Chapter 4: Extending the Cloud to the Edge

In the material leading up to this chapter, all of the development steps were performed on your device locally. Local development is useful for learning the tools and rapid prototyping but isn't representative of how you would typically operate a production device. In this chapter, you will treat your hub device as if it were actually deployed in the field and learn how to remotely interact with it using the cloud as a deployment engine.

Instead of authoring components on the device, you will learn how to use Amazon Web Services (AWS) IoT Greengrass to synchronize cloud resources, such as code, files, and machine learning (ML) models, to the edge and update devices via deployments. The tools, patterns, and skills you will learn in this chapter are important to your goals of extending the cloud to the edge and practicing how to manage an edge ML solution. You will connect a new client device to your hub device and learn how to bridge...