Day 28 — System Design 101

What you’ll learn here

• Load balancing — round-robin, least connections, consistent hashing
• Caching — when to cache, where to cache, invalidation strategies (the second-hardest problem in computer science)
• Sharding and replication — splitting data across machines, keeping it consistent
• SQL vs NoSQL — picking the right database, and when “rolling your own” is wrong
• A worked example: scaling a URL shortener from 10 users to 10 million

This is the bridge from “I can code DSA problems” to “I can design real systems.” Light on math, heavy on trade-offs.