DORA, the DevOps Research and Assessment model, developed by experts Nicole Forsgren, Jez Humble, and Gene Kim, evaluates an organization's software delivery and operational performance.
Engineering leaders leverage DORA metrics to assess deployment frequency, change lead time, failure rate, and service restoration time. These metrics offer insights into process efficiency and reliability.
DORA guides organizations in enhancing collaboration, streamlining workflows, and achieving faster, more reliable software delivery, aligning with DevOps principles for sustained success in technology and engineering.
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DORA Metrics Center
Resource center
Measuring DORA metrics involves assessing key indicators that provide insights into the effectiveness and efficiency of an organization's software delivery and operational performance. The four primary DORA metrics are:
01. Lead Time
Lead time is how long it takes your team to implement an enhancement or a bug fix. It’s the time elapsed between when your team receives a request and when they deploy the fix or enhancement to production. lead time = date request completed - date request receivedYou can calculate this with reports from tools like Jira, Trello, and Asana, that track your feature and deficiency tickets...
Developing software is a complex and time-consuming process. As a result, maximizing developer productivity is of utmost importance. When developers are able to work efficiently and effectively, they can produce high-quality code in a shorter amount of time. This article explores various strategies and techniques that can help increase developer productivity.
Developer productivity is a critical factor in software development. It directly impacts the time it takes to develop new features, fix bugs, and maintain code. The more productive developers are, the faster they can deliver value to end-users and meet project deadlines.
One important aspect of understanding developer productivity is recognizing the role of code dependencies. When code becomes tightly coupled and dependent on other parts of the system, it becomes difficult to make changes and increases the risk of introducing bugs. Breaking these dependencies through techniques like modularization and decoupling can significantly improve productivity.
In 2016 Deno Ray joined Uber as a Software Engineer. Back then Uber just started benchmarking its engineering organization. velocity was at around 1PR/developer/sprint. Production wasn’t doing well either: We experienced inconsistent behavior from newly introduced changes, high number of incidents and a long time to resolution.
The cause for many of these benchmarks was the fact that hundreds of developers were working on a single monorepo, many code changes and refactoring happened in pre-production and our environments were composed of hundreds of services.
To tackle these challenges , Uber went through two different phases: First we focused on developer velocity. Developer experience at its core came after that.
While DORA metrics provide a solid foundation for measuring team performance, they don’t always reveal the hidden inefficiencies in individual workflows. DevZero’s Open Developer Analytics (ODA) extends beyond DORA, offering a granular look into developer productivity by capturing command-level data on common bottlenecks like long build times or slow Git operations.
This real-time insight empowers engineering teams to pinpoint and resolve specific blockers that DORA metrics alone can’t uncover. With ODA, DevZero brings actionable, terminal-level analytics directly to your managed developer workspaces, making it easier than ever to optimize workflows and increase developer velocity. Learn more about ODA and how it builds on DORA metrics.
Ready to enhance your developer productivity?
Sign up for DevZero and start transforming your workflows today.
DORA metrics for popular Git projects
kubernetes/kubernetes
Production-Grade Container Scheduling and Management
Avg. commit time
12.56
Hours
Avg. commit size
19
lines
angular/angular
Deliver web apps with confidence 🚀
Avg. commit time
0.94
Hours
Avg. commit size
48
lines
vuejs/vue-router
🚦 The official router for Vue 2
Avg. commit time
495.81
Hours
Avg. commit size
6
lines
uber/cadence
Cadence is a distributed, scalable, durable, and highly available orchestration engine to execute asynchronous long-running business logic in a scalable and resilient way.
Avg. commit time
3.31
Hours
Avg. commit size
298
lines
twbs/bootstrap
The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.
Avg. commit time
23.39
Hours
Avg. commit size
15
lines
facebook/react
The library for web and native user interfaces.
Avg. commit time
2.44
Hours
Avg. commit size
71
lines
Why do customers use DevZero?
35%
Increase in coding time
Reduced refactoring, compiling and infrastructure handling time, due to always-ready production-like environment to run your code on, resulted in an increase in new code time.
35%
Increase in release frequency
Increased coding time and one environment per PR from code to release means faster CI cycles, less compile time and less time spent isolating bugs and fixing them.
40%
Increase in developers satisfaction
Top engineering organizations are characterized by high developer productivity and velocity. Those organizations invest in their developers experience and in return see high retention rates and better talent,
Visibility to your developers experience and workflows like never before
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Give your team an always-ready environment that mirrors production, allowing them to focus on coding, testing, and seamless deployments.
