Engineering breakdown of Architecting Redis In-Memory Eviction Strategies (4785). Bare-metal hardware performance requires isolated kernel parameters, tuned vm.swappiness, and careful maxmemory-policy selection to avoid latency spikes under memory pressure.
Eviction Policy Matrix
Redis offers eight eviction policies. The table below maps each policy to typical Kubernetes workload profiles, highlighting trade‑offs between hit‑rate, CPU overhead, and tail latency.
Policy
Use‑Case
CPU Impact
Latency Profile
volatile-lru
Cache with TTL
Low
Predictable
allkeys-lru
General purpose cache
Medium
Low tail
volatile-lfu
Frequency‑aware cache
Medium
Stable
allkeys-lfu
Hot‑key workloads
High
Lowest tail
volatile-random
Testing / low‑priority
Very Low
Variable
allkeys-random
Ephemeral data
Very Low
Variable
volatile-ttl
TTL‑driven expiry
Low
Predictable
noeviction
Strict durability
None
OOM risk
Hardware Performance Benchmark Telemetry
4.9x HIGHER THROUGHPUT
Votion Edge Bare-Metal Cluster420
Standard Virtual Hypervisor (AWS / GCP)85
METRIC: Random Disk IOPS (k)TELEMETRY: REAL-TIME HARDWARE HARDENING AUDIT
CODE_COMPILER // KUBERNETES REDIS STATEFULSET WITH LFU EVICTION
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