Merge pull request #82108 from huguesBouvier/patch-1

Change default port from 8000 to 443

Author: ktoliver

articles/iot-edge/tutorial-nested-iot-edge.md

@@ -83,9 +83,8 @@ To create a hierarchy of IoT Edge devices, you will need:
 
    ![The virtual machine will output a JSON upon creation, which contains its SSH handle](./media/tutorial-nested-iot-edge/virtual-machine-outputs.png)
 
-* Make sure that the following ports are open inbound for all devices except the lowest layer device: 8000, 443, 5671, 8883:
-  * 8000: Used to pull Docker container images through the API proxy.
-  * 443: Used between parent and child edge hubs for REST API calls.
+* Make sure that the following ports are open inbound for all devices except the lowest layer device: 443, 5671, 8883:
+  * 443: Used between parent and child edge hubs for REST API calls and to pull docker container images.
   * 5671, 8883: Used for AMQP and MQTT.
 
   For more information, see [how to open ports to a virtual machine with the Azure portal](../virtual-machines/windows/nsg-quickstart-portal.md).
@@ -231,7 +230,7 @@ Run the configuration and connectivity checks on your devices. For the **top lay
 For the **lower layer device**, the diagnostics image needs to be manually passed in the command:
 
    ```bash
-   sudo iotedge check --diagnostics-image-name <parent_device_fqdn_or_ip>:8000/azureiotedge-diagnostics:1.2
+   sudo iotedge check --diagnostics-image-name <parent_device_fqdn_or_ip>:443/azureiotedge-diagnostics:1.2
    ```
 
 On your **top layer device**, expect to see an output with several passing evaluations. You may see some warnings about logs policies and, depending on your network, DNS policies.
@@ -255,9 +254,9 @@ In the [Azure Cloud Shell](https://shell.azure.com/), you can take a look at the
 
 In addition the runtime modules **IoT Edge Agent** and **IoT Edge Hub**, the **top layer device** receives the **Docker registry** module and **IoT Edge API Proxy** module.
 
-The **Docker registry** module points to an existing Azure Container Registry. In this case, `REGISTRY_PROXY_REMOTEURL` points to the Microsoft Container Registry. In the `createOptions`, you can see it communicates on port 5000.
+The **Docker registry** module points to an existing Azure Container Registry. In this case, `REGISTRY_PROXY_REMOTEURL` points to the Microsoft Container Registry. By default, **Docker registry** listens on port 5000.
 
-The **IoT Edge API Proxy** module routes HTTP requests to other modules, allowing lower layer devices to pull container images or push blobs to storage. In this tutorial, it communicates on port 8000 and is configured to send Docker container image pull requests route to your **Docker registry** module on port 5000. Also, any blob storage upload requests route to module AzureBlobStorageonIoTEdge on port 11002. For more information about the **IoT Edge API Proxy** module and how to configure it, see the module's [how-to guide](how-to-configure-api-proxy-module.md).
+The **IoT Edge API Proxy** module routes HTTP requests to other modules, allowing lower layer devices to pull container images or push blobs to storage. In this tutorial, it communicates on port 443 and is configured to send Docker container image pull requests route to your **Docker registry** module on port 5000. Also, any blob storage upload requests route to module AzureBlobStorageonIoTEdge on port 11002. For more information about the **IoT Edge API Proxy** module and how to configure it, see the module's [how-to guide](how-to-configure-api-proxy-module.md).
 
 If you'd like a look at how to create a deployment like this through the Azure portal or Azure Cloud Shell, see [top layer device section of the how-to guide](how-to-connect-downstream-iot-edge-device.md#deploy-modules-to-top-layer-devices).
 
@@ -267,7 +266,7 @@ In the [Azure Cloud Shell](https://shell.azure.com/), you can take a look at the
    cat ~/nestedIotEdgeTutorial/iotedge_config_cli_release/templates/tutorial/deploymentLowerLayer.json
    ```
 
-You can see under `systemModules` that the **lower layer device's** runtime modules are set to pull from `$upstream:8000`, instead of `mcr.microsoft.com`, as the **top layer device** did. The **lower layer device** sends Docker image requests the **IoT Edge API Proxy** module on port 8000, as it cannot directly pull the images from the cloud. The other module deployed to the **lower layer device**, the **Simulated Temperature Sensor** module, also makes its image request to `$upstream:8000`.
+You can see under `systemModules` that the **lower layer device's** runtime modules are set to pull from `$upstream:443`, instead of `mcr.microsoft.com`, as the **top layer device** did. The **lower layer device** sends Docker image requests the **IoT Edge API Proxy** module on port 443, as it cannot directly pull the images from the cloud. The other module deployed to the **lower layer device**, the **Simulated Temperature Sensor** module, also makes its image request to `$upstream:443`.
 
 If you'd like a look at how to create a deployment like this through the Azure portal or Azure Cloud Shell, see [lower layer device section of the how-to guide](how-to-connect-downstream-iot-edge-device.md#deploy-modules-to-lower-layer-devices).
 
@@ -301,10 +300,8 @@ You can run `iotedge check` in a nested hierarchy, even if the child machines do
 
 When you run `iotedge check` from the lower layer, the program tries to pull the image from the parent through port 443.
 
-In this tutorial, we use port 8000, so we need to specify it:
-
 ```bash
-sudo iotedge check --diagnostics-image-name $upstream:8000/azureiotedge-diagnostics:1.2
+sudo iotedge check --diagnostics-image-name $upstream:443/azureiotedge-diagnostics:1.2
 ```
 
 The `azureiotedge-diagnostics` value is pulled from the container registry that's linked with the registry module. This tutorial has it set by default to https://mcr.microsoft.com:
@@ -336,4 +333,4 @@ To learn more about using gateways to create hierarchical layers of IoT Edge dev
 To see how Azure IoT Edge can create more solutions for your business, continue on to the other tutorials.
 
 > [!div class="nextstepaction"]
-> [Deploy an Azure Machine Learning model as a module](tutorial-deploy-machine-learning.md)
+> [Deploy an Azure Machine Learning model as a module](tutorial-deploy-machine-learning.md)