What metrics should you use to assess your CI pipeline's efficiency?

1 Cycle time

Cycle time is the measure of how long it takes for a code change to go from commit to deployment. It reflects the overall performance and throughput of your CI pipeline, as well as the complexity and size of your code changes. A shorter cycle time means that you can deliver value to your customers faster and respond to feedback more quickly. To optimize your cycle time, you can use techniques such as parallelizing your tests, caching your dependencies, and breaking down your code into smaller and more manageable chunks.

2 Build frequency

Build frequency is the measure of how often you trigger your CI pipeline to build and test your code changes. It indicates how frequently you integrate your code with the main branch and how aligned you are with the CI principle of making small and frequent commits. A higher build frequency means that you are following a consistent and regular development process and reducing the risk of conflicts and bugs. To increase your build frequency, you can use tools such as git hooks, schedulers, or webhooks that automatically trigger your CI pipeline when certain events occur.

4 Mean time to recovery

Mean time to recovery (MTTR) is the measure of how long it takes for you to fix a broken or failed CI pipeline and restore it to a working state. It indicates how resilient and reliable your CI pipeline is and how well you handle errors and incidents. A shorter MTTR means that you can minimize the impact of failures on your delivery process and maintain a high level of availability and performance. To reduce your MTTR, you can use strategies such as monitoring, alerting, logging, and rollback mechanisms.

5 Feedback latency

Feedback latency is the measure of how long it takes for you to receive feedback from your CI pipeline about the status and outcome of your code changes. It includes the time spent on building, testing, and reporting your code changes. It affects how quickly you can identify and correct issues, as well as how confident you are about your code quality and readiness. A lower feedback latency means that you can accelerate your development cycle and increase your productivity and satisfaction. To lower your feedback latency, you can use tools such as dashboards, notifications, or chatbots that provide you with real-time and actionable feedback.