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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 4

  1. Static resources are those that don't change across deployments to multiple devices and don't change after deployment. For example, code artifacts are a static resource that should not be altered after deployment or altered per device in a single deployment. Dynamic resources are fetched at deployment, install, or runtime, and may be different each time they are fetched or locally altered after fetching. For example, the customer-specific configuration for a smart home device is a dynamic resource that would be fetched and vary from device to device.
  2. IoT Greengrass component artifacts are stored in Amazon Simple Storage Service (Amazon S3) for reference in recipe files.
  3. You cannot modify an artifact stored in the cloud after it has been registered in a component. This would break the computed digest and flag to IoT Greengrass that the artifact is not safe to use.
  4. You can't write over artifact files after deployment since these are considered...
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