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Caching Strategy

  • 499 installs
  • 305 repo stars
  • Updated March 4, 2026
  • aj-geddes/useful-ai-prompts

caching-strategy is a skill that helps developers implement Redis, Memcached, CDN, and cache-invalidation patterns to reduce database load and improve API response latency.

About

caching-strategy is an aj-geddes/useful-ai-prompts skill for designing multi-layer caches that shrink database query volume and speed API responses under traffic spikes. The skill covers Redis and Memcached application caches, CDN edge caching for static and semi-static assets, TTL selection, and invalidation patterns that prevent stale reads after writes. Developers reach for caching-strategy when endpoints show repeated hot-key queries, p95 latency climbs, or origin databases saturate during peak load. Guidance includes quick-start patterns, reference architectures, and best practices for choosing what to cache, how long to keep it, and how to bust entries safely when upstream data changes.

  • Supports Redis, Memcached, CDN, and distributed caching implementations
  • Covers cache invalidation patterns, TTL management, and retry strategies
  • Reduces database query load and improves API response times under high traffic
  • Includes session storage, rate limiting, and expensive computation caching
  • Provides ready-to-use TypeScript service class with connection handling

Caching Strategy by the numbers

  • 499 all-time installs (skills.sh)
  • Ranked #828 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
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Listed on Skillselion
Installs499
repo stars305
Last updatedMarch 4, 2026
Repositoryaj-geddes/useful-ai-prompts

How do you add Redis and CDN caching to APIs?

Add Redis, Memcached, and CDN caching layers that cut database load and speed up API responses.

Who is it for?

Backend developers optimizing high-read APIs where database queries or origin fetches dominate latency and infrastructure cost.

Skip if: Low-traffic internal tools with negligible query volume or systems where strong immediate consistency forbids any cached reads.

When should I use this skill?

API p95 latency rises, databases show hot-query saturation, or traffic spikes require edge and application caching layers.

What you get

Cache layer design, Redis or Memcached configuration patterns, CDN rules, TTL policies, and invalidation workflow documentation.

  • cache architecture plan
  • invalidation workflow
  • redis or memcached configuration patterns

Files

SKILL.mdMarkdownGitHub ↗

Caching Strategy

Table of Contents

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:

GuideContents
Redis Cache Implementation (Node.js)Redis Cache Implementation (Node.js)
Cache Decorator (Python)Cache Decorator (Python)
Multi-Level CacheMulti-Level Cache
Cache Invalidation StrategiesCache Invalidation Strategies
HTTP Caching HeadersHTTP 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

Related skills

How it compares

Use caching-strategy for full-stack cache architecture and invalidation design rather than dropping Redis on a single endpoint without TTL or busting rules.

FAQ

Which cache technologies does caching-strategy cover?

caching-strategy covers Redis, Memcached, CDN edge caching, and invalidation patterns for backend APIs. The skill helps developers cut database load and improve response times with layered cache design and TTL policies.

When should developers apply caching-strategy?

caching-strategy fits high-read APIs with rising p95 latency or database hot-query saturation. Use it before traffic spikes when origin fetches dominate cost and cached reads can safely reduce load with clear invalidation rules.

Backend & APIsbackendintegrations

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