What Is DevOps Maturity, and How Do You Actually Measure It?

TL;DR

• DevOps maturity isn’t one score — it’s six independent dimensions (CI/CD & Deployment, Infrastructure as Code, Observability, Security & Compliance, Reliability & Incident Response, Developer Experience), and most teams are at different levels across each one.
• Each dimension has three practical tiers: Starting out, Getting there, and Running well — defined by what actually happens day to day, not by which tools are installed.
• The point of measuring isn’t the score itself — it’s finding your weakest dimension and fixing that one first. Moving one dimension from “Starting out” to “Getting there” usually matters more than polishing three areas that are already solid.
• This is the same framework we use in the opening week of DevOps Consulting engagements — you can run it yourself, free, in about twenty minutes.

Why “DevOps maturity” is worth measuring at all

Most engineering teams have an instinct for whether their DevOps practice is solid or held together with tape — but that instinct is usually shaped by whichever incident happened most recently, not by an honest look across the whole pipeline. A team that just survived a bad on-call week feels immature everywhere, even if their CI/CD pipeline is genuinely excellent. A team that hasn’t had an incident in months might be sitting on infrastructure nobody could rebuild from scratch, and just hasn’t found out yet.

A maturity framework fixes that by forcing the question dimension by dimension, with specific, concrete criteria instead of a vague “how good are we at DevOps” gut check. It doesn’t replace judgment — it gives judgment something structured to work from.

The six dimensions

CI/CD & Deployment — How builds get triggered, who can deploy to production, how long a commit takes to reach production, and what fraction of deployments need a rollback. This is the dimension most people think of first when they hear “DevOps,” and it’s usually the easiest to make visible progress on quickly.

Infrastructure as Code — Whether infrastructure is created through a cloud console by hand (ClickOps) or through reviewed, versioned code. The real test isn’t “do we use Terraform for some things” — it’s whether you could recreate your production environment from scratch without guesswork.

Observability — How you find out something is broken, whether you can trace a request end-to-end across services, and how long root-cause takes. Teams often over-index on “we have Grafana dashboards” without asking whether those dashboards actually catch issues before customers do.

Security & Compliance — Where secrets live, whether vulnerability scanning happens before code reaches production, and how fast a compromised credential could be rotated everywhere. This is the one dimension where “Starting out” carries real business risk regardless of company size — a leaked credential doesn’t care that you’re pre-seed.

Reliability & Incident Response — Whether on-call is a formal rotation or “whoever built the service gets woken up,” whether runbooks exist and get used, and whether SLOs actually influence what the team ships next or just sit on a dashboard nobody opens.

Developer Experience — How long it takes a new engineer to ship their first production change, how a new service gets created, and how reliable the local dev environment is. This dimension is easy to deprioritize because it doesn’t cause outages — but it’s a compounding tax on every engineer, every day, until someone fixes it.

The three levels, and what actually separates them

Each dimension breaks into three tiers — Starting out, Getting there, and Running well — and the difference between tiers is behavioral, not which product logos appear in your stack.

Take Infrastructure as Code as an example. “Starting out” means changes happen through the console and nobody’s fully sure what’s been touched by hand. “Getting there” means the core resources are codified but there are known gaps — someone can name the parts still managed manually. “Running well” means the environment could be rebuilt from a single pipeline run, and that claim has actually been tested, not just assumed.

The same pattern holds across all six dimensions: the top tier isn’t defined by tool sophistication, it’s defined by whether the team could prove the claim under pressure — during an incident, an audit, or a new hire’s first week.

How to actually use the result

The instinct after scoring yourself is to want to fix everything at once. Don’t. The dimension that’s weakest — genuinely weakest, not just most annoying this week — is where the next unit of effort returns the most. Moving one dimension from “Starting out” to “Getting there” is usually higher-leverage than moving three dimensions that are already “Getting there” up to “Running well,” because the bottom tier is where the real operational risk and daily friction concentrate.

This also means the framework is only useful if you answer it honestly — for where your team actually is today, not where the roadmap says you’ll be next quarter. A self-assessment scored optimistically just tells you what you already believed.

Real-world example

A Series-agnostic pattern we see constantly: a team scores “Running well” on CI/CD (deploys are fast, automated, low-rollback) and “Starting out” on Observability (alerts are noisy, root cause takes hours), and concludes they need to invest further in deployment tooling because that’s the dimension leadership talks about most. The maturity framework redirects that — the CI/CD investment has diminishing returns at that point, while the Observability gap is actively costing hours of engineering time per incident and delaying the thing that actually protects revenue: finding out something’s wrong before a customer does.

A platform team at a mid-size SaaS company ran this exact framework and found their weakest dimension wasn’t the one they expected — Developer Experience, not Security. New engineers were taking nearly three weeks to ship their first production change, quietly eating a meaningful chunk of every new hire’s ramp time. Two weeks of work on golden-path templates and a documented local-dev setup cut that to under a week, with no new tooling budget — just focused effort on the dimension the framework flagged, not the one that felt most urgent.

Trade-offs and what we’d avoid

• Don’t chase “Running well” across every dimension immediately. Full maturity everywhere is expensive to build and maintain, and most of that investment doesn’t pay off until your incident volume and team size justify it. Match the target tier to your actual stage, except in Security, where the bar shouldn’t drop just because the company is small.
• Don’t let one strong dimension hide a weak one. Teams anchor on whichever dimension they’re proudest of and generalize it to “we’re mature.” A great CI/CD pipeline says nothing about whether you can find the root cause of an incident in minutes instead of hours.
• Don’t treat the score as static. Re-run the assessment every couple of quarters, especially after headcount growth or a new compliance requirement — the dimension that was fine at 10 engineers is often the first thing to break at 30.
• Don’t skip the “could we prove it” test. A tier-3 answer that’s never been tested under real pressure is really a tier-2 answer wearing tier-3 clothing. If you haven’t actually tried rebuilding infrastructure from code, or run a tabletop incident drill, be honest about that gap.

Related reading: DORA Metrics Reference Guide for the quantitative side of measuring delivery performance, and SLOs that actually drive decisions for what “Running well” looks like specifically in the Reliability dimension.