Merge pull request #211174 from Blackmist/sdk-include

Include files for v2 prereqs

Author: v-regandowner

articles/machine-learning/how-to-deploy-custom-container.md

@@ -34,35 +34,12 @@ Custom container deployments can use web servers other than the default Python F
 
 ## Prerequisites
 
-* You must have an Azure resource group, in which you (or the service principal you use) need to have `Contributor` access. You'll have such a resource group if you configured your ML extension per the above article. 
+[!INCLUDE [cli & sdk](../../includes/machine-learning-cli-sdk-v2-prereqs.md)]
 
-* You must have an Azure Machine Learning workspace. You'll have such a workspace if you configured your ML extension per the above article.
+* You, or the service principal you use, must have `Contributor` access to the Azure Resource Group that contains your workspace. You'll have such a resource group if you configured your workspace using the quickstart article.
 
 * To deploy locally, you must have [Docker engine](https://docs.docker.com/engine/install/) running locally. This step is **highly recommended**. It will help you debug issues.
 
-# [Azure CLI](#tab/cli)
-
-* Install and configure the Azure CLI and ML extension. For more information, see [Install, set up, and use the CLI (v2)](how-to-configure-cli.md). 
-
-* If you've not already set the defaults for Azure CLI, you should save your default settings. To avoid having to repeatedly pass in the values, run:
-
-   ```azurecli
-   az account set --subscription <subscription id>
-   az configure --defaults workspace=<azureml workspace name> group=<resource group>
-   ```
-
-# [Python SDK](#tab/python)
-
-* If you haven't installed Python SDK v2, please install with this command:
-
-  ```azurecli
-  pip install --pre azure-ai-ml
-  ```
-
-  For more information, see [Install the Azure Machine Learning SDK v2 for Python](/python/api/overview/azure/ml/installv2).
-
----
-
 ## Download source code
 
 To follow along with this tutorial, download the source code below.

articles/machine-learning/how-to-deploy-managed-online-endpoint-sdk-v2.md

@@ -26,10 +26,8 @@ In this article, you learn how to deploy your machine learning model to managed
 
 ## Prerequisites
 
-* If you don't have an Azure subscription, create a free account before you begin. Try the [free or paid version of Azure Machine Learning](https://azure.microsoft.com/free/) today.
-* The [Azure Machine Learning SDK v2 for Python](/python/api/overview/azure/ml/installv2).
-* You must have an Azure resource group, and you (or the service principal you use) must have Contributor access to it.
-* You must have an Azure Machine Learning workspace.
+[!INCLUDE [sdk](../../includes/machine-learning-sdk-v2-prereqs.md)]
+
 * To deploy locally, you must install [Docker Engine](https://docs.docker.com/engine/) on your local computer. We highly recommend this option, so it's easier to debug issues.
 
 ### Clone examples repository

articles/machine-learning/tutorial-create-secure-workspace.md

@@ -436,7 +436,7 @@ For more information on creating a compute cluster and compute cluster, includin
 When Azure Container Registry is behind the virtual network, Azure Machine Learning can't use it to directly build Docker images (used for training and deployment). Instead, configure the workspace to use the compute cluster you created earlier. Use the following steps to create a compute cluster and configure the workspace to use it to build images:
 
 1. Navigate to [https://shell.azure.com/](https://shell.azure.com/) to open the Azure Cloud Shell.
-1. From the Cloud Shell, use the following command to install the 1.0 CLI for Azure Machine Learning:
+1. From the Cloud Shell, use the following command to install the 2.0 CLI for Azure Machine Learning:
 
     ```azurecli-interactive
     az extension add -n ml

includes/machine-learning-cli-prereqs.md

@@ -2,17 +2,17 @@
 author: blackmist
 ms.service: machine-learning
 ms.topic: include
-ms.date: 10/26/2021
+ms.date: 09/14/2022
 ms.author: larryfr
 ---
 
 Before following the steps in this article, make sure you have the following prerequisites:
 
 * An Azure subscription. If you don't have an Azure subscription, create a free account before you begin. Try the [free or paid version of Azure Machine Learning](https://azure.microsoft.com/free/).
 
-* The [Azure CLI](/cli/azure/) and the `ml` extension to the Azure CLI. For more information, see [Install, set up, and use the CLI (v2) (preview)](../articles/machine-learning/how-to-configure-cli.md).
+* The [Azure CLI](/cli/azure/) and the `ml` extension to the Azure CLI. For more information, see [Install, set up, and use the CLI (v2)](../articles/machine-learning/how-to-configure-cli.md).
 
     > [!IMPORTANT]
     > The CLI examples in this article assume that you are using the Bash (or compatible) shell. For example, from a Linux system or [Windows Subsystem for Linux](/windows/wsl/about). 
  
-* An Azure Machine Learning workspace. If you don't have one, use the steps in the [Install, set up, and use the CLI (v2) (preview)](../articles/machine-learning/how-to-configure-cli.md) to create one.
+* An Azure Machine Learning workspace. If you don't have one, use the steps in the [Install, set up, and use the CLI (v2)](../articles/machine-learning/how-to-configure-cli.md) to create one.

includes/machine-learning-cli-sdk-v2-prereqs.md

@@ -0,0 +1,26 @@
+---
+author: blackmist
+ms.service: machine-learning
+ms.topic: include
+ms.date: 09/14/2022
+ms.author: larryfr
+---
+
+Before following the steps in this article, make sure you have the following prerequisites:
+
+* An Azure subscription. If you don't have an Azure subscription, create a free account before you begin. Try the [free or paid version of Azure Machine Learning](https://azure.microsoft.com/free/).
+
+* An Azure Machine Learning workspace. If you don't have one, use the steps in the [Quickstart: Create workspace resources](../articles/machine-learning/quickstart-create-resources.md) article to create one.
+
+* The [Azure CLI](/cli/azure/) and the `ml` extension to the Azure CLI. For more information, see [Install, set up, and use the CLI (v2)](../articles/machine-learning/how-to-configure-cli.md).
+
+    > [!IMPORTANT]
+    > The CLI examples in this article assume that you are using the Bash (or compatible) shell. For example, from a Linux system or [Windows Subsystem for Linux](/windows/wsl/about). 
+
+* To install the Python SDK v2 (preview), use the following command:
+
+    ```bash
+    pip install --pre azure-ai-ml
+    ```
+
+    For more information, see [Install the Python SDK v2 for Azure Machine Learning](https://aka.ms/sdk-v2-install) (preview).

includes/machine-learning-sdk-v2-prereqs.md

@@ -0,0 +1,21 @@
+---
+author: blackmist
+ms.service: machine-learning
+ms.topic: include
+ms.date: 09/14/2022
+ms.author: larryfr
+---
+
+Before following the steps in this article, make sure you have the following prerequisites:
+
+* An Azure subscription. If you don't have an Azure subscription, create a free account before you begin. Try the [free or paid version of Azure Machine Learning](https://azure.microsoft.com/free/).
+
+* An Azure Machine Learning workspace. If you don't have one, use the steps in the [Quickstart: Create workspace resources](../articles/machine-learning/quickstart-create-resources.md) article to create one.
+
+* To install the Python SDK v2, use the following command:
+
+    ```bash
+    pip install --pre azure-ai-ml
+    ```
+
+    For more information, see [Install the Python SDK v2 for Azure Machine Learning](https://aka.ms/sdk-v2-install) (preview).