Jobs Description

The defined jobs are organized in stages that broadly indicate their role in the pipeline. They follow this order:

  1. Quality
  1. Get-version
  1. Docker-hub-build
  1. Docker-hub-test
  1. Docker-hub-pushtag
  1. Docs

Purpose of Each Job

1. hadolint

The hadolint job uses a ‘Hadolint’ Docker image to analyze the Dockerfile for this project and ensure it follows best practices and proper syntax. It’s typically the first step in the pipeline because it preemptively checks for errors and prevents the building and publishing of inappropriate Docker images.

 - hadolint --ignore DL3008 Dockerfile

This command uses ‘Hadolint’, a popular Dockerfile linter, to analyze the Dockerfile. The --ignore DL3008 flag specifically tells ‘Hadolint’ to ignore the DL3008 rule, which is about pinning versions in apt get install.

‘Hadolint’ will exit with a non-zero status code if any unignored issue is found, which will then fail the job and by extension the pipeline – preventing the building of majorly flawed images.

2. getsquid_vars

The getsquid_vars job is responsible for fetching the latest Squid version from their GitHub repo and updating the environment variable SQUID_VERSION, which is then used by jobs down the pipeline. It also updates the README with the latest Squid version.

 - export SQUID_VERSION=$(curl -LsXGET https://github.com/squid-cache/squid/releases/latest | grep -m 1 "Release" | cut -d " " -f4 |tr -d 'v')
 - echo "SQUID_VERSION=$SQUID_VERSION" > variables.env

The first line fetches the latest release version of Squid from their GitHub repo using curl, parses the output with grep to extract the version, and stores it in the SQUID_VERSION variable. The second line writes the value of SQUID_VERSION to a file named variables.env, which can then be sourced by other jobs to set their environment variable SQUID_VERSION.

3. docker-hub-build and docker-hub-build-arm

The docker-hub-build and docker-hub-build-arm jobs are responsible for building Docker images for AMD64 and ARM, respectively. They use the Docker-in-Docker (dind) service in GitLab CI/CD to accomplish this.

 - source variables.env
 - docker build --build-arg SQUID_VERSION=$SQUID_VERSION --pull -t $CONTAINER_BUILD_NOPROD_NAME .
 - docker push $CONTAINER_BUILD_NOPROD_NAME

In the script section, source variables.env sets the environment variable SQUID_VERSION to ensure the Docker image is built with the right Squid version. docker build ... instructs Docker to build an image using the current project’s Dockerfile, and --build-arg SQUID_VERSION=$SQUID_VERSION pass the SQUID_VERSION value into the Dockerfile as a build-time variable. Finally, after the image is built, it is pushed to Docker Hub using docker push.

4. docker-hub-test and docker-hub-test-arm

The docker-hub-test and docker-hub-test-arm jobs are responsible for testing the functionality of the build Docker images. They install curl and then try to access google.com through the squid proxy.

 - apt update && apt install -y curl --no-upgrade --no-install-recommends --no-install-suggests
 - export https_proxy=http://$CONTAINER_TEST_NAME:3128 && curl -k https://www.google.fr

The first line installs curl, a command-line tool for sending HTTP requests. The second line sets the http_proxy and https_proxy environment variables to use the squid proxy and then sends a GET request to google.com. If the squid proxy is properly set up and working, it should be able to reach google.com and receive a 200 OK response, otherwise, the job will fail.

5. dive and dive-arm

The dive and dive-arm jobs are used to inspect the Docker images, specifically to determine their size, and identify potential ways to make it more efficient. They do this using the ‘dive’ tool, which provides a detailed breakdown of the space taken up by each layer of the Docker image.

 - docker pull $CONTAINER_BUILD_NOPROD_NAME
 - dive $CONTAINER_BUILD_NOPROD_NAME

After pulling the Docker image from Docker hub, the ‘dive’ command is run to inspect the Docker image. It outputs a detailed analysis of the space used by each layer of the Docker image.

6. push-docker-hub and push-docker-hub-arm

The push-docker-hub and push-docker-hub-arm jobs are responsible for tagging and pushing Docker images to Docker hub. The images are tag with the Squid version.

 - source variables.env
 - docker pull $CONTAINER_BUILD_NOPROD_NAME
 - docker tag $CONTAINER_BUILD_NOPROD_NAME $HUB_REGISTRY_IMAGE:$SQUID_VERSION
 - docker push $HUB_REGISTRY_IMAGE:$SQUID_VERSION

First, the job imports environment variables from the variables.env file to source the SQUID_VERSION variable. Then, it pulls the image built in the docker-hub-build job. Once the image is pulled, it’s tagged with the SQUID_VERSION using docker tag ..., then pushed to Docker hub using docker push ....

7. chatgpt_analysis

The chatgpt_analysis job fetches a detailed analysis/explanation of each job in the pipeline from the openai API. The output of this job is a markdown file that explains each CI job in detail.

# series of commands to extract the content of jobs in the pipeline, the last commit and form JSON structure payload for API call
 - JOBS_CONTENT=$(cat .gitlab-ci.yml gitlabci/*)
 - LAST_COMMIT=$(git log -1 --pretty=format:"%h %s%n%b")
 - CONTENT=" ... " # Text content for ChatGPT to analyze
 - JSON_CONTENT=$(jq -n --arg model "gpt-4" --arg content "$CONTENT" ...)

# call to `openai` API
 - RESPONSE=$(curl -X POST https://api.openai.com/v1/chat/completions ...)

# Process and write the API response to a markdown file
 - echo $RESPONSE > chatgpt_analysis_$(date +%Y%m%d).md

8. update_dockerhub_readme

The update_dockerhub_readme job updates the README file for this Docker image’s Docker hub repository.

 # forming JSON payload
 - README_CONTENT=$(cat README.md)
 - PAYLOAD=$(jq -n --arg desc "$README_CONTENT"...)

 # API call to dockerhub login and getting token
 - TOKEN=$(curl -v -s -X POST -H "Content-Type:application/json" -d ...)

 # API call to update the Docker hub repository's README
 - curl -X PATCH -H "Authorization:JWT $TOKEN" -H "Content-Type:application/json" -d "$PAYLOAD" ...

It reads the contents of the README.md file, forms JSON payload of the readme content, fetches the login token by calling dockerhub API and then uses that token and JSON payload to update the README via the Dockerhub API.

Parameters, Environment Variables, and File References

The pipeline uses several environment variables:

References to .gitlab-ci.yml and variables.env are made for reading or sourcing environment variables used in building and pushing of Docker images.

Dependencies Between Jobs or Stages

Most jobs have dependencies defined by needs: keyword.

Expected Artifacts

Various artifacts are generated at different stages of the pipeline:

Git Commit Description

The commit 837a374 README Auto update [skip ci] is about auto-updating README with the latest Squid version. This update is made in the getsquid_vars job where after fetching the latest Squid version, the README_template.md is updated with that version and the date, then this template is copied to README.md and committed to the git repository. The [skip ci] flag denotes to GitLab CI to skip running the pipeline for this specific commit.