DevOps Metrics: 7 KPIs to Evaluate Your Team’s Maturity

Measuring the maturity of your DevOps team might sound difficult, but it isn’t at all. Simple key performance indicators (KPIs), such as the deployment success rate or mean time between failure, give a good indication of the maturity of your DevOps team. By “mature,” I mean that your team consistently and smoothly operates at a high level and can deploy several times a day with very little risk.

This article will answer these questions:

• What’s a mature DevOps team really like?
• How does a new DevOps team organize itself?
• What are the phases of DevOps maturity?
• What metrics should a DevOps team measure?

Let’s get started.

Elements That Define DevOps Maturity

It’s possible to measure DevOps maturity in many ways. Maturity includes cultural, technical, and process-related elements. And you can measure all of these through DevOps KPIs or metrics.

For example, on a cultural level, you’ll want to learn how DevOps engineers share knowledge among team members. An active environment of knowledge sharing is a good sign that your team works well together.

On a technical level, you’ll want to measure DevOps KPIs related to errors, mean time to repair a bug, or the availability of a service. It’s much easier to measure these technical metrics than it is to measure cultural elements.

Last, let’s have a look at process metrics. These are mostly concerned with measuring the time needed for completing certain tasks, such as spinning up a new instance of a service. How fast can a DevOps engineer do this? For a recently formed DevOps team, the required time to accomplish such a task might be much higher than it is for a mature team. That’s because an immature team is often still working on standardizing and optimizing processes.

Next, let’s discuss the different phases of maturity for a DevOps team.

Phases of DevOps Maturity

Tuckman’s stages of group development accurately describes what a newly formed DevOps team experiences. When a new team gets together, all team members go through the following four phases:

• Forming
• Storming
• Norming
• Performing

How do these phases translate to a DevOps team? Let’s find out.

Forming: Need for Leadership

During the forming phase, there’s a lack of clarity, which means the team needs a leader who can provide guidance and strategy. Often during this stage, you either won’t find any DevOps implementation or there’ll be a bare minimum.

During this phase, the team starts to explore possible ways of test automation and different tools for implementing continuous integration (CI). At this stage, DevOps engineers write simple scripts that help automate repeating tasks. It’s safe to say you’ll find an immature team at this stage.

Storming: Fundamental Progress

Next up is the forming stage, which matters because it reveals the team’s initial progress. The team members try to establish fundamentals, such as implementing a simple CI flow with integrated test automation.

At this stage, developers can push their code to the continuous integration (CI) pipeline and receive valuable feedback about it. Often at this stage, you’ll find a strong change toward DevOps culture. This means that basic DevOps tools such as a CI pipeline have been implemented with some basic test automation. Still, you won’t find much of a focus on defining KPIs because the DevOps team is still in the process of building a strong DevOps tooling baseline.

Norming: Independence and Shared Ownership

Next, the norming phase brings the team clear responsibilities and direction. It’s possible to delegate smaller decisions to team members. A change toward agile management of the team happens because the team no longer needs to consult its leader for every decision. Strong independence and a feeling of shared ownership by the team often emerge at this stage.

The norming phase is a time of strong automation—from building the code to testing the automation and code deployments. At this stage, you’ll often find a happy development team whose members are able to improve their efficiency through the integrated toolchain. Because of this, the team can establish continuous delivery.

Moreover, the DevOps team also implements monitoring as part of this phase. Through monitoring, team members can set different KPIs to measure the health of the DevOps team as well as its code and deployments.

Performing: Time for Fine-Tuning

Finally, we’ve arrived at the performing phase. A successful implementation of DevOps is a hallmark of this phase.

During this phase, you’ll find room for experimenting. The team finds optimizations through experimentation. Standardized processes have been established, and there’s an active atmosphere of knowledge sharing among team members.

A team that’s in the performing phase focuses on improving important metrics, such as availability or reducing the error rate.

Now that you understand the different phases of DevOps maturity, what are some ways you can measure that maturity?

7 DevOps Metrics You Should Measure

Let’s take a look at seven of the most important DevOps KPIs for measuring a team’s maturity.

MTTF: Mean Time to Failure

First of all, MTTF refers to the time until the next failure. For example, how often does your deployment cause a failure? Ideally, you’ll want the MTTF metric to be as low as possible. A high MTTF rate can indicate problems with the quality of your software. For example, you may not have enough tests covering different scenarios that might contain bugs.

MTTD: Mean Time to Detect

Next, MTTD is an important KPI for a DevOps team. It tells the team how long it takes before they detect an issue. Immature teams require quite some time to detect issues because they have no monitoring implemented. This means it’s much harder for an immature DevOps team to replay events leading up to an issue. They don’t have any data to fall back on.

In contrast, a more mature team that has monitoring implemented can detect issues faster through the data that team members capture, such as logs or performance data.

MTTR: Mean Time to Repair

MTTR refers to the time needed to fix an issue or error. An immature team might not have much experience and knowledge on the system, which means they’ll likely end up with a high average time.

However, a team at the performing stage won’t need much time to repair incidents. Why? That team has already gathered a lot of knowledge about the DevOps implementation and has been actively sharing knowledge about common incidents. It’s very likely the team has a ready-made solution to the problem.

MTBF: Mean Time Between Failures

The MTBF metric is the most straightforward one. It refers to the average time it takes for a component to fail. This metric is especially useful to determine how stable a particular component in your codebase is. If a particular component fails relatively quickly compared with other components, then you might want to validate the code or architecture for this component. Obviously, the goal is to have components that rarely fail!

Deployment Success Rate

Next, the deployment success rate calculates the rate of successful and unsuccessful deployments. This success rate should be as high as possible for mature teams.

You can improve the deployment success rate by automating and standardizing the deployment process. A higher deployment success ratio will reduce frustrations among team members and create a less stressful job experience.

Deployment Frequency

A high deployment frequency can be an indicator of an optimized CI pipeline. In addition, the ability to deploy frequently allows for a more agile approach toward the development team. Mature DevOps teams often have a high deployment frequency because they have their processes streamlined and standardized.

Next, let’s take a look at the importance of measuring the error rate.

Error Rate

Last, the error rate tells the DevOps team how often new bugs pop up in running applications. It’s important to capture spikes in the error rate because these can indicate that something isn’t right. For example, there might be a database that’s being overloaded with SQL requests, and the DevOps infrastructure isn’t able to scale as quickly as needed.

Here, log analysis can help the team detect such error spikes. Moreover, log analysis lets you measure the number of error log messages.

(Do you want to learn more about log analysis? Check out XPLG’s blog about log forensics.)

Maturity Through DevOps Metrics

In short, metrics are an important instrument to measure the maturity of your DevOps team. Make sure you understand the different phases of team formation through Tuckman’s model. It allows you to better understand how the team functions in each stage.

When measuring metrics, try to start simply, with metrics such as the deployment success rate or mean time to failure. These metrics give important intel about the stability of your DevOps implementation.

Good luck with your DevOps journey!

This post was written by Michiel Mulders. Michiel is a passionate blockchain developer who loves writing technical content. Besides that, he loves learning about marketing, UX psychology, and entrepreneurship. When he’s not writing, he’s probably enjoying a Belgian beer!