GitLab CI/CD Jobs - Squid squid-6.14 ChatGPT Analysis

Job List with Brief Description

Stages in the CI/CD pipeline:

  1. Quality
  2. Get-version
  3. Docker-hub-build
  4. Docker-hub-test
  5. Docker-hub-pushtag
  6. Docker-hub-build-arm
  7. Docker-hub-test-arm
  8. Docker-hub-pushtag-arm
  9. Test
  10. Docs

Each corresponding job is explained below:

hadolint

getsquid_vars

docker-hub-build

docker-hub-test

push-docker-hub

docker-hub-build-arm

docker-hub-test-arm

push-docker-hub-arm

chatgpt_analysis

Purpose of Each Job and Commands/Actions Used

hadolint

This job uses the hadolint tool to enforce the use of best practices in Dockerfiles.

before_script:
 - cd $CI_PROJECT_DIR 
script:
 - hadolint --ignore DL3008 Dockerfile

Here, we first navigate to the project directory (cd $CI_PROJECT_DIR). Then, using the hadolint command, we check the Dockerfile for any issues, ignoring particular rules (-ignore DL3008).

getsquid_vars

The purpose of this job is to automatically fetch the latest version of squid-cache from GitHub. The fetched squid version is stored in a file variables.env.

script:
 - apt update && apt install git curl ca-certificates -y --no-upgrade --no-install-recommends --no-install-suggests
 - 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
 - echo $SQUID_VERSION
 - sed -i "s/{{SQUID_VERSION}}/$SQUID_VERSION/g" README_template.md
 - sed -i "s/{{DATE}}/$(date +%Y%m%d)/g" README_template.md
 - cp README_template.md README.md
 - git config user.email "fredbcode"
 - git config user.name "fredbcode"
 - git add README.md
 - git commit -m "README Auto update [skip ci]" || true
 - git push https://$GITLAB_TOKEN@gitlab.com/fredbcode-images/squid.git HEAD:master || true

Explanation:

docker-hub-build

The docker-hub-build job builds a Docker image using the Dockerfile provided in the repository, and the SQUID_VERSION variable gathered from the getsquid_vars job. Then it pushes the image to DockerHub for storage.

before_script:
 - docker login -u "$DOCKER_HUB_USER" -p "$DOCKER_HUB_TOKEN" $DOCKER_HUB_REGISTRY
script:
 - source variables.env
 - docker build --build-arg SQUID_VERSION=$SQUID_VERSION --pull -t $CONTAINER_BUILD_NOPROD_NAME_AMD64 .
 - docker push $CONTAINER_BUILD_NOPROD_NAME_AMD64

Explanation:

docker-hub-test

The objective of this job is to test the image built in previous step. We specifically want to ensure that squid, the reverse proxy, is functioning correctly within the Docker image.

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

Explanation:

Similar steps are followed for docker-hub-build-arm, docker-hub-test-arm and push-docker-hub-arm but for arm architecture.

chatgpt_analysis

The objective of this job is to interact with the Chat GPT-4 API which will generate a detailed analysis. The obtained result is transformed into a Markdown and an HTML document, which are scp-ed to a remote server.

before_script:
 - apt update && apt install curl git jq ca-certificates pandoc openssh-client -y --no-upgrade --no-install-recommends --no-install-suggests
 - source variables.env
 - SQUID_VERSION=squid-$SQUID_VERSION
script: 
 - JOBS_CONTENT=$(cat .gitlab-ci.yml gitlabci/*)
 - LAST_COMMIT=$(git log -1 --pretty=format:"%h %s%n%b")
 - CONTENT="Please provide an in-depth explanation of the following GitLab CI/CD jobs with the following details, [TRUNCATED] at the end of the text add a line with \"Project:$CI_PROJECT_URL Pipeline:$CI_PIPELINE_URL Docker images:https://hub.docker.com/r/fredbcode\""
 - JSON_CONTENT=$(jq -n --arg model "gpt-4" --arg content "$CONTENT" '{model:$model, messages:[{role:"user", content:$content}] }')
 - RESPONSE=$(curl -X POST https://api.openai.com/v1/chat/completions -H "Authorization:Bearer $CHATGPT_API_KEY" -H "Content-Type:application/json" -d "$JSON_CONTENT")
 - ANSWER=$(echo $RESPONSE | jq 'del(.choices[0].message.content)')
 - RESPONSE=$(echo $RESPONSE | jq -r '.choices[0].message.content')
 - echo "$ANSWER"
 - echo -e "$RESPONSE" > chatgpt_analysis_$(date +%Y%m%d).md
 - mkdir -p ~/.ssh
 - eval $(ssh-agent -s)
 - '[[ -f /.dockerenv ]] && echo -e "Host *
    StrictHostKeyChecking no

" > ~/.ssh/config'
 - ssh-add <(echo "$SSH_NOSTROMO_KEY")
 - pandoc -s --from=markdown+smart --to=html --metadata=encoding=UTF-8 -o chatgpt_analysis_$(date +%Y%m%d).html chatgpt_analysis_$(date +%Y%m%d).md
 - scp -P 822 -r chatgpt_analysis*.html e2git@e2guardian.numsys.eu:/datas/e2/html/squid-ci/
 - echo "!!! See Artifact for explanations or https://e2guardian.numsys.eu !!!"

