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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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Toc

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

Cloud-out versus edge-in

Another common way of describing an architecture is based on its foundation and assumptions, and in what direction and manner it grows as its scope and responsibilities increase. If it starts out based in the cloud, using cloud-native best practices, and then later adds on capabilities that allow it to run in some fashion on the edge, that approach is described as cloud-out. On the other hand, if it starts out on the edge using edge-native development best practices, and then bursts to (hybrid) cloud infrastructure, that would be termed edge-in. Let’s look at each in turn, go over an example, and discuss their relative strengths and weaknesses.

Looking deeper at cloud-out architectures

Cloud-out architectures begin with the cloud; that is, with global compute infrastructure using cloud-native development best practices. While Chapter 11 will discuss these practices in depth, let’s list an abbreviated version to frame the discussion:

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