High Concurrency

← Series hub Next → Chapter 1: Overcoming the C10M Barrier To build a system capable of handling millions of Requests Per Second (RPS) — known as the C10M problem — vertical scaling is never enough. It requires a meticulously designed Distributed Architecture. 1. The Shift from C10K to C10M Answer-first: While C10K was solved by non-blocking I/O (like NGINX), C10M shifts the bottleneck to the OS kernel. Systems must bypass the kernel using DPDK or XDP to handle 10 million connections efficiently. ...

Answer-first: Architecting flash sale systems requires preventing database overload using multi-stage rate limiting and Redis-based inventory pre-decisions. Traffic shields block duplicate requests, and asynchronous checkout queues decouple order submission from payment processing. What You’ll Learn That AI Won’t Tell You Multi-stage cache invalidation strategies that keep checkout fast. Handling concurrent Redis connections during million-user flash sales. At exactly midnight on 11.11, Shopee users across Southeast Asia and Taiwan simultaneously tap the same button. In the first 10 seconds of a flash sale, a single product page can receive requests from millions of concurrent sessions — all competing to purchase the same 1,000 units of inventory. One oversell, one server crash, or one database deadlock during that window results in a cascade of chargebacks, angry users, and front-page news headlines. ...