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Intelligent Workloads at the Edge

Intelligent Workloads at the Edge

By : Indraneel (Neel) Mitra, Ryan Burke
4.8 (17)
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Intelligent Workloads at the Edge

Intelligent Workloads at the Edge

4.8 (17)
By: Indraneel (Neel) 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)
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1
Section 1: Introduction and Prerequisites
3
Section 2: Building Blocks
10
Section 3: Scaling It Up
13
Section 4: Bring It All Together

Checking compatibility with IoT Device Tester

IoT Device Tester (IDT) is a software client provided by AWS to assess device readiness for use in AWS IoT solutions. It assists developers by running a series of qualification tests to validate whether the destination system is ready to run the IoT Greengrass core software. Additionally, it runs a series of tests to prove that edge capabilities are already present, such as establishing MQTT connections to AWS and running ML models locally. IDT works for one device you are testing locally or scales up to run customized test suites against any number of device groups, so long as they are accessible over the network.

In the context of your role as the IoT architect at Home Base Solutions, you should use IDT to prove that your target edge device platform (in this case, platform refers to hardware and software) is capable of running the runtime orchestration tool of choice, IoT Greengrass. This pattern of using tools to prove compatibility...

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