with you!",[70,19949,19950,19953,19956,19959,19962,19965],{},[73,19951,19952],{},"GitHub Enterprise Server integration is ready!",[73,19954,19955],{},"Oobeya Team Scorecards now display all DORA Metrics!",[73,19957,19958],{},"DORA Metrics widgets now have a date range comparison feature! (Last 7 days vs. Previous 7 days)",[73,19960,19961],{},"Oobeya Agile Board Analytics module has a date range comparison feature!",[73,19963,19964],{},"Oobeya Agile Sprint Reports has a new comparison feature! (Sprint 25 vs. Last 10 Sprints Avg)",[73,19966,19967],{},"UI\u002FUX & performance improvements!",[501,19969],{},[18668,19971,19972],{"id":19637},[16,19973,19640],{},[613,19975,19977],{"id":19976},"github-enterprise-server-integration-is-ready",[16,19978,19952],{},[12,19980,19981],{},"We’re excited to announce that Oobeya now integrates with GitHub Enterprise Server! This new addon is available in our marketplace, and we’ve created a quick start guide to help you get started.",[12,19983,19984,19988],{},[4866,19985],{"alt":19986,"src":19987},"Oobeya GitHub integration overview","\u002Fassets\u002Fblog\u002Foobeya-github-enterprise-1-e1660306662327.png"," Oobeya GitHub Integration",[12,19990,19991,19992,247,19995,19999],{},"This integration enables Oobeya to be used with GitHub Enterprise Server, in addition to our already existing ",[514,19993,4528],{"href":18256,"rel":19994},[518],[514,19996,19998],{"href":18256,"rel":19997},[518],"GitHub Enterprise Cloud"," integrations.",[12,20001,20002,20007,20008,20011,20012,20015],{},[514,20003,20006],{"href":20004,"rel":20005},"https:\u002F\u002Fdocs.github.com\u002Fen\u002Fenterprise-server@3.5\u002Fadmin\u002Foverview\u002Fabout-github-enterprise-server",[518],"GitHub Enterprise Server"," is the on-premises version of ",[514,20009,4528],{"href":4526,"rel":20010},[518],", and we’re thrilled to offer this new integration to our users. With this new addon, you can easily connect ",[514,20013,469],{"href":12472,"rel":20014},[518]," to your GitHub Enterprise Server instance.​",[3354,20017,20018],{},[12,20019,20020,20021],{},"Read more on Oobeya Blog: ",[514,20022,20025],{"href":20023,"rel":20024},"https:\u002F\u002Foobeya.io\u002Fblog\u002Fgithub-enterprise-server-integration-is-ready\u002F",[518],"GitHub Enterprise Server Integration Is Ready!",[4331,20027,20029],{"id":20028},"how-does-oobeya-github-integration-work",[16,20030,20031],{},"How Does Oobeya GitHub Integration Work?",[12,20033,20034],{},"Oobeya GitHub addon collects and analyzes data\u002Factivities\u002Fsignals from GitHub and makes sense of them in multiple dimensions (individual, team, organization, system). It provides actionable insights to software engineering teams and leaders. This integration works with the following Oobeya analytics modules:",[1520,20036,20037,20043,20049],{},[73,20038,20039,20040],{},"Git Repository Analytics ",[16,20041,20042],{},"(Software Development Process)",[73,20044,20045,20046],{},"Pull Requests Analytics ",[16,20047,20048],{},"(Code Review Process)",[73,20050,20051,20052,20055],{},"Deployment Analytics – DORA Metrics ",[16,20053,20054],{},"(Software Delivery Process)"," (works with GitHub Actions, Jenkins, Azure DevOps, GitLabCI, TeamCity)",[3354,20057,20058],{},[12,20059,20060,20061,611],{},"See the Software Engineering Metrics that Oobeya delivers ",[514,20062,4354],{"href":10263,"rel":20063},[518],[501,20065],{},[613,20067,20069],{"id":20068},"oobeya-team-scorecards-now-display-all-dora-metrics",[16,20070,19955],{},[12,20072,20073,20074,20078],{},"Oobeya Team Scorecards now display ",[514,20075,20077],{"href":7188,"rel":20076},[518],"all four DORA Metrics",": Lead Time For Changes, Deployment Frequency, Change\u002FFailure Rate, and Time To Restore Service!",[12,20080,20081],{},"This means that teams can now track their progress against each of these important engineering metrics, and identify areas where they may need to focus their improvement efforts.",[12,20083,20084],{},"You can also drill down into each metric to see how your teams are doing. This is a great way to stay on top of your team's delivery performance and make sure that you're always improving.",[12,20086,20087,20091],{},[4866,20088],{"alt":20089,"src":20090},"Oobeya DORA metrics on team scorecards","\u002Fassets\u002Fblog\u002Foobeya-dora-team-docs.png"," DORA Metrics on Team Scorecards",[12,20093,20094],{},"We hope that this new feature will help teams to better understand their performance and continue to drive quality improvements in their engineering processes.",[501,20096],{},[613,20098,20100],{"id":20099},"dora-metrics-widgets-now-have-a-date-range-comparison-feature",[16,20101,20102],{},"DORA Metrics widgets now have a date range comparison feature!",[12,20104,20105],{},"DORA Metrics widgets now have a date range comparison feature! This means that you can now compare your current performance against a previous time period, and see how you're progressing. (for example, Last 7 days vs. Previous 7 days)",[12,20107,20108],{},"This new feature allows you to benchmark your progress and compare it against a date range of your choosing. This is a great tool for continuous improvement. We hope you find this new feature helpful!",[501,20110],{},[613,20112,20114],{"id":20113},"oobeya-agile-board-analytics-module-has-a-date-range-comparison-feature",[16,20115,19961],{},[12,20117,20118],{},"Oobeya Agile Board Analytics module has a date range comparison feature! This new feature will allow agile team members to compare the agile metrics across different time periods. This will help with continuous improvement by allowing Scrum Masters and Product Owners to see where their team's sprint success has improved or worsened.",[12,20120,20121,20125],{},[4866,20122],{"alt":20123,"src":20124},"Agile board time in state widget with date range comparison","\u002Fassets\u002Fblog\u002Foobeya-time-agile.png"," Agile Board Overview - Time in State widget with date range comparison",[613,20127,20129],{"id":20128},"oobeya-agile-sprint-reports-has-a-new-comparison-feature",[16,20130,20131],{},"Oobeya Agile Sprint Reports has a new comparison feature!",[12,20133,20134],{},"The Oobeya Agile Sprint Reports has a new comparison feature! This new feature will allow Product Owners to compare their sprint success against other sprints and benchmark their progress. This will help ensure that Product Owners are always aware of their sprint progress and can make necessary adjustments to ensure sprint success.",[12,20136,20137],{},"To use the comparison feature, simply select the sprints that you want to compare from the drop-down menu. You will then see the comparison of the selected sprints. This will allow you to quickly see how your team is progressing. We hope that you find this new feature helpful in achieving your sprint goals.",[12,20139,20140,20144],{},[4866,20141],{"alt":20142,"src":20143},"Agile sprint reports with sprint comparison","\u002Fassets\u002Fblog\u002Foobeya-agile-docs.png"," Agile Sprint Reports - Sprint Comparison",[18668,20146,20147],{"id":19878},[16,20148,20149],{},"💪 IMPROVEMENTS",[70,20151,20152,20155,20158,20160],{},[73,20153,20154],{},"[Gitwiser] Do not analyze a commit if it has already been analyzed in another branch analysis.",[73,20156,20157],{},"[Gitwiser] Allow limiting Gitwiser analysis by date to improve analysis performance.",[73,20159,19892],{},[73,20161,20162],{},"UI\u002FUX improvements",[501,20164],{},[3354,20166,20167,20171,20173],{},[12,20168,20169],{},[16,20170,19350],{},[12,20172,19906],{},[12,20174,19325,20175,19332],{},[514,20176,20178],{"href":19328,"rel":20177},[518],[16,20179,4824],{},{"title":526,"searchDepth":527,"depth":527,"links":20181},[20182,20183,20184,20185,20186],{"id":19976,"depth":527,"text":19952},{"id":20068,"depth":527,"text":19955},{"id":20099,"depth":527,"text":20102},{"id":20113,"depth":527,"text":19961},{"id":20128,"depth":527,"text":20131},[18874],"2022-08-15","Oobeya July 2022 Product Updates - GitHub Enterprise Server, Date Range Comparison, DORA Metrics Team View, and more...",{},"\u002Fblog\u002Foobeya-july-2022-updates",{"title":19936,"description":20189},"blog\u002Foobeya-july-2022-updates",[20195,8440,19458,19459,696,9660,18874,14804],"agile","-6afPrz0k8m33tV44N96_C14T_SJJQ8b-Z-c2juAST8",{"id":20198,"title":20199,"author":4245,"avatar":575,"body":20200,"categories":20322,"createAt":542,"date":20323,"description":20324,"extension":545,"meta":20325,"navigation":547,"path":20326,"position":542,"seo":20327,"spotImage":542,"spotText":542,"stem":20328,"tags":542,"__hash__":20329},"blog\u002Fblog\u002Fgithub-enterprise-server-integration-is-ready.md","GitHub Enterprise Server Integration Is Ready! - Blog",{"type":9,"value":20201,"toc":20318},[20202,20206,20213,20221,20230,20235,20248,20258,20265,20267,20269,20284,20289,20296,20301,20304,20312],[18668,20203,20204],{"id":19976},[16,20205,20025],{},[4331,20207,20209,20210,20212],{"id":20208},"were-excited-to-announce-that-oobeya-now-integrates-with-github-enterprise-server-this-new-addon-is-available-in-our-marketplace-and-weve-created-a-quick-start-guide-to-help-you-get-started","We’re excited to announce that Oobeya now integrates with ",[16,20211,20006],{},"! This new addon is available in our marketplace, and we’ve created a quick start guide to help you get started.",[12,20214,19991,20215,247,20218,19999],{},[514,20216,4528],{"href":18256,"rel":20217},[518],[514,20219,19998],{"href":18256,"rel":20220},[518],[12,20222,20223,20224,20229],{},"Oobeya has powerful integrations with popular SDLC \u002F DevOps tools. Each quarter, Oobeya increases its integrations in line with its roadmap. You can ",[514,20225,20228],{"href":20226,"rel":20227},"https:\u002F\u002Foobeya.io\u002Ffeedback\u002F",[518],"share your integration requests"," with the Oobeya Product Team.",[12,20231,20232],{},[4866,20233],{"alt":20234,"src":19987},"Oobeya GitHub Enterprise Server integration overview",[12,20236,20237,20007,20240,20011,20244,20247],{},[514,20238,20006],{"href":20004,"rel":20239},[518],[514,20241,4528],{"href":20242,"rel":20243},"https:\u002F\u002Fgithub.com",[518],[514,20245,469],{"href":12472,"rel":20246},[518]," to your GitHub Enterprise Server instance.",[12,20249,19666,20250,247,20253,20257],{},[514,20251,19671],{"href":8313,"rel":20252},[518],[514,20254,20256],{"href":19669,"rel":20255},[518],"activate"," the GitHub Enterprise Server integration. Once installed, you'll be able to connect your GitHub Enterprise Server account and start managing your GitHub repositories right from Oobeya. We hope you find this new integration helpful and we can't wait to hear your feedback!",[12,20259,20260,20264],{},[4866,20261],{"alt":20262,"src":20263},"Oobeya GitHub Enterprise addon dashboard","\u002Fassets\u002Fblog\u002Fgithub-enterprise-oobeya.png"," GitHub Enterprise Addon",[52,20266,20031],{"id":20028},[12,20268,20034],{},[1520,20270,20271,20275,20279],{},[73,20272,20039,20273],{},[16,20274,20042],{},[73,20276,20045,20277],{},[16,20278,20048],{},[73,20280,20281,20282,20055],{},"Deployment Analytics - DORA Metrics ",[16,20283,20054],{},[12,20285,20060,20286,611],{},[514,20287,4354],{"href":10263,"rel":20288},[518],[12,20290,20291,20295],{},[4866,20292],{"alt":20293,"src":20294},"Oobeya deployment analytics and DORA metrics dashboard","\u002Fassets\u002Fblog\u002Foobeya-deployment-dora-metrics.png"," Oobeya Deployment Analytics & DORA Metrics",[52,20297,20298],{"id":19266},[16,20299,20300],{},"Ready To Get Started Now?",[12,20302,20303],{},"If you’re not familiar with Oobeya, it’s an engineering intelligence platform that helps software development teams and leaders track and visualize their entire development and delivery processes.",[4331,20305,20307,20308,19429],{"id":20306},"if-youre-interested-in-learning-more-about-oobeya-you-can-reach-out-to-us-for-a-free-trial-and-get-started-today","If you’re interested in learning more about Oobeya, you can ",[514,20309,20311],{"href":18851,"rel":20310},[518],"reach out to us",[12,20313,20314,20315,611],{},"And as always, if you have any questions or feedback, please don’t hesitate to reach out to us ",[514,20316,4354],{"href":18851,"rel":20317},[518],{"title":526,"searchDepth":527,"depth":527,"links":20319},[20320,20321],{"id":20028,"depth":530,"text":20031},{"id":19266,"depth":530,"text":20300},[4232,18874],"2022-08-12","Oobeya now supports GitHub Enterprise Server, bringing GitHub data into engineering analytics, DORA metrics, and team insights.",{},"\u002Fblog\u002Fgithub-enterprise-server-integration-is-ready",{"title":20199,"description":20324},"blog\u002Fgithub-enterprise-server-integration-is-ready","bakNv_gS8_DGLqwULnZFunFOyUF8Q7cebw8ZdDD9JUo",{"id":20331,"title":20332,"author":4245,"avatar":575,"body":20333,"categories":20591,"createAt":542,"date":20323,"description":20592,"extension":545,"meta":20593,"navigation":547,"path":20594,"position":542,"seo":20595,"spotImage":542,"spotText":542,"stem":20596,"tags":20597,"__hash__":20598},"blog\u002Fblog\u002Foobeya-june-2022-product-updates.md","Oobeya June 2022 Product Updates - Blog",{"type":9,"value":20334,"toc":20583},[20335,20341,20345,20384,20386,20388,20394,20397,20401,20409,20412,20418,20427,20433,20457,20459,20465,20468,20472,20479,20486,20491,20494,20501,20504,20511,20515,20539,20541,20548,20554,20562,20565],[18668,20336,20338],{"id":20337},"oobeya-june-2022-updates-summary",[16,20339,20340],{},"Oobeya June 2022 Updates Summary",[4331,20342,20344],{"id":20343},"we-are-super-excited-to-introduce-you-to-our-new-features-and-improvements","🎉 We are super excited to introduce you to our new features and improvements!",[70,20346,20347,20354,20361,20368,20376],{},[73,20348,20349,20350],{},"DORA Stability Metrics -1: ",[514,20351,859],{"href":20352,"rel":20353},"https:\u002F\u002Fdocs.oobeya.io\u002Fproduct\u002Frelease-notes\u002Foobeya-june-2022-updates#dora-stability-metrics-1-change-failure-rate",[518],[73,20355,20356,20357],{},"DORA Stability Metrics 2: ",[514,20358,13349],{"href":20359,"rel":20360},"https:\u002F\u002Fdocs.oobeya.io\u002Fproduct\u002Frelease-notes\u002Foobeya-june-2022-updates#dora-stability-metrics-2-time-to-restore-service",[518],[73,20362,20363],{},[514,20364,20367],{"href":20365,"rel":20366},"https:\u002F\u002Fdocs.oobeya.io\u002Fproduct\u002Frelease-notes\u002Foobeya-june-2022-updates#executive-view-and-organization-wide-metrics",[518],"Executive View & Organization-Wide Metrics",[73,20369,20370,20375],{},[514,20371,20374],{"href":20372,"rel":20373},"https:\u002F\u002Fdocs.oobeya.io\u002Fproduct\u002Frelease-notes\u002Foobeya-june-2022-updates#improvements",[518],"Improvements"," on AgileSpace, Gitwiser, Sonarqube, and UI\u002FUX",[73,20377,20378,20379,20383],{},"Private Beta: ",[514,20380,910],{"href":20381,"rel":20382},"https:\u002F\u002Fdocs.oobeya.io\u002Fproduct\u002Frelease-notes\u002Foobeya-june-2022-updates#private-beta-cooking-something-special",[518]," (cooking something special...)",[501,20385],{},[18668,20387,19640],{"id":19637},[613,20389,20391],{"id":20390},"dora-stability-metrics-1-change-failure-rate",[16,20392,20393],{},"DORA Stability Metrics -1: Change Failure Rate",[12,20395,20396],{},"We have added Change Failure Rate to Oobeya Deployment Analytics [BETA]!",[12,20398,20399,15905],{},[16,20400,15904],{},[3354,20402,20403],{},[12,20404,20405,20406],{},"💡 Read more on Oobeya Blog: ",[514,20407,13487],{"href":11456,"rel":20408},[518],[12,20410,20411],{},"You can set your deployment status as a failure manually now.",[12,20413,20414,20417],{},[4866,20415],{"alt":20416,"src":2616},"DORA metrics deployment health status settings"," Setting deployment health status and fix deployment manually",[12,20419,20420,20421,247,20424,611],{},"In the next release, deployment failures will be detected automatically by ",[16,20422,20423],{},"Git tags",[16,20425,20426],{},"branch names",[12,20428,20429,12332],{},[4866,20430],{"alt":20431,"src":20432},"change-failure-rate-cfr","\u002Fassets\u002Fblog\u002Fchange-failure-rate-cfr.png",[3354,20434,20435,20452],{},[12,20436,20437,19688,20439,23,20442,23,20445,27,20448,20451],{},[16,20438,19682],{},[514,20440,19692],{"href":18260,"rel":20441},[518],[514,20443,19696],{"href":18264,"rel":20444},[518],[514,20446,18279],{"href":18277,"rel":20447},[518],[514,20449,14150],{"href":18256,"rel":20450},[518]," for now.",[12,20453,20454,20456],{},[16,20455,19708],{}," TeamCity, Spinnaker, BB Pipelines, Octopus, PagerDuty, OpsGenie, ServiceNow, and more...",[501,20458],{},[613,20460,20462],{"id":20461},"dora-stability-metrics-2-time-to-restore-service",[16,20463,20464],{},"DORA Stability Metrics -2: Time to Restore Service",[12,20466,20467],{},"We have added the Time to Restore Service \u002F Mean Time To Recovery (MTTR) metric to Oobeya Deployment Analytics [BETA]!",[12,20469,20470,18975],{},[16,20471,17061],{},[3354,20473,20474],{},[12,20475,20405,20476],{},[514,20477,13487],{"href":11456,"rel":20478},[518],[12,20480,20481,20485],{},[4866,20482],{"alt":20483,"src":20484},"mttr-time-to-restore-dora","\u002Fassets\u002Fblog\u002Fmttr-time-to-restore-dora.png"," DORA Metrics - Mean Time To Recovery (MTTR)",[613,20487,20489],{"id":20488},"executive-view-organization-wide-metrics",[16,20490,20367],{},[12,20492,20493],{},"You can set your own Organization Schema to create a hierarchical view in Oobeya.",[12,20495,20496,20500],{},[4866,20497],{"alt":20498,"src":20499},"Oobeya executive dashboard organization schema view","\u002Fassets\u002Fblog\u002Fexecutive-dashboard.png"," You can set your own Organization Schema to create a hierarchical view.",[12,20502,20503],{},"After you create your organization chart, you can view your organization-wide metrics with breakdowns. All the metrics shown will be customizable in this view.",[12,20505,20506,20510],{},[4866,20507],{"alt":20508,"src":20509},"Oobeya executive dashboard with organization-wide metrics","\u002Fassets\u002Fblog\u002Fexecutive-dashboard-1.png"," Organization-wide metrics along with breakdowns",[613,20512,20513],{"id":19878},[16,20514,20149],{},[70,20516,20517,20520,20523,20526,20529,20532,20535,20537],{},[73,20518,20519],{},"[AgileSpace] Added Total Story Points & Total Issue Count value to Sprint Reports",[73,20521,20522],{},"[AgileSpace] Added a new tab to Sprint Velocity Metrics widget: \"Team Members”",[73,20524,20525],{},"[AgileSpace] Added task