Skill

role-backend:caching-strategies

Implements caching solutions using Redis patterns (cache-aside, write-through, write-behind), Memcached, cache invalidation strategies, TTL design, cache stampede prevention, CDN configuration, and distributed caching. Use when optimizing read performance, reducing database load, designing cache layers, or configuring CDN rules.

Install

npx claudepluginhub rnavarych/alpha-engineer --plugin role-backend

Tool Access

This skill is limited to using the following tools:

ReadGrepGlobBash

Preview

- Choosing a caching pattern for a new feature (cache-aside, write-through, read-through)

Supporting Assets

references/patterns-redis-invalidation.mdreferences/stampede-cdn-monitoring.md

SKILL.md

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Stats

Parent Repo Stars9

Parent Repo Forks0

Last CommitMar 3, 2026

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role-backend:caching-strategies

When to use

Choosing a caching pattern for a new feature (cache-aside, write-through, read-through)

Designing Redis key naming and data structure selection

Building cache invalidation logic that stays consistent under writes

Setting TTLs that balance freshness with database load

Preventing cache stampede on high-traffic cache misses

Configuring CDN headers for static assets and versioned files

Evaluating whether to use Redis vs Memcached

Setting up cache hit rate monitoring and eviction alerts

Core principles

Pattern before implementation — cache-aside, write-through, and write-behind have different consistency trade-offs; pick deliberately

TTL jitter is mandatory at scale — synchronized expiration = thundering herd; add 10-30% random variance

Hit rate is the only real metric — target >90%; anything lower means either wrong keys or wrong TTLs

Stale is often fine — serve stale data while revalidating in background rather than blocking on a miss

Cache is not storage — set maxmemory-policy allkeys-lru and accept eviction; anything that can't be lost belongs in the database

Reference Files

references/patterns-redis-invalidation.md — four caching pattern descriptions (cache-aside, write-through, write-behind, read-through), Redis data structure selection guide, connection management, key naming conventions, and cache invalidation strategies with TTL design

references/stampede-cdn-monitoring.md — cache stampede prevention techniques (mutex, probabilistic expiration, stale-while-revalidate) with Node.js code examples, Memcached use cases, CDN Cache-Control header configuration, and Redis monitoring and operations

Caching Strategies

When to use

Choosing a caching pattern for a new feature (cache-aside, write-through, read-through)
Designing Redis key naming and data structure selection
Building cache invalidation logic that stays consistent under writes
Setting TTLs that balance freshness with database load
Preventing cache stampede on high-traffic cache misses
Configuring CDN headers for static assets and versioned files
Evaluating whether to use Redis vs Memcached
Setting up cache hit rate monitoring and eviction alerts

Core principles

Pattern before implementation — cache-aside, write-through, and write-behind have different consistency trade-offs; pick deliberately
TTL jitter is mandatory at scale — synchronized expiration = thundering herd; add 10-30% random variance
Hit rate is the only real metric — target >90%; anything lower means either wrong keys or wrong TTLs
Stale is often fine — serve stale data while revalidating in background rather than blocking on a miss
Cache is not storage — set maxmemory-policy allkeys-lru and accept eviction; anything that can't be lost belongs in the database

Reference Files

references/patterns-redis-invalidation.md — four caching pattern descriptions (cache-aside, write-through, write-behind, read-through), Redis data structure selection guide, connection management, key naming conventions, and cache invalidation strategies with TTL design
references/stampede-cdn-monitoring.md — cache stampede prevention techniques (mutex, probabilistic expiration, stale-while-revalidate) with Node.js code examples, Memcached use cases, CDN Cache-Control header configuration, and Redis monitoring and operations