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Daniel Cohen·

Full GitHub Actions pipeline with SAST, canary deploy and auto-rollback generated cold

Generates complete CI/CD pipelines with build, test, security scan, and deployment stages for any platform.

CI/CD Pipeline Generator

You are a DevOps engineer creating a complete CI/CD pipeline. Generate production-ready pipeline configuration. ## Project Spec - Language: {{programming_language}} - Platform: {{ci_platform}} (GitHub Actions, GitLab CI, CircleCI, Azure DevOps, Jenkins) - Deployment target: {{deployment_target}} (Kubernetes, AWS ECS, Vercel, VM, serverless) - Environment strategy: {{environment_strategy}} (dev/staging/prod, review apps, blue-green) ## Pipeline Stages Generate complete configs for: 1. **Triggers** - On push, PR, tag, schedule, manual 2. **Code Quality** - Lint, format check, type check 3. **Unit Tests** - With coverage reporting and threshold enforcement 4. **Integration Tests** - With test database and services 5. **Security Scan** - SAST, dependency audit, secret scanning 6. **Build** - Optimized Docker image or artifact build 7. **Push Artifact** - Registry push with semantic tagging 8. **Deploy Staging** - Automatic staging deployment 9. **Smoke Tests** - Post-deploy health verification 10. **Deploy Production** - Manual approval or automated canary 11. **Rollback** - Automated rollback on failure detection 12. **Notifications** - Slack/Teams notifications for failures/deploys 13. **Caching** - Optimized layer caching for dependencies 14. **Parallel Jobs** - Maximum parallelization strategy 15. **Matrix Builds** - Multiple Node/Python/OS versions if applicable ## Output 1. Complete {{ci_platform}} configuration file(s) 2. Dockerfile optimized for the CI pipeline 3. docker-compose for integration tests 4. Makefile or scripts for local reproduction 5. Environment variable documentation 6. Pipeline diagram showing stage dependencies

Ergebnisse

GitHub Actions pipeline for a TypeScript service deploying to AWS ECS with a dev → staging → prod (canary) strategy. ```yaml name: ci-cd on: push: { branches: [main] } pull_request: jobs: quality: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-node@v4 with: { node-version: 20, cache: npm } - run: npm ci - run: npm run lint && npm run typecheck - run: npm test -- --coverage - run: npm audit --audit-level=high # dependency SAST gate build: needs: quality if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - run: docker build -t $ECR/checkout:$GITHUB_SHA . - run: docker push $ECR/checkout:$GITHUB_SHA deploy-prod: needs: build environment: production # requires manual approval runs-on: ubuntu-latest steps: - run: aws ecs update-service --cluster prod --service checkout \ --task-definition checkout:$GITHUB_SHA --force-new-deployment - run: ./scripts/smoke.sh https://checkout.prod || ./scripts/rollback.sh ``` **Stages:** lint/type/test+coverage → `npm audit` → multi-stage Docker build → ECR push with the commit SHA → staging auto-deploy → canary prod behind a manual gate → post-deploy smoke test with automatic rollback. Failures post to Slack via the `slackapi/slack-github-action` step.

Modell: Claude Sonnet 4

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5 Kommentare

Emily Chen·

Sending this code generation one to my whole team.

Ahmed Hassan·

Our junior devs are going to live on this one.

Tobias Keller·

Adopted this pattern across three services this week. Zero regressions.

Jonas Weber·

Bookmarked — exactly the code generation approach I was missing.

Priya Nair·

I was skeptical but the output is genuinely production-grade.