Step-by-Step Guide: How to Create GitLab Pipeline for Your Projects

Creating a GitLab pipeline for your projects can significantly streamline your development workflow by automating tasks such as building, testing, and deploying your code. This step-by-step guide will walk you through the entire process, from setting up your GitLab project to optimizing and securing your pipeline.

Key Takeaways

  • Understand the basics of setting up a GitLab project and configuring its settings.
  • Learn how to create and structure your first GitLab YAML file for defining CI/CD pipelines.
  • Get to know the different stages of a pipeline and how to configure them for building, testing, and deploying your code.
  • Discover advanced pipeline features like pipeline variables, conditional logic, and parallel job execution.
  • Gain insights into optimizing pipeline performance and troubleshooting common issues.

Setting Up Your GitLab Project

Creating a New Project

To create a new project:

  1. Go to the top bar and click on Main menu. Go to Projects and select View all projects.
  2. Click on New project on the page’s right.
  3. Select one of the following options on the Create new project page:
    • Blank project
    • Built-in template
    • Custom template
    • Import a project from another repository
    • HIPAA audit template
    • Connect to an external repository

Configuring Project Settings

Once your project is created, you can configure various settings to tailor it to your needs. Key settings include:

  • Visibility Level: Choose whether your project is private, internal, or public.
  • Repository Settings: Configure branch protection, default branches, and more.
  • Integrations: Connect with external services like Slack, JIRA, or Kubernetes.

Adding Collaborators

Collaboration is crucial for any project. To add collaborators:

  1. Navigate to your project’s main page.
  2. Click on Settings > Members.
  3. Enter the username or email of the person you want to add.
  4. Select a role (Guest, Reporter, Developer, Maintainer, or Owner).
  5. Click Add to project.

Adding collaborators with the right permissions ensures smooth workflow and project security, especially if you’re using GitLab Ultimate.

Understanding GitLab CI/CD Pipelines

GitLab CI/CD pipeline illustration

What is a CI/CD Pipeline?

A CI/CD pipeline automates the process of integrating code changes, testing them, and deploying them to production. GitLab CI/CD is a powerful tool that helps streamline this process, ensuring that your code is always in a deployable state.

Benefits of Using GitLab CI/CD

Using GitLab CI/CD offers several advantages:

  • Automation: Reduces manual intervention, allowing for faster and more reliable deployments.
  • Consistency: Ensures that the same process is followed every time, reducing the risk of errors.
  • Scalability: Easily scales with your project, whether you’re a small team or a large enterprise.

Key Concepts and Terminology

Understanding the key concepts and terminology is crucial for effectively using GitLab CI/CD:

  • Pipeline: A collection of jobs that are executed in stages.
  • Job: A task to be executed, such as running tests or deploying code.
  • Stage: A group of jobs that run in parallel.
  • Runner: An application that executes the jobs in your pipeline.

For advanced features and more control, consider upgrading to GitLab Premium.

Creating Your First GitLab YAML File

Introduction to YAML Syntax

To create a pipeline in GitLab, we need to define it in a YAML file. This YAML file should reside in the root directory of your project and should be named gitlab-ci.yml. YAML, which stands for "YAML Ain’t Markup Language," is a human-readable data serialization standard that is commonly used for configuration files. Understanding the basic syntax of YAML is crucial for defining your pipeline correctly.

Defining Basic Pipeline Structure

The basic structure of a GitLab pipeline is defined using stages and jobs. A stage is a group of jobs that run in parallel, while jobs are individual tasks that run within those stages. Here is a simple example of a basic pipeline structure:

  - build
  - test
  - deploy

  stage: build
    - echo "Building the project..."

  stage: test
    - echo "Running tests..."

  stage: deploy
    - echo "Deploying the project..."

Using Predefined Keywords

GitLab provides a set of predefined keywords that are used to define a pipeline. These keywords help in specifying the behavior and structure of the pipeline. Some of the most commonly used keywords include:

  • stages: Defines the different stages of the pipeline.
  • script: Specifies the commands to be executed for a job.
  • only: Defines the conditions under which a job should run.
  • except: Specifies the conditions under which a job should not run.

Tip: For the complete .gitlab-ci.yml syntax, see the full CI/CD YAML syntax reference on the GitLab documentation site.

Configuring Pipeline Stages

Configuring pipeline stages in GitLab is a crucial step in setting up your CI/CD pipeline. Pipelines and their component jobs and stages are defined in the CI/CD pipeline configuration file for each project. Stages are defined by using the stages keyword. A typical pipeline might consist of multiple stages, executed in a specific order.

