Book Image

Intelligent Workloads at the Edge

By : Indraneel Mitra, Ryan Burke
Book Image

Intelligent Workloads at the Edge

By: Indraneel Mitra, Ryan Burke

Overview of this book

The Internet of Things (IoT) has transformed how people think about and interact with the world. The ubiquitous deployment of sensors around us makes it possible to study the world at any level of accuracy and enable data-driven decision-making anywhere. Data analytics and machine learning (ML) powered by elastic cloud computing have accelerated our ability to understand and analyze the huge amount of data generated by IoT. Now, edge computing has brought information technologies closer to the data source to lower latency and reduce costs. This book will teach you how to combine the technologies of edge computing, data analytics, and ML to deliver next-generation cyber-physical outcomes. You’ll begin by discovering how to create software applications that run on edge devices with AWS IoT Greengrass. As you advance, you’ll learn how to process and stream IoT data from the edge to the cloud and use it to train ML models using Amazon SageMaker. The book also shows you how to train these models and run them at the edge for optimized performance, cost savings, and data compliance. By the end of this IoT book, you’ll be able to scope your own IoT workloads, bring the power of ML to the edge, and operate those workloads in a production setting.
Table of Contents (17 chapters)
1
Section 1: Introduction and Prerequisites
3
Section 2: Building Blocks
10
Section 3: Scaling It Up
13
Section 4: Bring It All Together

Creating your first edge component

The most basic milestone of any developer education is the Hello, world example. For your first edge component deployed to IoT Greengrass, you will create a simple Hello, world application in order to reinforce concepts such as component definition, a dependency graph, and how to create a new deployment.

Reviewing an existing component

Before you get started with drafting a new component, take a moment to familiarize yourself with the existing components that have already been deployed by using the IoT Greengrass CLI. This CLI was installed by the --deploy-dev-tools true argument that was passed in during the installation. This tool is designed to help you with a local development loop; however, as a best practice, it is not installed in production solutions. It is installed at /greengrass/v2/bin/greengrass-cli. The following steps demonstrate how to use this tool:

  1. Try invoking the help command. In the Terminal app of your edge device...