Four continuous integration metrics you should follow

Whether a development team is considering a new continuous integration tool, or simply measuring their current tool, metrics are an important part of how we define a successful continuous integration strategy.

When implementing continuous integration, there are several questions to consider: How will this new tool make our team more efficient? What are the benefits of implementing this tool versus trying to improve our current CI solution? Why is this CI tool the right one for us? While these questions can gauge readiness and current feelings from the team, they are largely subjective. Metrics are a definitive way to show whether a solution is working, or not working, based on your team’s specific goals.

Key performance indicators (KPIs) are used in practically every industry to show data around goals. In enterprises, KPIs are often applied to business functions as well as individuals to measure performance and progress towards certain initiatives. Like any business investment, teams need to be able to show how their continuous integration solution is meeting their needs.

Continuous integration metrics can range significantly, depending on a team’s priorities or even the industry. Successful CI strategies can look different from team to team, but there are metrics that can highlight potential problems or areas of opportunity for any team.

Some key metrics for measuring continuous integration

Some of the key metrics for measuring the success of a continuous integration strategy include cycle time, time to value (TTV), uptime and error rate, and team retention rate. These metrics help gauge the efficiency, stability, and overall satisfaction within the software development process.

1. Cycle time

Cycle time is the speed at which a DevOps team can deliver a functional application, from the moment work begins to when it is providing value to an end user. In GitLab, we call this value stream analytics and it measures how long it takes your team to work in each stage of the developer workflow. By answering the question “How long does it take us to create something?” teams create a baseline that can then be revisited and improved upon.

2. Time to value

Once code is written, how long before it’s released? While cycle time measures the process, as a whole, time to value (TTV) focuses on the release process. This delay from when code is written to running in production is a bottleneck for many organizations. Having robust continuous delivery can help to overcome this barrier to quick deployments.

3. Uptime, error rate, infrastructure costs

Uptime is one of the biggest priorities for the ops team. Uptime is simply a measure of stability and reliability – how often is everything working as it should? With the right CI/CD strategy that automates the development lifecycle, ops leaders can focus more of their time on system stability and less time on workflow issues. If uptime and error rates seem high, it can illustrate a common CI/CD challenge between dev and ops teams. Operations goals are a key indicator of process success.

4. Team retention rate

While happiness is a metric that’s nearly impossible to measure, happy developers do tend to stick around. Retention rates can’t measure happiness, but it can shed some light on how well processes and applications are working for the team. It might be tough for developers to speak up if they don’t like how things are going, but looking at retention rates can be one step in identifying potential problems.

The benefits of CI/CD are felt throughout an organization: From HR to operations, teams work better and achieve goals. Establishing metrics around CI/CD performance can provide insights on many aspects of the business, not just development. These four CI/CD metrics can help to see how effective your continuous integration strategy is, and justify whether a new tool is needed to meet business goals.

Tracking continuous integration metrics is essential for evaluating DevOps performance and ensuring quality software delivery. Key metrics such as cycle time and time to value provide insights into the efficiency of development cycles and the speed of moving code to production. Uptime and error rates reflect the stability of the production environment, while team retention rates offer a glimpse into developer satisfaction.

By focusing on these metrics, organizations can enhance code quality, streamline the software development practice, and improve overall software development and delivery processes. Effective code reviews and continuous software testing further ensure that high-quality software is consistently produced.