Caching Strategies Every Backend Engineer Should Know
Cache-aside, read-through, write-through, write-behind — when each pattern fits, and the invalidation trade-offs nobody escapes.
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10 articles
Cache-aside, read-through, write-through, write-behind — when each pattern fits, and the invalidation trade-offs nobody escapes.
How Cache-Control directives and ETags interact with browser and CDN caches, and where each layer disagrees in ways that cause stale content bugs.
How semantic caching cuts LLM spend by reusing responses to meaningfully similar queries, and the correctness traps that come with it.
Practical TanStack Query patterns for query keys, cache invalidation, and optimistic updates that hold up in real React applications.
Why generic memcache stopped fitting Facebook's social graph, and how TAO's objects-and-associations model became the read path for billions of requests.
How Twitter outgrew stock Memcached, built Twemcache and the Pelikan framework, and turned caching into deliberately owned infrastructure rather than a commodity.
A tour of Redis's core data structures and the caching, rate-limiting, and leaderboard patterns each one is actually built for.
How Facebook turned a simple key-value cache into a cluster of thousands of memcached servers without drowning in stale reads and thundering herds.
The gap between what @Cacheable looks like it does and what it actually does, including key collisions, exception handling, and self-invocation.
Browser, CDN, application, and database caching each solve a different problem and fail differently — knowing which layer to reach for matters.