caching-strategies

Designing caching strategies involves selecting appropriate cache layers like CDN or Redis, choosing read/write patterns such as cache-aside or write-through, and specifying invalidation methods to reduce latency and prevent unnecessary database load in backend systems.

Use distributed caching with Redis for distributed systems requiring shared state across multiple nodes, whereas application-level caching suits single-instance scenarios. Choose based on your latency tradeoffs, read-heavy versus write-heavy workflows, and consistency requirements.

The best way to prevent cache stampedes and stale data is combining refresh-ahead patterns with proper TTL or event-based invalidation. This ensures consistent responses while minimizing thundering herd effects on upstream services during peak loads.

Handle cache invalidation across CDN and application layers by applying TTL, event-driven, or version-based invalidation strategies. Match each layer's invalidation method to your data consistency requirements and update frequency to minimize stale data risk.

Write-behind caching improves write-heavy workflow throughput by asynchronously writing to the database, but introduces temporary inconsistency. Pair it with robust event-based invalidation and careful failure handling to mitigate data loss risks.

Production-safe Redis practices include using TTL-based expiration handling to auto-evict stale keys and employing safe key scanning methods that avoid blocking operations, ensuring stable performance under high-throughput distributed caching workloads.