InfoQ - WebAssembly https://www.infoq.com InfoQ WebAssembly feed Podcast: Distributed LLM Inference on Kubernetes with llm-d, Wasm, & TornadoVM https://www.infoq.com/podcasts/distributed-llm-inference-kubernetes/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=WebAssembly <img src="https://res.infoq.com/podcasts/distributed-llm-inference-kubernetes/en/smallimage/infoq-podcast-500-1793797932006.jpg"/><p>In this episode, Edoardo Vacchi discusses the evolving landscape of WebAssembly on the backend, running Java workloads on GPUs using TornadoVM, and optimizing distributed AI inference using llm-d and vLLM on Kubernetes. Edoardo explains how llm-d manages cache locality (KV and prefix caches), request routing, and batch inference across Kubernetes clusters to maximize expensive GPU utilization.</p> <i>By Edoardo Vacchi</i> Java WebAssembly TornadoVM The InfoQ Podcast Artificial Intelligence Kubernetes Large language models AI, ML & Data Engineering podcast Mon, 09 Nov 2026 11:00:00 GMT https://www.infoq.com/podcasts/distributed-llm-inference-kubernetes/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=WebAssembly Edoardo Vacchi 2026-11-09T11:00:00Z /podcasts/distributed-llm-inference-kubernetes/en