Caching strategies
Where caches live, the patterns for using them (cache-aside, read-through, write-through, write-behind), choosing TTLs, eviction policies, keeping caches correct after writes, and the stampede and stale-data problems that bite in production.
CodexBash, , 5 min read
A cache keeps a copy of data somewhere faster than its original home, so the next request can skip the slow work. Done well, it turns a struggling database into a quiet one and a slow page into an instant one. Done badly, it shows users stale prices, wrong balances and other people's data. This article covers where caches sit, the standard patterns, and the problems to plan for from day one.
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