dropdown to Scope Changes widget",[73,20527,20528],{},"[AgileSpace] Added a new configuration option for Azure DevOps Story Points \u002F Effort fields",[73,20530,20531],{},"[Gitwiser] Added automated-reanalyze feature for Pull Request Analysis",[73,20533,20534],{},"[Sonarqube] Started hiding Sonarqube issues which are set as \"won't fix\" on Sonarqube",[73,20536,19892],{},[73,20538,20162],{},[501,20540],{},[613,20542,20544,20545],{"id":20543},"private-beta-cooking-something-special","🔒 ",[16,20546,20547],{},"PRIVATE BETA - Cooking something special",[12,20549,20550,20551,20553],{},"We are currently working on a new module called \"",[16,20552,910],{},"\".",[12,20555,20556,20557,20561],{},"Oobeya ",[16,20558,20559],{},[791,20560,910],{}," module identifies automatically symptoms of software development and delivery processes.",[12,20563,20564],{},"20+ symptoms are ready-to-use and auto-detect unhealthy practices of development teams in private beta.",[3354,20566,20567,20572,20574],{},[12,20568,20569,20570],{},"🏃 ",[16,20571,19319],{},[12,20573,19906],{},[12,20575,20576,20577,20582],{},"Click and ",[514,20578,20580],{"href":19328,"rel":20579},[518],[16,20581,4824],{}," now.",{"title":526,"searchDepth":527,"depth":527,"links":20584},[20585,20586,20587,20588,20589],{"id":20390,"depth":527,"text":20393},{"id":20461,"depth":527,"text":20464},{"id":20488,"depth":527,"text":20367},{"id":19878,"depth":527,"text":20149},{"id":20543,"depth":527,"text":20590},"🔒 PRIVATE BETA - Cooking something special",[18874],"Oobeya June 2022 Product Updates - DORA Metrics Change Failure Rate, Time To Restore Service, Executive View, and more...",{},"\u002Fblog\u002Foobeya-june-2022-product-updates",{"title":20332,"description":20592},"blog\u002Foobeya-june-2022-product-updates",[9660,18874,19931],"HqIVY5Dv65O2D1vYe_eTNjJrqRYk0SSP16Q__2_XCyk",{"id":20600,"title":20601,"author":4245,"avatar":575,"body":20602,"categories":21013,"createAt":542,"date":21014,"description":21015,"extension":545,"meta":21016,"navigation":547,"path":21017,"position":542,"seo":21018,"spotImage":542,"spotText":542,"stem":21019,"tags":21020,"__hash__":21021},"blog\u002Fblog\u002Fwhat-does-oobeya-mean.md","Oobeya 101: What Does Oobeya Mean? Why Did We Choose The Name Oobeya?",{"type":9,"value":20603,"toc":21005},[20604,20606,20613,20619,20626,20645,20651,20657,20661,20671,20674,20689,20694,20714,20724,20730,20732,20736,20752,20762,20773,20777,20842,20848,20850,20854,20873,20891,20893,20897,20908,20912,20960,20979,20981,20985,20991,20997],[52,20605,8449],{"id":8114},[12,20607,20608,20609,20612],{},"In today’s fast-paced software development world, ",[16,20610,20611],{},"engineering teams often struggle with misalignment, fragmented workflows, and a lack of clear visibility",". These challenges can lead to inefficiencies, delays, and difficulties in decision-making. ",[12,20614,20615,20616,8398],{},"Toyota encountered similar issues decades ago in its manufacturing process, where different teams operated in silos, leading to bottlenecks and wasted effort. To solve this, they introduced ",[16,20617,20618],{},"Oobeya—a collaborative space designed to improve transparency, coordination, and efficiency within the Toyota Production System (TPS).",[12,20620,20621,20622,20625],{},"The Oobeya approach created a ",[16,20623,20624],{},"centralized hub where teams could visualize work in progress, identify challenges early, and make informed decisions based on real-time data",".  ",[12,20627,20628,20629,20632,20633,20636,20637,20640,20641,20644],{},"Today, ",[16,20630,20631],{},"Oobeya’s principles extend beyond manufacturing into software development",", where teams navigate complex toolchains, distributed environments, and fast-moving projects. At ",[16,20634,20635],{},"Oobeya.io",", we have transformed this concept into a ",[16,20638,20639],{},"modern Engineering Intelligence Platform",", offering DevOps teams ",[16,20642,20643],{},"real-time visibility, actionable insights, and seamless collaboration"," to enhance software delivery performance. ",[12,20646,20647,20648,20650],{},"But what exactly does ",[16,20649,469],{}," mean? And why did we choose this name for our platform? ",[12,20652,20653,20656],{},[4866,20654],{"alt":4893,"src":20655},"\u002Fassets\u002Fblog\u002Foobeya-definition-e1711612640724.png"," What Does Oobeya Mean?",[52,20658,20660],{"id":20659},"_1-oobeya-the-meaning-behind-the-name","1. Oobeya: The Meaning Behind the Name ",[12,20662,20663,20664,20667,20668,50],{},"Oobeya (大部屋) is a ",[16,20665,20666],{},"Japanese word that means “Large Room”",". It originated from Lean Manufacturing and was a critical part of Toyota’s ",[16,20669,20670],{},"Kaizen and Lean methodologies",[18479,20672,20673],{},"\n![Oobeya in Kanji](\u002Fassets\u002Fblog\u002F1_T9ksBWgqmgzjz31xqnMZNg.png) Oobeya in Kanji\n",[12,20675,20676,20677,20680,20681,20684,20685,20688],{},"In the ",[16,20678,20679],{},"Toyota Production System",", Oobeya was a dedicated space where ",[16,20682,20683],{},"cross-functional teams gathered to monitor progress, share critical updates, and solve bottlenecks in real-time",". Instead of waiting for reports or relying on fragmented data, teams worked in one ",[16,20686,20687],{},"centralized, highly visual environment",", using walls filled with charts, KPIs, and objectives. ",[12,20690,20691,8398],{},[16,20692,20693],{},"The primary objectives of an Oobeya room include:",[70,20695,20696,20702,20708],{},[73,20697,20698,20701],{},[16,20699,20700],{},"Rapid decision-making"," with real-time visibility into processes. ",[73,20703,20704,20707],{},[16,20705,20706],{},"Reducing inefficiencies and rework"," by detecting issues early. ",[73,20709,20710,20713],{},[16,20711,20712],{},"Improving team collaboration"," by fostering alignment across departments. ",[3354,20715,20716,20721],{},[12,20717,20718],{},[16,20719,20720],{},"“To eliminate waste, you need to change how you look at things. You must continuously refine your process, neither tiring nor ceasing.”",[12,20722,20723],{}," — Taiichi Ohno, Father of the Toyota Production System ",[12,20725,20726,20727,50],{},"This same principle is now being applied to ",[16,20728,20729],{},"software development",[501,20731],{},[52,20733,20735],{"id":20734},"_2-oobeya-for-software-development-a-digital-large-room","2. Oobeya for Software Development: A Digital Large Room ",[12,20737,7616,20738,20740,20741,20744,20745,20748,20749,50],{},[16,20739,20635],{},", we have transformed the traditional Oobeya concept into a ",[16,20742,20743],{},"digital collaboration and analytics platform for DevOps teams",". In modern software engineering, teams use multiple tools—",[16,20746,20747],{},"GitHub, Jira, CI\u002FCD pipelines, testing platforms, and monitoring solutions","—but they often lack a ",[16,20750,20751],{},"unified accurate view of their software delivery performance",[12,20753,20754,20757,20758],{},[4866,20755],{"alt":20756,"src":20655},"OOBEYA: A Framework\u002FTool In The Toyota Production System"," Link: ",[514,20759,20760],{"href":20760,"rel":20761},"https:\u002F\u002Fwww.slideshare.net\u002FLeanUK\u002Fleading-using-the-oobeya-room-takashi-tanaka-sharon-tanner-qv-system-ls11-101111",[518],[12,20763,20764,20765,20768,20769,20772],{},"Oobeya acts as the ",[16,20766,20767],{},"digital “Large Room” for software organizations",", where all stakeholders—",[16,20770,20771],{},"engineering leaders, developers, DevOps teams, and product managers","—gain real-time visibility into engineering efficiency. ",[4331,20774,20776],{"id":20775},"how-oobeya-solves-challenges-for-devops-teams","How Oobeya Solves Challenges for DevOps Teams: ",[70,20778,20779,20792,20807,20820,20833],{},[73,20780,20781,20784,20785,20788,20789,50],{},[16,20782,20783],{},"End-to-End Visibility:"," Oobeya ",[16,20786,20787],{},"aggregates engineering data from repositories, issue tracking tools, and CI\u002FCD pipelines"," into a single ",[16,20790,20791],{},"real-time dashboard",[73,20793,20794,20797,20798,20800,20801,20804,20805,50],{},[16,20795,20796],{},"Bottleneck Detection:"," The ",[16,20799,6395],{}," proactively detects ",[16,20802,20803],{},"long cycle times, PR review delays, code quality issues, inefficient deployments",", and many more providing ",[16,20806,13451],{},[73,20808,20809,20812,20813,20816,20817,8398],{},[16,20810,20811],{},"Engineering Efficiency Metrics:"," Oobeya tracks essential ",[16,20814,20815],{},"DevOps performance metrics",", including DORA Metrics, Agile Metrics, ",[16,20818,20819],{},"cycle time, lead time, Sprint accuracy, Developer productivity, and pull request efficiency.",[73,20821,20822,20825,20826,20829,20830,50],{},[16,20823,20824],{},"Security & Compliance:"," Teams can monitor ",[16,20827,20828],{},"change failure rates, security vulnerabilities, and incident response times"," to improve ",[16,20831,20832],{},"software delivery resilience",[73,20834,20835,20838,20839,50],{},[16,20836,20837],{},"Data-Driven Decision Making:"," Move away from intuition-based management and leverage ",[16,20840,20841],{},"real-time engineering intelligence",[12,20843,20844,20845,50],{},"By unifying software development