7 Stages of CI/CD Pipeline in Software Development

Let's look at the most popular stages in the pipeline for CI/CD. These stages are incorporated into pipelines in CI/CD best practices for software development.

The trigger

The most effective pipelines trigger automatically whenever new code is uploaded into the repository.

You can configure your tool for CI/CD to?be able to poll?for any changes made to the Git repository or configure a Webhook for your CI/CD tool to alert the tool when the developer pushes.?Move.

The primary reason behind doing the above is for the running of the pipeline to be automated and without friction.

If you allow the pipeline to run manually, some people might overlook running it or decide not to. It is much better to automatize this step.

The greatest confidence is derived from knowing that your program will be tested for every modification.

Code check

In the initial stage, during the first stage, the CI server will download the repository for source code, like GitHub and Bitbucket.

The CI/CD tool typically receives data via a poll or a webhook. It specifies which commit has triggered the pipeline.

The pipeline will then check the source code and begin the process at a particular commit date.

Create the code

If you're using a compiled language such as Java first, the most important step is to build your program.

It means your CI tool must have access to the various tools to build you require to build your application. For instance, if it's Java, you'll need an application like Maven and Gradle.

Ideally, this stage should operate in a clean, fresh environment. It is among the most appealing uses that Docker container containers can serve in that they can make new build environments quickly and repeatedly.

Run unit tests

The next important element of your CI/CD process is unit testing. This is where you can configure your CI/CD tool to run the tests within your codebase.

It is possible to utilize Maven and Gradle to accomplish this in Java and?Jest?in JavaScript.

The objective now is not just to ensure that all unit tests are passed but also to ensure it is also to make sure that these tests are kept up-to-date and updated as the code base expands.

If your application is growing quickly, yet the number of tests is the same, it could be better, as it could indicate that the code base may contain large chunks of the base code that have yet to be tested.

As per Martin Fowler, most tests you write should comprise unit tests. Unit tests give you the greatest "bang for your buck." They are simple to write, cost-effective and have the lowest maintenance costs.

Package the code

When all the tests pass, you can proceed to package your code. How you package your app depends on your programming language and target environment.

If you're running Java, you could build a JAR file. In the case of Docker containers, you could create an image of a Docker image.

Whatever format you use for packaging, the best practice is to build the binary once. Only create a new binary for each environment, which can complicate your pipeline.

Run acceptance tests

It's the moment to conduct?acceptance tests?for your applications.

Acceptance tests are an effective means to make sure that your software fulfills the task it was created to do and that it is in compliance with the original specifications.

However, manual acceptance testing is lengthy and laborious. Therefore, a growing variety of methods can conduct automated acceptance testing.

Many testing for acceptance can be done automated. Tools like Cucumber and its Gherkin syntax define acceptance criteria, and Selenium can mimic user actions, for example, opening websites or clicking on hyperlinks.

The goal of this stage is to cut down or eliminate the amount of time spent trying to test manually.

If your process is the creation of a binary, then transferring it to a team of testers to be tested manually in a manual manner, then you be aware that this process takes quite a long time. Automating most tests will reduce the time required to get your application into the hands of actual users.

Delivery or Deployment

Once the application is test-driven, it can be moved to the deployment or delivery stage.

At this point, you've got an artifact ready to be distributed (continuous delivery). You can go to CI/CD heaven and automatically deploy your application (continuous deployment).

Many pipelines fail to the end of the road. It's unfortunate. It's a great benefit to have the ability to automate the deployment of your software in production.

For continuous deployment, you'll need an environment for production to deploy your application to. If you're deploying to the public cloud, use an API provided by the provider to launch your app. In the case of Kubernetes, you could employ Helm charts to make your application available for deployment.

Then, finally, it's the end of your pipe!

When a developer next puts code in the repository, it will be repeated.