4:00 PM - 5:30 PM (UTC)

Join us to learn how to effectively deploy an intelligent microservice-based application into Azure Kubernetes Service (AKS) and integrate with Azure OpenAI. We’ll walk through setting up the application environment, deploying Azure OpenAI services and configuring a deployment of an existing model, and integrating that with our application.

4:00 PM - 5:30 PM (UTC)

Today we’ll be migrating our application from using token-based authentication for Azure OpenAI to using Azure Kubernetes Service (AKS) Workload Identity. AKS Workload Identity allows specified workloads to use a Microsoft Entra Id to control access to Azure services like Azure OpenAI, removing the need to manage individual authentication tokens and providing greater visibility into access control for your Azure services.

4:00 PM - 5:30 PM (UTC)

Intelligent Applications on Azure Kubernetes Service (AKS) have similar deployment and operational concerns to other microservice-based applications. In this session, we’ll look at how we can leverage the features of AKS and the AKS and Azure ecosystem to ensure that our intelligent applications can scale effectively, operate resiliently, and offer visibility into the metrics necessary.

4:00 PM - 6:30 PM (UTC)

While our demo applications may have all of our services open to the public internet, in real life, access control is a requirement. We’ll explore using Azure Virtual Networks and private endpoints to restrict access to Azure OpenAI, while ensuring access for our microservices application. Additionally, we’ll look into how we expose our applications in our Azure Kubernetes Service cluster to the internet safely and securely.