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Deploy & cloud (DevOps)41k · #4822

gitlab-ci-patterns

Teaches your AI agent to ship projects and manage infrastructure and automate repetitive tasks.

What it does

This set of instructions helps create automated workflows for GitLab CI/CD. It organizes tasks like building, testing, and deploying your code efficiently.

When to use it

  • ✓Automating repetitive tasks in GitLab.
  • ✓Organizing the continuous integration/continuous deployment process.
  • ✓Setting up automatic testing and deployments.

Example of what to ask your AI

“I want to set up a CI/CD pipeline in GitLab to build, test, and deploy my web application.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/wshobson/agents/blob/main/plugins/cicd-automation/skills/gitlab-ci-patterns/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/wshobson/agents/blob/main/plugins/cicd-automation/skills/gitlab-ci-patterns/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

It defines clear steps (stages) for each part of the process, such as 'build', 'test', and 'deploy'. It uses configurations to speed up the process (caching) and ensure deployments are secure.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add wshobson/agents --skill gitlab-ci-patterns

Or download just the file:

curl -L https://raw.githubusercontent.com/wshobson/agents/main/plugins/cicd-automation/skills/gitlab-ci-patterns/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

GitLab CI Patterns

Comprehensive GitLab CI/CD pipeline patterns for automated testing, building, and deployment.

Purpose

Create efficient GitLab CI pipelines with proper stage organization, caching, and deployment strategies.

When to Use

  • Automate GitLab-based CI/CD
  • Implement multi-stage pipelines
  • Configure GitLab Runners
  • Deploy to Kubernetes from GitLab
  • Implement GitOps workflows

Basic Pipeline Structure

stages:
  - build
  - test
  - deploy

variables:
  DOCKER_DRIVER: overlay2
  DOCKER_TLS_CERTDIR: "/certs"

build:
  stage: build
  image: node:20
  script:
    - npm ci
    - npm run build
  artifacts:
    paths:
      - dist/
    expire_in: 1 hour
  cache:
    key: ${CI_COMMIT_REF_SLUG}
    paths:
      - node_modules/

test:
  stage: test
  image: node:20
  script:
    - npm ci
    - npm run lint
    - npm test
  coverage: '/Lines\s*:\s*(\d+\.\d+)%/'
  artifacts:
    reports:
      coverage_report:
        coverage_format: cobertura
        path: coverage/cobertura-coverage.xml

deploy:
  stage: deploy
  image: bitnami/kubectl:1.31
  script:
    - kubectl apply -f k8s/
    - kubectl rollout status deployment/my-app
  only:
    - main
  environment:
    name: production
    url: https://app.example.com

Docker Build and Push

build-docker:
  stage: build
  image: docker:24
  services:
    - docker:24-dind
  before_script:
    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
  script:
    - docker build -t $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA .
    - docker build -t $CI_REGISTRY_IMAGE:latest .
    - docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
    - docker push $CI_REGISTRY_IMAGE:latest
  only:
    - main
    - tags

Multi-Environment Deployment

Set KUBE_CA_CERT_FILE as a GitLab file variable containing the cluster CA certificate, and provide KUBE_TOKEN through a protected, masked CI variable. The file variable contains a path that kubectl uses to verify the API server certificate. Protect both develop and main so the deployment jobs can read the protected token.

.deploy_template: &deploy_template
  image: bitnami/kubectl:1.31
  before_script:
    - kubectl config set-cluster k8s --server="$KUBE_URL" --certificate-authority="$KUBE_CA_CERT_FILE" --embed-certs=true
    - kubectl config set-credentials admin --token="$KUBE_TOKEN"
    - kubectl config set-context default --cluster=k8s --user=admin
    - kubectl config use-context default

deploy:staging:
  <<: *deploy_template
  stage: deploy
  script:
    - kubectl apply -f k8s/ -n staging
    - kubectl rollout status deployment/my-app -n staging
  environment:
    name: staging
    url: https://staging.example.com
  only:
    - develop

deploy:production:
  <<: *deploy_template
  stage: deploy
  script:
    - kubectl apply -f k8s/ -n production
    - kubectl rollout status deployment/my-app -n production
  environment:
    name: production
    url: https://app.example.com
  when: manual
  only:
    - main

Terraform Pipeline

stages:
  - validate
  - plan
  - apply

variables:
  TF_ROOT: ${CI_PROJECT_DIR}/terraform
  TF_VERSION: "1.6.0"

before_script:
  - cd ${TF_ROOT}
  - terraform --version

validate:
  stage: validate
  image: hashicorp/terraform:${TF_VERSION}
  script:
    - terraform init -backend=false
    - terraform validate
    - terraform fmt -check

plan:
  stage: plan
  image: hashicorp/terraform:${TF_VERSION}
  script:
    - terraform init
    - terraform plan -out=tfplan
  artifacts:
    paths:
      - ${TF_ROOT}/tfplan
    expire_in: 1 day

apply:
  stage: apply
  image: hashicorp/terraform:${TF_VERSION}
  script:
    - terraform init
    - terraform apply -auto-approve tfplan
  dependencies:
    - plan
  when: manual
  only:
    - main

Security Scanning

include:
  - template: Security/SAST.gitlab-ci.yml
  - template: Security/Dependency-Scanning.gitlab-ci.yml
  - template: Security/Container-Scanning.gitlab-ci.yml

trivy-scan:
  stage: test
  image: aquasec/trivy:0.58.0
  script:
    - trivy image --exit-code 1 --severity HIGH,CRITICAL $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
  allow_failure: true

Caching Strategies

# Cache node_modules
build:
  cache:
    key: ${CI_COMMIT_REF_SLUG}
    paths:
      - node_modules/
    policy: pull-push

# Global cache
cache:
  key: ${CI_COMMIT_REF_SLUG}
  paths:
    - .cache/
    - vendor/

# Separate cache per job
job1:
  cache:
    key: job1-cache
    paths:
      - build/


…
FAQ

What are 'stages'?

These are the different phases of your pipeline, like building the code, running tests, and then deploying the application. Each stage happens in a specific order.

What is 'caching'?

It's a way to temporarily store files that are used frequently, like code dependencies. This speeds up the pipeline in subsequent runs.

What are 'runners'?

These are the 'workers' of GitLab CI/CD. They execute the tasks defined in your pipeline on machines or containers.

Details

Original description by the author

Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.

repo: wshobson/agents

Popularity

GitHub stars
41k
Ranking position
#4822
License
MIT
Updated
10/15/2026

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