How to Migrate to GitLab CI

Migrating to a new continuous integration and continuous delivery (CI/CD) platform can feel like a huge step. You’ve likely spent a lot of time setting up your current system. The thought of moving everything can be daunting. But, what if the move could streamline your workflow, make your team more efficient, and even save you money? That’s exactly what a move to GitLab CI can offer.

This article will walk you through the process of migrating to GitLab CI. It will also provide the information you need to make the move with as little disruption as possible. We will discuss the key differences between GitLab CI and other popular options. You’ll learn the steps involved in the migration process, and some of the best practices to follow for a smooth transition.

Table of Contents

Understanding GitLab CI

GitLab CI is a part of the GitLab platform that lets you automate your software development pipeline. It allows you to build, test, and deploy code each time you commit a change to your repository. This helps catch errors early. It also makes sure that the code is always in a releasable state.

How GitLab CI Works

GitLab CI uses a YAML file named .gitlab-ci.yml placed in the root of your repository. This file defines your CI/CD pipeline. Each time you push code, GitLab Runner picks up the job. It then follows the steps you defined.

The pipeline is made up of stages. These can be things like build, test, and deploy. Within each stage, there are jobs. Jobs are the actual tasks that run your code.

GitLab Runner is an application that executes the jobs. It is a separate process. This means that you can run jobs on different machines from where GitLab is hosted. You can use shared runners provided by GitLab. Or, you can set up your own runners.

Benefits of GitLab CI

Migrating to GitLab CI can bring many benefits, such as:

Deep Integration: GitLab CI is built directly into GitLab. This removes the need for third-party tools.
Ease of Use: The .gitlab-ci.yml is simple to write. Also, it is easy to understand.
Flexibility: You can customize your pipelines to fit your unique project needs.
Scalability: GitLab CI can handle anything from small personal projects to large enterprise-level ones.
Cost-Effective: It can be more affordable than other CI/CD solutions. Especially if you’re already using GitLab for your repositories.
Community Support: GitLab has a large and active community. This gives you access to plenty of resources and help.

Assessing Your Current CI/CD Setup

Before you start your move, it is important to understand your current setup. This will help you plan your migration to GitLab CI.

Identifying Your Current Tools

Make a list of all the tools involved in your current CI/CD process. This may include:

CI servers like Jenkins, CircleCI, or GitHub Actions
Build tools such as Maven, Gradle, or npm
Testing frameworks such as JUnit, Mocha, or Cypress
Deployment tools like Docker, Kubernetes, or Ansible
Notification systems like Slack or email

Mapping Your Current Pipelines

Take a hard look at how your pipelines are set up. Note the different stages, jobs, and dependencies. This mapping will be very important when creating your GitLab CI setup.

Here is what you might think about:

Build Process: How is your code compiled? What steps are needed to create a deployable package?
Testing Process: What tests do you run? How are your tests organized?
Deployment Process: Where do you deploy your code? How is it deployed?
Artifact Handling: How are build artifacts stored? How are they made available for deployment?
Branching Strategy: How are branches used? How is code merged?

Identifying Pain Points

What problems are you facing with your current CI/CD setup? Are builds slow? Do you have flaky tests? Do deployments fail often? Identifying pain points early will help you know what to fix when moving to GitLab CI.

Gathering Key Requirements

List out your must-haves for the new system. This could be certain test tools, security scans, or specific deployment flows.

Planning Your Migration

With the assessment done, it’s time to plan your move.

Setting Goals

Be clear about what you want to achieve by moving to GitLab CI. Do you want to reduce build times? Make it easier for your team to deploy? Have clear goals that will help measure your progress.

Defining Migration Scope

You do not have to move everything at once. Decide which projects to move first. A good strategy is to start with smaller, less-critical projects. This allows you to learn the ropes and fix problems. It also ensures that you aren’t risking too much at once.

Choosing Your GitLab Runner Setup

Decide how you will set up your GitLab Runners. You can use shared runners provided by GitLab. Or, you can set up your own runners on your infrastructure.

Shared Runners

Shared runners are provided by GitLab. They are easy to use. They are also good for projects that do not need specific hardware.

Specific Runners

Specific runners are set up by you. They allow you to run jobs in your own environment. You can install them on a machine you control. Or in your own cloud instance.

Planning for Downtime

Think about how long your move will take. And how much disruption it will have. Plan for some downtime. Do the move at a time when it will cause the least trouble.

Creating a Rollback Plan

Have a way to switch back to your old CI/CD setup, should things go wrong. This might mean keeping your current setup running until you’re certain the migration went well. This will also ensure that you’re not locked out if something goes south.

Setting Up GitLab CI

Now, you’ll get your hands dirty and begin setting up your pipelines.

Creating Your `.gitlab-ci.yml` File

Your .gitlab-ci.yml file is the heart of your GitLab CI setup. This file defines your CI/CD pipeline. It’s a YAML file that resides in the root directory of your repository.

