How do I start measuring DORA metrics?

Start with Deployment Frequency and Lead Time — they're the easiest to measure from your CI/CD pipeline data. Most teams can pull this from GitHub Actions, GitLab CI, or Jenkins. Change Failure Rate and MTTR require incident tracking (PagerDuty, Opsgenie, or a shared spreadsheet). Don't aim for perfection — directional data is enough to drive improvement.

Are DORA metrics enough to measure engineering team health?

DORA measures delivery performance, but it doesn't capture developer experience, collaboration quality, or satisfaction. That's why many engineering leaders pair DORA with the SPACE framework — DORA for delivery health, SPACE for the human side of engineering.

Can DORA metrics be gamed?

Any metric can be gamed if used punitively. Deploying empty commits inflates frequency; ignoring incidents hides failure rate. The antidote is pairing DORA with qualitative feedback and using metrics to start conversations, not to create rankings. Teams that understand why these metrics matter don't need to game them.

DORA Metrics Explained: The Four Keys to Software Delivery

What is a DORA Metrics?

DORA metrics are four key indicators of software delivery performance, originally validated by Google's DevOps Research and Assessment (DORA) team through years of industry research. The four metrics — Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Mean Time to Restore — together measure how fast a team can ship reliable software. DORA has become the industry benchmark for engineering organizations that want to improve delivery without sacrificing stability.

Key Takeaways

DORA consists of four metrics: Deployment Frequency, Lead Time, Change Failure Rate, and MTTR
High-performing teams deploy on demand with lead times under one day
Stability and speed are not trade-offs — elite teams excel at both
Use DORA as a baseline, then layer in developer experience metrics for the full picture

What DORA Measures

DORA measures software delivery performance — specifically, how quickly and reliably a team can get changes into production. The research, led by Dr. Nicole Forsgren, Gene Kim, and Jez Humble, found that these four metrics are the strongest predictors of both engineering performance and organizational outcomes like profitability and market share.

The Four Key Metrics

1

Deployment Frequency

How often your team releases to production. Elite teams deploy on demand — multiple times per day. Low performers deploy less than once per month. Higher frequency means smaller batches, lower risk, and faster feedback loops.

2

Lead Time for Changes

The time from a code commit to that code running in production. Elite teams achieve lead times under one day. This metric reveals bottlenecks in your CI/CD pipeline, code review process, and deployment workflow.

3

Change Failure Rate

The percentage of deployments that cause a failure in production (requiring a hotfix, rollback, or patch). Elite teams maintain a change failure rate under 5%. This metric measures the reliability of your release process.

4

Mean Time to Restore (MTTR)

The time it takes to recover from a production failure. Elite teams restore service in under one hour. MTTR measures your team's incident response capability and the resilience of your systems.

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DORA Performance Levels

Metric	Elite	High	Medium	Low
Deployment Frequency	On demand	Weekly to monthly	Monthly to semi-annually	Less than once per 6 months
Lead Time	Less than 1 day	1 day to 1 week	1 week to 1 month	More than 1 month
Change Failure Rate	0–5%	6–10%	11–15%	16–30%
MTTR	Less than 1 hour	Less than 1 day	1 day to 1 week	More than 1 week