Add Intelligence to Serverless with AI on Azure

What you'll learn

Serverless is more popular than ever. Many organizations have either augmented their applications with serverless components, or have built entire solutions based on serverless, owing to cost savings and a higher level of abstraction over infrastructure that speeds development and reduces operational overhead. Microservices have been used for years as a way to break up monolithic applications to smaller components that can have separate deployment and scaling requirements, providing greater flexibility for how applications are built and maintained. Artificial Intelligence enables organizations to innovate by using machines to help gain insights on their data and making predictions. In this session, we discuss how all three of these concepts work together to rapidly create and host intelligent solutions at scale. We first cover the basics of building serverless microservices in Azure, then the array of AI options we can use to layer machine learning as a component of the solution. To help you follow along, we will be showing a working serverless microservices solution that will be modified to add in some AI components. By the end of the session with Joel Hulen, you will see how combining AI with serverless opens up many opportunities to make your applications even more awesome, in a way that will scale with (hopefully increased) demand.

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