
GitLab CI Patterns
FreeStreamline your GitLab CI/CD workflows with proven patterns.
Free · Opens the source repo
What GitLab CI Patterns does
GitLab CI Patterns provides a structured approach to creating efficient CI/CD pipelines using GitLab. This skill focuses on multi-stage workflows, caching strategies, and deployment techniques that enhance automation in software development. With the help of pre-defined YAML configurations, developers can quickly set up pipelines for building, testing, and deploying applications, ensuring that best practices are followed throughout the process.
The skill is particularly useful for teams looking to implement GitLab CI/CD effectively. It includes comprehensive examples for various stages of the pipeline, such as building Docker images, running tests, and deploying applications to Kubernetes. By utilizing caching mechanisms, it optimizes pipeline performance, reducing build times and resource consumption. Moreover, the inclusion of security scanning templates helps maintain code quality and security standards, making it a valuable addition to any DevOps toolkit.
Whether you are new to GitLab CI/CD or looking to refine your existing workflows, this skill offers practical solutions to common challenges. It covers essential topics like configuring GitLab runners, managing environment variables, and setting up manual gates for production deployments. By following the provided patterns, teams can achieve a more organized and efficient CI/CD process, ultimately leading to faster delivery cycles and improved software quality.
When to use it
Use this skill when you need to automate testing, building, and deployment processes in GitLab CI/CD.
When not to use it
This skill may not be suitable for teams using CI/CD tools other than GitLab or those requiring highly customized pipeline configurations.
What you can build with it
Setting Up a New Project
Quickly establish a CI/CD pipeline for a new GitLab project using the provided templates.
Optimizing Build Times
Implement caching strategies to reduce build times and improve overall pipeline efficiency.
Automating Kubernetes Deployments
Deploy applications to Kubernetes directly from GitLab CI/CD with minimal setup.
How to install GitLab CI Patterns
View source1. Install with the skills CLI
npx skills add wshobson/agents/gitlab-ci-patterns --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by wshobsonGitLab 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 $CI_REGISTRY_IMAGE:latest
only:
- main
- tags
Multi-Environment Deployment
.deploy_template: &deploy_template
image: bitnami/kubectl:1.31
before_script:
- kubectl config set-cluster k8s --server="$KUBE_URL" --insecure-skip-tls-verify=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/
job2:
cache:
key: job2-cache
paths:
- dist/
Dynamic Child Pipelines
generate-pipeline:
stage: build
script:
- python generate_pipeline.py > child-pipeline.yml
artifacts:
paths:
- child-pipeline.yml
trigger-child:
stage: deploy
trigger:
include:
- artifact: child-pipeline.yml
job: generate-pipeline
strategy: depend
Best Practices
- Use specific image tags (node:20, not node:latest)
- Cache dependencies appropriately
- Use artifacts for build outputs
- Implement manual gates for production
- Use environments for deployment tracking
- Enable merge request pipelines
- Use pipeline schedules for recurring jobs
- Implement security scanning
- Use CI/CD variables for secrets
- Monitor pipeline performance
Related Skills
github-actions-templates- For GitHub Actionsdeployment-pipeline-design- For architecturesecrets-management- For secrets handling
Frequently asked questions about GitLab CI Patterns
Similar skills
Turborepo
Optimized build system for JavaScript/TypeScript monorepos.
Azure Pipelines Validation
Streamline your Azure DevOps pipeline changes locally.
Azure Developer CLI
Streamline your Azure project workflows with best practices.
Azure Container Registry CLI
Manage Azure Container Registry resources with ease.
Aspire
Build and orchestrate polyglot distributed applications seamlessly.
Vercel CLI
Manage and deploy Vercel projects from the command line.
