Caching Strategies

Multi-layer caching reduces high latency in web APIs by storing frequently accessed data across application, CDN, and database tiers. Patterns like cache-aside and read-through populate caches on misses, minimizing database load and accelerating response times.

Implement cache-aside with Redis by loading data from cache first, falling back to the database, then populating the cache. Write-through patterns ensure writes propagate to both storage and cache consistently, using code examples in JavaScript and Python.

Use write-behind caching when asynchronous database writes are acceptable to prioritize application performance. Write-through caching is better when immediate consistency between the cache and database is required for data integrity.

CDN and ETag strategies improve content freshness by enabling edge caching and validating cached responses with the origin server. ETags allow conditional requests, reducing bandwidth and ensuring users receive updated content without unnecessary full reloads.

Handle cache invalidation in distributed caches by configuring TTL expiration times and using targeted invalidation strategies. This ensures stale data is purged automatically or on writes, maintaining consistency across application, CDN, and database layers.