DevOps Maturity Model: How to Know What Stage Your Team Is Actually In

The theory behind DevOps is simple: break down silos between teams and align their day-to-day activities to achieve more predictable release cycles. In reality, however, many organizations fail to do so, despite following DevOps best practices and using state-of-the-art tools. Naturally, a question pops up: how do you actually figure out at what stage of the DevOps maturity model your company is?

That’s precisely what this short yet comprehensive guide is all about, so stick around. We’ll kick things off by looking into DevOps maturity stages, and then go into conducting a thorough DevOps maturity model assessment to help you figure out at what step of the ladder you’re on.

What Exactly Is the DevOps Maturity Model?

At its core, a DevOps maturity model is a way for organizations to see the bigger picture. It enables software development companies to assess how well they have adopted the DevOps model and pinpoint areas for improvement.

For instance, a mature DevOps culture means your devs, ops, and other teams, such as security and QA, share aligned views. Communication between these pieces of the software development puzzle is flowing smoothly, with CI/CD maturity at an all-time high. However, reaching this level is easier said than done.

What Are the Levels of DevOps Maturity?

Before we can talk about why teams fail to reach full engineering process maturity, we should first define the DevOps phases. There are typically five of these:

1. Initial: In this phase, an organization’s processes are still largely manual, with automation in its earliest stages. Development and operations operate in silos, with little to no collaboration between these teams, which often leads to irregular releases.
2. Managed: As you move up the ladder, you start seeing basic DevOps practices being implemented, albeit inconsistently. There’s some degree of automation here, but most processes remain manual.
3. Defined: At this stage, DevOps practices become standardized across an organization. Collaboration becomes more consistent, and automation becomes the norm. Yet, there’s still a long road ahead.
4. Measured: When teams reach this phase, observability maturity is at its highest level. Organizations are collecting key performance metrics, such as deployment frequency and lead time, and using them to identify areas for improvement.
5. Optimized: Teams at the highest level of operational maturity automate the majority of their processes and continuously monitor performance. Collaboration between developers and operations is seamless, resulting in highly efficient processes.

Common Reasons Teams Get Their Actual Stage Wrong

Even the biggest organizations can get stuck at a particular phase of the DevOps maturity matrix. And while there are dozens of reasons this can happen, in most cases, it boils down to this:

• CI/CD tools without ownership: Incomplete DevOps adoption is one of the main culprits behind an incorrectly assessed maturity level. Teams will implement popular tools like Kubernetes and Jenkins and run pipelines daily. But when builds fail, they’ll play the blame game instead of improving the flow.
• Metrics without action: Organizations that continuously track deployment frequency, lead time for changes, change failure rate, and time to restore service are at the upper echelons of DevOps. However, even they still can’t reach full release management maturity without actually acting on these metrics.
• Automation without consistency: Consistency is a primary objective of process automation, yet many DevOps teams struggle with it. They’ll fully automate one service, while another still relies on manual steps, which often results in spaghetti code and unreliability.

How Do I Conduct a DevOps Maturity Model Assessment?

Now that you understand the stages and know which false maturity signals to watch for, we can finally dive into the DevOps assessment itself. Below is a practical framework that’ll help your team assess the reality of the situation:

• Preparation: Some teams will want to increase deployment frequency. Others may want to focus on reducing the change failure rate. Whatever it is that you aim to achieve, it’s essential to kick things off by clearly defining your goals.
• Evaluation: With objectives in place, you can assess your existing DevOps tools and processes. DORA metrics are crucial here, but you should also run surveys and interviews to see how teams feel about communication and collaboration.
• Analysis: Honesty is a crucial aspect of this assessment, and precisely what you’ll need when analyzing security, observability, and manual processes, and looking for other gaps. If you manage to stay honest, you’ll know exactly what to focus on next.
• Implementation: With an action plan in place, you’re ready to make improvements. It’s a good idea to start small, with a few quick wins boosting your morale. However, it’s also vital to treat improvement as ongoing work, not a one-time thing.

Conclusion

DevOps is supposed to bring devs and ops (and other teams) together and take collaboration and automation to a whole new level. In reality, though, many teams get stuck when adopting these practices. This often leads to a misperception of an organization’s own DevOps maturity model.

An accurate maturity assessment requires a deep dive into delivery workflows and the results those workflows produce. And when teams are brutally honest about it, their true stage becomes clear, opening a path toward real progress.