System design from First Principle[10/15] - Caching

Your app doesn't feel slow because of bad code. It's slow because of physics. Every time your CPU needs data, that data has a physical home — and the distance between that home and your processor is the single most important factor in your system's speed. In this video, I explain the full Memory Hierarchy: from L1 cache (half a second on a human scale) all the way down to a network round-trip (2.5 years on the same scale). Here's what we cover: → The Memory Ladder — why the gap between RAM and disk is 7 orders of magnitude → The 90/10 Rule — why 90% of your requests hit just 10% of your data, and why that's your lucky break → Temporal & Spatial Locality — the two properties that make caching theoretically possible → Cache-Aside, Write-Through & Write-Back — the three strategies, when to use each, and what happens when you get it wrong → Cache Invalidation — why Phil Karlton called it one of the two hard problems in CS (and he was right) → The Thundering Herd — the spectacular failure mode that has taken down production systems at real companies → Cache Warming & Bloom Filters — how to protect your database from its own users → Where caching actually lives — browser, CDN, Redis, DB buffer pool, OS page cache This is Video 10 in the System Design series. No fluff. No hand-waving. Just the mental models you actually need. READING LIST — Designing Data-Intensive Applications — Martin Kleppmann (Chapter 5) — Redis documentation: Eviction Policies — Google SRE Book (free online): Chapter on Caching — Cloudflare Learning: How CDNs Work — High Scalability blog: Latency Numbers Every Programmer Should Know #SystemDesign #SoftwareEngineering #Caching #Redis #WebDevelopment #BackendDevelopment #ComputerScience #ProgrammingTutorial #MemoryHierarchy #SoftwareArchitecture #LearnToCode #DatabaseOptimization #CloudComputing #ThunderingHerd #CacheInvalidation