The pipeline uses stages to structure the jobs, with each stage serving a unique purpose in the CI/CD process. The stages in the pipeline are listed below. Some stages have multiple jobs, and all jobs within a stage are run parallelly by the GitLab runner.
This job uses the hadolint Dockerfile linter to check your Dockerfile for best practices and to help you avoid common mistakes. Hadolint ensures that the Dockerfile is written in a clean, maintainable, robust, and idiomatic way.
This job fetches the version of Squid that will be used to build Docker images. It’s also responsible for updating a README file with details of the new Squid version and pushing this change to the git repository.
These jobs are used to build Squid Docker images for both amd64 and arm architecture types respectively.
These jobs all pertain to testing the newly created Docker images. They perform a variety of tests including exporting HTTPs proxy and testing connectivity, parsing Squid configuration, and using dive to analyze image layers and size efficiency.
These jobs are used to tag and push the newly created Docker images to Docker Hub. It means updating Squid images in Docker Hub repository with the new Squid version tags.
The chatgpt_analysis job automates the quality analysis
report generation for GitLab CI/CD Jobs and pushes the resulting HTML
file to a remote server.
The update_dockerhub_readme job is responsible for
updating the Docker Hub README file with the latest changes.