Fastapi Microservices Serverless
This one's built for developers deploying FastAPI services to Lambda, Cloud Run, or similar serverless platforms. It pushes you toward stateless design patterns with Redis for session management, proper API gateway integration with Kong or AWS, and the async patterns that actually matter for cold start optimization. The focus on OpenTelemetry and distributed tracing makes sense when you're running microservices that need to talk to each other across cloud boundaries. It's opinionated about idempotent endpoints and connection pooling strategies, which honestly saves you from common serverless pitfalls. If you're moving FastAPI apps from traditional hosting to serverless or building cloud-native from scratch, this covers the architectural decisions you'll need to make.
- skills.sh installs
- 749
- GitHub stars
- 302
- last updated
- Aug 21, 2026
Install
$ npx -y skills add mindrally/skills --skill fastapi-microservices-serverless --agent claude-codeInstalls into .claude/skills of the current project.
Files
FastAPI Microservices Serverless
You are an expert in building FastAPI microservices for serverless and cloud-native environments.
Core Principles
- Design stateless services with Redis caching
- Implement API Gateway integration (Kong, AWS API Gateway)
- Follow serverless and cloud-native patterns
- Use security middleware (OAuth2, OpenTelemetry)
- Optimize performance with async capabilities
Stateless Design
- Store session data in Redis or external stores
- Design idempotent endpoints
- Use environment variables for configuration
- Implement proper health checks
API Gateway Integration
- Configure routing and rate limiting
- Implement authentication at gateway level
- Use proper API versioning
- Handle CORS appropriately
Serverless Patterns
- Optimize cold start times
- Use connection pooling carefully
- Implement proper timeout handling
- Design for horizontal scaling
Security
- Implement OAuth2 authentication
- Use OpenTelemetry for observability
- Validate all inputs with Pydantic
- Implement proper error handling
Performance
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- Repository
- github.com/mindrally/skills
- Categories
- Python, Cloud & Infrastructure
- First seen
- Jun 3, 2026
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