analytics, ",[16,20846,20847],{},"Oobeya eliminates silos, improves collaboration, and helps teams continuously optimize their software delivery process",[501,20849],{},[52,20851,20853],{"id":20852},"_3-oobeya-in-accelerate-high-performance-software-teams","3. Oobeya in Accelerate: High-Performance Software Teams ",[12,20855,20856,20857,20864,20865,20868,20869,20872],{},"In 2018, a book called ",[514,20858,20861],{"href":20859,"rel":20860},"https:\u002F\u002Fitrevolution.com\u002Fproduct\u002Faccelerate\u002F",[518],[16,20862,20863],{},"Accelerate"," was published by ",[16,20866,20867],{},"Nicole Forsgren, Jez Humble, and Gene Kim",". (Learn more about Accelerate and ",[514,20870,3261],{"href":8931,"rel":20871},[518],".) ",[12,20874,20875,20876,20879,20880,20882,20883,20886,20887,20890],{},"Steve Bell and Karen Whitley Bell wrote a chapter (",[16,20877,20878],{},"Chapter 16 - High-Performance Leadership And Management",") for the ",[791,20881,20863],{}," book to share the Oobeya experiences of ",[16,20884,20885],{},"ING Netherlands",". I highly recommend reading this chapter to explore the ",[16,20888,20889],{},"Oobeya experiences and practices"," of an IT organization. ",[501,20892],{},[52,20894,20896],{"id":20895},"_4-why-oobeya-is-the-future-of-engineering-intelligence"," 4. Why Oobeya is the Future of Engineering Intelligence ",[12,20898,20899,20900,20903,20904,20907],{},"Software engineering is evolving, and ",[16,20901,20902],{},"traditional performance-tracking methods are no longer enough",". DevOps teams need ",[16,20905,20906],{},"real-time insights, cross-platform visibility, and automated issue detection"," to stay ahead. ",[4331,20909,20911],{"id":20910},"what-sets-oobeya-apart","What Sets Oobeya Apart? ",[70,20913,20914,20924,20934,20944,20954],{},[73,20915,20916,20919,20920,20923],{},[16,20917,20918],{},"Cross-Platform Integration:"," Works seamlessly with ",[16,20921,20922],{},"GitHub, GitLab, Bitbucket, Jira, Azure DevOps, Jenkins, and more.","  ",[73,20925,20926,20929,20930,20933],{},[16,20927,20928],{},"Real-Time Accurate Insights:"," Provides ",[16,20931,20932],{},"continuous monitoring of software delivery performance"," to detect inefficiencies before they impact development.  ",[73,20935,20936,20939,20940,20943],{},[16,20937,20938],{},"Comprehensive Metrics Dashboard:"," Tracks ",[16,20941,20942],{},"DORA Metrics, Agile Metrics, Developer Experience Metrics, Cycle Time, and Comparative Metrics"," for performance benchmarking.  ",[73,20945,20946,20949,20950,20953],{},[16,20947,20948],{},"Security & Compliance Monitoring:"," Ensures ",[16,20951,20952],{},"risk-free deployments"," with built-in security tracking.  ",[73,20955,20956,20959],{},[16,20957,20958],{},"Developer Experience (DevEx) Insights:"," Reduces friction, improves focus time, and enhances productivity. ",[12,20961,20962,20963,20966,20967,20970,20971,20974,20975,20978],{},"Oobeya is ",[16,20964,20965],{},"not just an analytics tool","—it is a ",[16,20968,20969],{},"true Software Engineering Intelligence Platform"," designed to help teams shift from ",[16,20972,20973],{},"reactive"," problem-solving to ",[16,20976,20977],{},"proactive"," optimization. ",[501,20980],{},[52,20982,20984],{"id":20983},"_5-take-the-next-step-transform-your-devops-performance-with-oobeya"," 5. Take the Next Step: Transform Your DevOps Performance with Oobeya ",[12,20986,20987,20990],{},[16,20988,20989],{},"Oobeya isn’t just a concept—it’s a game-changer for software teams."," Oobeya helps teams improve efficiency, reduce risks, and accelerate value delivery by bringing visibility, data intelligence, and proactive insights into DevOps workflows**.** ",[12,20992,20993,20994,8398],{},"📢 ",[16,20995,20996],{},"Want to see how Oobeya can transform your DevOps performance?",[12,20998,512,20999,21004],{},[514,21000,21002],{"href":4082,"rel":21001},[518],[16,21003,519],{}," and experience!",{"title":526,"searchDepth":527,"depth":527,"links":21006},[21007,21008,21009,21010,21011,21012],{"id":8114,"depth":530,"text":8449},{"id":20659,"depth":530,"text":20660},{"id":20734,"depth":530,"text":20735},{"id":20852,"depth":530,"text":20853},{"id":20895,"depth":530,"text":20896},{"id":20983,"depth":530,"text":20984},[16837,541],"2022-07-22","Accelerate your software development process with Oobeya, the software engineering intelligence platform for complete visibility and transparency.",{},"\u002Fblog\u002Fwhat-does-oobeya-mean",{"title":20601,"description":21015},"blog\u002Fwhat-does-oobeya-mean",[540,9660],"2w31cd5LWug71yAVimn5C-YpIUsJTcnym5ZQO1kTySA",{"id":21023,"title":21024,"author":4245,"avatar":575,"body":21025,"categories":21346,"createAt":542,"date":21347,"description":21348,"extension":545,"meta":21349,"navigation":547,"path":21350,"position":542,"seo":21351,"spotImage":542,"spotText":542,"stem":21352,"tags":21353,"__hash__":21356},"blog\u002Fblog\u002Fstack-overflow-2022-developer-survey-where-is-the-industry-heading.md","Stack Overflow 2022 Developer Survey: Where Is The Industry Heading? - Blog",{"type":9,"value":21026,"toc":21344},[21027,21031,21044,21049,21052,21054,21060,21065,21074,21080,21092,21101,21107,21116,21121,21130,21136,21141,21148,21154,21163,21185,21192,21198,21203,21206,21209,21231,21240,21245,21250,21259,21268,21274,21279,21288,21295,21298,21303,21311,21317],[18668,21028,21030],{"id":21029},"stack-overflow-2022-developer-survey-where-is-the-industry-heading","Stack Overflow 2022 Developer Survey: Where Is The Industry Heading?",[12,21032,21033,21034,21039,21040,21043],{},"The results of ",[514,21035,21038],{"href":21036,"rel":21037},"https:\u002F\u002Fstackoverflow.com\u002F",[518],"Stack Overflow","’s ",[16,21041,21042],{},"2022 Developer Survey"," were recently published. The survey gathered information from 70,000 developers from various countries, roles, and technologies.",[3354,21045,21046],{},[12,21047,21048],{},"“This report is based on a survey of 73,268 software developers from 180 countries around the world.” - Stack Overflow Developer Survey 2022",[12,21050,21051],{},"Let’s look at my highlights from these survey results to understand where the industry is heading.",[501,21053],{},[4331,21055,21057],{"id":21056},"_1-git-is-the-king-the-use-of-git-is-increasing-year-by-year",[16,21058,21059],{},"1. Git is the king: The use of Git is increasing year by year.",[3354,21061,21062],{},[12,21063,21064],{},"“No other technology is as widely used as Git. Especially among Professional Developers.”",[18479,21066,21067],{},[12,21068,21069,21073],{},[4866,21070],{"alt":21071,"src":21072},"What are the primary version control systems you use?","\u002Fassets\u002Fblog\u002F1_QQ5KWakXiNFGhk-j6PE4vg.png"," What are the primary version control systems you use?",[4331,21075,21077],{"id":21076},"_2-version-control-universe-github-gitlab-bitbucket-azure-devops",[16,21078,21079],{},"2. Version Control Universe: GitHub, GitLab, Bitbucket, Azure DevOps.",[12,21081,21082,21083,1044,21086,21091],{},"If you’re building a product that integrates with version control platforms — ",[791,21084,21085],{},"that is what I did at",[514,21087,21089],{"href":5051,"rel":21088},[518],[791,21090,469],{}," — this is your universe: GitHub, GitLab, Bitbucket, and Azure DevOps. You need to cover these immediately because the entire software development industry lives in this universe.",[18479,21093,21094],{},[12,21095,21096,21100],{},[4866,21097],{"alt":21098,"src":21099},"What version control hosting service are you using?","\u002Fassets\u002Fblog\u002F1_eJMPU12eV1ZpYUIJqdHg4A.png"," What version control hosting service are you using?",[4331,21102,21104],{"id":21103},"_3-docker-usage-is-increasing-year-by-year",[16,21105,21106],{},"3. Docker usage is increasing year by year.",[12,21108,21109,21110,21115],{},"Every developer should now be familiar with ",[514,21111,21114],{"href":21112,"rel":21113},"https:\u002F\u002Fwww.docker.com\u002F",[518],"Docker",". Developers must first learn the concept and the technology behind it. Then, they must gain hands-on experience with it.",[3354,21117,21118],{},[12,21119,21120],{},"“Last year we saw Git as a fundamental tool to being a developer. This year it appears that Docker is becoming a similar fundamental tool for Professional Developers, increasing from 55% to 69%.”",[18479,21122,21123],{},[12,21124,21125,21129],{},[4866,21126],{"alt":21127,"src":21128},"Which developer tools have you done extensive development work in over the past year, and which do you want to work in over the next year?","\u002Fassets\u002Fblog\u002F1_CgKTibqjAbIsJgnSyvbAxg.png"," Which developer tools have you done extensive development work in over the past year, and which do you want to work in over the next year?",[4331,21131,21133],{"id":21132},"_4-docker-and-kubernetes-are-in-every-developers-toolbox",[16,21134,21135],{},"4. Docker and Kubernetes are in every developer’s toolbox.",[3354,21137,21138],{},[12,21139,21140],{},"“Docker and Kubernetes are in first and second place as the most loved and wanted tools.”",[18479,21142,21143],{},[12,21144,21145,21129],{},[4866,21146],{"alt":21127,"src":21147},"\u002Fassets\u002Fblog\u002F1_BbNOq69AoNgqCEi-sVHMRg.png",[4331,21149,21151],{"id":21150},"_5-communication-matters-developers-love-slack",[16,21152,21153],{},"5. Communication