Distributed Systems

Ditch the chaotic agent-to-agent calls. Learn how to build a clean, production-grade multi-agent system using LangGraph's shared state and a structured message bus.

Ever watched a tiny service hiccup spiral into a full-blown outage? It's often the "helpful" retries that are to blame. Let's break down why this happens and compare how RPC and event-driven architectures handle the pressure.

AI agents need a reliable way to communicate. Let's ditch the complex, stateful sessions and build a clean, secure, and asynchronous protocol that lets our agents work together, scale effortlessly, and handle long-running tasks without breaking a sweat.

Ever felt the pain of writing separate code for batch and streaming data? Let's walk through how to build a single, elegant Apache Beam pipeline that handles both, using a hands-on example with windowing and late data.

Hitting that dreaded "out of memory" error with your giant AI model? Don't worry, we've all been there. Let's walk through Tensor Parallelism, a clever way to split your model across multiple GPUs and get training again.

Staring at a stack of GPUs and wondering how to speed up your AI model training? Let's break down the two main ways to do it: Data Parallelism and Distributed Data Parallelism. We'll make it simple, I promise.

Ever feel like your app is trying to do too much at once? Let's walk through how to build a smart, asynchronous task routing system with Python and Kombu, just like the pros do.