Merge pull request #47977 from kgremban/aug1-tutorials

PRMerger19 · web-flow · commit 7378922a6823 · 2018-08-01T14:52:47.000-07:00
Review Edge tutorials for MVC standards
diff --git a/articles/iot-edge/quickstart-linux.md b/articles/iot-edge/quickstart-linux.md
@@ -41,37 +41,32 @@ Add the Azure IoT extension to the cloud shell instance.
    ```azurecli-interactive
    az extension add --name azure-cli-iot-ext
    ```
-
+   
 ## Prerequisites
 
-This quickstart uses a Linux machine as an IoT Edge device. If you don't have one available for testing, you can create one using the Azure CLI. 
+Cloud resources: 
 
-Create a new resource group. You can use this resource group for the other Azure resources that you create in this quickstart, for easy management.  
+* A resource group to manage all the resources you use in this quickstart. 
 
    ```azurecli-interactive
    az group create --name IoTEdgeResources --location westus
    ```
 
-Create the virtual machine. You don't need a very large virtual machine to test IoT Edge. A size like **B1ms** is sufficient.
+* A Linux virtual machine to act as your IoT Edge device. 
 
    ```azurecli-interactive
    az vm create --resource-group IoTEdgeResources --name EdgeVM --image Canonical:UbuntuServer:16.04-LTS:latest --admin-username azureuser --generate-ssh-keys --size Standard_B1ms
    ```
 
 ## Create an IoT hub
 
-Start the quickstart by creating your IoT Hub in the Azure portal.
+Start the quickstart by creating your IoT Hub with Azure CLI. 
+
 ![Create IoT Hub][3]
 
 The free level of IoT Hub works for this quickstart. If you've used IoT Hub in the past and already have a free hub created, you can use that IoT hub. Each subscription can only have one free IoT hub. 
 
-1. In the Azure cloud shell, create a resource group if you didn't as part of the prerequisites. By putting all the resources for the quickstarts and tutorials in a group, you can manage them together. 
-
-   ```azurecli-interactive
-   az group create --name IoTEdgeResources --location westus
-   ```
-
-1. Create an IoT hub in your new resource group. The following code creates a free **F1** hub in the resource group **IoTEdgeResources**. Replace *{hub_name}* with a unique name for your IoT hub.
+The following code creates a free **F1** hub in the resource group **IoTEdgeResources**. Replace *{hub_name}* with a unique name for your IoT hub.
 
    ```azurecli-interactive
    az iot hub create --resource-group IoTEdgeResources --name {hub_name} --sku F1 
diff --git a/articles/iot-edge/quickstart.experimental.md b/articles/iot-edge/quickstart.experimental.md
@@ -177,8 +177,14 @@ Configure the runtime with your IoT Edge device connection string that you copie
      workload_uri: "http://<GATEWAY_ADDRESS>:15581"
    ```
 
-8. Find the **Moby Container Runtime settings** section and verify that the value for **network** is set to `nat`.
+8. Find the **Moby Container Runtime settings** section and verify that the value for **network** is uncommented and set to **azure-iot-edge**
 
+   ```yaml
+   moby_runtime:
+     docker_uri: "npipe://./pipe/docker_engine"
+     network: "azure-iot-edge"
+   ```
+   
 9. Save the configuration file. 
 
 10. In PowerShell, restart the IoT Edge service.
diff --git a/articles/iot-edge/quickstart.md b/articles/iot-edge/quickstart.md
@@ -34,18 +34,6 @@ The module that you deploy in this quickstart is a simulated sensor that generat
 
 If you don't have an active Azure subscription, create a [free account][lnk-account] before you begin.
 
