MISC-TN-005: Running AWS Greengrass Core on SBCSPG

Info Box Applies to SBCSPG

This technical note was validated against specific versions of hardware and software. It may not work with other versions.

History

Version	Date	Notes
1.0.0	August 2019	First public release

Introduction

In these days, we are witnessing the cloud war. Almost every week, the top three cloud providers⁠—Amazon, Microsoft, and Google⁠—add new services and new functionalities.

Technically speaking, it is hard to determine which platform is the best. Although basic services are similar, each platoform has different peculiarities that make it more or less suitable for a specific application.

In principle, DAVE Embedded Systems' products are designed to be cloud-agnostic in order to let the users the freedom to choose the cloud platform they think best fits their needs.

This Technical Note, for instance, shows how to interface the SBCSPG Industrial IoT gateway to Amazon Web Services (AWS). Specifically, it shows how to configure and run the AWS Greengrass Core (GGC) on the device. According to AWS website, AWS IoT Greengrass is

software that lets you run local compute, messaging, data caching, sync, and ML inference capabilities on connected devices in a secure way. With AWS IoT Greengrass, connected devices can run AWS Lambda functions, execute predictions based on machine learning models, keep device data in sync, and communicate with other devices securely – even when not connected to the Internet.

AWS IoT Greengrass seamlessly extends AWS to devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. With AWS IoT Greengrass, you can use familiar languages and programming models to create your device software in the cloud, and then deploy it to your devices. AWS IoT Greengrass can be programmed to filter device data and only transmit necessary information back to the cloud.

In other words, GGC allows you to implement edge computing functionalities easily and quickly by deploying them on the edge device through the AWS platform.

Cloud and Edge computing in a typical IIoT scenario (image source: [1])

It is worth remembering that edge computing means a distributed computing paradigm which brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth, according to Wikipedia. Within the processing power limits of the edge device, moving such computations to the edge is an effective way to optimize costs. When the Internet connection is intermittent or poor, it can be even mandatory to meet system's requirements.