SD #010 - Designing a Distributed Cache System

Distributed caching is one of the most frequently asked system design interview questions — and one of the most important real-world backend optimizations. If you're preparing for backend roles (especially senior-level), you should be able to clearly explain: Why we need a distributed cache How it works internally How it scales What trade-offs exist How to handle failures Let’s walk through it step by step in a clean, practical, interview-ready way. The Problem - Why Do We Need a Cache? Imagine a system serving millions of users. Every request: Client → App Server → Database Problems: Database becomes a bottleneck High latency (disk I/O is slow) Expensive horizontal scaling Increased infrastructure cost Now imagine 90% of requests are reads for the same popular data (product details, user profile, configuration, etc.). We are repeatedly fetching the same data from disk. That’s inefficient. The Core Idea of Caching Instead of hitting the database every time: Client → App → Cache → Datab