Hosting AI models with Ray and GKE: why, how and what for?

Abstract

Have you ever wondered how Kubernetes can make deploying AI models easier? Or why has Ray become the go-to tool for scaling AI across clusters? In this talk, we’ll dig into the how, why, and what of running AI models on Google Kubernetes Engine (GKE) with Ray, perfect for devs, DevOps, and anyone pumped about AI and ML.

We’ll start from scratch, breaking down why Kubernetes is such a game-changer for AI, how Ray solves tough distributed processing challenges, and even how to set up ML pipelines that flow from CI to CT—all on Kubernetes. Plus, we’ll bring it all to life with a live demo, hosting a stable diffusion model right before your eyes!

If you want to level up your AI model deployment, this session is your roadmap.