Here’s a very basic example:

stages:
  - build
  - test
  - deploy

build_job:
  stage: build
  script:
    - echo "Building the application"

test_job:
  stage: test
  script:
    - echo "Running tests"

deploy_job:
  stage: deploy
  script:
    - echo "Deploying the application"

This very basic file creates three stages (build, test, deploy). It also creates a job in each stage that only prints a line to the console.

Let’s break down the components of this file:

stages: This section defines the names of your pipeline stages. Jobs with matching stage labels will run in the sequence defined here.
build_job, test_job, deploy_job: These are job definitions. You can name jobs anything.
stage: This is the stage each job belongs to.
script: These are the commands that run inside each job.

Defining Stages

Stages are the logical steps in your pipeline. They are run in order. For example, a common pipeline might have a build stage, then a test stage, and finally a deploy stage.

Defining Jobs

Jobs are the tasks that run inside each stage. Jobs within a stage can run in parallel. Or, you can configure them to run in a specific order.

Script Section

The script section includes the commands that actually perform the work for the job. These are often the build commands, test commands, or deploy commands.

Image Section

The image section defines the Docker image to use for the job. This helps ensure a clean, consistent, and reproducible environment for your code to run.

Services Section

The services section defines any linked Docker containers you might need to use. It’s good if your pipeline depends on databases or other services.

Cache Section

The cache section allows you to save and reuse data between jobs. This speeds up builds by storing build dependencies or results.

Artifacts Section

The artifacts section allows you to store outputs of a job. This could be the compiled code, test results, or anything else you need from one job in another.

Setting up GitLab Runners

GitLab runners are the agents that execute the jobs defined in your .gitlab-ci.yml file.

Installing GitLab Runners

You can install GitLab Runners on various operating systems like Linux, macOS, and Windows. Follow the documentation on the GitLab website for detailed instructions.

Registering GitLab Runners

After installation, you need to register the Runner with your GitLab instance. This involves specifying the GitLab URL and registration token. You also have to add a tag (so it is easy to find) and other settings.

Configuring Runners

You can configure your runners to use specific executors like Docker, Shell, or Kubernetes. Choose an executor that suits your project needs.

Testing Your Pipelines

After setting up your initial pipeline, test it. Make small changes and see if they run as expected. Check if they do what you want them to. This will help you fix mistakes early in the process.

Migrating Your Existing Pipelines

Now that you understand how GitLab CI works and have a simple pipeline running, you can focus on moving your existing pipelines.

Translating Your Current Pipelines

Take the pipeline map from earlier and translate it into a GitLab CI configuration. Map each step in your old pipeline to a stage and a job in GitLab CI.

Example Translation

Let’s say your current pipeline in Jenkins has the following steps:

Checkout code
Build code using Maven
Run unit tests
Package the application
Deploy the package to a staging server

You can translate this to a GitLab CI pipeline like this:

stages:
  - build
  - test
  - package
  - deploy

build_job:
  stage: build
  image: maven:3.8.1-openjdk-17
  script:
    - mvn compile

test_job:
  stage: test
  image: maven:3.8.1-openjdk-17
  script:
    - mvn test

package_job:
  stage: package
  image: maven:3.8.1-openjdk-17
  script:
    - mvn package
  artifacts:
    paths:
      - target/*.jar

deploy_job:
  stage: deploy
  image: docker:latest
  script:
    - docker run my-app:latest

In this example, the Jenkins steps were mapped to GitLab CI jobs. We also configured the Docker images and scripts for each job. Artifacts are created in the package_job and used in the deploy_job.

Using Templates

GitLab CI allows the use of templates. These can be reused to avoid repeating code. This is very useful when many of your projects have common steps.

Including Templates

You can include templates at the beginning of your .gitlab-ci.yml file using the include keyword.

include:
  - template: Docker.gitlab-ci.yml
  - local: .gitlab/my-custom-template.yml

GitLab also has a library of pre-built templates that handle many common use cases.

Managing Dependencies

Many pipelines have dependencies on external services or libraries. Make sure to include these dependencies in your GitLab CI setup.

Using Cache

The cache keyword can store dependencies. This speeds up future builds.

Using Services

The services keyword allows you to use linked Docker containers with your jobs. This ensures your build environment has access to databases or other linked resources.

Setting up Variables

Define environment variables in GitLab CI. This helps you customize your builds and deployments without changing your code.

CI/CD Variables

Go to your project’s Settings -> CI/CD -> Variables section to set up variables. This lets you manage these values through the GitLab UI. You can also mask them if they are sensitive.

Using `.env` files

You can also use .env files to manage variables. However, these files have to be committed to your repository. Thus they are not the best way to manage secret data.

Testing Your Migrated Pipelines

After migrating your pipeline, test it thoroughly. Run it with different code changes. See if it does what you want it to do. Look for possible problems or areas where you can improve.

