romankovsv/claude-code-python-devops-mlops/deployment-patterns
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Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies for Python applications.
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npx vskill@latest install romankovsv/claude-code-python-devops-mlops/deployment-patternsSKILL.md
The same SKILL.md was published earlier as izangi2714/claude-code-python-stack/deployment-patterns.
Deployment Patterns for Python
Production deployment workflows and CI/CD best practices.
When to Activate
- Setting up CI/CD pipelines for Python projects
- Dockerizing Python/Django/FastAPI applications
- Planning deployment strategy
- Implementing health checks and readiness probes
Deployment Strategies
| Strategy | Use When | Pros | Cons | |
|---|---|---|---|---|
| Rolling | Standard deploys | Zero downtime | Two versions run simultaneously | |
| Blue-Green | Critical services | Instant rollback | 2x infrastructure | |
| Canary | Risky changes | Catches issues early | Requires traffic splitting |
Python Dockerfile
GitHub Actions (Python)
Health Check Endpoint (FastAPI)
Production Readiness Checklist
- [ ] All tests pass (unit, integration, E2E)
- [ ] No hardcoded secrets
- [ ] Health check endpoint works
- [ ] Docker image builds reproducibly
- [ ] Environment variables validated at startup
- [ ] Resource limits set
- [ ] SSL/TLS enabled
- [ ] Alerts configured
- [ ] Log aggregation set up
- [ ] Rollback plan documented
- [ ] Dependencies scanned for CVEs
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Source
- SKILL.md in the repositoryCheckingskills/deployment-patterns/SKILL.md
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