The pipeline defined in the .gitlab-ci.yml features
multiple jobs divided across several stages. In chronological order,
these jobs are:
hadolint: This job falls under the
Quality stage. It checks for common style issues and best
practices in the Dockerfile using Hadolint, a Dockerfile
linter.
getsquid_vars: In the Get-version
stage, this job obtains the latest version of Squid from GitHub and
creates an environment variable that includes this version.
docker-hub-build and
docker-hub-build-arm: In the Docker-hub-build
stage, these jobs build Docker images for AMD64 and ARM architectures,
respectively. They also push these images (tagged with
build-noprod) to Docker Hub.
docker-hub-test and
docker-hub-test-arm: These jobs are part of the
Docker-hub-test stage. They test the Docker containers
built in the previous stage by initiating an HTTPS request via the Squid
proxy.
dive and dive-arm: Also in the
Docker-hub-test stage, these jobs analyze the layer
efficiency of the Docker images originally built for AMD64 and ARM
architectures.
push-docker-hub and
push-docker-hub-arm: Within the
Docker-hub-pushtag stage, these jobs tag the Docker images
built in the Docker-hub-build stage with the Squid version
and then push them to Docker Hub.
chatgpt_analysis: This job falls under the
Docs stage. It uses OpenAI’s GPT model to generate in-depth
explanations of the GitLab CI/CD pipeline based on a predefined content
template.
update_dockerhub_readme: Also in the
Docs stage, this job updates the README on the Docker Hub
repository page for the Docker images with the README documentation from
the GitLab repository.
Let’s now go into detail for each job:
hadolintPurpose: This job serves as a linting step for the Dockerfile. It uses the Hadolint tool, a Dockerfile linter.
Commands explanation: - cd $CI_PROJECT_DIR: Changes the
working directory to the project directory. -
hadolint --ignore DL3008 Dockerfile: Runs Hadolint on the
Dockerfile while ignoring the DL3008 rule (which pertains to pinning apt
package versions).
getsquid_varsPurpose: This job fetches the latest version of Squid from GitHub, saves it in an environment variable, and generates a new version of the README file.
Commands explanation: -
apt update && apt install git curl ca-certificates -y --no-upgrade --no-install-recommends --no-install-suggests:
Updates the package lists for upgrades and new package installation,
then installs necessary packages (git for version control, curl for data
transfer, and ca-certificates for SSL/TSL certificates). -
export SQUID_VERSION=$(curl -LsXGET https://github.com/squid-cache/squid/releases/latest | grep -m 1 "Release" | cut -d " " -f4 |tr -d 'v')
and echo "SQUID_VERSION=$SQUID_VERSION" > variables.env:
Fetches the latest Squid version number from GitHub, stores it in an
environment variable SQUID_VERSION, and then saves this
environment variable in a variables.env file. -
sed -i "s/{{SQUID_VERSION}}/$SQUID_VERSION/g" README_template.md
and
sed -i "s/{{DATE}}/$(date +%Y%m%d)/g" README_template.md:
Replaces placeholders in the README_template.md file with
the fetched Squid version and the current date. -
git add README.md and
git commit -m "README Auto update [skip ci]" || true:
Commits the updated README file to the Git repository.
docker-hub-build
and docker-hub-build-armPurpose: These two jobs build Docker images fitted to the fetched Squid version for different CPU architectures (AMD64 and ARM respectively) and upload the built images to Docker Hub.
Commands explanation: -
docker login -u "$DOCKER_HUB_USER" -p "$DOCKER_HUB_TOKEN" $DOCKER_HUB_REGISTRY:
Logs into Docker Hub using environment variables to provide the user
credentials. - source variables.env: Retrieves and exports
the variables defined in the variables.env file. -
docker build --build-arg SQUID_VERSION=$SQUID_VERSION --pull -t $CONTAINER_BUILD_NOPROD_NAME .:
Builds a Docker image from the Dockerfile in the current directory,
using the Squid version as a build argument. -
docker push $CONTAINER_BUILD_NOPROD_NAME: Pushes the built
Docker image to Docker Hub.
docker-hub-test
and docker-hub-test-armPurpose: These jobs test if the previously built Docker images can run and handle traffic by initiating an HTTPS request via the Squid proxy.
Commands explanation: -
apt update && apt install -y curl --no-upgrade --no-install-recommends --no-install-suggests:
Updates package lists and installs curl for making the HTTPS request. -
export https_proxy=http://$CONTAINER_TEST_NAME:3128 && curl -k https://www.google.fr:
Uses Squid as a proxy for an HTTPS request to Google’s homepage.
dive and
dive-armPurpose: These jobs analyze the layer efficiency and provide information about wasted space and the efficiency score of the Docker images initially built for AMD64 and ARM architectures.
Commands explanation: -
docker pull $CONTAINER_BUILD_NOPROD_NAME: Pulls the
specified Docker image from Docker Hub. -
dive $CONTAINER_BUILD_NOPROD_NAME: Runs the dive command on
the Docker image to analyze its size, efficiency, and waste.
push-docker-hub
and push-docker-hub-armPurpose: These jobs tag the Docker images from the
Docker-hub-build stage with the Squid version number and
update Docker Hub with these newly tagged images.
Commands explanation: -
docker login -u "$DOCKER_HUB_USER" -p "$DOCKER_HUB_TOKEN" $DOCKER_HUB_REGISTRY:
Logs into Docker Hub using stored environment variables for the user
credentials. - source variables.env: Retrieves and exports
the variables defined in the variables.env file. -
docker pull $CONTAINER_BUILD_NOPROD_NAME and
docker tag $CONTAINER_BUILD_NOPROD_NAME $HUB_REGISTRY_IMAGE:$SQUID_VERSION
and docker push $HUB_REGISTRY_IMAGE:$SQUID_VERSION: Pulls
the Docker image from Docker Hub, tags it with the Squid version, and
then pushes it back to Docker Hub.
chatgpt_analysisPurpose: This job uses the OpenAI GPT-3 model to generate an in-depth explanation of the jobs in the GitLab CI/CD pipeline.
