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You are sitting in a Meta interview. They ask you to design Twitter. You start drawing databases and load balancers. The interviewer stops you, and you fail. Why? Because you didn't do the math first. 📉 Welcome to Day 15 of "100 Days of System Design." Today, we are mastering Chapter 2 of Alex Xu's System Design Interview book: Back-of-the-Envelope Estimation. Forget textbook lectures; this is an insider masterclass on how to prove your architecture will survive the real world before you ever write a single line of code. In this action-packed math breakdown, we cover: 1. The Latency Cheat Sheet 🏎️💨 We visualize the "Latency Numbers Every Programmer Should Know" in our vibrant minimalist vector style. See a glowing green racecar (RAM access) moving instantly, compared to a slow, heavy, rusting cargo ship (Disk access). Reading from disk is 100,000 times slower than reading from memory. Memorize that. 2. Calculating QPS (Queries Per Second) 🌊 Watch as a cute, pulsing load balancer gets hit by glowing data orbs. If you have 100 million Daily Active Users, and each user opens the app 5 times a day... that is 500 million requests. Divide by 100,000 seconds in a day. Boom. You have 5,000 QPS. 3. But wait, what about the spikes? 🏈 The Superbowl happens. We explain why Peak QPS is usually double your average and why you must architect for that crash, not the average day. 4. Storage Nightmare 💾🔥 If just 10% of those users upload a 1-megabyte photo, that is 10 Terabytes of data a day. A standard database instantly melts under that crushing weight. Conclusion: End of Phase 1 🏁🏆 Estimation proves your architecture works. You have officially mastered the foundations of System Design! Tomorrow for Day 16, we enter Phase 2 and tackle the hardest problem in distributed caching: Consistent Hashing. Hit subscribe so you don't miss the jump into distributed systems! 👇 References: System Design Interview by Alex Xu (Chapter 2) #SystemDesign #BackOfTheEnvelopeEstimation #TechInterview #MetaInterview #GoogleInterview #SoftwareArchitecture #QPS #Latency #BackendEngineering #100DaysOfSystemDesign #BigData