A popular cache key expires and many requests hit the database at once. How would you prevent that?

Prevent a cache stampede on hot keys

Explains what happens when a hot key expires and how request coalescing, TTL jitter, background refresh, and stale serving help.

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A cache stampede happens when many requests miss the same key at once and all try to rebuild it. I would prevent that by making only one request rebuild the value while others wait briefly, use a stale value, or receive a bounded fallback. Adding TTL jitter also helps avoid many hot keys expiring at the same time.

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Hot keys, cache stampede, request coalescing, TTL jitter, stale-while-revalidate, background refresh, and source protection.

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Cache stampedes are a classic production failure: the cache works until it suddenly sends all traffic back to the source at the same moment.
A cache stampede happens when many requests miss the same key at once and all try to rebuild it. I would prevent that by making only one request rebuild the value while others wait briefly, use a stale value, or receive a bounded fallback. Adding TTL jitter also helps avoid many hot keys expiring at the same time.
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Inside one process I can use single-flight request coalescing so concurrent callers share one rebuild task. Across replicas, a short lease can nominate one refresher while others serve an acceptable stale value or wait for a bounded period. TTL jitter prevents unrelated hot keys from expiring together, and source concurrency limits remain in place if coordination fails. Negative caching can protect repeated not-found lookups, but only with a short lifetime that will not hide newly created data.

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Letting every miss rebuild the same expensive value.
Using a distributed lock without expiration or failure handling.
Setting identical TTLs on many hot keys.
Serving stale data where immediate correctness is required.

A popular cache key expires and many requests hit the database at once. How would you prevent that?

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