Core Distributed Systems Patterns

Load Balancing

Problem: single server can't handle all traffic.

Approaches: Round Robin (simple, ignores load) | Weighted Round Robin (accounts for capacity) | Least Connections (fewest active) | IP Hash (session affinity) | Layer 4/transport (IP/port, fast) | Layer 7/application (HTTP-aware, smarter)

Placement: client-to-web | web-to-app | app-to-database

Trade-offs: LB itself is SPOF -- use active-passive pair | session affinity complicates horizontal scaling -- prefer stateless servers | health checks critical

Caching

Problem: repeated DB reads are slow.

Strategies: Cache-aside/lazy loading (app checks cache, fills on miss -- most common) | Write-through (write cache+DB simultaneously) | Write-behind (cache only, async to DB) | Read-through (cache fronts DB transparently)

Cache-aside pattern: Read: cache.get(key) -> hit? return : db.read -> cache.set -> return | Write: db.write -> cache.delete(key)