Distributed cache

Design a Memcached/Redis-style cache tier that absorbs most reads for a database. The hard parts are not the hash map: they are partitioning, hot keys, invalidation races and what happens when a cache node restarts empty.

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Duration 45:00

Requirements checklist

get, set with TTL, delete for keys up to 250 B and values up to 1 MB.Used cache-aside by many services.Optional: atomic increment and compare-and-set.Sub-millisecond p99 inside a data centre.Sustain a hit rate high enough that the database never sees more than its capacity — including after a node restart.Losing a cache node must not take the database down.Stale reads bounded in time (TTL) and cleared on write (invalidation).

Clarifying questions

What is the database's read capacity, and the peak read rate?
How stale may cached data be?
Value sizes and working-set size?
Is the cache a pure cache, or do some features rely on it as storage?

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requirements

Suggested time: about 6 minutes. States the database's capacity as the real constraint on hit rate.

Notes for requirements