Table of Contents

Introduction to the Data-Driven Edge with Machine Learning

Foundations of Edge Workloads

Building the Edge

Extending the Cloud to the Edge

Ingesting and Streaming Data from the Edge

Processing and Consuming Data on the Cloud

Machine Learning Workloads at the Edge

DevOps and MLOps for the Edge

Fleet Management at Scale

Reviewing the Solution with AWS Well-Architected Framework

About the Author

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.

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