tranhieutt/gitlab-ci-patterns

---

name: gitlab-ci-patterns type: reference description: "Provides GitLab CI/CD pipeline patterns including stages, jobs, artifacts, caching, and environment deployments. Use when working with .gitlab-ci.yml or when the user mentions GitLab CI or GitLab pipelines." paths: ["/.gitlab-ci.yml", "/ci/", "/.gitlab/**"] effort: 3 allowed-tools: Read, Glob, Grep user-invocable: true when_to_use: "When implementing or optimizing GitLab CI/CD pipelines, multi-stage workflows, or distributed runners"

GitLab CI Patterns

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

Do not use this skill when

• The task is unrelated to gitlab ci patterns
• You need a different domain or tool outside this scope

Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

Purpose

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

Use this skill when

• 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:latest
  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:latest
  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:latest
  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

Reference Files

• assets/gitlab-ci.yml.template - Complete pipeline template
• references/pipeline-stages.md - Stage organization patterns

Best Practices

1. Use specific image tags (node:20, not node:latest)
2. Cache dependencies appropriately
3. Use artifacts for build outputs
4. Implement manual gates for production
5. Use environments for deployment tracking
6. Enable merge request pipelines
7. Use pipeline schedules for recurring jobs
8. Implement security scanning
9. Use CI/CD variables for secrets
10. Monitor pipeline performance

Related Skills

• github-actions-templates - For GitHub Actions
• deployment-pipeline-design - For architecture
• secrets-management - For secrets handling

When to Use

• Use when 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...