gitlab-cicd-pipeline
Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and caching. Configure runners, Docker integration, and deployment strategies.
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name: gitlab-cicd-pipeline description: > Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and caching. Configure runners, Docker integration, and deployment strategies.
GitLab CI/CD Pipeline
Table of Contents
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
Quick Start
Minimal working example:
# .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
// ... (see reference guides for full implementation)
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents | |---|---| | Complete Pipeline Configuration | Complete Pipeline Configuration | | GitLab Runner Configuration | GitLab Runner Configuration | | Docker Layer Caching Optimization | Docker Layer Caching Optimization | | Multi-Project Pipeline | Multi-Project Pipeline | | Kubernetes Deployment | Kubernetes Deployment, Performance Testing Stage, Release Pipeline with Semantic Versioning |
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
onlyandexcept - 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
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