[00:02] "We might have 10,000 users. How will we handle rights?" There's only two possibilities. Either A, they're hopelessly stuck in 2010 where that number was large, or B, they want to make sure you know about vertical
[00:16] scaling. You don't need a massive database cluster to handle immense scale. You can rent boxes with hundreds of cores for a few grand a month. Maybe you don't believe this operates at scale. OpenAI scaled out their service
[00:28] of ChatGPT with only a single primary serving rights. Now, that's admittedly with hundreds of read replicas for queries, but you get the point. So, do the math first. What's your actual write throughput, and does it fit on one big
[00:42] beefy box? If we assume 10,000 users are making rights every 10 seconds, that's 1,000 TPS. Nothing. That reflection helps your interviewer know you don't sprinkle complexity on a system that
[00:55] doesn't need it. If you really have outgrown a single Postgres instance, ask if it's even the right database. Postgres updates a B-tree on every insert, whereas other databases like Cassandra use an LSM tree, which
[01:09] basically just append to a log. This is way faster for rights. scaling rights in this series, so follow for more and view the whole scaling rights pattern breakdown on our website hellointerview.com.