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Go, gRPC, Kafka ML Pipeline: Scalable Design

Design a scalable ML pipeline with Go, gRPC, and Kafka. Get architecture, code, and deployment strategies. Build a production-ready system now!

9.1

Performance Score

3,367ms response time

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Last tested: 5 months ago

The Prompt

You are a senior backend engineer. Design and implement a complete, scalable machine learning pipeline using Go + gRPC + Kafka.

ARCHITECTURE REQUIREMENTS:
- Technology: Go + gRPC + Kafka
- Features: presence tracking
- Scale: 10M messages/day

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.

IMPORTANT: Consider edge cases and provide comprehensive solutions.

DEPTH: Provide deep technical details and architectural decisions. [Ref: ea273539]