Book Image

Intelligent Workloads at the Edge

By : Indraneel Mitra, Ryan Burke
Book Image

Intelligent Workloads at the Edge

By: Indraneel Mitra, Ryan Burke

Overview of this book

The Internet of Things (IoT) has transformed how people think about and interact with the world. The ubiquitous deployment of sensors around us makes it possible to study the world at any level of accuracy and enable data-driven decision-making anywhere. Data analytics and machine learning (ML) powered by elastic cloud computing have accelerated our ability to understand and analyze the huge amount of data generated by IoT. Now, edge computing has brought information technologies closer to the data source to lower latency and reduce costs. This book will teach you how to combine the technologies of edge computing, data analytics, and ML to deliver next-generation cyber-physical outcomes. You’ll begin by discovering how to create software applications that run on edge devices with AWS IoT Greengrass. As you advance, you’ll learn how to process and stream IoT data from the edge to the cloud and use it to train ML models using Amazon SageMaker. The book also shows you how to train these models and run them at the edge for optimized performance, cost savings, and data compliance. By the end of this IoT book, you’ll be able to scope your own IoT workloads, bring the power of ML to the edge, and operate those workloads in a production setting.
Table of Contents (17 chapters)
1
Section 1: Introduction and Prerequisites
3
Section 2: Building Blocks
10
Section 3: Scaling It Up
13
Section 4: Bring It All Together

Defining data models for IoT workloads

According to the IDC, the sum of the world's data will grow from 33 zettabytes (ZB) in 2018 to 175 ZB by 2025. Additionally, the IDC estimates that there will be 41.6 billion connected IoT devices or things, generating 79.4 ZB of data in 2025 (https://www.datanami.com/2018/11/27/global-datasphere-to-hit-175-zettabytes-by-2025-idc-says/). Additionally, many other sources reiterate that data and information are the currency, the lifeblood, and even the new oil of the information industry.

Therefore, the data-driven economy is here to stay and the Internet of Things (IoT) will act as the enabler to ingest data from a huge number of devices (or endpoints), such as sensors and actuators, and generate aggregated insights for achieving business outcomes. Thus, as an IoT practitioner, you should be comfortable with the basic concepts of data modeling and how that enables data management on the edge.

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