In this episode, we delve into sharding, a pivotal concept in system design that enables applications to scale effectively by distributing data across multiple machines. We'll explain how sharding works as a horizontal scaling technique, allowing systems to handle more traffic and data without relying on increasing the resources of a single machine (vertical scaling).

We also highlight how sharding is applied in various distributed system components, from databases and caches to key-value stores. Additionally, we unpack the CAP theorem—a core principle in distributed systems—explaining the trade-offs between consistency, availability, and partition tolerance, and how these trade-offs shape the design of scalable systems.

Whether you're preparing for a system design interview or simply looking to understand scalable architecture, this episode covers everything you need to know about sharding and the CAP theorem to build robust, distributed systems. Tune in to master these critical concepts and stand out in your next interview!