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Real-World Edge Computing

Real-World Edge Computing

By : Robert High, Sanjeev Gupta
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Real-World Edge Computing

Real-World Edge Computing

By: Robert High, Sanjeev Gupta

Overview of this book

Edge computing holds vast potential to revolutionize industries, yet its implementation poses unique challenges. Written by industry veterans Rob High and Sanjeev Gupta, this comprehensive guide bridges the gap between theory and practice. Distilling expertise from their combined decades of experience in edge computing and hybrid cloud mesh solutions, this book equips software developers and DevOps teams with the knowledge and skills needed to deploy edge solutions at scale in production environments. It also explores foundational standards and introduces key factors that may impede the scaling of edge solutions. While edge computing draws from the successes of cloud computing, crucial distinctions separate the two. High and Gupta elucidate these distinctions, helping you grasp the nuanced dynamics of edge-computing ecosystems. With a focus on leveraging Open Horizon to overcome pitfalls and optimize performance, this book will help you confidently navigate the intricacies of constructing and deploying resilient edge solutions in real-world production settings. By the end of this book, you’ll have acquired a deep understanding of essential success factors for building and deploying robust edge solutions in real-world production settings, leveraging Open Horizon for scalable edge deployments.
Table of Contents (24 chapters)
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1
Part 1: Managing the Edge
7
Part 2: Working on the Edge
13
Part 3: Advancing the Edge System
17
Part 4: Edge Management in Practice

Deploying a Service to consume a published model

As mentioned before, ML models are typically large files and can take several minutes to get delivered to the target Edge nodes asynchronously, depending upon the network bandwidth. In this example, we will use a small text file with easily readable text content to show the delivery of the file to the target service. This simple exercise will help us practice different commands and examine the model delivery process.

In this exercise, we will use a new service-mms example service. This example is a variation of helloMMS to practice MMS foundational concepts. This knowledge will be useful in the complete ML-based object detection application described in Chapter 14.

This standalone service-mms service, in addition to handling MMS functions, also exposes an endpoint that can be queried by another service to retrieve the model file delivered by MMS. The service-mms service also marks or deletes the newly delivered model file so that...

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