Matters: Developers love Slack.",[18479,21155,21156],{},[12,21157,21158,21162],{},[4866,21159],{"alt":21160,"src":21161},"Which communication tools did you use regularly over the past year, and which do you want to work with over the next year?","\u002Fassets\u002Fblog\u002F1_RN8RavC2To1KrUX7tt5RFw.png"," Which communication tools did you use regularly over the past year, and which do you want to work with over the next year?",[12,21164,21165,21168,21169,21174,21175,21180,21181,21184],{},[16,21166,21167],{},"But where is Discord?"," I guess those who don’t like ",[514,21170,21173],{"href":21171,"rel":21172},"https:\u002F\u002Fslack.com\u002F",[518],"Slack"," have already gone to ",[514,21176,21179],{"href":21177,"rel":21178},"https:\u002F\u002Fdiscord.com\u002F",[518],"Discord",", but Discord was not included in this survey. We have Slack and Microsoft Teamstons on ",[514,21182,469],{"href":5051,"rel":21183},[518]," in order to communicate with developers and teams. We also plan to add the Discord integration for dev teams using Oobeya.",[18479,21186,21187],{},[12,21188,21189,21162],{},[4866,21190],{"alt":21160,"src":21191},"\u002Fassets\u002Fblog\u002F1_A3OCnurG1vRm4U9L1zcpTQ.png",[4331,21193,21195],{"id":21194},"_6-you-probably-have-knowledge-silos-as-productivity-killers",[16,21196,21197],{},"6. You probably have knowledge silos as productivity killers.",[3354,21199,21200],{},[12,21201,21202],{},"“68% of respondents say they encounter a knowledge silo at least once a week. For People Managers, 73% report encountering a knowledge silo at least once a week.”",[12,21204,21205],{},"Engineering leaders must first change the culture of one-time-communication (communicating need-to-know information once and quickly) to break down existing knowledge silos.",[12,21207,21208],{},"See below the tips for breaking down knowledge silos and increasing overall productivity:",[1520,21210,21211,21214,21217,21224],{},[73,21212,21213],{},"Create a clear and accurate documentation system",[73,21215,21216],{},"Practice pair programming",[73,21218,21219,21220,6347],{},"Perform better code reviews (See ",[514,21221,21223],{"href":19176,"rel":21222},[518],"the code review tips here",[73,21225,21226,21227,21230],{},"Use Git analytics to identify knowledge silos in the development team. (",[514,21228,469],{"href":5051,"rel":21229},[518]," provides you insights into existing knowledge silos in your codebase and teams.)",[18479,21232,21233],{},[12,21234,21235,21239],{},[4866,21236],{"alt":21237,"src":21238},"How frequently do you experience each of the following?","\u002Fassets\u002Fblog\u002F1_Io_h1QGnq1ogantK9eFyUQ.png"," How frequently do you experience each of the following?",[3354,21241,21242],{},[12,21243,21244],{},"“62% of all respondents spend more than 30 minutes a day searching for answers or solutions to problems.",[3354,21246,21247],{},[12,21248,21249],{},"25% spending more than an hour each day. Regardless of being an independent contributor or people manager, this is time that could be spent learning or building.”",[18479,21251,21252],{},[12,21253,21254,21258],{},[4866,21255],{"alt":21256,"src":21257},"On an average day, how much time do you typically spend searching for answers or solutions to problems you encounter at work?","\u002Fassets\u002Fblog\u002F1_DcJSA8cgCAmIuyv1Uiz4ig.png"," On an average day, how much time do you typically spend searching for answers or solutions to problems you encounter at work?",[3354,21260,21261],{},[12,21262,21263,21264,21267],{},"“For a team of 50 developers, the amount of time spent searching for answers\u002Fsolutions adds up to between 333–651 hours of ",[791,21265,21266],{},"time lost per week"," across the entire team.”",[4331,21269,21271],{"id":21270},"_7-smaller-organizations-often-tend-to-be-in-the-office",[16,21272,21273],{},"7. Smaller organizations often tend to be in the office.",[3354,21275,21276],{},[12,21277,21278],{},"“85% of developers say their organizations are at least partially remote. Smaller organizations are most likely to be in-person, with 20% of 2–19 employee organizations in-person.”",[18479,21280,21281],{},[12,21282,21283,21287],{},[4866,21284],{"alt":21285,"src":21286},"Which best describes your current work situation?","\u002Fassets\u002Fblog\u002F1_fzsQodUcWWbtJHLkuMlVPw.png"," Which best describes your current work situation?",[4331,21289,21291,21294],{"id":21290},"_8-developer-experience-processes-tools-and-programs-within-an-organization",[16,21292,21293],{},"8. Developer Experience",": Processes, tools, and programs within an organization.",[12,21296,21297],{},"I believe software organizations today should invest more in improving the overall developer experience. Development teams should gain more visibility into their software development and delivery pipelines and strive to build a transparent and accountable working environment to increase developer experience and productivity.",[3354,21299,21300],{},[12,21301,21302],{},"“Only 16% of organizations have Innersource initiatives.”",[18479,21304,21305],{},[12,21306,21307,21310],{},[4866,21308],{"alt":6012,"src":21309},"\u002Fassets\u002Fblog\u002F1_s292CcxC8h0DvZY5CAu_3g.png"," Developer Experience",[4331,21312,21314],{"id":21313},"resources",[16,21315,21316],{},"Resources",[70,21318,21319,21327,21334,21341],{},[73,21320,21321,21322,18750],{},"Check out the complete Stack Overflow ",[514,21323,21326],{"href":21324,"rel":21325},"https:\u002F\u002Fsurvey.stackoverflow.co\u002F2022\u002F",[518],"Survey Results here",[73,21328,21329,21330,18750],{},"Check out the ",[514,21331,21333],{"href":5051,"rel":21332},[518],"Oobeya Engineering Intelligence Platform here",[73,21335,21336,21337],{},"Read the blog post: ",[514,21338,21340],{"href":19176,"rel":21339},[518],"Why Code Reviews Should Be Your Favorite Activity",[73,21342,21343],{},"Keywords to learn more: knowledge silos, developer experience, git analytics, innersource initiatives…",{"title":526,"searchDepth":527,"depth":527,"links":21345},[],[16837,541],"2022-06-25","The results of Stack Overflow’s 2022 Developer Survey were published. The survey gathered info from 70k developers. Let’s read the highlights.",{},"\u002Fblog\u002Fstack-overflow-2022-developer-survey-where-is-the-industry-heading",{"title":21024,"description":21348},"blog\u002Fstack-overflow-2022-developer-survey-where-is-the-industry-heading",[18882,19930,19359,2620,11825,8865,19458,19460,21354,21355,541],"knowledge-silos","software","SqrGtRwR3Hamb-9itlXAehW88yLy4LHTcYmxAqcQyhM",{"id":21358,"title":21359,"author":4245,"avatar":575,"body":21360,"categories":21732,"createAt":542,"date":21733,"description":21734,"extension":545,"meta":21735,"navigation":547,"path":21736,"position":542,"seo":21737,"spotImage":542,"spotText":542,"stem":21738,"tags":21739,"__hash__":21743},"blog\u002Fblog\u002Fhow-to-measure-dora-metrics-accurately.md","How to Measure DORA Metrics Accurately? - Blog",{"type":9,"value":21361,"toc":21719},[21362,21372,21378,21386,21392,21395,21398,21406,21409,21412,21415,21421,21424,21430,21448,21454,21457,21460,21463,21466,21469,21475,21478,21484,21487,21493,21519,21522,21554,21571,21605,21627,21633,21639,21663,21667],[12,21363,21364,21367,21368,21371],{},[514,21365,848],{"href":7188,"rel":21366},[518]," are quite popular in the industry. However, working with them is extremely difficult. Let’s take a look at how your company can measure DORA Metrics to gain complete visibility into complex DevOps pipelines. If Azure is a core part of your stack, this companion guide on ",[514,21369,21370],{"href":16225},"Azure DevOps DORA metrics"," is a useful next read.",[613,21373,21375],{"id":21374},"what-is-dora",[16,21376,21377],{},"What is DORA?",[12,21379,21380,21381,21385],{},"DORA, short for DevOps Research and Assessment, is a framework that aims to help software engineering teams improve their development and delivery processes. The ",[514,21382,21384],{"href":21383},"\u002Fglossary\u002Fdora-metrics","DORA metrics definition"," encompasses four key performance indicators that are critical for understanding and enhancing software delivery capabilities.",[613,21387,21389],{"id":21388},"why-are-dora-metrics-so-important-to-track-for-the-industry",[16,21390,21391],{},"Why are DORA Metrics so important to track for the industry",[12,21393,21394],{},"As software engineering organizations scale, fundamental software development and delivery processes become more and more complex. The number of tools used in the software delivery life cycle (SDLC) increases as processes become more sophisticated. Different teams within the company set up and run various delivery pipelines. During this process, visibility into the software development and delivery cycles is significantly reduced.",[12,21396,21397],{},"DORA (DevOps Research and Assessment) sought to find a solution to this complexity and invisibility problem:",[70,21399,21400,21403],{},[73,21401,21402],{},"How do you identify your organization’s elite performers?",[73,21404,21405],{},"What should low-performing teams focus on?",[12,21407,21408],{},"Once