Stage 3 · Build
Performance & Caching at Scale
Redis Cache Invalidation
Design TTLs, versioned keys, write-through updates, pub/sub invalidation, and stale data safeguards.
8 min readBuilding Backend ApplicationsBuild
Invalidation Strategies
Cache invalidation is hard because it must happen consistently across multiple application instances. If one instance invalidates a cache entry but others do not, stale data persists until TTL expiry.
| Strategy | Consistency | Complexity |
|---|---|---|
| TTL expiry | Eventually consistent | Low |
| Delete on write | Mostly consistent | Low |
| Pub/Sub broadcast | Consistent | Medium |
| Write-through | Consistent | Medium |
Versioned Keys
Goversioned-cache-keys.go
32 linesLn 1, Col 1Go
Versioned keys make all old cache entries miss automatically. When the version bumps, the new key is different. Old entries expire naturally via TTL. No explicit invalidation needed.
Pub/Sub Invalidation
Goredis-pub/sub-for-cross-instance-invalidation.go
27 linesLn 1, Col 1Go
Pub/Sub broadcasts invalidation to all instances. Each instance deletes its local cache. This ensures consistency across instances within milliseconds.
Stale Data Safeguards
Gostale-while-error-pattern.go
33 linesLn 1, Col 1Go
The stale cache has a longer TTL than the fresh cache. If the database is down, stale data is served. This provides resilience at the cost of potentially outdated data.
Cache Warming
Gopre-populating-cache.go
16 linesLn 1, Col 1Go
Warm the cache before traffic arrives. This prevents a thundering herd on startup or after a deployment. Pre-populate the most frequently accessed data.
Monitoring Hit Rates
Gocache-hit-rate-metrics.go
21 linesLn 1, Col 1Go
Track cache hits and misses. The hit rate tells you how effective your cache is. Below 80% hit rate means your cache strategy needs improvement.
Invalidate before update
Always invalidate the cache before updating the database. If you update the database first, another request may read stale data and repopulate the cache before invalidation happens.
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