6:00 em - 7:00 em (UTC)

What does it take to turn an AI idea into a real, scalable application without hiding the infrastructure behind a black box? We'll start with an open source GitHub repository and use GitHub Copilot to understand, adapt, and operate a complete AI workload. We deploy Ray and KubeRay on Azure Kubernetes Service (AKS), run LLM batch inference on an NVIDIA GPU, and explore how Azure Linux provides a lightweight, secure container host for the Kubernetes nodes under the hood. Along the way, we'll connect the layers that make the application work using containers, Kubernetes resources, GPU scheduling, and open source operators. We'll also explore autoscaling, network isolation, authentication, metrics, dashboards, and cost-aware management. Leave with a reusable GitHub repo and a clear roadmap for building open source AI systems on Azure.

6:00 em - 7:00 em (UTC)

What does it take to build a cloud-native platform foundation for modern applications and AI workloads? Join us to explore Azure Red Hat OpenShift (ARO) and the role of open-source Kubernetes in your platform strategy. We’ll introduce ARO, explore hosted control planes, and discuss how OpenShift Virtualization brings virtual machines onto a cloud-native platform alongside containerized applications. Along the way, we’ll examine ARO’s security posture and platform considerations for financial services and other highly regulated industries. Leave with a clearer understanding of ARO’s capabilities and how to evaluate it as part of your application modernization and AI infrastructure strategy.

7:00 em - 8:00 em (UTC)

Modern AI applications still rely on databases. They store application data, embeddings, conversation history, and the context that powers retrieval. In this session, we'll explore Azure's open-source database offerings, including PostgreSQL, MySQL, and Azure DocumentDB, and discuss where each fits. We'll then take a deeper look at Azure HorizonDB, Microsoft's cloud-native PostgreSQL-compatible service. Through demos, you'll see how to build AI-powered retrieval workflows with vector search and AI pipelines, while gaining a practical understanding of where different open-source database technologies fit in modern application architectures.

7:00 em - 8:00 em (UTC)

AI on Linux is only part of the story. In this demo-led session, Karl Abbott explores how AI can assist with operating Linux environments on Azure. Join this demo-led session exploring AI-assisted Linux operations on Azure. Follow a real-world workflow as an application is deployed, monitored, intentionally disrupted, and troubleshot with AI assistance. See GitHub Copilot in action and explore how Azure agents can complement the operational toolkit. Leave with practical ideas for bringing AI into day-to-day Linux operations, from deployment and observability to troubleshooting. Resources: https://learn.microsoft.com/en-us/linux/ [eventID:27670]