When should I add caching to my application?

When you see repeated reads of the same data, high database load from identical queries, or latency issues from slow computations. Do not cache prematurely — measure first, then cache the hot paths.

What is a cache stampede and how do I prevent it?

A cache stampede occurs when a popular cache entry expires and many concurrent requests all hit the database to regenerate it. Solutions include lock-based recomputation (only one request regenerates the cache), probabilistic early expiration, and stale-while-revalidate patterns.

Caching Strategies Explained

Store frequently accessed data closer to the consumer to reduce latency, cost, and database load.

Caching Strategies

Caching strategies are patterns for storing and retrieving frequently accessed data in a fast-access layer (like memory or CDN) to reduce latency, database load, and computation cost. Common strategies include cache-aside, read-through, write-through, and write-behind.

Explanation

Caching places a copy of frequently accessed data closer to the consumer — in memory (Redis, Memcached), at the edge (CDN), or on the client (browser cache, service worker). The goal is to avoid expensive operations (database queries, API calls, computations) by serving pre-computed or previously fetched results. The most common strategies are: Cache-aside (lazy loading) — the application checks the cache first; on a miss, it fetches from the source, stores the result in cache, and returns it. Read-through — the cache itself is responsible for loading data from the source on a miss. Write-through — writes go to both cache and database simultaneously, ensuring consistency. Write-behind (write-back) — writes go to the cache immediately and are asynchronously flushed to the database, improving write performance at the risk of data loss. The hardest problem in caching is invalidation — knowing when cached data is stale. Time-based expiration (TTL) is the simplest approach. Event-based invalidation (purge the cache when the underlying data changes) is more accurate but requires infrastructure to propagate change events. Many production issues stem from stale caches serving outdated data or cache stampedes (many requests hitting the database simultaneously when a popular cache entry expires).

Bookuvai Implementation

Bookuvai projects use a multi-layer caching strategy: browser caching with appropriate Cache-Control headers for static assets, CDN caching for public API responses, and Redis-based application caching for database query results and session data. Cache invalidation is event-driven — database writes trigger cache purges via a message bus. Our AI PM includes caching architecture in the technical design milestone to ensure performance targets are met.

Key Facts

Cache-aside is the most common pattern for read-heavy applications
Cache invalidation is one of the two hard problems in computer science
Multi-layer caching (browser, CDN, application, database) maximizes performance

Related Terms

Frequently Asked Questions

When should I add caching to my application?: When you see repeated reads of the same data, high database load from identical queries, or latency issues from slow computations. Do not cache prematurely — measure first, then cache the hot paths.
What is a cache stampede and how do I prevent it?: A cache stampede occurs when a popular cache entry expires and many concurrent requests all hit the database to regenerate it. Solutions include lock-based recomputation (only one request regenerates the cache), probabilistic early expiration, and stale-while-revalidate patterns.