Anyscale on Azure is now generally available. Built by the creators of Ray, the most widely adopted AI compute engine, it runs inside your own Azure tenant so your data stays within your existing governance, and it gives teams a production-ready platform to build, train, and serve AI without stitching infrastructure together.In this session, you'll learn:
- What Anyscale on Azure is and where it fits in your AI stack
What Anyscale on Azure is and where it fits in your AI stack
- How it integrates with the Azure services you already use, including Microsoft Entra ID, Azure RBAC, Azure Policy, Azure Monitor, and Microsoft Cost Management
How it integrates with the Azure services you already use, including Microsoft Entra ID, Azure RBAC, Azure Policy, Azure Monitor, and Microsoft Cost Management
- What you need to get started, from your Azure tenant to your first Ray cluster
What you need to get started, from your Azure tenant to your first Ray cluster
- A live demo of building, training, and serving a real AI workload on Anyscale in an Azure environment
A live demo of building, training, and serving a real AI workload on Anyscale in an Azure environment
Whether you're a platform engineer, ML engineer, or architect deciding where to run AI on Azure, you'll leave knowing how Anyscale on Azure works and how to get up and running.
