caching-strategy

SKILL.md

Caching Strategy

Table of Contents

Overview

When to Use

Quick Start

Reference Guides

Best Practices

Overview

Implement effective caching strategies to improve application performance, reduce latency, and decrease load on backend systems.

When to Use

Reducing database query load

Improving API response times

Handling high traffic loads

Caching expensive computations

Storing session data

CDN integration for static assets

Implementing distributed caching

Rate limiting and throttling

Quick Start

Minimal working example:

import Redis from "ioredis";

interface CacheOptions {
  ttl?: number; // Time to live in seconds
  prefix?: string;
}

class CacheService {
  private redis: Redis;
  private defaultTTL = 3600; // 1 hour

  constructor(redisUrl: string) {
    this.redis = new Redis(redisUrl, {
      retryStrategy: (times) => {
        const delay = Math.min(times * 50, 2000);
        return delay;
      },
      maxRetriesPerRequest: 3,
    });

    this.redis.on("connect", () => {
      console.log("Redis connected");
    });

    this.redis.on("error", (error) => {
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide
Contents

Redis Cache Implementation (Node.js)
Redis Cache Implementation (Node.js)

Cache Decorator (Python)
Cache Decorator (Python)

Multi-Level Cache
Multi-Level Cache

Cache Invalidation Strategies
Cache Invalidation Strategies

HTTP Caching Headers
HTTP Caching Headers

Best Practices

✅ DO

Set appropriate TTL values

Implement cache warming for critical data

Use cache-aside pattern for reads

Monitor cache hit rates

Implement graceful degradation on cache failure

Use compression for large cached values

Namespace cache keys properly

Implement cache stampede prevention

Use consistent hashing for distributed caching

Monitor cache memory usage

❌ DON'T

Cache everything indiscriminately

Use caching as a fix for poor database design

Store sensitive data without encryption

Forget to handle cache misses

Set TTL too long for frequently changing data

Ignore cache invalidation strategies

Cache without monitoring

Store large objects without consideration

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