Optimizing Your GitLab CI Pipelines

After you’ve moved over, think about ways to optimize.

Improving Build Times

Slow build times can hurt the efficiency of your team. Look for ways to reduce these.

Using Caching

Make use of caching to reuse build artifacts or dependencies. It will also avoid re-downloading each time.

Parallel Jobs

Run jobs in parallel when possible. This will speed up the entire process. Especially for jobs that are not related.

Using Specific Runners

You can use specific runners. Especially ones with high power. This is useful if you have resource-heavy builds.

Improving Testing

Flaky tests can be a source of problems. This also creates a lot of noise. Here are some ways to fix it.

Using Test Reports

GitLab has a great interface for test reports. It is helpful for finding flaky tests and debugging them.

Using Parallel Testing

If your tests allow, run them in parallel. This will speed up testing and give you feedback sooner.

Improving Deployment

Poorly designed deployments can be a huge problem. Here are some things to help you with deployment.

Using Deployment Environments

GitLab allows you to define different deployment environments like staging, pre-production, and production. This ensures that your deployments are well-organized.

Using Rollbacks

Use the rollback features in GitLab to easily revert to a prior version if your new deployment has problems.

Using Blue/Green Deployments

Consider blue/green deployments. These allow you to switch to a new version without downtime.

Security Considerations

Security should be a key thing you think about when setting up your pipelines.

Secure Variables

Always store secrets securely in GitLab CI. Use masked variables so that you do not leak sensitive data. Also limit access to who can change the variables.

Code Scanning

Use GitLab’s code scanning tools to catch security issues early in the development process.

Container Scanning

If you use Docker images, scan them for vulnerabilities before deployment. This will prevent any insecure packages from being added to your system.

Review Permissions

Make sure you review permissions on your CI/CD setup. Only give access to those who need it.

Best Practices for GitLab CI

When you are using GitLab CI, here are some best practices to follow:

Keep Your .gitlab-ci.yml Simple: Avoid making your file too complicated. Try to be clear and easy to understand.
Use Templates: Use templates to reuse code between projects. This makes your configuration easier to maintain.
Use Tags: Use tags on your runners to manage them more effectively.
Test Often: Always test your pipelines. Start small and make sure each part works well.
Document Everything: Make sure to document your pipelines and configurations. This makes it easier for new team members to understand. It also makes it easier to fix problems later.
Monitor Your Pipelines: Keep track of your pipeline performance. See if there are places where it can be improved.
Follow Security Practices: Always make security a priority. Follow the security practices. Do not ignore or dismiss security practices.

Troubleshooting Common Issues

When you are moving to GitLab CI, here are some common issues you may encounter:

Pipeline Failures: The most common is when a job fails. Read the logs to find the issue. You also might have to test your code to make sure it works.
Runner Issues: Your runners might be slow, not working, or not taking jobs. Check the runner logs to debug this. You might have to restart the runner service. You might also have to make changes to the runner’s configuration.
Variable Issues: If a job fails because of a missing variable, double-check that the variable is properly set up in GitLab.
Cache Problems: If your cache is not working right, clear the cache. Then rebuild.
Permission Problems: Make sure that the user running the GitLab Runner has access to all the things it needs access to.

Making the Most of GitLab CI

GitLab CI has many features. Here are some ways to make the most out of it:

Using Merge Request Pipelines

You can set up pipelines to run on each merge request. This lets you test changes before merging them into the main branch. This way, you catch problems early and reduce the number of problems being released to your users.

Using Scheduled Pipelines

You can also schedule pipelines to run at specific times. This is good for tasks like regular backups or security scans.

Using Manual Pipelines

You can also make a manual pipeline. This means that a job only starts if you make it start manually. This is good for deployments that you need to verify and sign off on first.

Using API Integration

GitLab CI supports API integration. This allows you to start pipelines or get status updates from other systems.

Continuous Learning

As you continue to use GitLab CI, keep learning.

Keeping Up with Updates

GitLab releases new versions often. Stay up to date. This will help you use the latest features and fix any security problems.

Reading Documentation

The GitLab documentation is very detailed. It includes a lot of good information. Read this documentation to use GitLab CI at its best.

Engaging with the Community

Join the GitLab community forums and discussions. Learn from other users. See what other problems they had. See how they fixed it.

Making the Switch to GitLab CI

Migrating to a new CI/CD system is a lot of work. But, with careful planning, it can improve your software development. You can build, test, and deploy code more efficiently. You can also ensure the quality of the software being delivered.

GitLab CI is a great tool. It has many features, such as its ease of use, flexibility, and deep integration with the GitLab platform. If you are looking for a way to streamline your workflow, save time, and ensure your software’s quality, then look into moving to GitLab CI.

As you start to move over, remember to assess your current setup, plan carefully, and test everything thoroughly. Learn from the community and make sure that you’re using GitLab CI to the best of its abilities. With the right approach, the move will boost your team’s productivity. It’ll also help you deliver software much faster.