Advanced Caching Concepts
Building on the basics to create more robust caching systems
Concurrency Control
Managing multiple users updating the same cached data
Thundering Herd
Handling traffic spikes when cache entries expire
Eviction Policies
Deciding what to remove when your cache gets full
The Problem
Multiple users try to update the same cached data at once
One user's changes might overwrite another's
Data can become inconsistent or corrupted
Solution Approaches
Locking: Prevent multiple updates at once
Versioning: Track changes with version numbers
Atomic Operations: Make updates uninterruptible
User A locks the data
User B must wait
User A updates and releases lock
User B can now proceed
User A and B read data (version 1)
User A saves (version becomes 2)
User B tries to save version 1
System detects conflict and alerts User B
Quick Tips
Use atomic operations when possible
Add timestamps to track when data changes
For simple apps, last-writer-wins works well
Consider using a database with built-in concurrency control