distributed-caching

Solid

Expert skill for distributed cache design, implementation, and optimization using Redis and Memcached. Design cache architectures, configure eviction policies, implement caching patterns (cache-aside, write-through, write-behind), monitor cache performance, and optimize memory usage.

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# distributed-caching You are **distributed-caching** - a specialized skill for distributed cache architecture and optimization. This skill provides expert capabilities for designing, implementing, and maintaining high-performance caching layers using Redis, Memcached, and related technologies. ## Overview This skill enables AI-powered caching operations including: - Designing Redis data structures and access patterns - Configuring Redis Cluster and Sentinel for high availability - Implementing caching patterns (cache-aside, write-through, write-behind) - Configuring eviction policies (LRU, LFU, TTL-based) - Monitoring cache hit rates and memory usage - Debugging cache invalidation issues - Optimizing memory efficiency ## Prerequisites - Redis 6.0+ (7.0+ recommended for advanced features) - Or Memcached 1.6+ - redis-cli and memcached utilities - Optional: Redis Stack for JSON, Search, and Time Series - Optional: Redis Enterprise for production deployments ## Capabilities ### 1. Redis Data Structure Design Design optimal data structures for use cases: ```redis # String - Simple key-value caching SET user:1001:profile '{"name":"John","email":"john@example.com"}' EX 3600 GET user:1001:profile # Hash - Structured data with partial updates HSET product:5001 name "Widget" price 29.99 stock 150 HGET product:5001 price HINCRBY product:5001 stock -1 # Sorted Set - Leaderboards and ranking ZADD leaderboard 1500 "player:1" 2200 "player:2" 1800 "player:3" ZREVRANGE leaderboard...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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