This is the code repository for Intelligent Workloads at the Edge, published by Packt.

Deliver cyber-physical outcomes with data and machine learning using AWS IoT Greengrass

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.

This book covers the following exciting features:

• Build an end-to-end IoT solution from the edge to the cloud
• Design and deploy multi-faceted intelligent solutions on the edge
• Process data at the edge through analytics and ML
• Package and optimize models for the edge using Amazon SageMaker
• Implement MLOps and DevOps for operating an edge-based solution
• Onboard and manage fleets of edge devices at scale
• Review edge-based workloads against industry best practices

If you feel this book is for you, get your copy today!

All of the code is organized into folders.

The code will look like the following:

#Feature group name
weather_feature_group_name_offline = 'weather-feature-groupoffline'
+ strftime('%d-%H-%M-%S', gmtime())

Following is what you need for this book: This book is for IoT architects and software engineers responsible for delivering analytical and machine learning–backed software solutions to the edge. AWS customers who want to learn and build IoT solutions will find this book useful. Intermediate-level experience with running Python software on Linux is required to make the most of this book.

With the following software and hardware list you can run all code files present in the book (Chapter 1-10).

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

• Hands-On Edge Analytics with Azure IoT [Packt] [Amazon]

• Developing IoT Projects with ESP32 [Packt] [Amazon]

Indraneel Mitra is a Principal Solutions Architect for IoT at Amazon Web Services. He has 17+ years of IT consulting and architecting experience with start ups and Fortune 500 customers across different industry verticals. He has spoken at different events, including AWS re:Invent, AWS Summits, AWS Webinar and Twitch shows, the RSA cybersecurity conference, the Emerging Technologies for Enterprise (ETE) conference, and local meetups on different topics for many years as a seasoned public speaker. Neel is also the co-author and trainer of the popular IoT course, AWS IoT: Developing and Deploying an Internet of Things, available on Coursera and edX. He holds an M.S. in software engineering from BITS Pilani, India.

Ryan Burke is a Senior Sustainability Application Architect at Amazon Web Services, formerly the Worldwide Technical Leader for IoT. He has worked in information technology since 2006, developing web services, user experiences, and architecting IoT solutions. He has spoken to audiences on IoT topics at events including AWS re:Invent, SxSW, TDWI, and local meetup communities. He holds a B.S. in computer science from the Georgia Institute of Technology, and served 6 years as a communications officer in the U.S. Air Force Reserves. In his free time, Ryan enjoys yoga, coffee snobbery, games of all kinds, and annoying his family with a new smart home project.