@entrepreneurship93: Comment CACHE and I'll send you the caching flow cheat sheet. Why does the same app feel slow the first time, then almost instant the next? Follow one food-delivery menu request from a phone to a server and database, then see what changes when the app keeps a nearby copy. ⚡ A cache is a copy kept close. The first fetch does the slow trip, saves the result, and the next tap gets served from the cache instead of making the whole round trip again. ⚡ The catch is stale data. Change a price and the copy still shows the old one, so a TTL gives the copy a lifetime and expires it, while a server cache like Redis keeps thousands of repeat lookups off the database. ⚡ Caches stack into layers: the phone cache, the server cache, then the database. Big image files ride a CDN, so a photo comes from a city near you instead of halfway across the planet. ⚡ Memory is limited, so an eviction rule drops whatever nobody used in a while. The menu you open every day stays; the place you tried once gets dropped. Do the work once, then remember the answer until the copy expires or gets removed. Comment CACHE for the cheat sheet. Which layer do you reach for first: the client, the server, or the CDN? 👇 #caching #webdevelopment #backend #systemdesign #redis

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