In the past few years, there has been a shift away from monolithic architecture (with for example its large centralized deployments) to microservice architectures with small independent deployments, allowing much more flexibility and agile delivery. Traditionally virtual machines and containers were the main options for deploying microservices but they involve a lot of operational effort, configuration, and maintenance. More recently, there has been a growing interest in Serverless computing due to the increase in developer productivity, built in auto-scaling abilities, and reduced operational costs. In combining both microservices and serverless computing, organizations will benefit from having the servers and capacity planning managed by the cloud provider, making them much easier to deploy and run at scale. In this course we show you how to build an end-to-end serverless application for your organization. We have selected a data API use case that could reduce costs and give you more flexibility in how you and your clients consume or present your application, metrics and insight data. We make use of the latest serverless deployment and build framework, share our experience on testing, and provide best practices for running a serverless stack in a production environment. All the resource files are added to the GitHub repository at https://github.com/packtpublishing/building-a-scalable-serverless-microservice-rest-data-api-