Caching Optimizer

Intelligent caching strategy optimization for applications and APIs

Quick Commands

Analyze cache effectiveness

npx @j0kz/caching-optimizer analyze

Generate caching strategy

npx @j0kz/caching-optimizer suggest --profile=api

Clear and warm cache

npm run cache:clear && npm run cache:warm

Monitor cache metrics

npx @j0kz/caching-optimizer monitor

Core Functionality

Key Features

• Cache Analysis: Hit/miss ratios and effectiveness

• Strategy Optimization: LRU, LFU, TTL recommendations

• Multi-Layer Caching: Memory, Redis, CDN coordination

• Cache Warming: Preload frequently accessed data

• Invalidation Strategies: Smart cache busting

Detailed Information

For comprehensive details, see:

cat .claude/skills/caching-optimizer/references/caching-patterns.md

cat .claude/skills/caching-optimizer/references/redis-optimization.md

cat .claude/skills/caching-optimizer/references/cdn-strategies.md

Usage Examples

Example 1: Implement Multi-Layer Cache

import { CachingOptimizer } from '@j0kz/caching-optimizer';

const optimizer = new CachingOptimizer({ layers: [ { type: 'memory', size: '100MB', ttl: 300 }, { type: 'redis', size: '1GB', ttl: 3600 }, { type: 'cdn', ttl: 86400 } ] });

// Automatic layer selection const data = await optimizer.get('user:123', async () => { return await fetchUserFromDB(123); });

Example 2: Cache Effectiveness Analysis

const metrics = await optimizer.analyze({ period: '24h', breakdown: true });

console.log(Hit Rate: ${metrics.hitRate}%); console.log(Miss Rate: ${metrics.missRate}%); console.log(Eviction Rate: ${metrics.evictionRate}%);

// Get recommendations const suggestions = optimizer.suggest(metrics); suggestions.forEach(s => console.log(s));

Caching Strategies

Common Patterns

Cache-Aside (Lazy Loading)

const data = cache.get(key) || await loadAndCache(key);

Write-Through

await Promise.all([ cache.set(key, data), database.save(key, data) ]);

Write-Behind (Write-Back)

cache.set(key, data); queue.push({ action: 'save', key, data });

Cache Keys Strategy

// Hierarchical keys for batch invalidation const keyPatterns = { user: 'user:{id}', userPosts: 'user:{userId}:posts', post: 'post:{id}', postComments: 'post:{postId}:comments:{page}' };

Configuration

{ "caching-optimizer": { "default": { "strategy": "lru", "maxSize": "512MB", "ttl": 3600, "compression": true }, "layers": { "memory": { "enabled": true, "maxSize": "128MB" }, "redis": { "enabled": true, "cluster": false, "db": 0 }, "cdn": { "enabled": true, "provider": "cloudflare" } }, "monitoring": { "metrics": ["hitRate", "missRate", "latency"], "alertThreshold": { "hitRate": 0.8, "latency": 100 } } } }

Cache Invalidation

// Tag-based invalidation await optimizer.tag(['user:123', 'posts']).set(key, data); await optimizer.invalidateTag('user:123');

// Pattern-based invalidation await optimizer.invalidatePattern('user:123:*');

// Time-based invalidation await optimizer.set(key, data, { ttl: 3600, slide: true });

Notes

• Supports Redis, Memcached, and in-memory caching

• Automatic cache stampede prevention

• Compression for large values

• Distributed caching support for microservices