In today’s world of rapid releases and growing complexity, manual deployments just don’t cut it anymore. Teams need speed, consistency, and visibility and that’s where GitLab CI/CD comes in.
Every developer wants smoother builds, faster testing, and reliable deployments. GitLab CI/CD makes this possible through automation, but its many features can seem confusing at first.
This guide simplifies the essentials and explains how GitLab CI/CD connects everything from code to deployment in a clear, structured way.
What is a GitLab Pipeline?
A GitLab pipeline is a defined series of steps that runs every time code changes are pushed to the repository. Think of it like a software assembly line. Each step (called a job) completes a specific task: building, testing, deploying, and more.
Pipelines make sure code is valid, tested, and ready for production without manual work.
Types of pipelines:
Parent-child pipelines: One pipeline triggers several smaller ones in parallel.
Parent-child pipelines can be used in a variety of ways.
In this example:-
We are viewing the .gitlab-ci.yml at the repository's top level. It has a job that kicks off a downstream (child) pipeline based of a rule (changes: [frontend/**]) that uses configuration stored within the repository under frontend/.gitlab-ci.yml. That way, when a frontend file changes, a pipeline runs with jobs defined in a separate file, breaking up 1 large configuration.
Multi-project pipelines: Pipelines that span across projects.
In this example, the Payment team moved its code to a different repo. This job exists in the original repo for the app and triggers a pipeline when a change is made ensuring the payments assets are also tested.
Merge request pipelines: Run automatically when changes are pushed to a merge request.
In this example, the deployment to a staging environment will not occur on branches that are associated with a merge request. This allows developers to get feedback faster without running the unnecessary staging deployment job.
Key Benefits of GitLab CI/CD:
- Faster Feedback Loops
- Earlier Bug Detection
- Improved Team Collaboration
- Automated Processes
- More Frequent Releases
Reusable CI/CD Components in GitLab
CI/CD Components are reusable, versioned building blocks for pipelines. Think of them as modular templates that are:
To use a component, include it using the same include keyword but with a component: reference instead of local, project, or remote.
Using the include Keyword in GitLab CI/CD:
- The include keyword in CI/CD (especially in tools like GitLab CI) is used inside the main pipeline configuration file (e.g., .gitlab-ci.yml) to bring in other YAML files.
- It allows you to split your pipeline configuration into multiple smaller files or reuse existing configurations improving readability, maintainability, and consistency across projects.
Benefits:
- Helps modularize CI/CD pipelines.
- Supports multiple sources (local, project, remote, or template).
- Makes it easier to share and update common CI logic.
How Component and include are used:
The first include line adds a reusable linting component from GitLab’s catalog, using Python 3.10.
The second includes a local deployment file. They keep the pipeline modular and reusable
Understanding Variables in GitLab CI/CD
- Variables store configuration values used across jobs and pipelines.
- They prevent hardcoding sensitive or repetitive data like tokens or URLs.
- Can be defined at project, group, or pipeline.
Let's look at some actual pipeline files to see how variables solve the problem:
By defining a variable like $DOCKER_REGISTRY, you can replace repeated values such as registry.old-company.com across multiple pipeline files. If the registry ever changes, you only need to update the variable once, and every job will automatically use the new value.
Types of Variables in GitLab CI/CD
GitLab Predefined Variables
GitLab automatically provides variables in every pipeline - things like your commit ID, branch name, and pipeline source. For example:
Custom Variables in GitLab CI/CD
While GitLab's predefined variables handle project metadata, custom variables let you manage your specific configuration needs. API endpoints, database credentials, feature flags - anything that changes between environments or shouldn't live in your code.
Example for Custom variable
This example defines two custom variables for environment and deployment path.
They are used in the job script to make the pipeline flexible without hardcoding values
Using Artifacts and Cache in GitLab CI/CD
Artifacts
- Move files between pipeline stages (like build → deploy).
- Store compiled code, reports, or build outputs.
- Example: Make a built frontend bundle available to the deploy stage.
- Expire by default, but expiration can be customized.
Cache
- Stores reusable data to speed up jobs.
- Ideal for dependencies or package installs.
- Example: Cache node_modules to skip reinstalling in each run.
- Shared across jobs and pipelines within the same project.
- Focused on speed, not file sharing.
When to Use Artifacts vs Cache
Using Rules in GitLab Pipelines:
Define when a job should run using the rules keyword.
- Use if conditions with variables (e.g., CI_PIPELINE_SOURCE). Example: Run a job only when the pipeline is triggered.
- Trigger jobs only on specific events or file changes.
- Support when: options like always, never, or on_success.
Examples of Job Rules in GitLab:
Deploy Only from Main
This deploys job will always run on the main branch. Otherwise, it will never run.
Run Tests on Merge Requests
This conditional rule ensures that a job only runs when a merge request event is triggered:
Workflow Rules
Similarly, the workflow keyword also can be used for implementing rules at pipeline level.
Conclusion:
GitLab CI/CD can seem complex at first, but once you understand its building blocks, it becomes a powerful ally in automating your workflow. From defining pipelines and rules to reusing components and variables, every piece helps create a smoother, more reliable development process.
Start small, experiment, and let GitLab handle the repetitive work so you can focus on writing great code. Over time, you’ll find your automation growing smarter, faster, and easier to manage.
Final Verdict
GitLab CI/CD brings clarity, speed, and control to modern software delivery.
It turns complex, manual workflows into a smooth, automated pipeline — so teams can focus on building, not babysitting builds.
“Automate Smarter. Deliver Faster - turn every push into a reliable release”
Mihir Sawai
Hewlett Packard Enterprise ( PSD- GCC )