DORA metrics are the four key measures used to assess DevOps and software delivery performance. They track deployment frequency, lead time for changes, change failure rate, and mean time to recovery, helping teams understand both delivery speed and operational reliability.
These metrics give engineering leaders a practical way to identify bottlenecks, reduce delivery risk, and improve software performance over time. In this guide, we explain what DORA metrics are, how they relate to wider DevOps metrics, and how to use them to improve software delivery across your engineering and CI/CD practices.
What Are DORA Metrics?
DORAs metrics are the data points that demonstrate the performance of a DevOps software pipeline and engineering quality.
DevOps combines practices, tools, and culture that enhance an organisation’s ability to deliver products faster than traditional processes.
The metrics help increase efficiency by providing quantitative analysis of the teams’ performance. They demonstrate actionable insights about the performance of a software development team. Also, metrics directly reveal the capabilities and processes of DevOps software development and help teams notice and remove the bottlenecks in the processes.
Therefore, having the means to understand and assess the effectiveness of your DevOps practices will help teams deliver quality code faster and allow continuous improvement.
Just like the proverb says that you can’t improve what you can’t measure, it is crucial to look at several metrics. But how do you get started?
The 4 DORA Metrics at a Glance
The four most widely used DevOps metrics are deployment frequency, lead time for changes, change failure rate, and mean time to recovery (MTTR). Together, these metrics help engineering teams understand delivery speed, reliability, and operational resilience.
The 4 DORA Metrics You Should Track
Four widely recognised key metrics are used to distinguish the team’s performance: Lead time, Change failure rate, Deployment frequency, and Mean time to recovery (MTTR). Let’s explore each of these metrics.
1. Lead time
Lead time measures the time from making a commitment and releasing it to production. This metric should be as small as possible to highlight the team’s agility. To measure lead time, teams must clearly define when work begins and ends. Teams generally start tracking lead time when development work is first scheduled in a project management tool like Jira.
Optimising this metric will motivate the team to shorten the overall time to deployment by tackling smaller chunks of work and optimising the integration of the testing process.
2. Change failure rate
Change failure rate refers to the ratio between unsuccessful and successful changes. Failure here includes changes that lead to service degradation or an outage that requires remediation. Such as deployment failures. High-performing teams generally have 0-15% change failure rates out of all the executed deployments.
DevOps teams can use this as a measurement to track their progress. For example, the change failure rate was 50% last week due to two deployment failures. This week, it came down to 25% due to automating the deployment; the goal was to lower it by half.
To measure the change failure rate, it is necessary to know how many deployments have been attempted and how many failed in production. The team has to identify and understand the root cause of the failure. Generally, the practices that enable shorter lead times, such as test automation and working in small batches, reduce failure rates.
3. Deployment frequency
Deployment frequency measures the number of successful releases to production over a certain period. Understanding the frequency of new code being deployed into production is crucial to define DevOps success.
High-performing teams can deploy new code into the production many times a day, while low-performing teams are limited to deploying weekly or monthly. To improve customer satisfaction, DevOps teams aim to increase deployment frequency even if the change is small.
4. Mean time to recovery
Simply put, Mean time to recover (MTTR) measures the time it takes an organisation to recover from a production failure. To measure this metric, you need to know when the incident happens and when the service is restored.
People often misunderstand that MTTR is about the time it takes to fix a build. But it’s about assessing the capabilities of the DevOps team to respond to customer support issues. Their ability to resolve and deploy solutions quickly.
Faster MTTR enhances customer satisfaction because the decreased frequency of failures minimises the lead time. And increased deployment frequency reduces failure rate and mean time to recover.
Why DORA Metrics Matter for Continuous Improvement
DORAs Metrics provide quantifiable insights into the efficiency, reliability, and stability of your software delivery lifecycle. By analysing data points like deployment frequency, lead time for changes, change failure rate, and mean time to recovery (MTTR), engineering teams can implement evidence-based improvements across CI/CD pipelines.
These metrics drive continuous feedback loops, enabling data-driven prioritisation of automation, process refinement, and incident response. In high-performing DevOps environments, metrics aren’t optional, they’re the diagnostic tools that validate architecture decisions and optimise flow.
How DORA Metrics Support Better Delivery Decisions
Tracking DevOps metrics helps teams move beyond assumptions and make better delivery decisions based on evidence. By reviewing trends in speed, stability, and recovery, organisations can prioritise improvements that reduce risk, improve flow, and strengthen software delivery performance over time.
Why Measuring DORA Metrics Is Harder Than It Looks
DevOps metrics effectively gain visibility of your current DevOps state and give you the crucial key to improving your DevOps performance. Having understood the four key metrics, have you considered how to measure your organisation’s DevOps capabilities?
DevOps Capabilities are crucial to moving the dial on the four key metrics. Most organisations find it hard to gather these DevOps metrics and measurement capabilities. So what can you do? Think about getting a SKILup assessment.
How to Assess DORA Metrics in Practice
The DevOps institute has introduced SKILup assessment, which defines the state of your DevOps by measuring and accelerating continuous improvement. It is a comprehensive and five-dimensional model that uses the Likert scale and heat maps to deliver insights into each dimension.
The five dimensions are:
- Human aspects
- Process and frameworks
- Functional composition
- Intelligent automation
- Technology ecosystem
Catapult CX is one of the only SKILup assessment consulting partners in the UK
We offer what others don’t. We help our clients to understand their DevOps metrics and analyse the data to create their Roadmap.
We help teams build the best-suited DevOps model for their organisation and enable teams to improve DevOps performance continuously.
If your delivery metrics are hard to measure, inconsistent across teams, or not driving meaningful improvement, we can help you assess the gaps and build a clearer roadmap.
DORA Metrics FAQ
What are DORA metrics?
DORA metrics are the four key measures used to assess software delivery performance in DevOps environments. They are deployment frequency, lead time for changes, change failure rate, and mean time to recovery. Together, they help teams evaluate both delivery speed and operational reliability.
What are the 4 DORA metrics?
The four DORA metrics are deployment frequency, lead time for changes, change failure rate, and mean time to recovery (MTTR). These metrics are widely used to measure how effectively teams deliver and maintain software in production.
What is the difference between DORA metrics and DevOps metrics?
DORA metrics are a specific set of four software delivery measures. DevOps metrics is a broader term that can also include engineering, quality, security, and operational indicators beyond the DORA framework. In practice, DORA metrics are often the starting point for measuring DevOps performance.
Why do DORA metrics matter?
DORA metrics matter because they turn software delivery performance into something measurable. They help teams identify bottlenecks, reduce risk, improve deployment reliability, and make better decisions about process, tooling, and automation.
How do DORA metrics improve CI/CD performance?
DORA metrics help teams see where delivery slows down or becomes unstable. By tracking trends in lead time, deployment frequency, recovery time, and failed changes, teams can improve test automation, release processes, rollback readiness, and delivery flow across the CI/CD pipeline.
How often should DORA metrics be reviewed?
DORA metrics should be monitored continuously where possible and reviewed regularly, usually weekly or during retrospectives and operational reviews. Frequent review helps teams spot negative trends early and make improvements before delivery performance degrades further.
Are DORA metrics only useful for large organisations?
No. DORA metrics are useful for teams of all sizes. Smaller teams can use them to improve flow and reduce delivery friction, while larger organisations can use them to compare performance across systems, teams, or business units.
