Back to Skills

gitlab-cicd-pipeline

aj-geddes
Updated Today
21 views
7
7
View on GitHub
Designdesign

About

This skill enables developers to design and implement comprehensive GitLab CI/CD pipelines for automating build, test, and deployment workflows. It covers configuring multi-stage pipelines, jobs, artifacts, caching, and Docker integration. Use it for setting up automated testing, container registry workflows, Kubernetes deployments, and optimizing pipeline performance.

Documentation

GitLab CI/CD Pipeline

Overview

Create comprehensive GitLab CI/CD pipelines that automate building, testing, and deployment using GitLab Runner infrastructure and container execution.

When to Use

  • GitLab repository CI/CD setup
  • Multi-stage build pipelines
  • Docker registry integration
  • Kubernetes deployment
  • Review app deployment
  • Cache optimization
  • Dependency management

Implementation Examples

1. Complete Pipeline Configuration

# .gitlab-ci.yml
image: node:18-alpine

variables:
  DOCKER_DRIVER: overlay2
  FF_USE_FASTZIP: "true"

stages:
  - lint
  - test
  - build
  - security
  - deploy-review
  - deploy-prod

cache:
  key: ${CI_COMMIT_REF_SLUG}
  paths:
    - node_modules/
    - .npm/

lint:
  stage: lint
  script:
    - npm install
    - npm run lint
    - npm run format:check
  artifacts:
    reports:
      codequality: code-quality-report.json
    expire_in: 1 week

unit-tests:
  stage: test
  script:
    - npm install
    - npm run test:coverage
  artifacts:
    reports:
      coverage_report:
        coverage_format: cobertura
        path: coverage/cobertura-coverage.xml
      junit: test-results.xml
    paths:
      - coverage/
    expire_in: 1 week
  coverage: '/Coverage: \d+\.\d+%/'

integration-tests:
  stage: test
  services:
    - postgres:13
    - redis:7
  variables:
    POSTGRES_DB: test_db
    POSTGRES_USER: test_user
    POSTGRES_PASSWORD: test_password
  script:
    - npm run test:integration
  only:
    - merge_requests
    - main

build:
  stage: build
  image: docker:latest
  services:
    - docker:dind
  variables:
    DOCKER_HOST: tcp://docker:2375
    REGISTRY: registry.gitlab.com
  script:
    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
    - docker build -t $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA .
    - docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
    - docker tag $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA $CI_REGISTRY_IMAGE:latest
    - docker push $CI_REGISTRY_IMAGE:latest
  only:
    - main
    - tags

security-scan:
  stage: security
  image: alpine:latest
  script:
    - apk add --no-cache git
    - git clone https://github.com/aquasecurity/trivy.git
    - ./trivy image $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
  allow_failure: true

deploy-review:
  stage: deploy-review
  environment:
    name: review/$CI_COMMIT_REF_SLUG
    url: https://$CI_COMMIT_REF_SLUG.review.example.com
    auto_stop_in: 1 week
  script:
    - helm upgrade --install review-$CI_COMMIT_REF_SLUG ./chart
      --set image.tag=$CI_COMMIT_SHA
      --set environment=review
  only:
    - merge_requests

deploy-prod:
  stage: deploy-prod
  environment:
    name: production
    url: https://example.com
  script:
    - helm upgrade --install prod ./chart
      --set image.tag=$CI_COMMIT_SHA
      --set environment=production
  only:
    - main
  when: manual

2. GitLab Runner Configuration

#!/bin/bash
# install-runner.sh

# Register GitLab Runner
gitlab-runner register \
  --url https://gitlab.com/ \
  --registration-token $RUNNER_TOKEN \
  --executor docker \
  --docker-image alpine:latest \
  --docker-privileged \
  --docker-volumes /certs/client \
  --description "Docker Runner" \
  --tag-list "docker,linux" \
  --run-untagged=false \
  --locked=false \
  --access-level not_protected

# Start runner
gitlab-runner start

3. Docker Layer Caching Optimization

# .gitlab-ci.yml
stages:
  - build

build-image:
  stage: build
  image: docker:latest
  services:
    - docker:dind
  variables:
    DOCKER_HOST: tcp://docker:2375
    DOCKER_TLS_CERTDIR: ""
  script:
    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY

    # Pull previous image for cache
    - docker pull $CI_REGISTRY_IMAGE:latest || true

    # Build with cache
    - docker build
        --cache-from $CI_REGISTRY_IMAGE:latest
        --tag $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
        --tag $CI_REGISTRY_IMAGE:latest
        .

