Anyscale on Azure: Scale Python AI workloads with managed Ray on AKS

From Azure Friday by Scott Hanselman

June 2, 2026

About this episode

Scott Hanselman discusses scaling Python AI workloads on Azure with Omar Shorbaji from Anyscale.

Scott Hanselman talks with Omar Shorbaji from the Anyscale engineering team about how Anyscale on Azure scales Python AI workloads from a single notebook to thousands of CPUs and GPUs. Built on Ray, the most widely adopted AI compute engine, Anyscale gives you a unified runtime to build, train, and serve, running directly on Azure Kubernetes Service without the complexity of managing Kubernetes. See a live demo that fine-tunes a vision-language-action robotics policy, with the metrics you need to push GPU utilization higher. Chapters 00:00 - Introduction 00:52 - Ray and the Anyscale platform 03:11 - Start of demo: Workspaces 04:38 - Running a job and viewing utilization metrics 05:24 - Choosing the right scale 06:53 - Abstracting Kubernetes on AKS 08:53 - Wrap up and where to learn more Recommended resources Learn Docs Anyscale on Azure Connect Scott Hanselman | Twitter/X: @SHanselman Anyscale | Twitter/X: @anyscalecompute Azure Friday | Twitter/X: @AzureFriday Azure | Twitter/X: @Azure

People in this episode

Host: Scott Hanselman

Guest: Omar Shorbaji

Topics covered

  • Python AI workloads
  • Anyscale
  • Ray
  • Azure Kubernetes Service
  • GPU utilization
  • Robotics policy

Keywords

  • Anyscale
  • Azure
  • Ray
  • AI workloads
  • Kubernetes
  • GPU utilization
  • demo
  • robotics

Mentioned in this episode

Organizations: Anyscale, Azure Kubernetes Service, Ray, Azure, Anyscale on Azure, Azure Friday

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