The four metrics
1. Deployment frequency
How often your team deploys to production.| Performance | Frequency |
|---|---|
| Elite | On-demand (multiple times per day) |
| High | Weekly to monthly |
| Medium | Monthly to every six months |
| Low | Less than once every six months |
2. Lead time for changes
Time from code commit to running in production.| Performance | Lead time |
|---|---|
| Elite | Less than one day |
| High | One day to one week |
| Medium | One week to one month |
| Low | More than six months |
3. Change failure rate
Percentage of deployments that cause a failure requiring remediation (rollback, hotfix, or patch).| Performance | Failure rate |
|---|---|
| Elite | 0–15% |
| High | 16–30% |
| Medium | 16–30% |
| Low | 46–60% |
4. Time to restore service (MTTR)
How long it takes to recover from a failure in production.| Performance | Recovery time |
|---|---|
| Elite | Less than one hour |
| High | Less than one day |
| Medium | One day to one week |
| Low | More than six months |
Why DORA matters
DORA research (now part of Google Cloud) demonstrated that these four metrics predict both software delivery performance and organizational performance. Teams that excel on all four metrics:- Deploy more frequently with fewer failures
- Recover faster when things break
- Have higher employee satisfaction
- Deliver more business value
How monitoring helps
Uptime monitoring directly impacts two DORA metrics:Change failure rate
Monitoring immediately tells you whether a deployment caused a failure. Without monitoring, failed deployments can go undetected for hours, distorting your metrics.Time to restore service
Faster detection (MTTD) means faster restoration (MTTR). Automated monitoring with clear alerting is the foundation of rapid recovery.Improving DORA metrics
| Metric | Improvement strategy |
|---|---|
| Deployment frequency | Smaller PRs, CI/CD automation, feature flags |
| Lead time | Automated testing, trunk-based development, fast CI |
| Change failure rate | Better testing, canary deploys, monitoring-gated rollouts |
| Time to restore | Automated rollback, playbooks, alerting with context |
Monitoring as Code and DORA
Monitoring as Code specifically improves DORA metrics by:- Deployment frequency — monitoring config deploys alongside code changes
- Lead time — automated validation catches issues in CI, not production
- Change failure rate — monitoring changes are reviewed in PRs like code
- MTTR — consistent monitoring setup across environments speeds diagnosis
MTTR & MTTD
The incident metrics that feed into DORA’s MTTR.
CI/CD patterns
Automate monitoring deploys to improve all four metrics.