-## Prerequisites
-
-This quickstart turns your Windows computer or virtual machine into an IoT Edge device. If you're running Windows in a virtual machine, enable [nested virtualization][lnk-nested] and allocate at least 2GB memory. 
-
-Have the following prerequisites ready on the machine that you're using for an IoT Edge device:
-
-1. Make sure you're using a supported Windows version:
-   * Windows 10 or newer
-   * Windows Server 2016 or newer
-2. Install [Docker for Windows][lnk-docker] and make sure it's running.
-3. Configure Docker to use [Linux containers](https://docs.docker.com/docker-for-windows/#switch-between-windows-and-linux-containers)
-
 [!INCLUDE [cloud-shell-try-it.md](../../includes/cloud-shell-try-it.md)]
 
 You use the Azure CLI to complete many of the steps in this quickstart, and Azure IoT has an extension to enable additional functionality. 
@@ -56,25 +44,41 @@ Add the Azure IoT extension to the cloud shell instance.
    az extension add --name azure-cli-iot-ext
    ```
 
-## Create an IoT hub
+## Prerequisites
 
-Start the quickstart by creating your IoT Hub in the Azure portal.
-![Create IoT Hub][3]
+Cloud resources: 
 
-The free level of IoT Hub works for this quickstart. If you've used IoT Hub in the past and already have a free hub created, you can use that IoT hub. Each subscription can only have one free IoT hub. 
-
-1. In the Azure cloud shell, create a resource group. The following code creates a resource group called **IoTEdgeResources** in the **West US** region. By putting all the resources for the quickstarts and tutorials in a group, you can manage them together. 
+* A resource group to manage all the resources you use in this quickstart. 
 
    ```azurecli-interactive
    az group create --name IoTEdgeResources --location westus
    ```
 
-1. Create an IoT hub in your new resource group. The following code creates a free **F1** hub in the resource group **IoTEdgeResources**. Replace *{hub_name}* with a unique name for your IoT hub.
+A Windows computer or virtual machine to act as your IoT Edge device: 
+
+* Use a supported Windows version:
+   * Windows 10 or newer
+   * Windows Server 2016 or newer
+* If it's a virtual machine, enable [nested virtualization][lnk-nested] and allocate at least 2GB memory. 
+* Install [Docker for Windows][lnk-docker] and make sure it's running.
+* Configure Docker to use [Linux containers](https://docs.docker.com/docker-for-windows/#switch-between-windows-and-linux-containers)
+
+## Create an IoT hub
+
+Start the quickstart by creating your IoT Hub with Azure CLI. 
+
+![Create IoT Hub][3]
+
+The free level of IoT Hub works for this quickstart. If you've used IoT Hub in the past and already have a free hub created, you can use that IoT hub. Each subscription can only have one free IoT hub. 
+
+The following code creates a free **F1** hub in the resource group **IoTEdgeResources**. Replace *{hub_name}* with a unique name for your IoT hub.
 
    ```azurecli-interactive
    az iot hub create --resource-group IoTEdgeResources --name {hub_name} --sku F1 
    ```
 
+   If you get an error because there's already one free hub in your subscription, change the SKU to **S1**. 
+
 ## Register an IoT Edge device
 
 Register an IoT Edge device with your newly created IoT Hub.
@@ -204,7 +208,13 @@ Configure the runtime with your IoT Edge device connection string that you copie
      workload_uri: "http://<GATEWAY_ADDRESS>:15581"
    ```
 
-8. Find the **Moby Container Runtime settings** section and verify that the value for **network** is set to `nat`.
+8. Find the **Moby Container Runtime settings** section and verify that the value for **network** is uncommented and set to **azure-iot-edge**
+
+   ```yaml
+   moby_runtime:
+     docker_uri: "npipe://./pipe/docker_engine"
+     network: "azure-iot-edge"
+   ```
 
 9. Save the configuration file. 
 
diff --git a/articles/iot-edge/tutorial-c-module.md b/articles/iot-edge/tutorial-c-module.md
@@ -16,28 +16,36 @@ ms.custom: mvc
 
