aca 0.3.1

A Rust-based agentic tool that automates coding tasks using Claude Code and OpenAI Codex CLI integrations
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Caching Strategy for High-Performance Data Access

OVERVIEW
========
Implement a multi-layer caching system to improve response times for frequently accessed data.

CACHE LAYERS
============

1. Application Cache (Redis)
   - Store user sessions
   - Cache API responses for 5-15 minutes
   - Use LRU eviction policy

2. Database Query Cache
   - Cache complex aggregation queries
   - Invalidate on data changes
   - Use query fingerprinting for cache keys

3. CDN/Edge Cache
   - Cache static assets
   - Cache API responses for public data
   - Geographic distribution for global users

IMPLEMENTATION DETAILS
=====================

Cache Keys Format:
- User data: "user:{user_id}:{version}"
- API responses: "api:{endpoint}:{params_hash}"
- Query results: "query:{table}:{query_hash}"

TTL Strategy:
- User sessions: 30 minutes
- API responses: 5-15 minutes based on data volatility
- Query results: 10-60 minutes based on update frequency

Cache Warming:
- Pre-populate frequently accessed data during low-traffic periods
- Use background jobs to refresh cache before expiration
- Implement cache warming for new deployments

MONITORING
==========
- Track cache hit/miss ratios
- Monitor cache memory usage
- Alert on cache performance degradation
- Track cache invalidation patterns