Cachepatronen

Cachepatronen, in computing, are established designs for storing data in fast-access storage to improve performance and scalability. They describe when data should be cached, how it is refreshed, and how consistency with the primary data store is maintained. Caching can operate at multiple layers, including client-side memory, application servers, databases, and content delivery networks.

Common cachepatronen include:

- Cache-aside (lazy loading): the application queries the cache first; on a miss, it loads from the data store and then populates the cache for subsequent requests.

- Read-through: the cache itself handles misses by loading data from the data store and updating itself, usually through a cache interface or library.

- Write-through: on write operations, data is written to both the cache and the underlying data store, keeping them synchronized.

- Write-behind (write-back): writes are written to the cache and are persisted to the data store asynchronously, which can improve write latency but introduces potential durability considerations.

- Refresh-ahead: the cache proactively refreshes entries before expiration to reduce the chance of serving stale data.

Key concepts also include expiration and eviction policies, such as TTL (time-to-live) and eviction schemes (LRU, LFU, FIFO), used to manage cache memory and data staleness. Invalidation strategies determine how the cache is updated when underlying data changes, balancing freshness with performance. Cache stampede prevention techniques, such as locking, probabilistic expiration, or throttled refresh, mitigate overwhelming the data store during spikes.

Common implementations include in-memory caches (Redis, Memcached) and CDN-based content caching. The choice of cachepatronen depends on data volatility, read/write ratio, consistency requirements, and deployment architecture.