    # Push images
    - docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
    - docker push $CI_REGISTRY_IMAGE:latest
  cache:
    key: ${CI_COMMIT_REF_SLUG}-docker
    paths:
      - .docker/

4. Multi-Project Pipeline

# .gitlab-ci.yml
stages:
  - build
  - test
  - deploy

build:backend:
  stage: build
  script:
    - cd backend && npm run build
  artifacts:
    paths:
      - backend/dist/

build:frontend:
  stage: build
  script:
    - cd frontend && npm run build
  artifacts:
    paths:
      - frontend/dist/

test:backend:
  stage: test
  needs: ["build:backend"]
  script:
    - cd backend && npm test
  artifacts:
    reports:
      junit: backend/test-results.xml

test:frontend:
  stage: test
  needs: ["build:frontend"]
  script:
    - cd frontend && npm test
  artifacts:
    reports:
      junit: frontend/test-results.xml

deploy:
  stage: deploy
  needs: ["test:backend", "test:frontend"]
  script:
    - echo "Deploying backend and frontend..."
  when: manual

5. Kubernetes Deployment

# .gitlab-ci.yml
deploy-k8s:
  stage: deploy
  image: alpine/k8s:latest
  script:
    - mkdir -p $HOME/.kube
    - echo $KUBE_CONFIG_ENCODED | base64 -d > $HOME/.kube/config
    - chmod 600 $HOME/.kube/config

    # Update image in deployment
    - kubectl set image deployment/app-deployment
        app=$CI_REGISTRY_IMAGE:$CI_COMMIT_SHA
        -n production

    # Wait for rollout
    - kubectl rollout status deployment/app-deployment -n production
  environment:
    name: production
    kubernetes:
      namespace: production
  only:
    - main
  when: manual

6. Performance Testing Stage

# .gitlab-ci.yml
performance:
  stage: test
  image: grafana/k6:latest
  script:
    - k6 run tests/performance.js
  artifacts:
    reports:
      performance: performance-results.json
    expire_in: 1 week
  allow_failure: true
  only:
    - main
    - merge_requests

7. Release Pipeline with Semantic Versioning

# .gitlab-ci.yml
release:
  stage: deploy-prod
  image: node:18-alpine
  script:
    - npm install -g semantic-release @semantic-release/gitlab

    # Configure git
    - git config user.email "[email protected]"
    - git config user.name "CI Bot"

    # Run semantic-release
    - semantic-release
  only:
    - main
  when: manual

Best Practices

✅ DO

  • Use stages to organize pipeline flow
  • Implement caching for dependencies
  • Use artifacts for test reports
  • Set appropriate cache keys
  • Implement conditional execution with only and except
  • Use needs: for job dependencies
  • Clean up artifacts with expire_in
  • Use Docker for consistent environments
  • Implement security scanning stages
  • Set resource limits for jobs
  • Use merge request pipelines

❌ DON'T

  • Run tests serially when parallelizable
  • Cache everything unnecessarily
  • Leave large artifacts indefinitely
  • Store secrets in configuration files
  • Run privileged Docker without necessity
  • Skip security scanning
  • Ignore pipeline failures
  • Use only: [main] without proper controls

Gitlab Runner Executor Types

# Docker executor (recommended)
gitlab-runner register --executor docker

# Kubernetes executor
gitlab-runner register --executor kubernetes

# Shell executor (local)
gitlab-runner register --executor shell

# Machine executor (for auto-scaling)
gitlab-runner register --executor machine

Resources

Quick Install

/plugin add https://github.com/aj-geddes/useful-ai-prompts/tree/main/gitlab-cicd-pipeline

Copy and paste this command in Claude Code to install this skill

GitHub 仓库

aj-geddes/useful-ai-prompts
Path: skills/gitlab-cicd-pipeline

Related Skills

langchain

Meta

LangChain is a framework for building LLM applications using agents, chains, and RAG pipelines. It supports multiple LLM providers, offers 500+ integrations, and includes features like tool calling and memory management. Use it for rapid prototyping and deploying production systems like chatbots, autonomous agents, and question-answering services.

View skill

Algorithmic Art Generation

Meta

This skill helps developers create algorithmic art using p5.js, focusing on generative art, computational aesthetics, and interactive visualizations. It automatically activates for topics like "generative art" or "p5.js visualization" and guides you through creating unique algorithms with features like seeded randomness, flow fields, and particle systems. Use it when you need to build reproducible, code-driven artistic patterns.

View skill

webapp-testing

Testing

This Claude Skill provides a Playwright-based toolkit for testing local web applications through Python scripts. It enables frontend verification, UI debugging, screenshot capture, and log viewing while managing server lifecycles. Use it for browser automation tasks but run scripts directly rather than reading their source code to avoid context pollution.

View skill

finishing-a-development-branch

Testing

This skill helps developers complete finished work by verifying tests pass and then presenting structured integration options. It guides the workflow for merging, creating PRs, or cleaning up branches after implementation is done. Use it when your code is ready and tested to systematically finalize the development process.

View skill