 # Tutorial: Develop a C IoT Edge module and deploy to your simulated device
 
-You can use IoT Edge modules to deploy code that implements your business logic directly to your IoT Edge devices. This tutorial walks you through creating and deploying an IoT Edge module that filters sensor data. You'll use the simulated IoT Edge device that you created in the Deploy Azure IoT Edge on a simulated device in [Windows][lnk-tutorial1-win] or [Linux][lnk-tutorial1-lin] tutorials. In this tutorial, you learn how to:    
+You can use IoT Edge modules to deploy code that implements your business logic directly to your IoT Edge devices. This tutorial walks you through creating and deploying an IoT Edge module that filters sensor data. In this tutorial, you learn how to:    
 
 > [!div class="checklist"]
 > * Use Visual Studio Code to create an IoT Edge module in C
-> * Use Visual Studio Code and Docker to create a docker image and publish it to your registry 
+> * Use Visual Studio Code and Docker to create a docker image and publish it to a container registry 
 > * Deploy the module to your IoT Edge device
 > * View generated data
 
 
 The IoT Edge module that you create in this tutorial filters the temperature data generated by your device. It only sends messages upstream if the temperature is above a specified threshold. This type of analysis at the edge is useful for reducing the amount of data communicated to and stored in the cloud. 
 
-If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free) before you begin.
+[!INCLUDE [quickstarts-free-trial-note](../../includes/quickstarts-free-trial-note.md)]
 
 
 ## Prerequisites
 
-* The Azure IoT Edge device that you created in the quickstart for [Linux](quickstart-linux.md) or [Windows devices](quickstart.md).
-* The primary key connection string for the IoT Edge device.  
+An Azure IoT Edge device:
+
+* You can use your development machine or a virtual machine as an Edge device by following the steps in the quickstart for [Linux](quickstart-linux.md) or [Windows devices](quickstart.md).
+
+Cloud resources:
+
+* A standard-tier [IoT Hub](../iot-hub/iot-hub-create-through-portal.md) in Azure. 
+
+Development resources:
+
 * [Visual Studio Code](https://code.visualstudio.com/). 
 * [C/C++ extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode.cpptools) for Visual Studio Code.
 * [Azure IoT Edge extension](https://marketplace.visualstudio.com/items?itemName=vsciot-vscode.azure-iot-edge) for Visual Studio Code.
-* [Docker CE](https://docs.docker.com/install/) on your development machine. 
+* [Docker CE](https://docs.docker.com/install/). 
 
 
 ## Create a container registry
diff --git a/articles/iot-edge/tutorial-csharp-module.md b/articles/iot-edge/tutorial-csharp-module.md
@@ -27,18 +27,26 @@ You can use Azure IoT Edge modules to deploy code that implements your business
 
 The IoT Edge module that you create in this tutorial filters the temperature data that's generated by your device. It only sends messages upstream if the temperature is above a specified threshold. This type of analysis at the edge is useful for reducing the amount of data that's communicated to and stored in the cloud. 
 
-If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free) before you begin.
+[!INCLUDE [quickstarts-free-trial-note](../../includes/quickstarts-free-trial-note.md)]
 
 
 ## Prerequisites
 
-* The Azure IoT Edge device that you created in the quickstart for [Linux](quickstart-linux.md) or [Windows devices](quickstart.md).
-* The primary key connection string for the IoT Edge device.  
+An Azure IoT Edge device:
+
+* You can use your development machine or a virtual machine as an Edge device by following the steps in the quickstart for [Linux](quickstart-linux.md) or [Windows devices](quickstart.md).
+
+Cloud resources:
+
+* A standard-tier [IoT Hub](../iot-hub/iot-hub-create-through-portal.md) in Azure. 
+
+Development resources:
+
 * [Visual Studio Code](https://code.visualstudio.com/). 
 * [C# for Visual Studio Code (powered by OmniSharp) extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode.csharp).
 * [Azure IoT Edge extension](https://marketplace.visualstudio.com/items?itemName=vsciot-vscode.azure-iot-edge) for Visual Studio Code. 
 * [.NET Core 2.1 SDK](https://www.microsoft.com/net/download).
-* [Docker CE](https://docs.docker.com/install/) on your development machine. 
+* [Docker CE](https://docs.docker.com/install/)
 
