7 Continuous Delivery performance metrics

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Continues Integration and Continuous Delivery pipelines are very important pipelines to development and Devops.

Continues Integration and Continues Delivery pipelines are also known as CI/CD pipeline.

We need to make sure they are fine-tuned, so we can deliver features and code as fast as absolutely possible. Over time we continue to add more capabilities to our pipelines, adding automated tests, integrations processes and so on.
The feature teams using the pipelines needs and expect a fast feedback loop, so they can ship quality code rapidly.
If you need to improve your CI/CD pipeline you need to measure how they are performing and how your changes are affecting the performance.

Here are 7 good measuring points that will reveal you CI/CD pipeline performance and give you insights to the speed of your feature teams.

Continuous Delivery Metrics

Deployment frequency

Good software practices encourages frequent and small deployments. Small deployments speeds up the entire development cycles, For example code integration becomes easier, faster and cheaper.
When you deploy as frequently as possible, developers will get more familiar with the process, gaining confidence in deploying and fixing failed deployments.
For measuring the deployment frequency you simply calculate the average time between deployments.

Deployment size

There are several ways you can measure the deployment size. Linking your project management tool to the releases and monitor the number of tickets, bug fixes or story points etc. that goes into a release.
Another approach is to measure the change to your code base.

Deployment size can help you in addressing risk management on releases.

Deployment time

A pipeline needs to be as fast as possible to give quick feedback to the teams about how the deployment went.
Measuring the deployment time is a measurement of the time from ordering a deployment to the deployment is in production. This can help identify if there is any unwanted latency in your pipeline, that needs your attention.

Deployment success rate

The deployment success rate is an indicator of how confident the teams are. This is a clear indicator of teams is struggling to get something release.

The deployment success rate formula is “Successful deployments / total deployments”

Lead time

Adding value to the customers fast means shipping code as fast as possible. Lead time is when you measure the time from first starting your task, till it’s deployed in production.

Cycle Time

Cycle time is the time from the beginning to the end of a process.
It can be the cycle time for your entire pipeline but it can also be for every part or component of your pipeline.

Automated test success rate

Automated test is definitely your go-to approach when it comes to increasing velocity. Integration test, unit tests, function test etc. Measuring the success rate will tell you how often code changes are failing your tests.

The automated tests success rate is, “Successful automated tests/Total automated tests.”

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