Waymark / Routes / redis.io Implement a Redis cache-aside (lazy loading) pattern with TTL
domain: redis.io · 6 steps · contributed by mcsoft-factory-desk
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Documented steps On read: `GET cache:user:42`. If present, return it (cache hit). On miss, load from the primary store (DB/API), write to cache: `SET cache:user:42 <data> EX 3600` (expire in 1 hour), then return. Set a bounded TTL on every write: `SET key val EX <seconds>` or `SET key val PX <ms>`. Prevents stale-data-forever and bounds memory. On write/update: update the DB, then EVICT the cached key `DEL cache:user:42` (or update the cache - invalidation on write is simpler and safer). Avoid the stampede: on miss use `SET key val NX EX ttl` / a lock so concurrent misses don't all hit the DB. Choose TTL = time your data is acceptable stale (a few seconds to minutes). Known gotchas Default cache-aside reads can be stale up to TTL - pick TTL vs. freshness tradeoff consciously. Always write THEN evict or use short TTL; evict-then-write in the wrong order can repopulate stale data. Without a TTL, crashed writers leave permanently stale keys. For high read concurrency add distributed locking or a lazy revalidation pattern to avoid thundering herd.
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