GitLab CI CD Tutorial for Beginners [Crash Course]

Introduction

This tutorial provides a comprehensive guide to using GitLab CI/CD by building a complete CI/CD pipeline for a Python demo project. It covers everything from the basic concepts of GitLab CI/CD to deploying a Dockerized application on a remote server. The tutorial is designed for beginners and aims to equip you with the knowledge needed to implement your own CI/CD pipelines.

Step 1: Understand GitLab CI/CD

• GitLab CI/CD automates the software development process.
• CI stands for Continuous Integration, which involves automatically testing code changes.
• CD stands for Continuous Deployment or Continuous Delivery, enabling you to deploy applications to production automatically or with minimal manual intervention.

Step 2: Compare GitLab with Other CI/CD Platforms

• GitLab offers an integrated solution for version control and CI/CD, unlike some platforms that require third-party tools.
• It provides features such as built-in pipelines, Docker support, and Kubernetes integration.

Step 3: Overview of GitLab Architecture

• GitLab consists of components like the GitLab server, GitLab Runner, and CI/CD pipelines.
• Understand how these components interact to facilitate automated testing and deployment.

Step 4: Set Up Your Development Environment

• Create accounts on GitLab and DockerHub.
• Install Python and Pip on your local machine to run the demo application.
• Ensure you have Docker installed for containerization.

Step 5: Configure the Pipeline

• Create a file named .gitlab-ci.yml in your repository.
• This file defines the stages and jobs of your CI/CD pipeline.
• Example configuration:

  stages:
    - test
    - build
    - deploy
  
  test:
    stage: test
    script:
      - python -m unittest discover
  
  build:
    stage: build
    script:
      - docker build -t your-image-name .
  
  deploy:
    stage: deploy
    script:
      - docker push your-image-name
  

Step 6: Run Tests

• Implement unit tests in your Python application.
• The tests will run automatically when you push your code to the repository.

Step 7: Build and Push Docker Image

• Use Docker commands in your GitLab CI/CD pipeline to build and push the Docker image.
• Here's a sample command to build the image:

  docker build -t your-dockerhub-username/your-image-name .
  

Step 8: Use Variables for Login Credentials

• Store sensitive information such as DockerHub credentials in GitLab CI/CD variables.
• Define these variables in your GitLab project settings.

Step 9: Implement Docker in Docker

• Configure your GitLab Runner to use Docker in Docker (DinD) for building your Docker images.
• Add the following to your .gitlab-ci.yml:

  variables:
    DOCKER_DRIVER: overlay2
  services:
    - docker:dind
  

Step 10: Define Stages

• Clearly define the stages of your pipeline in the .gitlab-ci.yml.
• Ensure that each job is assigned a stage in the correct order.

Step 11: Prepare the Deployment Server

• Create an Ubuntu server on DigitalOcean for deployment.
• SSH into the server to set up the environment.

Step 12: Deploy the Application

• Use deployment scripts within the .gitlab-ci.yml to automate the deployment to your DigitalOcean server.
• Example deployment command:

  ssh user@your-server-ip 'docker run -d your-dockerhub-username/your-image-name'
  

Step 13: Validate Application Deployment

• Check if the application is running successfully after deployment.
• Access the application via the server's IP address.

Step 14: Clean Up Resources

• After testing, remember to delete the server on DigitalOcean to avoid unnecessary charges.

Conclusion

You have now learned how to set up a complete CI/CD pipeline using GitLab for a Python application. This tutorial covered everything from basic concepts to practical implementation, including testing, building, and deploying with Docker. As a next step, consider exploring advanced features like monitoring and scaling your applications within GitLab CI/CD.