What are DORA metrics?
DORA metrics are four measurements of software delivery performance developed by the DevOps Research and Assessment (DORA) team. They emerged from six years of research involving tens of thousands of engineering teams worldwide and are now the most widely validated framework for assessing DevOps capability.
The core finding: high-performing teams are not trading speed for stability. Elite performers deploy more frequently and more reliably than low performers — speed and quality move together.
The four metrics
1. Deployment Frequency
How often does your team deploy to production? This metric captures delivery cadence. Higher frequency generally means smaller, lower-risk changes and faster feedback from real users.
| Band | Deployment frequency |
|---|---|
| Elite | Multiple times per day |
| High | Once per day to once per week |
| Medium | Once per week to once per month |
| Low | Less than once per month |
2. Lead Time for Changes
How long does it take from code commit to production deployment? This measures the efficiency of the delivery pipeline — from writing code to delivering value to users.
| Band | Lead time |
|---|---|
| Elite | Less than one hour |
| High | One hour to one day |
| Medium | One day to one week |
| Low | More than one month |
3. Time to Restore Service (MTTR)
How quickly can your team restore service after an incident? This measures the operational response capability of the team and the quality of observability, runbooks, and incident processes.
| Band | Time to restore |
|---|---|
| Elite | Less than one hour |
| High | Less than one day |
| Medium | Less than one week |
| Low | More than one week |
4. Change Failure Rate
What percentage of deployments cause a failure requiring remediation (rollback, hotfix, or patch)? This measures deployment quality and testing effectiveness.
| Band | Change failure rate |
|---|---|
| Elite | 0–15% |
| High | 16–30% |
| Medium | 31–45% |
| Low | More than 45% |
Key research findings
Elite performers are significantly more likely to meet their reliability and performance targets. They also report lower burnout rates and better team culture. The research consistently finds that you do not have to choose between speed and stability — the practices that improve one tend to improve the other.
The strongest levers for improvement are: investing in CI/CD automation (improves deployment frequency and lead time), improving test coverage and quality (reduces change failure rate), and investing in observability and runbooks (reduces MTTR).