you begin to define and measure the metrics of the software delivery process, you will be able to improve them. Based on significant scientific research, DORA metrics empower engineering teams and leaders to improve their software development and delivery processes.",[12,21410,21411],{},"The DORA study’s approach attracted the interest of all engineering teams, from large-scale enterprises to small teams. Many engineering teams have tried to measure their DORA metrics by developing in-house tools since the beginning of the study. Because they could not adjust quickly enough to the changing and diversifying tools and methodologies within the company, in-house tools developed for specific processes have usually gone into junk. Many companies trying to measure DORA metrics with a ready-to-use product, on the other hand, struggled to locate a product that could fit their delivery pipeline and easily track accurate DORA metrics.",[12,21413,21414],{},"Let’s talk about what are DORA Metrics basically and how you can track them accurately.",[613,21416,21418],{"id":21417},"what-are-dora-metrics",[16,21419,21420],{},"What are DORA Metrics?",[12,21422,21423],{},"DORA metrics, also known as Accelerate Metrics or the Four Key Metrics, are pivotal in assessing the efficiency and effectiveness of DevOps practices. These metrics include Lead Time for Changes, Deployment Frequency, Change Failure Rate, and Time to Restore Service. By tracking these metrics, organizations can gain insights into their DevOps performance, identifying areas for improvement.",[52,21425,21427],{"id":21426},"dora-metrics-aka-accelerate-metrics-four-key-metrics",[16,21428,21429],{},"DORA Metrics (A.K.A. Accelerate Metrics & Four Key Metrics)",[1520,21431,21432,21436,21440,21444],{},[73,21433,21434,18961],{},[16,21435,18960],{},[73,21437,21438,18966],{},[16,21439,15886],{},[73,21441,21442,15905],{},[16,21443,15904],{},[73,21445,21446,18975],{},[16,21447,17061],{},[613,21449,21451],{"id":21450},"how-to-calculate-dora-metrics",[16,21452,21453],{},"How to Calculate DORA Metrics?",[12,21455,21456],{},"To accurately calculate DORA metrics, organizations must gather data from various stages of their development and delivery pipeline. This involves integrating tools for source control, continuous integration (CI), continuous deployment (CD), application performance monitoring (APM), and incident management. Tools like Oobeya simplify this process by offering a centralized platform for tracking and analyzing these metrics across different tools and platforms, thereby providing a comprehensive view of the DevOps performance.",[12,21458,21459],{},"You can set your own goals for these steps in Oobeya. By establishing specific goals for each of the DORA metrics core objectives, teams can systematically address inefficiencies and strive for continuous improvement. Setting benchmarks for lead time, deployment frequency, change failure rate, and time to restore service enables teams to measure progress and identify areas for optimization.",[12,21461,21462],{},"In conclusion, enhancing your DevOps processes with a clear understanding and measurement of DORA metrics is crucial for improving software delivery performance. By leveraging tools like Oobeya, organizations can gain invaluable insights into their development and delivery processes, enabling them to make informed decisions to optimize their operations. Remember, the journey towards DevOps excellence is ongoing, and continuously measuring and improving DORA metrics is key to achieving operational agility and excellence.",[12,21464,21465],{},"Incorporating the provided keywords and subheadings into the content not only broadens the article's scope but also enhances its visibility and utility for readers interested in DevOps practices, particularly in relation to DORA metrics.",[12,21467,21468],{},"Calculating DORA metrics involves analyzing various stages of the software development process. For instance, the 'Lead Time for Changes' metric is calculated from the moment a commit is made until it is successfully deployed in production. Similarly, 'Deployment Frequency' measures how often an organization successfully releases to production, while 'Change Failure Rate' and 'Time to Restore Service' focus on the reliability and resilience of the deployment process.",[613,21470,21472],{"id":21471},"how-much-does-it-cost-to-measure-dora-metrics",[16,21473,21474],{},"How Much Does It Cost To Measure DORA Metrics?",[12,21476,21477],{},"The cost of implementing DORA metrics can vary widely depending on the organization's existing infrastructure and tools. However, utilizing platforms like Oobeya for tracking these metrics can significantly reduce the overhead associated with custom tool development and maintenance, offering a cost-effective solution for organizations seeking to enhance their DevOps capabilities.",[613,21479,21481],{"id":21480},"how-to-improve-dora-metrics",[16,21482,21483],{},"How to Improve DORA Metrics",[12,21485,21486],{},"Improving DORA metrics requires a strategic approach that involves optimizing various aspects of the software development and delivery processes. Enhancements in automation, continuous integration, and deployment (CI\u002FCD) practices, and fostering a culture of collaboration between development and operations (DevOps) can lead to significant improvements in these metrics. Specifically, focusing on reducing lead time and deployment frequency, while minimizing change failure rates and time to restore service, are key areas for improvement.",[613,21488,21490],{"id":21489},"tracking-dora-metrics-with-oobeya",[16,21491,21492],{},"Tracking DORA Metrics with Oobeya",[12,21494,21495,1044,21502,21507,21508,21511,21512,1044,21515,611],{},[514,21496,21498],{"href":516,"rel":21497},[518],[16,21499,21500],{},[791,21501,469],{},[16,21503,21504],{},[791,21505,21506],{},"Deployment Analytics"," is an easy-to-use tool that delivers accurate DORA metric results for all software development and DevOps teams. It analyzes the entire software development and delivery pipeline and calculates DORA metrics by connecting to various tools within the organization. You can connect ",[791,21509,21510],{},"Source Control, CI\u002FCD, APM, Incident Management, and Issue Tracking"," tools to track and ",[16,21513,21514],{},"measure accurate DORA metrics with",[16,21516,21517],{},[791,21518,19682],{},[12,21520,21521],{},"No matter how you built your delivery cycle. It is easy to set up.",[70,21523,21524,21527,21530,21533,21536,21539,21542,21545,21548],{},[73,21525,21526],{},"GitLab x GitLab CI",[73,21528,21529],{},"GitHub x Jenkins",[73,21531,21532],{},"GitHub x GitHub Actions",[73,21534,21535],{},"GitHub x AzureDevOps Releases",[73,21537,21538],{},"GitLab x Jenkins",[73,21540,21541],{},"Azure Repos x AzureDevOps Releases",[73,21543,21544],{},"Azure Repos x Jenkins",[73,21546,21547],{},"Bitbucket Server\u002FCloud x Jenkins",[73,21549,21550,21551,8398],{},"and more… on the way… View all integrations here at ",[514,21552,4219],{"href":4219,"rel":21553},[518],[12,21555,21556,21557,247,21560,21563,21564,21567,21568,3444],{},"Oobeya analyzes all ",[16,21558,21559],{},"commits, pull requests,",[16,21561,21562],{},"deployment pipelines"," and generates detailed ",[791,21565,21566],{},"historical"," reports of DORA metrics. Oobeya Deployment Analytics (DORA) Report includes the following features and ",[791,21569,21570],{},"more",[70,21572,21573,21578,21583,21588,21593,21599],{},[73,21574,21575,21577],{},[16,21576,13285],{}," (average time & breakdown & DORA badge)",[73,21579,21580,21582],{},[16,21581,825],{}," (average & chart & DORA badge)",[73,21584,21585,21587],{},[16,21586,859],{}," (average & DORA badge)",[73,21589,21590,21592],{},[16,21591,13349],{}," \u002F Mean Time to Recovery (MTTR) (average time & DORA badge)",[73,21594,21595,21598],{},[16,21596,21597],{},"List of deployments"," during the selected period (breakdown, lead time, contributors…)",[73,21600,21601,21604],{},[16,21602,21603],{},"Deploy size"," for each deployment (small, medium, large, gigantic)",[12,21606,21607,21610,21611,247,21614,365,21617,21622,21623,21626],{},[16,21608,21609],{},"The “Lead Time For Changes” breakdown"," includes four significant steps such as ",[791,21612,21613],{},"coding time, code review time, waiting for deploy time,",[791,21615,21616],{},"deployment time",[16,21618,21619],{},[791,21620,21621],{},"Visualizing"," these steps ",[16,21624,21625],{},"helps you pinpoint bottlenecks"," in your software development and delivery cycle. ",[12,21628,21629,21632],{},[4866,21630],{"alt":21631,"src":16796,"title":21631},"Measure DORA Metrics with Oobeya"," Measure DORA Metrics with Oobeya",[52,21634,21636],{"id":21635},"beyond-dora-metrics-explore-the-oobeya-platform",[16,21637,21638],{},"Beyond DORA Metrics, Explore the Oobeya Platform",[12,21640,21641,21642,23,21644,21647,21648,19287,21650,21653,21654,247,21656,21658,21659,611],{},"Furthermore, rather than ",[791,21643,19278],{},[514,21645,469],{"href":516,"rel":21646},[518]," (",[791,21649,19286],{},[791,21651,21652],{},"team health\u002Fsymptoms, custom dashboards, git analytics, agile