redis-patterns

Optimize Redis cache and key design by classifying state, picking the right data structure, defining lifecycle with TTLs, and ensuring atomicity. This approach prevents memory bloat and improves performance in distributed systems.

Best practices for Redis rate limiting and session management involve using atomic operations, structured key design, and TTL eviction policies. These patterns ensure consistent distributed state while preventing memory leaks.

Avoid blocking Redis by strictly prohibiting unsafe commands like KEYS *. Instead, use structured key design and scan-based iteration to ensure operational safety and maintain system throughput.

Choose Redis Pub/Sub for ephemeral fire-and-forget messaging, and Redis Streams for durable, consumer-group message processing. Selecting the correct pattern ensures reliable event delivery in distributed systems.

Handle Redis failure modes and connection pooling by implementing robust retry logic, circuit breakers, and pool size limits. This ensures distributed system resilience and prevents cascading failures during network issues.