Setting Up Build Stage

The build stage is usually the first stage in a pipeline. It involves compiling the source code and preparing it for testing. You can define a job within this stage to compile your code. For example:

  - build

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

Defining Test Stage

The test stage follows the build stage and is used to run various tests on the compiled code. This ensures that the code is functioning as expected. You can have multiple jobs within this stage to run different types of tests:

  - build
  - test

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

Deploying with Deploy Stage

The deploy stage is the final stage where the application is deployed to a staging or production environment. This stage can have jobs that handle the deployment process:

  - build
  - test
  - deploy

  stage: deploy
    - echo "Deploying the project..."
    - make deploy

Remember, you can configure specific aspects of your pipelines through the GitLab UI. For example, you can check console logs in detail by clicking on a job under any stage.

Adding Jobs to Your Pipeline

Creating Simple Jobs

Creating simple jobs in GitLab CI/CD is straightforward. You define jobs in the .gitlab-ci.yml file, specifying the script to run. Each job can be assigned to a specific stage, such as build, test, or deploy. This helps in organizing and managing the pipeline efficiently.

Using Scripts in Jobs

Scripts are the core of any job in GitLab CI/CD. They define the commands that need to be executed. You can use shell scripts, Python scripts, or any other scripting language. It’s essential to ensure that the scripts are well-tested and reliable to avoid pipeline failures.

Setting Job Dependencies

In GitLab CI/CD, you can set dependencies between jobs to control the order of execution. This is particularly useful when certain jobs need to be completed before others can start. By defining dependencies, you can create a more robust and efficient pipeline.

Properly setting job dependencies can significantly enhance the efficiency of your pipeline, ensuring that tasks are executed in the correct order without unnecessary delays.

Running Your Pipeline

Committing Changes to Trigger Pipeline

To start a pipeline for demonstration purposes, commit and push a change directly over GitLab’s web editor. For the first test, open the and add an additional line. Every commit pushed to GitLab generates a pipeline attached to that commit. If multiple commits are pushed together, a pipeline is created for the last commit only.

Monitoring Pipeline Execution

If you click on a job under any stage, you can check console logs in detail. If you have any artifacts created in your pipeline jobs, you can find them by clicking on the 3 dots for the pipeline instance. This allows you to monitor the progress and results of each job in your pipeline.

Handling Pipeline Failures

Pipelines can be manually executed, with predefined or manually-specified variables. You might do this if the results of a pipeline (for example, a code build) are required outside the standard operation of the pipeline. To execute a pipeline manually:

  1. Navigate to your project in GitLab.
  2. Use the left sidebar to navigate GitLab.
  3. Go to the CI/CD section and select Pipelines.
  4. Click on the Run Pipeline button.
  5. Specify when jobs run with rules if needed.

Ensuring you have runners available to run your jobs is crucial. If you’re using, you can skip this step as provides instance runners for you.

Using GitLab Runners

In GitLab, runners are agents that run your CI/CD jobs. To view available runners:

  • Go to Settings > CI/CD and expand Runners.

As long as you have at least one runner that’s active, with a green circle next to it, you have a runner available to process your jobs.

If you don’t have a runner:

Install GitLab Runner on your local machine.
Register the runner for your project. Choose the shell executor.

Advanced Pipeline Features

Using Pipeline Variables

Pipeline variables are essential for customizing your CI/CD process. They allow you to define values that can be reused across multiple jobs and stages. Variables can be defined at different levels, such as project, group, or instance level, providing flexibility in managing your pipeline configurations. You can also mask sensitive variables to enhance security.

Implementing Conditional Logic

Conditional logic in GitLab pipelines enables you to control the execution flow based on specific conditions. This feature is particularly useful for complex workflows where certain jobs should only run under specific circumstances. By using rules and only/except keywords, you can fine-tune when and how your jobs are executed.

Parallel Execution of Jobs

To optimize the efficiency of your CI/CD pipeline, you can configure jobs to run in parallel. This reduces the overall pipeline duration and speeds up the feedback loop. Parallel execution is especially beneficial for large projects with multiple independent tasks. You can group jobs by stage or needs configuration to ensure they run concurrently without conflicts.

Mastering these advanced features will significantly enhance your GitLab CI/CD pipeline, making it more robust and efficient.

Securing Your GitLab Pipeline

Securing your GitLab pipeline is essential for safeguarding your software delivery process and protecting against potential security threats. This section will guide you through the best practices and configurations to ensure your pipeline remains secure.

Managing Secrets and Tokens

One of the most critical aspects of securing your pipeline is managing secrets and tokens. Store sensitive information like API keys or passwords as secure variables in GitLab and use them in your pipeline jobs. This practice helps in keeping your sensitive data out of your codebase.

