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Caching
memoization, caching layers, invalidation.
Measure
- cache profiling → hit/miss rate, size, eviction
- invalidation analysis → staleness frequency
- cache overhead → lookup + maintenance cost
- metrics → hit ratio, avg lookup time, invalidation freq
Optimize
- multi-level caching → hot (mem) → warm (shared) → cold (backend)
- cache warming → pre-populate known-accessed data
- efficient invalidation → TTL, version keys, event-driven
- cache-aside → application manages; only cache frequent reads
- write-through vs write-behind → by read/write ratio + consistency needs
Pitfalls
- cache stampede → concurrent uncached keys overwhelm backend
- stale data → invalidation missing
- over-caching → rarely-accessed wastes memory + lookup overhead
- unbounded cache → evicts or exhausts memory
# Caching
memoization, caching layers, invalidation.
## Measure
- cache profiling → hit/miss rate, size, eviction
- invalidation analysis → staleness frequency
- cache overhead → lookup + maintenance cost
- metrics → hit ratio, avg lookup time, invalidation freq
## Optimize
- multi-level caching → hot (mem) → warm (shared) → cold (backend)
- cache warming → pre-populate known-accessed data
- efficient invalidation → TTL, version keys, event-driven
- cache-aside → application manages; only cache frequent reads
- write-through vs write-behind → by read/write ratio + consistency needs
## Pitfalls
- cache stampede → concurrent uncached keys overwhelm backend
- stale data → invalidation missing
- over-caching → rarely-accessed wastes memory + lookup overhead
- unbounded cache → evicts or exhausts memory