Explanations: - We first update the package lists and install the necessary packages: curl, git, jq (command-line JSON processing tool), ca-certificates, pandoc (text conversion tool), and openssh-client - Have access to the SQUID_VERSION variable from variables.env by sourcing it - Then, we concatenate all the CI/CD configuration files, and store the last commit message. - Next, we construct content for the ChatGPT by combining pre-defined text with job content and the last commit - We then format the content into an appropriate JSON payload to interact with the ChatGPT API - The payload is POSTed to the API, and response is captured - The ANSWER variable is used to hold the response without specific fields. While RESPONSE holds the text content from the choices.message.content field of the response JSON. - It echoes out the ANSWER variable and writes the RESPONSE variable to a markdown (.md) file, named with the current date (chatgpt_analysis_$(date +%Y%m%d).md) - It then generates the SSH key, and configures the SSH client for a non-interactive environment. - Then it converts the markdown file, which contains the ChatGPT’s elaborate explanations, into an HTML file. - Finally, the HTML file is scp-ed to a remote web server for public viewing and an announcement message is printed

update_dockerhub_readme

This job makes an update to the readme of the docker image on dockerhub with the README.md present on the git repository. It uses curl and jq to make the PATCH request to Dockerhub’s API.

before_script:
 - apt update && apt install -y curl jq ca-certificates --no-upgrade --no-install-recommends --no-install-suggests
script:
 - README_CONTENT=$(cat README.md) 
 - PAYLOAD=$(jq -n --arg desc "$README_CONTENT" '{"full_description":$desc}')
 - echo "Payload JSON:$PAYLOAD"
 - TOKEN=$(curl -v -s -X POST -H "Content-Type:application/json" -d '{"username":"'"$DOCKER_HUB_USER"'","password":"'"$DOCKER_HUB_PASSWORD"'"}' https://hub.docker.com/v2/users/login/ | jq -r .token)
 - curl -X PATCH -H "Authorization:JWT $TOKEN" -H "Content-Type:application/json" -d "$PAYLOAD" https://hub.docker.com/v2/repositories/$HUB_REGISTRY_IMAGE
only:
 - master

Explanation:

Parameters, Environment Variables, and File References

Below are the significant parameters, environment variables, and files referenced in the job.

Environment Variables

Dependencies between Jobs or Stages

The script part of each job is only run if all jobs from prior stages succeed. For example, all jobs in the Docker-hub-build stage will only run if the jobs in the Get-version stage have succeeded.

Most of the jobs have dependencies on other jobs. This dependency is usually because of shared environment variables:

Expected Outcomes or Artifacts

For every job that executes successfully, it can potentially generate an output or an “artifact”. This could be test results, a compiled app, jar files, war files, Docker images, logs, or any files generated during the run of the job. The specific artifacts for this CI/CD pipelines include:

  1. The getsquid_vars job generates variables.env which contains the latest squid version
  2. The docker-hub-build-amd64 and docker-hub-build-arm jobs generate a docker image and push it to DockerHub
  3. chatgpt_analysis job generates ‘chatgpt_analysis_ date .md’ and ‘chatgpt_analysis_ date .html’ files which contain in-depth analysis and these files are scp-ed to a remote web server for public viewing
  4. update_dockerhub_readme updates the README.md on the image page on DockerHub.

Latest Commit: Fix Healthcheck

The commit message “Fix Healthcheck” indicates that this commit introduces changes that aim to fix health checks in the application. Health checks are used to probe systems and applications for their status.

In terms of CI/CD pipelines, this could signify changes to tests that are performed as part of the pipeline, changes to configurations, or corrections to scripts that perform these checks.

In this particular pipeline, there isn’t a job that indicates a health check. The commit might be fixing an issue which is outside of the pipeline, maybe in the application for which the pipeline is made (here, Squid). The exact impact of this commit would therefore depend on the nature of the “health check” that has been fixed. The changes related to the commit can be viewed by accessing GitLab with the commit hash 2d97f25.

Please note that it’s not necessary that each commit impacts the pipeline and triggers a new pipeline run. The workflow:rules:if condition states that if a commit message includes the “[skip ci]” tag, the pipeline associated with that commit will not run. Hence, a commit can be made without triggering a CI/CD pipeline.