Why DevOps Metrics Matter
You can't improve what you don't measure. But most teams don't measure their delivery performance at all.
How long does it take your team to go from first commit to running in production?
Most teams can’t answer this. They ship code, stay busy, feel productive - but have no idea whether they’re getting faster or slower.
The Cost of Not Knowing
“Feels like we’re shipping slower lately.” “I think code review is the bottleneck.” “We should probably deploy more often.”
These might be true. Or not. Without data, there’s no way to tell.
Acting on bad assumptions gets expensive. You spend three months refactoring CI/CD because someone said deployments were slow - then discover the real bottleneck was code review. You hire another engineer, but your process can’t absorb the extra capacity. Output stays flat while costs go up.
Story Points Miss the Point
Story points measure effort, not results. You can close 50 points in a sprint and ship nothing to production. You can inflate estimates to make the graph look better.
DORA metrics measure outcomes instead:
- Deployment Frequency: how often you ship to production
- Lead Time: how long from first commit to production
- Change Failure Rate: how often deploys cause problems
- Mean Time to Recovery: how fast you fix things when they break
These aren’t estimates. They’re facts about your delivery pipeline.
What Measurement Does
You set up tracking and discover you deploy every 18 days, not weekly like you assumed. Lead time is 12 days. A third of your deploys need a hotfix.
Uncomfortable. But now you can do something about it.
Why does code sit in review for 5 days? Why does deployment take 3 hours? Once you see the numbers, you ask better questions. You automate deployment - lead time drops. Smaller PRs - review time drops. More tests - fewer failures.
Over months, small wins compound. The metrics didn’t fix anything directly - they made it possible to see what needed fixing.
What Happens Without It
Process degrades slowly. Deploys get less frequent. Lead times stretch. Failures creep up. It’s gradual enough that nobody notices until shipping anything takes a month.
There’s also no shared understanding. Engineers think deploys are fast. Product thinks they’re slow. Leadership has no idea. Everyone argues from different assumptions.
Numbers give everyone the same starting point.
When Metrics Go Wrong
The most common problem is treating metrics as targets. “Your deployment frequency is too low - fix it.” But the real question is “what’s preventing us from deploying safely?”
Gaming is the other failure mode. Tie metrics to performance reviews and people optimize for the number, not the outcome. Push empty commits for frequency. Measure from PR approval for lead time. Reclassify incidents to hide failures.
Metrics work for learning. They break when used for judgment.
Some teams overdo it - 47 dashboards, more time measuring than improving. If you’re not acting on a metric, stop tracking it.
How to Start
Measure where you are. Don’t judge it, just get a baseline.
Pick one metric to improve - whichever is furthest from where you want it. Make a small change. See if the number moves. Once it improves, move to the next one.
Make the data visible. When everyone sees the same numbers, everyone thinks about how to improve them.
Pick one DORA metric. Track it however you can - spreadsheet, sticky note, whatever.
Someone will ask why it’s that number. And what would make it better.
That’s the whole point.