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articles/machine-learning/how-to-manage-workspace-cli.md

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@@ -22,15 +22,15 @@ In this article, you learn how to create and manage Azure Machine Learning works
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You can also use the following methods to create and manage Azure Machine Learning workspaces:
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- [Azure Machine Learning studio](quickstart-create-resources.md#create-the-workspace)
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- [Azure portal or Python SDK](how-to-manage-workspace.md)
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- [Azure portal](how-to-manage-workspace.md)
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- [Python SDK](how-to-manage-workspace.md)
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- [Azure PowerShell](how-to-manage-workspace-powershell.md)
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- [Visual Studio Code with the Azure Machine Learning extension](how-to-setup-vs-code.md)
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## Prerequisites
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- An Azure subscription with a free or paid version of Azure Machine Learning. If you don't have an Azure subscription, [create a free account before you begin](https://azure.microsoft.com/free/).
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- If you want to run the Azure CLI commands in this article locally, you need [Azure CLI](/cli/azure/install-azure-cli) installed.
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- [Azure CLI](/cli/azure/install-azure-cli) installed, if you want to run the Azure CLI commands in this article locally.
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If you run the Azure CLI commands in [Azure Cloud Shell](https://azure.microsoft.com//features/cloud-shell/), you don't need to install anything. The browser accesses the latest cloud version of Azure CLI and the Azure Machine Learning extension.
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[!INCLUDE [application-insight](includes/machine-learning-application-insight.md)]
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- The Azure Machine Learning workspace uses Azure Container Registry for some operations, and automatically creates a Container Registry instance when it first needs one.
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[!INCLUDE [machine-learning-delete-acr](includes/machine-learning-delete-acr.md)]
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## Connect to your Azure subscription
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If you use Azure Cloud Shell from the Azure portal, you can skip this section. The cloud shell automatically authenticates you using the Azure subscription you're signed in with.
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:::code language="YAML" source="~/azureml-examples-main/cli/resources/workspace/privatelink.yml":::
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After you create the workspace by running `az ml workspace create -g <resource-group-name> --file <configuration-file>.yml`, use the [Azure networking CLI commands](/cli/azure/network/private-endpoint#az-network-private-endpoint-create) to create a private link endpoint for the workspace.
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After you create the workspace by running `az ml workspace create`, use the [Azure networking CLI commands](/cli/azure/network/private-endpoint#az-network-private-endpoint-create) to create a private link endpoint for the workspace.
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```azurecli-interactive
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az network private-endpoint create \
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--zone-name 'privatelink.notebooks.azure.net'
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```
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For more information on using a private endpoint and virtual network with your workspace, see:
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For more information on using a private endpoint and virtual network with your workspace, see the following articles:
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- [Configure a private endpoint for your Azure Machine Learning workspace](how-to-configure-private-link.md).
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- [Private endpoint configuration for your Azure Machine Learning workspace](how-to-configure-private-link.md)
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- [Virtual network isolation and privacy overview](how-to-network-security-overview.md)
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### Resource management private links
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Moving an Azure Machine Learning workspace is currently in preview. For more information, see [Move Azure Machine Learning workspaces between subscriptions (preview)](how-to-move-workspace.md).
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### Delete the Azure container registry
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The Azure Machine Learning workspace uses Azure Container Registry for some operations, and automatically creates a Container Registry instance when it first needs one.
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[!INCLUDE [machine-learning-delete-acr](includes/machine-learning-delete-acr.md)]
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### Delete a workspace
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To delete a workspace after it's no longer needed, use the following command:
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az ml workspace delete -n <workspace-name> -g <resource-group-name>
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```
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The default behavior for Azure Machine Learning is to *soft delete* the workspace. The workspace isn't immediately deleted, but instead is marked for deletion. For more information, see [Soft delete](./concept-soft-delete.md).
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The default behavior for Azure Machine Learning is to *soft-delete* the workspace. The workspace isn't immediately deleted, but instead is marked for deletion. For more information, see [Soft delete](./concept-soft-delete.md).
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[!INCLUDE [machine-learning-delete-workspace](includes/machine-learning-delete-workspace.md)]
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