Coding claude-3.5-opus ⭐ Featured

Scalable IoT Backend with Python: FastAPI & Celery

Design a scalable IoT data pipeline using Python, FastAPI, Celery, and RabbitMQ. Get production-ready code, architecture, and deployment strategies.

9.2

Performance Score

2,688ms response time

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0 copies

Last tested: 5 months ago

The Prompt

You are a senior backend engineer. Design and implement a complete, scalable IoT data processing using Python + FastAPI + Celery + RabbitMQ.

ARCHITECTURE REQUIREMENTS:
- Technology: Python + FastAPI + Celery + RabbitMQ
- Features: load balancing
- Scale: 100K events/second

IMPLEMENTATION REQUIREMENTS:
1. Complete system architecture with diagrams
2. API design (REST/GraphQL/gRPC)
3. Real-time communication setup
4. Database design (SQL/NoSQL/hybrid)
5. Caching strategy (Redis/Memcached)
6. Message queue implementation
7. Authentication and authorization
8. Rate limiting and DDoS protection
9. Monitoring and alerting
10. Load testing and optimization
11. Deployment strategy (Docker, Kubernetes)
12. Disaster recovery plan

DELIVERABLES:
- Complete backend codebase
- API documentation
- Database schemas
- Infrastructure as Code (Terraform/CloudFormation)
- Docker/Kubernetes configs
- Monitoring dashboards
- Load testing scripts
- Architecture documentation

Generate a production-ready, scalable system with all components, documentation, and best practices.

NOTE: Focus on scalability, security, and best practices throughout.

ENHANCEMENT: Add real-world examples and case studies.

SCOPE: Include both MVP and full-featured versions. [Ref: 24153976]