Cache Invalidation

Cache API responses versus domain objects

Compares caching response-shaped read models with caching domain entities or raw database objects.

Choose a TTL and expiration strategy for cached data

Explains how TTL choices balance freshness, load reduction, user expectations, and operational safety.

Compare cache-aside, read-through, and write-through caching

Compares cache-aside, read-through, and write-through by read and write ownership, freshness, failure behavior, invalidation, fallback, stampede control, and operational complexity.

Compare in-memory cache and distributed cache

Explains when local process memory is enough and when shared Redis-style caching is worth the extra dependency.

Explain stale data and eventual consistency in caching

Explains when stale cache reads are acceptable, when they are dangerous, and how to make freshness visible.

Invalidate cached data safely after writes

Explains delete-on-write, versioned keys, event-driven invalidation, and the race conditions around cache freshness.

Distributed Caching & Redis

Redis, cache-aside, invalidation, sessions, stampedes, and cache operations.

A practical backend track covering distributed caching with Redis, cache-aside reads, TTLs, invalidation, key scope, stale data, sessions, stampedes, Redis outages, locks, rate limiting, memory pressure, and production observability.