Performance Optimization & Caching Layer

[Sakeeb91]

Priority

P1

Story Points

8

Dependencies

Depends on #6 (Shared Libraries), #7 (API Gateway), #21 (Docker Compose)

Summary

Implement comprehensive performance optimization strategies including Redis caching, API rate limiting, database query optimization, response compression, and performance benchmarking to ensure the platform can handle production workloads efficiently.

Background

Current performance gaps:

• Redis URL in environment but not used
• No caching layer implemented
• No API rate limiting
• No response compression
• Database queries not optimized
• No performance benchmarks established

Acceptance Criteria

• Redis caching layer implemented and integrated
• API rate limiting per user/IP/API key
• Database query result caching
• Response compression middleware (gzip/brotli)
• Performance indexes on database tables
• Query result caching patterns documented
• Performance benchmarks established (baseline metrics)
• Load testing suite implemented
• Performance monitoring dashboard

Key Features

• Redis-based caching with TTL
• Multi-tier rate limiting (auth endpoints, API, heavy operations)
• Response compression
• Query result caching patterns
• Load testing with k6
• Performance benchmarking

Documentation

Full specification in: docs/issues/ (to be created)

Related Issues

• Shared Libraries Package Setup #6: Shared Libraries
• API Gateway Service #7: API Gateway
• Local Development Environment with Docker Compose #21: Docker Compose
• Database Performance & Operations Improvements #23: Database Performance