Name: Role Backendcaching Strategies
Author: rnavarych

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

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

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

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