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Edge Computing Patterns for Solution Architects

You're reading from   Edge Computing Patterns for Solution Architects Learn methods and principles of resilient distributed application architectures from hybrid cloud to far edge

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781805124061
Length 214 pages
Edition 1st Edition
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Authors (2):
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Ashok Iyengar Ashok Iyengar
Author Profile Icon Ashok Iyengar
Ashok Iyengar
Joseph Pearson Joseph Pearson
Author Profile Icon Joseph Pearson
Joseph Pearson
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Table of Contents (17) Chapters Close

Preface 1. Part 1:Overview of Edge Computing as a Problem Space FREE CHAPTER
2. Chapter 1: Our View of Edge Computing 3. Chapter 2: Edge Architectural Components 4. Part 2: Solution Architecture Archetypes in Context
5. Chapter 3: Core Edge Architecture 6. Chapter 4: Network Edge Architecture 7. Chapter 5: End-to-End Edge Architecture 8. Part 3: Related Considerations and Concluding Thoughts
9. Chapter 6: Data Has Weight and Inertia 10. Chapter 7: Automate to Achieve Scale 11. Chapter 8: Monitoring and Observability 12. Chapter 9: Connect Judiciously but Thoughtlessly 13. Chapter 10: Open Source Software Can Benefit You 14. Chapter 11: Recommendations and Best Practices 15. Index 16. Other Books You May Enjoy

Connectivity and the data plane

In this section, we cover issues related to data at rest and in motion, specifically from the perspective of edge computing, data virtualization and the edge, and transparent progressive failover starting at the edge and moving cloudward. You will learn about various options available to edge computing architectures that will assist in automating data management, placement, and migration capabilities.

Optimizing data availability without connectivity

Part and parcel of manipulating and storing data is the movement of data, which necessarily includes connectivity. But what if that connectivity is not available, is intermittent, or is slow with low throughput and high latency? How can you ensure that all local data is available to all services and applications that can access it even while remote data is not?

One technique to consider is using a data virtualization solution that can access local data in any format and allow SQL-like querying of...

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