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Install Azure IoT Edge - Windows | Microsoft Docs
Install the Azure IoT Edge runtime on a simulated device in Windows and deploy your first module
iot-edge
kgremban
timlt
kgremban
elioda
10/05/2017
article
iot-edge

Deploy Azure IoT Edge on a simulated device in Windows - Public preview

Azure IoT Edge moves the power of the cloud to your Internet of Things (IoT) devices. This tutorial walks you through creating a simulated IoT Edge device that generates sensor data. You learn how to:

[!div class="checklist"]

  • Create an IoT hub
  • Register an IoT Edge device
  • Start the IoT Edge runtime
  • Deploy a module
  • View generated data

The simulated device that you create in this tutorial is a monitor on a wind turbine that generates temperature, humidity, and pressure data. You're interested in this data because your turbines perform at different levels of efficiency depending on the weather conditions. The other Azure IoT Edge tutorials build upon the work you do here by deploying modules that analyze the data for business insights.

Prerequisites

This tutorial assumes that you're using a computer or virtual machine running Windows to simulate an Internet of Things device.

Tip

If you're running Windows in a virtual machine, enable nested virtualization and allocate at least 2GB memory.

  1. Make sure you're using a supported Windows version:

    • Windows 10
    • Windows Server

  2. Install Docker for Windows and make sure it's running.

  3. Install Python 2.7 on Windows and make sure you can use the pip command.

  4. Run the following command to download the IoT Edge control script.

    pip install -U azure-iot-edge-runtime-ctl

Note

Azure IoT Edge can run either Windows containers or Linux containers. If you want to use Windows containers, you have to satisfy these alternative prerequisites:

  1. Make sure you're using a supported Windows version:

    • Windows IoT Core (Build 16299) on a x64-based device
    • Windows 10 Fall Creators Update
    • Windows Server 1709 (Build 16299)

  2. Run the following command in an Admin PowerShell console to install and configure the prerequisites:

    Invoke-Expression (Invoke-WebRequest -useb https://aka.ms/iotedgewin)

    This script provides the following:

    • Docker, configured to use Windows containers. If you already have Docker on your machine, go through the steps to switch to Windows containers.
    • Python 3.6
    • The IoT Edge control script (iotedgectl.exe)

Create an IoT hub

[!INCLUDE iot-hub-create-hub]

Register an IoT Edge device

[!INCLUDE iot-edge-register-device]

Configure the IoT Edge runtime

The IoT Edge runtime is deployed on all IoT Edge devices. It comprises two modules. First, the IoT Edge agent facilitates deployment and monitoring of modules on the IoT Edge device. Second, the IoT Edge hub manages communications between modules on the IoT Edge device, and between the device and IoT Hub.

Use the following steps to install and start the IoT Edge runtime:

  1. Configure the runtime with your IoT Edge device connection string from the previous section.

    iotedgectl setup --connection-string "{device connection string}" --auto-cert-gen-force-no-passwords

  2. Start the runtime.

    iotedgectl start

  3. Check Docker to see that the IoT Edge agent is running as a module.

    docker ps

Deploy a module

[!INCLUDE iot-edge-deploy-module]

View generated data

You can monitor your new IoT Edge device's status by clicking on it in IoT Edge Explorer page of your IoT hub.

You can view the telemetry the device is sending by using the IoT Hub explorer tool.

Next steps

In this tutorial, you created a new IoT Edge device and used the Azure IoT Edge cloud interface to deploy code onto the device. Now, you have a simulated device generating raw data about its environment.

This tutorial is the prerequisite for all of the other IoT Edge tutorials. You can continue on to any of the other tutorials to learn how Azure IoT Edge can help you turn this data into business insights at the edge.

[!div class="nextstepaction"] Deploy your own code as a module Deploy Azure Stream Analytics as a module