During Build! 2017 Microsoft has announced the availability of Azure IoT Edge, which would bring in some of the cloud capabilities to edge devices/networks within your Enterprise. This would enable industrial devices to utilize the capabilities of IoT in Azure within their constrained resources .
With this Microsoft now makes it easier for developers to move some of their computing needs to these devices. Edge devices are mostly having small foot print based to high end machines within your company network.
The essential capabilities to be supported by Azure IoT edge include:
- Perform Edge Analytics (a cut down version of Azure Stream Analytics)- Instead of doing analytics in cloud developer/implementer can move the basic cloud data processing and analytical capabilities to Edge Device. Run your machine learning algorithms in Edge device and take predictive analytics steps.
- Perform Artificial Intelligence processing at edge device itself. Availability of Microsoft Cognitive Service on edge device would bring in whole lot of automation capabilities. Imagine Alexa/Siri working without internet connection, it should be able to provide you reminders etc.
- Perform RealTime Decision making locally based on predefined rules.
- Reduce bandwidth costs
- Connect to other Edge devices and legacy devices within the constrained/corporate network.
- Deploy IoT solutions to Edge Device from Cloud and provide updates as needed.
- Operate offline without the need of real-time internet connectivity or intermittent connectivity. Doesn’t have to rely on Cloud to provide commands for processing, can do offline data capture and processing of information from other devices connected and take decisions without the need to rely on a connected cloud service.
Azure IoT Edge enables seamless deployment of cloud services such as:
- Azure Machine Learning
- Azure Stream Analytics
- Azure Functions
- Artificial Intelligence, including Cognitive Services
- Azure IoT Hub communication and device management features
Along with sharing the image represents Azure’s Enterprise Digital Vision, we will discuss about the same in later sessions:
Getting Started & More information: