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Intelligent Workloads at the Edge

You're reading from   Intelligent Workloads at the Edge Deliver cyber-physical outcomes with data and machine learning using AWS IoT Greengrass

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801811781
Length 374 pages
Edition 1st Edition
Tools
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Authors (2):
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Ryan Burke Ryan Burke
Author Profile Icon Ryan Burke
Ryan Burke
Indraneel (Neel) Mitra Indraneel (Neel) Mitra
Author Profile Icon Indraneel (Neel) Mitra
Indraneel (Neel) Mitra
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Introduction and Prerequisites
2. Chapter 1: Introduction to the Data-Driven Edge with Machine Learning FREE CHAPTER 3. Section 2: Building Blocks
4. Chapter 2: Foundations of Edge Workloads 5. Chapter 3: Building the Edge 6. Chapter 4: Extending the Cloud to the Edge 7. Chapter 5: Ingesting and Streaming Data from the Edge 8. Chapter 6: Processing and Consuming Data on the Cloud 9. Chapter 7: Machine Learning Workloads at the Edge 10. Section 3: Scaling It Up
11. Chapter 8: DevOps and MLOps for the Edge 12. Chapter 9: Fleet Management at Scale 13. Section 4: Bring It All Together
14. Chapter 10: Reviewing the Solution with AWS Well-Architected Framework 15. Other Books You May Enjoy Appendix 1 – Answer Key

Chapter 2: Foundations of Edge Workloads

This chapter will explore the next level of detail regarding edge workloads and your first hands-on activity. You will learn how AWS IoT Greengrass meets the needs for designing and delivering modern edge ML solutions. You will learn how to prepare your edge device to work with AWS by deploying a tool that checks your device for compatible requirements. Additionally, you will learn how to install the IoT Greengrass core software and deploy your first IoT Greengrass core device. You will learn about the structure of components, examine the fundamental unit of software in IoT Greengrass, and write your first edge workload component.

By the end of this chapter, you should start to feel comfortable with the basics of IoT Greengrass and its local development life cycle.

In this chapter, we are going to cover the following main topics:

  • The anatomy of an edge ML solution
  • IoT Greengrass for the win
  • Checking compatibility with...
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