Eviction policies

When memory is full, the cache must drop something. LRU removes the least recently used key, LFU the least frequently used, which keeps popular items better under scans. No eviction means writes fail instead.

Where it shows up in real systems

  • In-memory cache

    The hit ratio depends on how much of the working set fits in memory, the TTL and the eviction policy. If the cache goes down or is flushed, every read falls on the database at once: plan for that stampede. Write-behind is fast but loses writes if a node dies without a replica.

    In production: Redis (Amazon ElastiCache, Azure Cache), Valkey, Memcached, Dragonfly

See it break, then fix it

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