Caching fundamentals, strategies, and types.
Cache-aside (lazy loading) puts your application in control: check the cache first, and only hit the database on a miss, then populate the cache for next time.
Write-through caching synchronously writes data to both cache and database before confirming success to the application. This pattern guarantees strong consiste
Write-behind (also called write-back) is a caching pattern where writes go to cache first and are asynchronously propagated to the database later, dramatically
Refresh-ahead is a proactive caching pattern that automatically refreshes cache entries before they expire, based on predictions about which items will be acces
Client caching stores resources directly in the user's browser or device, eliminating network requests for repeated content. HTTP cache headers (Cache-Control,
CDN caching distributes static content across geographically dispersed edge servers, serving users from the nearest location to minimize latency. Edge locations
Web server caching places a reverse proxy (Nginx, Varnish, Apache Traffic Server) between clients and application servers to cache HTTP responses. This reduces
Database caching stores frequently accessed data in memory layers within the database itself—query cache, buffer pool, and materialized views—to reduce disk I/O
Application caching uses in-memory data stores (like Redis or Memcached) positioned between your application servers and databases to dramatically reduce latenc
Cache eviction policies determine which items to remove when cache capacity is reached. LRU (Least Recently Used) works best for temporal locality, LFU (Least F
Cache invalidation is the process of removing or updating stale data from a cache to maintain consistency with the source of truth. It's famously one of the har
Read-through caching moves cache management logic from application code into the cache library itself. When your application requests data, the cache library au