 
 ## Create a container registry
diff --git a/articles/iot-edge/tutorial-deploy-function.md b/articles/iot-edge/tutorial-deploy-function.md
@@ -1,6 +1,6 @@
 ---
 title: Deploy Azure functions with Azure IoT Edge | Microsoft Docs 
-description: Deploy an Azure function as a module to an edge device.
+description: In this tutorial, you deploy an Azure function as a module to an edge device.
 author: kgremban
 manager: timlt
 ms.author: kgremban
@@ -31,14 +31,21 @@ The Azure function that you create in this tutorial filters the temperature data
 
 ## Prerequisites
 
-To test the function module that you build in this tutorial, you need an IoT Edge device. You can use the device that you configured in the [Linux](quickstart-linux.md) or [Windows](quickstart.md) quickstart.
+An Azure IoT Edge device:
+
+* You can use your development machine or a virtual machine as an Edge device by following the steps in the quickstart for [Linux](quickstart-linux.md) or [Windows devices](quickstart.md).
+
+Cloud resources:
+
+* A standard-tier [IoT Hub](../iot-hub/iot-hub-create-through-portal.md) in Azure. 
+
+Development resources:
 
-You must have the following prerequisites on your development machine: 
 * [Visual Studio Code](https://code.visualstudio.com/). 
 * [C# for Visual Studio Code (powered by OmniSharp) extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode.csharp).
 * [Azure IoT Edge extension](https://marketplace.visualstudio.com/items?itemName=vsciot-vscode.azure-iot-edge) for Visual Studio Code. 
 * [The .NET Core 2.1 SDK](https://www.microsoft.com/net/download).
-* [Docker CE](https://docs.docker.com/install/) on your development machine. 
+* [Docker CE](https://docs.docker.com/install/). 
 
 ## Create a container registry
 In this tutorial, you use the Azure IoT Edge extension for VS Code to build a module and create a **container image** from the files. Then you push this image to a **registry** that stores and manages your images. Finally, you deploy your image from your registry to run on your IoT Edge device.  
diff --git a/articles/iot-edge/tutorial-deploy-machine-learning.md b/articles/iot-edge/tutorial-deploy-machine-learning.md
@@ -1,6 +1,6 @@
 ---
 title: Deploy Azure Machine Learning with Azure IoT Edge | Microsoft Docs
-description: Deploy Azure Machine Learning as a module to an edge device
+description: In this tutorial, you deploy Azure Machine Learning as a module to an edge device
 author: kgremban
 manager: timlt
 ms.author: kgremban
@@ -11,7 +11,7 @@ services: iot-edge
 ms.custom: mvc
 ---
 
-# Deploy Azure Machine Learning as an IoT Edge module - preview
+# Tutorial: Deploy Azure Machine Learning as an IoT Edge module (preview)
 
 You can use IoT Edge modules to deploy code that implements your business logic directly to your IoT Edge devices. This tutorial walks you through deploying an Azure Machine Learning module that predicts when a device fails based on simulated machine temperature data. For more information about Azure ML on IoT Edge, see [Azure Machine Learning documentation](../machine-learning/desktop-workbench/use-azure-iot-edge-ai-toolkit.md).
 
@@ -28,15 +28,23 @@ In this tutorial, you learn how to:
 >[!NOTE]
 >Azure Machine Learning modules on Azure IoT Edge are in public preview. 
 
