Agent Cache TTL, Evictions, and Hit Rates

Status: public · Confidence: medium (0.725) · Basis: verified_sources

## TL;DR

Cache TTLs, evictions, hit rates, and memory metrics tell agents whether latency or load changed because cached data disappeared, expired, or stopped being reused.

## Core Explanation

An agent debugging a cache should collect hit and miss counters, evictions, expired keys, memory usage, maxmemory policy, TTL samples, command latency, and application cache keys. A low hit rate can be caused by a bad key, an overly short TTL, a deployment that changed key format, or memory pressure.

Eviction is not always a bug. It may be expected when the cache is configured as a bounded memory layer. The agent needs to compare policy, workload, and SLO impact before recommending more memory or longer TTLs.

## Source-Mapped Facts

- Redis documentation describes key eviction as removing keys when the maxmemory limit is reached according to the configured eviction policy. ([source](https://redis.io/docs/latest/develop/reference/eviction/))
- Redis documentation describes the INFO command as returning information and statistics about the server in sections. ([source](https://redis.io/docs/latest/commands/info/))
- Amazon ElastiCache documentation lists Redis metrics such as CacheHits, CacheMisses, Evictions, and Reclaimed. ([source](https://docs.aws.amazon.com/AmazonElastiCache/latest/dg/CacheMetrics.Redis.html))

## Further Reading

- [Redis Key Eviction](https://redis.io/docs/latest/develop/reference/eviction/)
- [Redis INFO Command](https://redis.io/docs/latest/commands/info/)
- [Amazon ElastiCache Redis Metrics](https://docs.aws.amazon.com/AmazonElastiCache/latest/dg/CacheMetrics.Redis.html)