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Microsoft moves cloud intelligence to the network edge

Cloud computing has become a concept that most people in technology recognize and at least partially understand, so it’s no surprise that the cloud is no longer the cutting edge. Instead, the edge is the edge — innovators are moving cloud compute capabilities to devices at the edge of the network so that processing can happen faster. The quintessential use case for mobile edge computing is the autonomous car. Massive compute capabilities will be needed very close to end user devices in order to achieve the low latency processing needed.

The latest innovation in this space comes from Microsoft, which is adding a platform called Azure IoT Edge to its existing IoT gateway. Azure IoT Edge is cross platform runs on both Windows and Linux, since Linux is the operating system used by many IoT developers. Microsoft said Azure IoT can run on devices even smaller than a Raspberry Pi with as little as 128 megabytes of memory.

“IoT edge devices range from small footprint devices (e.g. smaller than a Raspberry Pi) and gateways to industrial machines and autonomous vehicles,” said Microsoft’s Sam George, partner director for Azure IoT, in a blog post. “Instead of simply generating data and sending it to the cloud, these IoT edge devices can process and analyze data to gain insights, and then quickly act on them locally and autonomously.”

George said Azure IoT Edge will give companies more flexibility as they try to assemble developer teams to implement IoT solutions.

“With Azure IoT Edge, developers can use any programming languages including C, Node.js, Java, Microsoft .NET, and Python to build and configure code,” George said. “By using the same programming languages you use in the cloud to build and test your IoT applications and then deploy them to your edge devices, Azure IoT Edge greatly reduces development work required to build and maintain an IoT solution and its backend infrastructure.”

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