GitLab CI pipelines are essential for automating the Continuous Integration (CI) and Continuous Deployment (CD) process. These pipelines allow developers to break down the build, testing, and deployment workflows into distinct tasks, known as “jobs,” which are grouped into logical phases called stages. This structure helps to accelerate development and reduces the likelihood of errors when deploying code to production.

In this article, we will walk you through how to configure a GitLab CI pipeline with stages.

What are GitLab CI Pipelines?

In GitLab, a CI pipeline is a series of automated tasks that run every time there’s a change in your project. Each task in the pipeline belongs to a specific stage, and the stages represent different steps in your software development process, such as building, testing, and deploying the code.

Why are Stages Important in CI/CD?

By dividing your pipeline into stages, you ensure that each part of the process runs only when the previous stage has been successfully completed. This logical separation minimizes the risk of moving to the next step with incomplete or erroneous code.

Setting Up a GitLab CI Pipeline

The first step in setting up a GitLab CI pipeline is configuring the .gitlab-ci.yml file. This file dictates how your pipeline behaves and is written in YAML syntax.

Configuring the .gitlab-ci.yml File

To begin, define the stages in the file. Here’s a minimal example that sets up three stages:

stages:
  - build
  - test
  - deploy

This configuration defines three stages: build, test, and deploy.Defining Jobs for Each StageOnce the stages are defined, you can create the jobs that will run in each stage. Each job represents a specific task and runs in the corresponding stage. Below is an example with three jobs—one for each stage:

build-job:
  stage: build
  script:
    - echo "Building the project..."
    - make build

test-job:
  stage: test
  script:
    - echo "Running tests..."
    - make test

deploy-job:
  stage: deploy
  script:
    - echo "Deploying to production..."
    - make deploy

Here, each job has its own task. The build job compiles the project, the test job runs the tests, and the deploy job deploys the code to production.Advanced GitLab Pipeline ConfigurationsAs your CI/CD pipeline grows, you may need more advanced features like managing artifacts and handling dependencies between jobs.Using Dependencies Between JobsIn more complex pipelines, jobs may need to rely on the output from previous jobs. For example, the test job might require the build job’s output before running. You can handle this with the dependencies directive:

test-job:
  stage: test
  script:
    - echo "Running tests..."
    - make test
  dependencies:
    - build-job

In this configuration, the test-job will depend on build-job and use its output, ensuring a smooth transition between stages.

Managing Artifacts Across Stages

You can also use artifacts to pass files between stages. For example, you may want to save the build output and make it available for the test or deploy stage:

build-job:
  stage: build
  script:
    - echo "Building project..."
    - make build
  artifacts:
    paths:
      - build/

This stores the build output in the build/ directory and makes it available to subsequent stages.Optimizing Pipeline PerformanceTo speed up your pipeline execution, GitLab offers several tools to optimize performance.Parallel Execution with the needs DirectiveWhen tasks are independent, you can run them in parallel to reduce the overall pipeline time. The needs directive allows you to specify dependencies between jobs and run them as soon as their requirements are met:

test-job:
  stage: test
  needs: ["build-job"]
  script:
    - make test

deploy-job:
  stage: deploy
  needs: ["test-job"]
  script:
    - make deploy

In this example, test-job starts as soon as build-job finishes, and deploy-job runs once the test is complete.

Caching in GitLab CI

Caching can help reduce the time spent downloading dependencies by storing them between runs. For example:

build-job:
  stage: build
  cache:
    paths:
      - node_modules/
  script:
    - npm install
    - npm run build

Here, node_modules/ is cached, so it doesn’t need to be re-downloaded on every build.

Running Jobs in Parallel with a Matrix

GitLab CI also supports parallel execution of jobs with different parameters using the parallel directive. This is useful when you need to run tests with different configurations or environments.

test-job:
  stage: test
  image: python:$VERSION
  script:
    - pytest
  parallel:
    matrix:
      - VERSION: ['3.8', '3.9', '3.10', '3.12']

In this case, four jobs will run in parallel, each using a different version of Python.

Conclusion

Using stages in GitLab CI pipelines not only improves organization but also allows you to automate your CI/CD process more efficiently. By leveraging advanced features like parallel execution, dependencies, artifacts, and caching, you can build robust pipelines that speed up your development cycle and minimize errors in production.

By setting up pipelines that are both flexible and efficient, you ensure that your CI/CD process is reliable, scalable, and suited to meet the demands of modern software development.