Setting Permissions

Properly setting permissions is crucial to ensure that only authorized personnel can make changes to your pipeline configurations. Use GitLab’s built-in permission settings to control who can view, edit, and execute the pipeline. This minimizes the risk of unauthorized access and potential security breaches.

Auditing Pipeline Activities

Regularly auditing pipeline activities can help you identify and mitigate potential security risks. Review pipeline logs and job outputs to ensure that your pipeline is running smoothly and efficiently. Regular audits can also help in detecting any unusual activities that might indicate a security threat.

Conclusion: Securing CI/CD pipelines in GitLab is essential for safeguarding your software delivery process and protecting against potential security threats.

Optimizing Pipeline Performance

Reducing Pipeline Duration

Reducing the duration of your pipeline is crucial for maintaining efficiency and productivity. One effective strategy is to parallelize jobs wherever possible. This can be achieved by breaking down complex tasks into smaller, independent jobs that can run simultaneously. Additionally, consider using caching to store intermediate results and avoid redundant computations.

Caching Dependencies

Caching dependencies can significantly speed up your pipeline by reusing previously downloaded or built components. GitLab CI/CD provides built-in support for caching, allowing you to specify which files or directories to cache. This can be particularly useful for large projects with numerous dependencies.

Optimizing Resource Usage

Efficient resource usage is key to optimizing pipeline performance. Monitor your pipeline’s resource consumption and adjust the allocation of CPU, memory, and disk space as needed. You can also use GitLab’s built-in tools to analyze and optimize resource usage, ensuring that your pipeline runs smoothly without unnecessary bottlenecks.

Efficient pipelines not only save time but also reduce costs and improve overall project workflow.

Troubleshooting Common Issues

Debugging Pipeline Errors

When your pipeline fails, the first step is to check the job logs. These logs provide detailed information about what went wrong. Look for error messages and stack traces that can give you clues. Failed to start session with scanner is a common error message you might encounter. In such cases, retry the job, and if the problem persists, reach out to support.

Resolving Runner Issues

Runners are the backbone of your CI/CD pipeline. If a runner is not working correctly, your jobs will not execute. Common issues include runners being offline or not having the necessary permissions. Ensure that your runners are properly configured and have the required access to your project.

Fixing YAML Syntax Errors

YAML syntax errors are a frequent cause of pipeline failures. YAML is very particular about indentation and formatting. Use a YAML validator to check your .gitlab-ci.yml file for syntax errors. Even a small mistake can cause the entire pipeline to fail.

Always validate your YAML files before committing to avoid unnecessary pipeline failures.


Creating a GitLab CI/CD pipeline for your projects is a powerful way to automate your development workflow, ensuring that your code is always tested, built, and deployed efficiently. By following the steps outlined in this guide, you should now have a solid understanding of how to set up and configure your own pipeline. Remember, the key to a successful CI/CD pipeline is continuous improvement and adaptation to your project’s needs. Don’t hesitate to explore more advanced features and customize your pipeline to fit your specific requirements. Happy coding!

Frequently Asked Questions

What is a GitLab CI/CD pipeline?

A GitLab CI/CD pipeline is a series of automated processes that allow you to build, test, and deploy your code. It is defined using a YAML file in your project’s root directory and consists of multiple stages and jobs.

How do I create a new project in GitLab?

To create a new project in GitLab, log in to your GitLab account, click on the ‘New Project’ button, and follow the prompts to set up your project. You can choose to create a blank project, import an existing repository, or use a project template.

What are GitLab runners?

GitLab runners are lightweight, portable agents that run the jobs defined in your CI/CD pipeline. They can be shared or specific to your projects and can be configured to run on different environments.

How do I trigger a pipeline in GitLab?

You can trigger a pipeline in GitLab by committing and pushing changes to your repository. Each commit will trigger the pipeline to run, and you can monitor the pipeline’s execution through the GitLab interface.

What is the purpose of the .gitlab-ci.yml file?

The .gitlab-ci.yml file is used to define the structure and behavior of your GitLab CI/CD pipeline. It includes stages, jobs, scripts, and other configurations that determine how your pipeline will run.

How can I monitor the execution of my pipeline?

You can monitor the execution of your pipeline through the GitLab interface. Navigate to your project’s ‘CI/CD > Pipelines’ section to view the status, logs, and details of each pipeline run.

What should I do if my pipeline fails?

If your pipeline fails, you should review the error messages and logs provided by GitLab. Common issues include syntax errors in the .gitlab-ci.yml file, missing dependencies, or misconfigured runners. Address the errors and re-run the pipeline.

Can I use conditional logic in my GitLab pipeline?

Yes, you can use conditional logic in your GitLab pipeline by leveraging predefined keywords and variables. This allows you to control the execution of jobs based on specific conditions, such as branch names, environment variables, or job outcomes.

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