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

Business outcomes

Thus far we talked about the various technology-related measurements and metrics. Those become important because they directly or indirectly affect business outcomes. The common business drivers that enterprises focus on are as follows:

  • Customer experience: Maintaining an optimally operating system improves customer experience. If the system is not performing well, it eventually affects the customer and adversely affects customer satisfaction.
  • Regulatory compliance: Whether it is via traceability, audit logging, or security-related metrics, observability helps with meeting regulatory requirements. Through constant observance, the system must help maintain security and privacy standards.
  • Risk mitigation: Continuous and automated observability can aid in identifying potential risks early and taking proactive mitigation measures. This would reduce the impacts of such risks, which could be expensive.