analytics…",") that aim to provide complete ",[16,21655,19294],{},[16,21657,19298],{}," processes. Learn more about the ",[514,21660,21662],{"href":516,"rel":21661},[518],"Oobeya Engineering Management Platform",[4331,21664,21665],{"id":13186},[16,21666,13189],{},[70,21668,21669],{},[73,21670,21671],{},[70,21672,21673],{},[73,21674,21675,21676,21679],{},"Oobeya website: ",[514,21677,516],{"href":516,"rel":21678},[518],[70,21680,21681,21688,21694,21701,21708],{},[73,21682,21683,21684],{},"Oobeya DORA Metrics — Fill out the form for Free Edition: ",[514,21685,21686],{"href":21686,"rel":21687},"https:\u002F\u002Foobeya.io\u002Fdora-metrics\u002F",[518],[73,21689,21690,21691],{},"DORA research program: ",[514,21692,11244],{"href":11244,"rel":21693},[518],[73,21695,21696,21697],{},"DORA DevOps Quick Check: ",[514,21698,21699],{"href":21699,"rel":21700},"https:\u002F\u002Fwww.devops-research.com\u002Fquickcheck.html",[518],[73,21702,21703,21704],{},"State of DevOps: ",[514,21705,21706],{"href":21706,"rel":21707},"https:\u002F\u002Fcloud.google.com\u002Fblog\u002Fproducts\u002Fdevops-sre\u002Fannouncing-dora-2021-accelerate-state-of-devops-report",[518],[73,21709,21710,21711,21714,21715],{},"Accelerate. ",[16,21712,21713],{},"Authors:"," Nicole Forsgren, Jez Humble, and Gene Kim: ",[514,21716,21717],{"href":21717,"rel":21718},"https:\u002F\u002Fitrevolution.com\u002Fbook\u002Faccelerate\u002F",[518],{"title":526,"searchDepth":527,"depth":527,"links":21720},[21721,21722,21723,21726,21727,21728,21729],{"id":21374,"depth":527,"text":21377},{"id":21388,"depth":527,"text":21391},{"id":21417,"depth":527,"text":21420,"children":21724},[21725],{"id":21426,"depth":530,"text":21429},{"id":21450,"depth":527,"text":21453},{"id":21471,"depth":527,"text":21474},{"id":21480,"depth":527,"text":21483},{"id":21489,"depth":527,"text":21492,"children":21730},[21731],{"id":21635,"depth":530,"text":21638},[1232],"2022-06-11","Learn how to measure DORA Metrics accurately with Oobeya. Get detailed historical reports and improve the development and delivery processes.",{},"\u002Fblog\u002Fhow-to-measure-dora-metrics-accurately",{"title":21359,"description":21734},"blog\u002Fhow-to-measure-dora-metrics-accurately",[18882,19359,21740,8865,8440,540,19360,19458,19460,21741,21742],"delivery-efficiency","jenkins","software-efficiency","D16d6LuOkuwwrzek5AFbHheFOAmO6J2PUTjLjJp0hcA",{"id":21745,"title":21340,"author":4245,"avatar":575,"body":21746,"categories":22324,"createAt":542,"date":21733,"description":22325,"extension":545,"meta":22326,"navigation":547,"path":22327,"position":542,"seo":22328,"spotImage":542,"spotText":542,"stem":22329,"tags":22330,"__hash__":22331},"blog\u002Fblog\u002Fwhy-code-reviews-should-be-your-favorite-activity.md",{"type":9,"value":21747,"toc":22293},[21748,21752,21758,21769,21787,21789,21792,21811,21827,21834,21841,21852,21873,21880,21895,21917,21924,21931,21950,21952,21956,21962,21971,21975,21986,21990,22001,22005,22008,22012,22023,22027,22030,22032,22036,22039,22045,22050,22055,22060,22064,22072,22076,22084,22088,22102,22104,22108,22115,22124,22127,22135,22144,22164,22173,22175,22179,22184,22187,22191,22194,22197,22204,22208,22211,22214,22222,22226,22229,22235,22243,22247,22250,22258,22261,22267,22269,22273,22287],[613,21749,21751],{"id":21750},"why-code-reviews-should-be-your-favorite-activity-and-why-you-should-be-better-in-code-review","Why Code Reviews Should Be Your Favorite Activity And Why You Should Be Better In Code Review",[12,21753,21754,21755,21757],{},"Tips for being a better code reviewer, creating better ",[514,21756,14598],{"href":14597},", and accelerating with pull request analytics…",[12,21759,21760,21761,21764,21765,21768],{},"The code review process is an essential key to maintaining and improving ",[16,21762,21763],{},"product quality",". But it can also be a bottleneck, and unnerving activity for your development team, and may reduce your development productivity. Therefore, you should care about the ",[16,21766,21767],{},"best practices of the code review"," process outlined in this article.",[70,21770,21771,21774,21777,21780],{},[73,21772,21773],{},"Why Should You Care About Code Reviews? 🤔",[73,21775,21776],{},"5 Tips To Be A Better Pull Request Reviewer. 🤓",[73,21778,21779],{},"4 Tips To Create Better Pull Requests. 😎",[73,21781,21782,21783,21786],{},"Pull Request Analytics with ",[514,21784,469],{"href":516,"rel":21785},[518],". 📊",[501,21788],{},[613,21790,21773],{"id":21791},"why-should-you-care-about-code-reviews",[12,21793,21794,21795,8398,21798,19295,21801,21804,21805,19295,21808,611],{},"Most of the development teams already know the importance of the code review activity as practitioners. This section tells ",[16,21796,21797],{},"C-Levels,",[16,21799,21800],{},"Product Managers,",[16,21802,21803],{},"Engineering Managers"," that investing in the code review processes rewards you with ",[16,21806,21807],{},"better products",[16,21809,21810],{},"better development teams",[12,21812,21813,21814,19279,21816,19295,21819,21822,21823,21826],{},"Development teams can improve their ",[16,21815,21763],{},[16,21817,21818],{},"development skills,",[16,21820,21821],{},"team collaboration"," with a ",[16,21824,21825],{},"better code review"," process.",[12,21828,21829,21833],{},[4866,21830],{"alt":21831,"src":21832},"Improve product quality, development skills, and team collaboration with a better code review process.","\u002Fassets\u002Fblog\u002F1_3iV5t3WNlTnCELiUNA3JaA.png"," Improve product quality, development skills, and team collaboration with a better code review process.",[52,21835,21837,21840],{"id":21836},"_1-product-quality",[16,21838,21839],{},"1. Product Quality"," ✅",[12,21842,21843,21844,21847,21848,21851],{},"Each product team wants to ",[16,21845,21846],{},"deliver faster while staying reliable",". At this point, the code review process can be considered as ",[16,21849,21850],{},"a gatekeeper for the codebase",". Code reviews:",[70,21853,21854,21857,21863,21870],{},[73,21855,21856],{},"Prevent potential bugs, accidental errors, and structural errors.",[73,21858,21859,21860,611],{},"Improve ",[16,21861,21862],{},"code quality",[73,21864,21865,21866,21869],{},"Reduce and limit ",[16,21867,21868],{},"technical debt"," in the codebase.",[73,21871,21872],{},"Keep the code clear, readable, and maintainable.",[52,21874,21876,21879],{"id":21875},"_2-personal-growth",[16,21877,21878],{},"2. Personal Growth"," 💯",[12,21881,21882,21883,21886,21887,21890,21891,21894],{},"Code reviews offer an excellent opportunity for ",[16,21884,21885],{},"personal growth",". It drives you to ",[16,21888,21889],{},"learn for"," code reviews and ",[16,21892,21893],{},"learn from"," code reviews. Code reviews:",[70,21896,21897,21904,21911],{},[73,21898,21899,21900,21903],{},"Make you more ",[16,21901,21902],{},"curious"," about clean coding, SOLID, DRY principles, etc.",[73,21905,21906,21907,21910],{},"Force you to get a ",[16,21908,21909],{},"deeper understanding"," of the code.",[73,21912,21913,21914,611],{},"Give you a great chance to ",[16,21915,21916],{},"learn from others",[52,21918,21920,21923],{"id":21919},"_3-team-collaboration",[16,21921,21922],{},"3. Team Collaboration"," 🙌",[12,21925,21926,21927,21930],{},"Code reviews increase team collaboration and get everyone together on the same page. Code reviews also create a unique opportunity for ",[16,21928,21929],{},"remote team members"," to interact with each other. Code reviews:",[70,21932,21933,21940],{},[73,21934,21935,21936,21939],{},"Increase ",[16,21937,21938],{},"knowledge sharing"," within the team.",[73,21941,21942,21943,21946,21947,611],{},"Enhance ",[16,21944,21945],{},"team interactions"," and improve ",[16,21948,21949],{},"collaboration",[501,21951],{},[613,21953,21955],{"id":21954},"_5-tips-to-be-a-better-pull-request-reviewer","5 Tips To Be A Better Pull Request Reviewer 🤓",[12,21957,21958,21959],{},"A pull request (or merge request) is a method to perform a code review activity for your codebase. You can find five tips below ",[16,21960,21961],{},"to be a better code reviewer:",[18479,21963,21964],{},[12,21965,21966,21970],{},[4866,21967],{"alt":21968,"src":21969},"5 tips to be a better code reviewer","\u002Fassets\u002Fblog\u002F1_DMt79GWTO_oCQJgIPOEn8Q.png"," 5 tips to be a better code reviewer",[52,21972,21974],{"id":21973},"_1-focus-on-pull-request","1. Focus on Pull Request.",[70,21976,21977,21980,21983],{},[73,21978,21979],{},"Focus on the pull request, and fully understand its context.",[73,21981,21982],{},"Find relevant tasks and documentation about the change requested.",[73,21984,21985],{},"Ask “why” on each line of the change.",[52,21987,21989],{"id":21988},"_2-comment-on-pull-request","2. Comment on Pull Request.",[70,21991,21992,21995,21998],{},[73,21993,21994],{},"Comment on the pull requests. Explain the problematic units.",[73,21996,21997],{},"Ask why and suggest better methods if necessary.",[73,21999,22000],{},"Also, be kind and give constructive feedback. It may boost your team’s morale.",[52,22002,22004],{"id":22003},"_3-improve-your-programming-skills","3. Improve your programming skills.",[12,22006,22007],{},"Always