This tests: System design depth Understanding of distributed systems Trade-off navigation (CAP, consistency, latency) Real-world edge case handling Let’s go step by step and design Redis-like cache from first principles , not using cloud-managed services. 🚀 Goal: Build a Redis-like Distributed In-Memory Cache 🧾 1. Requirements Gathering (Clarify with interviewer) 🔹 Functional Support GET , SET , DEL , TTL Handle concurrent reads/writes Cache keys across multiple nodes Optional: Support pub/sub, data structures (hash, list) 🔹 Non-Functional Low latency (<1ms typical) High availability & fault tolerance Scalable horizontally Eventual or strong consistency Memory-optimized with TTL eviction Absolutely! Back-of-the-envelope estimations are crucial in system design interviews — they demonstrate your pragmatism , ability to roughly size a system, and to make sound trade-offs . Let’s break it down for your Redis-like...
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