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

Automating service delivery

The goal of service delivery is to reduce the number of steps required to deliver a service. This is true in IT as well as in edge computing. Whether it is a simple application or a machine learning (ML) model to be deployed on edge devices quickly and securely, automating those steps is what teams strive for. Doing so helps eliminate configuration errors and scale such solutions.

Physical installation of devices is not something that the OT can automate, but the configuration of the devices and deployment of applications that run on those devices can be automated. If a large bank that has over 10,000 ATMs across the country wants to apply an update to its ATMs, it cannot afford to send personnel to every ATM. Rather, the update is done remotely either through command-line scripts or a DevOps toolchain. Another good example is damage detection sensors on wind turbine blades monitored by edge nodes located on top of the wind turbines.

DevOps

Collaboration...