Azure IoT Edge is an Internet of Things (IoT) service that builds on top of Azure IoT Hub. This service is meant for organizations who want to analyze data on devices “on the edge” vs “in the cloud”. Edge computing centers around moving code that usually runs in the cloud to a local device or its proximity. This is achieved through gateway devices that serve as a link between IoT enabled devices/equipment and the cloud.
“In the cloud” allows you to do remote monitoring and manage your machines, devices, and your factory and merge data incoming from multiple IoT devices. You also benefit from infinite computing storage and can leverage machine learning algorithms and other artificial intelligence tools.
The reason you want to use “on the edge” is to benefit from low latency tight control loops that require near real-time response. You also benefit from translating protocols, connecting devices that normally wouldn’t be able to access the internet. Since you’d be on the edge, you are on your own property and can guarantee the data is staying there – thus benefitting from privacy of data and protection of IP.
By moving parts of your workload to the edge, your devices can spend less time sending messages to the cloud and react more quickly to changes in status.
The most promising edge computing platform
Amazon and Microsoft are the only public clouds that have a defined edge computing strategy. But which of these has got the “edge” as the most promising edge computing platform? In our opinion – Azure IoT Edge – and here’s why:
In April 2018, Microsoft announced that it will be investing over $5billion in IoT technology. Their goal is simple: to give every customer the ability to transform their business and the world with connected solutions. Microsoft plans to continue research and development and both customers and partners can expect new programs, products, resources and offerings to gain an intelligent edge. Azure IoT edge can:
Simplify development: IoT Edge supports OS, for example, Windows and Linux, and various languages, like Node.js, C, Java, .NET Core 2.0, and Python, so you can code in a language you know and apply existing business logic without starting from zero.
Operate offline and react in near-time: The edge devices still work safely and independently even with a low latency or irregular connection to the cloud. The device administrator updates the most recent devices to ensure consistent operations.
Open sourcing platform: IoT Edge is accessible as an open source venture on Github. Customers are gaining confidence and trust since adaptability allows them to modify their deployments.
Security: An expansion of the Azure IoT platform that leverages the advantages of services like Device Provisioning Service to provision thousands of devices safely. The security core protecting the IoT Edge device has a built in security manager that protects all its components by abstracting the secure silicon hardware.
Artificial Intelligence (AI): It is easy to run machine learning algorithms at the edge. Each model can be packaged and delivered as a standard model. Customer teams can teach their models on Azure and since each model is just a container, new models can be deployed rapidly to the edge.
The Azure IoT Edge release is Microsoft’s first phase in their new edge computing strategy. It is also a pinnacle in their vision for systems of intelligence, the next generation of enterprise applications.
Learn more how industries are leveraging IoT & Machine Learning to gain a truly competitive edge and uncover untapped sources of data here or visit our blogs to learn more about AI, the Cloud, IIoT and more.