Book Image

Edge Computing Patterns for Solution Architects

By : Ashok Iyengar, Joseph Pearson
Book Image

Edge Computing Patterns for Solution Architects

By: Ashok Iyengar, Joseph Pearson

Overview of this book

Enriched with insights from a hyperscaler’s perspective, Edge Computing Patterns for Solution Architects will prepare you for seamless collaboration with communication service providers (CSPs) and device manufacturers and help you in making the pivotal choice between cloud-out and edge-in approaches. This book presents industry-specific use cases that shape tailored edge solutions, addressing non-functional requirements to unlock the potential of standard edge components. As you progress, you’ll navigate the archetypes of edge solution architecture from the basics to network edge and end-to-end configurations. You’ll also discover the weight of data and the power of automation for scale and immerse yourself in the edge mantra of low latency and high bandwidth, absorbing invaluable do's and don'ts from real-world experiences. Recommended practices, honed through practical insights, have also been added to guide you in mastering the dynamic realm of edge computing. By the end of this book, you'll have built a comprehensive understanding of edge concepts and terminology and be ready to traverse the evolving edge computing landscape.
Table of Contents (17 chapters)
Free Chapter
1
Part 1:Overview of Edge Computing as a Problem Space
4
Part 2: Solution Architecture Archetypes in Context
8
Part 3: Related Considerations and Concluding Thoughts

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...