Technologies/Redis/redis.keyspace.misses
RedisRedisMetric

redis.keyspace.misses

Number of failed lookups of keys in the main dictionary
Dimensions:None
Available on:Native (1)DatadogDatadog (1)OpenTelemetryOpenTelemetry (1)PrometheusPrometheus (1)

Summary

Cumulative counter of key lookup attempts where the requested key did not exist in Redis. High miss rates relative to hits indicate cache ineffectiveness — applications are requesting keys that were never stored or have been evicted. Spikes in misses may indicate cache warmup after restart, mass eviction events, or application bugs requesting non-existent keys. Monitor the miss rate (misses / (hits + misses)) as a key cache health indicator.

Interface Metrics (4)
Native
Number of failed lookups of keys in the main dictionary
Dimensions:None
DatadogDatadog
Failed key lookups
Dimensions:None
OpenTelemetryOpenTelemetry
Number of failed lookups of keys
Dimensions:None
PrometheusPrometheus
Failed key lookups
Dimensions:None
Sources
redis.stats.keyspace_missesredis.io
redis.stats.keyspace_missesdocs.datadoghq.com
redis.keyspace.missesopentelemetry.io
redis_keyspace_misses_totalgithub.com
Related Insights (2)
Memory Fragmentation Amplifies Cache Eviction Pressurewarning

High Redis memory fragmentation ratio (>1.5) causes actual memory usage to exceed redis.memory.maxmemory limits, triggering premature key evictions and reducing cache hit rates even when logical memory usage appears healthy.

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High Eviction Rate Indicates Memory Pressurewarning

When redis.keys.evicted rate increases significantly, Redis is evicting keys to stay within maxmemory limits, potentially causing cache miss storms and degraded application performance as hot data is prematurely evicted.

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