+[!INCLUDE [quickstarts-free-trial-note](../../includes/quickstarts-free-trial-note.md)]
+
+
 ## Prerequisites
 
-To test the Machine Learning module that you build in this tutorial, you need an IoT Edge device. You can use the device that you configured in the quickstart for [Linux](quickstart-linux.md) or [Windows devices](quickstart.md). 
+An Azure IoT Edge device:
+
+* You can use your development machine or a virtual machine as an Edge device by following the steps in the quickstart for [Linux](quickstart-linux.md) or [Windows devices](quickstart.md).
+* The Azure Machine Learning module does not support ARM processors.
+
+Cloud resources:
 
-The Azure Machine Learning module does not support ARM processors.
+* A standard-tier [IoT Hub](../iot-hub/iot-hub-create-through-portal.md) in Azure. 
 
-Have the following prerequisites on your development machine: 
+Development resources:
 * An Azure Machine Learning account. Follow the instructions in [Create Azure Machine Learning accounts and install Azure Machine Learning Workbench](../machine-learning/service/quickstart-installation.md#create-azure-machine-learning-services-accounts). You do not need to install the workbench application for this tutorial. 
-* Model Management for Azure ML on your machine. To set up your environment and create an account, follow the instructions in [Model management setup](../machine-learning/desktop-workbench/deployment-setup-configuration.md). During deployment setup, it is recommended to choose the local steps instead of cluster, where possible.
+* Model Management for Azure ML. To set up your environment and create an account, follow the instructions in [Model management setup](../machine-learning/desktop-workbench/deployment-setup-configuration.md). During deployment setup, it is recommended to choose the local steps instead of cluster, where possible.
 
 ### Disable process identification
 
diff --git a/articles/iot-edge/tutorial-deploy-stream-analytics.md b/articles/iot-edge/tutorial-deploy-stream-analytics.md
@@ -1,6 +1,6 @@
 ---
 title: Tutorial - Deploy ASA jobs to Azure IoT Edge devices | Microsoft Docs 
-description: Deploy Azure Stream Analytics as a module to an Iot Edge device
+description: In this tutorial, you deploy Azure Stream Analytics as a module to an Iot Edge device
 author: kgremban
 manager: timlt
 ms.author: kgremban
@@ -11,7 +11,7 @@ services: iot-edge
 ms.custom: mvc
 ---
 
-# Tutorial: Deploy Azure Stream Analytics as an IoT Edge module - preview
+# Tutorial: Deploy Azure Stream Analytics as an IoT Edge module (preview)
 
 Many IoT solutions use analytics services to gain insight about data as it arrives in the cloud from the IoT devices. With Azure IoT Edge, you can take [Azure Stream Analytics][azure-stream] logic and move it onto the device itself. By processing telemetry streams at the edge, you can reduce the amount of uploaded data and reduce the time it takes to react to actionable insights.
 
@@ -31,10 +31,19 @@ In this tutorial, you learn how to:
 >[!NOTE]
 >Azure Stream Analytics modules for IoT Edge are in [public preview](https://azure.microsoft.com/support/legal/preview-supplemental-terms/).
 
+[!INCLUDE [quickstarts-free-trial-note](../../includes/quickstarts-free-trial-note.md)]
+
 ## Prerequisites
 
-* An IoT hub
-* The IoT Edge device that you created and configured in the quickstart for [Windows][lnk-quickstart-win] or [Linux][lnk-quickstart-lin]. 
+An Azure IoT Edge device:
+
+* You can use your development machine or a virtual machine as an Edge device by following the steps in the quickstart for [Linux](quickstart-linux.md) or [Windows devices](quickstart.md).
+* The Azure Machine Learning module does not support ARM processors.
+
+Cloud resources:
+
+* A standard-tier [IoT Hub](../iot-hub/iot-hub-create-through-portal.md) in Azure. 
+
 
 ## Create an Azure Stream Analytics job
 
diff --git a/articles/iot-edge/tutorial-node-module.md b/articles/iot-edge/tutorial-node-module.md
diff --git a/articles/iot-edge/tutorial-python-module.md b/articles/iot-edge/tutorial-python-module.md