improve your programming skills and keep your knowledge up-to-date about programming best practices, clean code principles, etc.",[52,22009,22011],{"id":22010},"_4-automate-everything","4. Automate everything.",[70,22013,22014,22017,22020],{},[73,22015,22016],{},"Automation is the first gatekeeper of code reviews. Automate what can be automated in the code review process.",[73,22018,22019],{},"Enable automated build, unit and integration testing, static code analysis, etc.",[73,22021,22022],{},"Focus on the code, not on style. Style checks can be automated.",[52,22024,22026],{"id":22025},"_5-care-about-time","5. Care about time.",[12,22028,22029],{},"Time is important… Don’t be a procrastinator. Don’t block others’ work.",[501,22031],{},[613,22033,22035],{"id":22034},"_4-tips-to-create-better-pull-requests","4 Tips To Create Better Pull Requests 😎",[12,22037,22038],{},"Before submitting a pull request for review, check out the four tips below by yourself:",[52,22040,22042],{"id":22041},"_1-keep-it-small",[16,22043,22044],{},"1. Keep it small.",[70,22046,22047],{},[73,22048,22049],{},"Reviewers usually don’t dive deep into code if the pull request size is so big.",[12,22051,22052],{},[4866,22053],{"alt":22049,"src":22054},"\u002Fassets\u002Fblog\u002F1_1ro4aSFt_IcHTat1DcAVaw.png",[70,22056,22057],{},[73,22058,22059],{},"If they decide to battle with your changes, it will take too much time to review the pull request and block other developers.",[52,22061,22063],{"id":22062},"_2-code-faster","2. Code faster.",[70,22065,22066,22069],{},[73,22067,22068],{},"Break large features into small pieces and keep the coding time short for each pull request.",[73,22070,22071],{},"Reduce cycle time, see the problems earlier.",[52,22073,22075],{"id":22074},"_3-review-faster","3. Review faster.",[70,22077,22078,22081],{},[73,22079,22080],{},"Don’t let your code changes stale.",[73,22082,22083],{},"Prevent potential merge conflicts.",[52,22085,22087],{"id":22086},"_4-be-ready-to-be-reviewed","4. Be ready to be reviewed.",[70,22089,22090,22093,22096,22099],{},[73,22091,22092],{},"Review yourself before submitting your pull request.",[73,22094,22095],{},"Give it a clear and descriptive title and write a good description.",[73,22097,22098],{},"Check the style of the code.",[73,22100,22101],{},"Run your local tests.",[501,22103],{},[18668,22105,22107],{"id":22106},"pull-request-analytics-with-oobeya","Pull Request Analytics with OOBEYA ✅",[12,22109,22110,22111,22114],{},"The code review process is a black box for ",[16,22112,22113],{},"engineering management",". You may be familiar with code review best practices, but you may still have difficulty in managing and controlling this process.",[18479,22116,22117],{},[12,22118,22119,22123],{},[4866,22120],{"alt":22121,"src":22122},"Oobeya Pull Request Analytics feature","\u002Fassets\u002Fblog\u002F1_YbsxgBtwCCmAr67gZTyIiw.png"," Oobeya Pull Request Analytics feature",[12,22125,22126],{},"You can get visibility into the code review process by using pull request analytics tools. With the help of pull request analytics tools such as Oobeya, you can:",[70,22128,22129,22132],{},[73,22130,22131],{},"Learn if you have an efficient code review process or not. Detect your bottlenecks.",[73,22133,22134],{},"Receive Slack\u002FTeams alerts about oversized, stale, lightning, and overdue pull requests.",[18479,22136,22137],{},[12,22138,22139,22143],{},[4866,22140],{"alt":22141,"src":22142},"Oobeya Slack integration","\u002Fassets\u002Fblog\u002F1_h3J6lTuwY63ZnNL9xfLs7Q.png"," Oobeya Slack integration",[12,22145,10765,22146,6406,22150,23,22153,23,22156,23,22159,22163],{},[514,22147,22149],{"href":8313,"rel":22148},[518],"integrates",[514,22151,6908],{"href":18260,"rel":22152},[518],[514,22154,6905],{"href":18264,"rel":22155},[518],[514,22157,4528],{"href":18256,"rel":22158},[518],[514,22160,18270],{"href":22161,"rel":22162},"https:\u002F\u002Fdocs.oobeya.io\u002Fintegrations\u002Fscm-addons\u002Fbitbucket-cloud-integration",[518],", and both server and cloud editions.",[18479,22165,22166],{},[12,22167,22168,22172],{},[4866,22169],{"alt":22170,"src":22171},"Oobeya Market Place","\u002Fassets\u002Fblog\u002F1_4YniW04ViFqYA77j_9pCQg.png"," Oobeya Market Place",[501,22174],{},[613,22176,22178],{"id":22177},"pull-request-metrics","Pull Request Metrics 📊",[12,22180,22181],{},[4866,22182],{"alt":19503,"src":22183},"\u002Fassets\u002Fblog\u002F1_yFo7wBkacnBX2bcJYGbfog.png",[12,22185,22186],{},"See below the metrics of pull request activities and how you can improve your engineering process by tracking them.",[52,22188,22190],{"id":22189},"_1-work-in-progress","1. Work In Progress",[12,22192,22193],{},"WIP PRs show open pull requests, risk labels, and bottlenecks of the development process.",[12,22195,22196],{},"You can see the risky pull requests and take action to resolve them earlier. Alerts and reminders for open pull requests can help you improve your cycle time.",[18479,22198,22199],{},[12,22200,22201,19505],{},[4866,22202],{"alt":19503,"src":22203},"\u002Fassets\u002Fblog\u002F1_68hXs-z8nLd7P1y7DMHYNQ.png",[52,22205,22207],{"id":22206},"_2-coding-time-time-to-open","2. Coding Time (Time to open)",[12,22209,22210],{},"Coding time shows the time elapsed between the first commit and open time for pull requests.",[12,22212,22213],{},"Long coding time may block developers to see the problems earlier. Long coding time is a major risk for the high cycle time. Developers should break large features into small pieces and keep the coding time short for each pull request.",[18479,22215,22216],{},[12,22217,22218,22221],{},[4866,22219],{"alt":19503,"src":22220},"\u002Fassets\u002Fblog\u002F1_SDjZxvGzIULR_8BVccSZVQ.png"," Oobeya Pull Request Analytics - Coding Time",[52,22223,22225],{"id":22224},"_3-code-review-cycle-time-time-to-review","3. Code Review Cycle Time (Time to review)",[12,22227,22228],{},"Code review cycle time shows the time elapsed between the open time and merge time of a pull request.",[12,22230,22231,22232,22234],{},"You can see the ",[16,22233,19521],{}," pull requests in red below. If code review time took longer than the goal, the pull request is identified as stale. Long review time is a blocker for development teams.",[18479,22236,22237],{},[12,22238,22239,22242],{},[4866,22240],{"alt":19503,"src":22241},"\u002Fassets\u002Fblog\u002F1_OEtqdDsGSph3BSzZ--79aw.png"," Oobeya Pull Request Analytics - Review Time",[52,22244,22246],{"id":22245},"_4-pull-request-size","4. Pull Request Size",[12,22248,22249],{},"Pull request size shows the total changed size (lines added, removed, and changed) of a pull request.",[18479,22251,22252],{},[12,22253,22254,22257],{},[4866,22255],{"alt":19503,"src":22256},"\u002Fassets\u002Fblog\u002F1_N8eflTt8pOawGQtPv_Drwg.png"," Oobeya Pull Request Analytics - PR Size",[12,22259,22260],{},"You can set a goal for PR size and send alerts to Slack\u002FTeams channels if the size is bigger than the goal.",[18479,22262,22263],{},[12,22264,22265,22143],{},[4866,22266],{"alt":22141,"src":22142},[501,22268],{},[613,22270,22272],{"id":22271},"let-the-power-be-with-you-️","Let The Power Be With You ⭐️",[12,22274,22275,22276,22279,22280,22283,22284,611],{},"If you want to build a ",[16,22277,22278],{},"high-performing technology organization",", it’s time to meet ",[16,22281,22282],{},"pull request analytics"," with ",[514,22285,469],{"href":516,"rel":22286},[518],[12,22288,22289,22290],{},"You can learn more about the product, schedule a demo, or see the live demo by visiting Oobeya’s website: ",[514,22291,5051],{"href":516,"rel":22292},[518],{"title":526,"searchDepth":527,"depth":527,"links":22294},[22295,22296,22304,22311,22317,22323],{"id":21750,"depth":527,"text":21751},{"id":21791,"depth":527,"text":21773,"children":22297},[22298,22300,22302],{"id":21836,"depth":530,"text":22299},"1. Product Quality ✅",{"id":21875,"depth":530,"text":22301},"2. Personal Growth 💯",{"id":21919,"depth":530,"text":22303},"3. Team Collaboration 🙌",{"id":21954,"depth":527,"text":21955,"children":22305},[22306,22307,22308,22309,22310],{"id":21973,"depth":530,"text":21974},{"id":21988,"depth":530,"text":21989},{"id":22003,"depth":530,"text":22004},{"id":22010,"depth":530,"text":22011},{"id":22025,"depth":530,"text":22026},{"id":22034,"depth":527,"text":22035,"children":22312},[22313,22314,22315,22316],{"id":22041,"depth":530,"text":22044},{"id":22062,"depth":530,"text":22063},{"id":22074,"depth":530,"text":22075},{"id":22086,"depth":530,"text":22087},{"id":22177,"depth":527,"text":22178,"children":22318},[22319,22320,22321,22322],{"id":22189,"depth":530,"text":22190},{"id":22206,"depth":530,"text":22207},{"id":22224,"depth":530,"text":22225},{"id":22245,"depth":530,"text":22246},{"id":22271,"depth":527,"text":22272},[541],"Tips for being a better code reviewer, creating better pull requests, and accelerating with pull request analytics…",{},"\u002Fblog\u002Fwhy-code-reviews-should-be-your-favorite-activity",{"title":21340,"description":22325},"blog\u002Fwhy-code-reviews-should-be-your-favorite-activity",[18882,19930,11825,19458,19460,19462,541],"7SeAwLYTvQrnK8j-_Z4gKKJ0L3zaJ-Pt1ZcXQvZHS-I",1775216694842]