Redis runs entirely in RAM, making eviction policy selection a critical lever for latency‑sensitive workloads on bare‑metal. When the maxmemory limit is reached, Redis must decide which keys to discard. The six built‑in policies (noeviction, allkeys-lru, volatile-lru, allkeys-lfu, volatile-lfu, allkeys-random, volatile-random, volatile-ttl) each have distinct CPU‑cache footprints and interaction with the kernel's page‑reclaim subsystem. On bare‑metal, NUMA placement, huge‑page configuration, and vm.swappiness dramatically affect eviction latency. This guide walks through systematic troubleshooting: metric correlation, policy‑specific failure modes, and a reproducible benchmark harness.
Eviction Policies Deep Dive
LRU vs LFU: LRU approximates recency using a 24‑bit LRU clock per object; LFU adds a logarithmic counter (8 bits) and a decay timer. LFU's extra counter increases per‑key memory by ~1 byte but reduces scan overhead under skewed access patterns. Volatile vs Allkeys: Volatile policies only consider keys with an EXPIRE set, which can be leveraged to protect hot metadata. Random & TTL: Random eviction is O(1) but can evict hot keys; volatile-ttl evicts the soonest‑expiring key, useful for session caches.
Monitoring & Metrics
Key Redis INFO fields: evicted_keys, expired_keys, used_memory, mem_fragmentation_ratio. Correlate with OS metrics: pgmajfault, pgfault, numa_hit/miss. Use redis-cli --latency-history and perf record -g -p to capture eviction‑induced latency spikes. Enable slowlog-log-slower-than 1000 to surface commands that trigger eviction scans.
Hardware Performance Benchmark Telemetry
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