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

Functional requirements

In Chapter 1, we talked about cloud-out and edge-in paradigms. Cloud-out is where computing is taken out of the data center and brought to the far edges of the network. Conversely, the movement of the generated data from the source or the edge to a location with more computational resources for analysis is the edge-in part. Those facets drive functional requirements in an edge computing solution. We will discuss the common functional requirements of an edge computing solution in the subsequent sections.

Sensing

This is where we still deal with traditional sensors (e.g., IoT/accelerometers, thermometers, or actuators) as architectural components that acquire data and help create a signal. When combining technologies such as edge and artificial intelligence (AI), you introduce new ways of designing and deploying technology, thus improving and automating situational awareness with sense-making systems. These are deployed in stores, shop floors, industrial...