Commands explanation: -
apt update && apt install curl git jq ca-certificates pandoc openssh-client -y --no-upgrade --no-install-recommends --no-install-suggests:
Updates the package lists and installs necessary packages (curl, git,
jq, ca-certificates, pandoc, and openssh-client).
update_dockerhub_readmePurpose: This job updates the full description of the Docker Hub repository with the README content from the GitLab repository.
Commands explanation: - README_CONTENT=$(cat README.md)
and
PAYLOAD=$(jq -n --arg desc "$README_CONTENT" '{"full_description":$desc}'):
Reads the content of the README.md file and formats it into JSON. -
TOKEN=$(curl -s -X POST -H "Content-Type:application/json" -d '{"username":"'"$DOCKER_HUB_USER"'","password":"'"$DOCKER_HUB_PASSWORD"'"}' https://hub.docker.com/v2/users/login/ | jq -r .token):
Logs in to Docker Hub and retrieve the authentication token. -
curl -X PATCH -H "Authorization:JWT $TOKEN" -H "Content-Type:application/json" -d "$PAYLOAD" https://hub.docker.com/v2/repositories/$HUB_REGISTRY_IMAGE:
Updates the full description of the Docker repository with the README
content.
Several parameters, environment variables, and file references are used throughout the pipeline:
Environment variables: These are used to store values such as
Docker Hub credentials (DOCKER_HUB_USER and
DOCKER_HUB_PASSWORD) or references to Docker Hub images.
They are generally defined in the variables part of the
GitLab CI/CD definition file or in separate environment files such as
variables.env.
File references:
variables.env: This file stores the recently fetched
Squid version.README.md: This file stores the description of the
project in Markdown format. It is updated with the latest Squid version
and is used to update the Docker Hub repository description.README_template.md: This file serves as a template to
generate the README.md file. It contains placeholders for variables such
as Squid versions or dates.Dockerfile: This is the file used to define the Docker
images that are built, tested, and pushed to Docker Hub. It is analyzed
by the hadolint job.$CI_PROJECT_DIR variable allows
jobs to navigate to the project directory. This directory contains
important files like the Dockerfile and the README files related to the
project.Several jobs depend on each other:
docker-hub-build and docker-hub-build-arm
depend on the getsquid_vars job for the Squid version
information.docker-hub-test and docker-hub-test-arm
depend on docker-hub-build and
docker-hub-build-arm respectively since the Docker images
they test cannot be created without the build jobs.Docker-hub-test stage (which includes
docker-hub-test, docker-hub-test-arm,
dive, dive-arm, SquidParseConfig)
depends on the Docker-hub-build stage.push-docker-hub and
push-docker-hub-arm jobs depend on their respective
docker-hub-test and docker-hub-test-arm jobs
to ensure only tested images are pushed to Docker Hub.chatgpt_analysis job depends on
getsquid_vars, docker-hub-test, and
docker-hub-test-arm jobs and cannot run until those jobs
complete successfully.update_dockerhub_readme depends on the
getsquid_vars job to access the updated README.md with the
recent Squid version.A brief description of the expected outcomes or artifacts from each job:
hadolint: This job doesn’t create any artifacts but it
will fail the pipeline if any linting issue is found.getsquid_vars: Produces an updated
README.md and a variables.env file, which is
used by other jobs.docker-hub-build and docker-hub-build-arm:
These jobs build the Docker images and push them to Docker Hub.docker-hub-test and docker-hub-test-arm:
These jobs don’t generate any artifacts. They simply test the Docker
containers and ensure that they are working properly.dive and dive-arm: These jobs display
information about image size and layer efficiency. They do not produce
any artifacts.push-docker-hub and push-docker-hub-arm:
These jobs tag the Docker images built in the
Docker-hub-build stage with the Squid version and then push
them to Docker Hub.chatgpt_analysis:chatgpt_analysis_<date>.md) that contains the
detailed GitLab CI/CD jobs analysis produced by the OpenAI GPT
model.update_dockerhub_readme: Updates the description of the
Docker Hub repository with the content of the README.md. This job
doesn’t produce any artifacts.Commit SHA: 8a317bb
This commit updated the README.md file, which involved
auto-updating the file with the latest Squid version. This auto-update
is critical because the README file, which serves as the full
description on the Docker Hub repository, provides information about the
latest Squid version used in the Docker images.
The commit message was “README Auto update [skip ci]”. The
[skip ci] tag in the commit message indicates that running
the pipeline, which would normally be triggered by a commit, should be
skipped for this change.
The specific change involved replacing a placeholder in the
README_template.md with the fetched Squid version and the
current date, then copying the content to README.md.
Following this, the changes were committed using Git commands:
git add README.md and
git commit -m "README Auto update [skip ci]".
Lastly, the updated README was pushed to the GitLab repository using the provided GITLAB_TOKEN for authentication.
This commit was crucial in making sure that both the GitLab repositories and Docker Hub repositories have up-to-date information about the Squid version used in the Docker images. However, this specific commit did not impact the CI/CD pipelines as the pipeline run was skipped for this commit.
Project: https://gitlab.com/fredbcode-images/squid Pipeline: https://gitlab.com/fredbcode-images/squid/-/pipelines/1633503940 Docker images: https://hub.docker.com/r/fredbcode