Distributed-systems

Loose coupling. High throughput. Independent deployments. Everyone knows EDA is scalable — but almost nobody talks about what happens after you ship it to production. Here are the real engineering tradeoffs every Java developer needs to understand.

Explore why LinkedIn outgrew Apache Kafka, the metadata and scaling bottlenecks they hit at 32 trillion events per day, and how their next-gen architecture solves the problem.

A deep-dive into the distributed system design behind scaling ads to billions of WhatsApp users — covering real-time auctions, microservices, failure handling, and the engineering trade-offs that make it all work.