Azure IoT Edge brings smarts to devices at the cloud’s edge

Devices on the edge of internet should be able to act on their own, and connect only when needed. That’s what Azure IoT Edge enables

Azure IoT Edge brings smarts to devices at the cloud’s edge

It can be hard to pin down a definition of edge computing. Some companies look at it in terms of networks, others in terms of datacenters. For Microsoft, it’s a distributed cloud that encompasses every computer, no matter how small and how limited.

Microsoft CEO Satya Nadella uses the term “intelligent edge,” in which container-based machine learning models are deployed where needed along with your own code and Azure features like stream analytics and serverless Azure Functions.

That vision is the foundation of Azure IoT Edge, which has now been released as a public beta, and expands Microsoft’s Azure IoT Suite.

Although there are some ready-to-use machine learning models in Azure IoT Edge, Microsoft is avoiding an overly prescriptive approach. No two IoT deployments are the same, even in similar industries, and predefined solutions would quickly become lowest common denominators, reducing their effectiveness.

Where to download Azure IoT Edge

Most of the code you’ll need is in GitHub, especially the tools needed to take Azure Machine Learning models and deploy them onto devices.

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