Caching stores frequently accessed data in a faster layer so the system can avoid repeating expensive work.

Common cache types

• Browser cache: stores eligible resources in the browser.
• CDN cache: stores content at edge locations.
• Application cache: stores computed or frequently used values.
• Distributed cache: a shared system such as Redis or Memcached.
• Database systems may also cache internal data or selected results.

Cache-aside pattern

• Check the cache first.
• On a hit, return the cached value.
• On a miss, query the source of truth.
• Store the result in cache, then return it.

Common problems

• Cache invalidation: remove or refresh old values after source data changes.
• Cache stampede: many requests reload the same expired value simultaneously.
• Stale data: cache contains an outdated value.
• Cache penetration: repeated misses bypass the cache.

Practices

• Choose appropriate TTLs.
• Invalidate or update entries when data changes.
• Consider negative caching, request coalescing, or locks for expensive misses.
• Protect sensitive data and monitor hit rate, latency, memory, and evictions