In this pipeline, there are 12 jobs that are executed in the following order of stages: 1. Quality 2. Get-version 3. Docker-hub-build 4. Docker-hub-test 5. Docker-hub-push 6. Docker-hub-build-arm 7. Docker-hub-test-arm 8. Docker-hub-push-arm 9. Test 10. Docs
hadolint (Quality): This job checks the Dockerfile for
potential security vulnerabilities.getsquid_vars (Get-version): This job fetches the
version of Squid from GitHub and updates the README file with the new
version.docker-hub-build (Docker-hub-build): This job uses
Docker to build the Squid image for amd64.docker-hub-test (Docker-hub-test): This job tests the
built Docker image to ensure it is working properly.push-docker-hub (Docker-hub-push): This job pushes the
tested Docker image to Docker Hub.docker-hub-build-arm (Docker-hub-build-arm): This job
uses Docker to build the Squid image for ARM devices.docker-hub-test-arm (Docker-hub-test-arm): This job
tests the build Docker image on an ARM device to ensure it is working
properly.push-docker-hub-arm (Docker-hub-push-arm): This job
pushes the tested Docker image for ARM devices to Docker Hub.SquidParseConfig (Test): This job tests whether the
Squid configuration file is valid. This aims to catch any potential
configuration errors before the image is pushed.chatgpt_analysis (Docs): This job generates
documentation about the current pipeline. It uses the ChatGPT AI model
to generate the explanation.dive-arm, dive (Docker-hub-test) : These
jobs analyze the Docker images that were built in the previous stages,
providing statistics about their size and usage.update_dockerhub_readme (Docs): This job updates the
Docker Hub description for the Squid project with the contents of the
project’s README file on GitLab.Each job performs a specific function as part of the pipeline. For
instance, the docker-hub-build and
docker-hub-build-arm jobs build Docker images for amd64 and
arm platforms, respectively. During both jobs, the
variables.env file, which contains environment variables
like the Squid version, is sourced with the source bash
command. These environment variables are then used as Docker build
arguments.
The docker-hub-test and docker-hub-test-arm
jobs use these built Docker images as services and test them to ensure
that the Squid proxy works correctly. This is done by running a
curl command that fetches a webpage via the Squid proxy. If
the curl command fails, it indicates that the Squid proxy
is not working correctly.
The push-docker-hub and push-docker-hub-arm
jobs are responsible for pushing these Docker images to Docker Hub. This
is done using Docker commands such as docker login,
docker pull, docker tag, and
docker push.
The SquidParseConfig job checks the Squid configuration
file for potential errors using the Squid -k parse command.
If there’s an error in the configuration file, the job will fail.
The chatgpt_analysis job uses the OpenAI ChatGPT API to
generate an explanation of each job in the pipeline. The explanation is
then saved as a Markdown and HTML file.
The update_dockerhub_readme job updates the description
of the project on Docker Hub with the contents of the README on
GitLab.
The dive and dive-arm jobs analyze the
Docker images for their layers size and wasted space. This is done using
the dive tool and provides insights on where space could be
saved in the Docker images.
Shell scripts in this pipeline reference several environment
variables and files. The variables.env file is a key file
in this pipeline because it contains the version of Squid being built
(SQUID_VERSION). This file is referenced in several jobs
with the source bash command, and the
SQUID_VERSION environment variable is used as a Docker
build argument.
Environment variables that are used in various jobs in this pipeline
include: - CI_BUILDS_DIR - CI_PROJECT_NAME -
CI_COMMIT_BRANCH - CI_PROJECT_DIR -
DOCKER_HUB_REGISTRY - DOCKER_HUB_USER -
DOCKER_HUB_TOKEN - HUB_REGISTRY_IMAGE -
DOCKER_HUB_PASSWORD
Some of these environment variables are used as parameters in Docker
or shell commands. For example, the HUB_REGISTRY_IMAGE
variable is used in the docker-hub-build* jobs to tag the
Docker image that has been built.
Configuration files referenced in the pipeline include: -
Squid.conf: The Squid configuration file used by the
SquidParseConfig job.
Docker images used in the pipeline include: -
hadolint/hadolint:latest-debian for the
hadolint job - debian:stable-slim for the
chatgpt_analysis job - docker:19.03.8-dind for
docker-hub-build* jobs - wagoodman/dive:latest
for dive* jobs
Several jobs depend on other jobs using the needs
keyword. This keyword specifies that a job should be run after another
job is successfully completed.
For example, the docker-hub-test job has
needs: ["docker-hub-build"] meaning it can only run after
the docker-hub-build job has successfully completed.
Similarly, the push-docker-hub job depends on the
docker-hub-test and getsquid_vars jobs.
For each job, some expected results or artifacts are:
getsquid_vars: The variables.env file is
created as an artifact. It contains the latest version of Squid from
GitHub.docker-hub-build* jobs: Docker images are built and
pushed to Docker Hub. The directory ($CI_PROJECT_DIR) of
the job is retained as an artifact for two hours.SquidParseConfig: The outcome of this job is ensuring
the Squid configuration file is valid and has no errors.chatgpt_analysis: The Markdown and HTML explanation
files are produced as artifacts.update_dockerhub_readme: The desired outcome is that
the Docker Hub description of the Squid project is updated with the
contents of the project’s README on GitLab.dive* jobs: The expected outcome is an analysis of the
Docker images layers and their size.The latest commit 6bf909d README Auto update [skip ci]
changes the README file automatically based on the latest Squid version
from GitHub. This happens in the getsquid_vars job.
This commit impacts the pipeline by updating the Docker Hub
description of the Squid project in the
update_dockerhub_readme job. It also impacts the
chatgpt_analysis job since it uses the README file in the
explanation generation process.
The pipeline for the Squid project covers the complete lifecycle of the Squid Docker image, from fetching the latest Squid version, building and testing the Docker images, and updating the project’s documentation. It ensures the Docker images for the Squid project are built correctly, with the right version, and are pushed to Docker Hub.
Project: https://gitlab.com/fredbcode-images/squid
Pipeline: https://gitlab.com/fredbcode-images/squid/-/pipelines/2097645790
Docker images: https://hub.docker.com/r/fredbcode