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Copy file name to clipboardExpand all lines: articles/machine-learning/how-to-managed-network.md
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@@ -25,7 +25,7 @@ Azure Machine Learning provides preview support for managed virtual network (VNe
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When you enable managed virtual network isolation, a managed VNet is created for the workspace. Managed compute resources (compute clusters and compute instances) for the workspace automatically use this managed VNet. The managed VNet can use private endpoints for Azure resources that are used by your workspace, such as Azure Storage, Azure Key Vault, and Azure Container Registry.
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The following diagram shows a managed virtual network uses private endpoints to communicate with the storage, key vault, and container registry used by the workspace.
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The following diagram shows how a managed virtual network uses private endpoints to communicate with the storage, key vault, and container registry used by the workspace.
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:::image type="content" source="./media/how-to-managed-network/managed-virtual-network-architecture.png" alt-text="Diagram of managed virtual network isolation.":::
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| Outbound mode | Description | Scenarios |
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| ----- | ----- | ----- |
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| Allow internet outbound | Allow all internet outbound traffic from the managed VNet. | Recommended if you need access to machine learning artifacts on the Internet, such as python packages or pretrained models. |
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| Allow only approved outbound | Outbound traffic is allowed by specifying service tags. | Recommended if you want to minimize the risk of data exfiltration but you need to prepare all required machine learning artifacts in your private locations. |
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| Allow only approved outbound | Outbound traffic is allowed by specifying service tags. | Recommended if you want to minimize the risk of data exfiltration but you will need to prepare all required machine learning artifacts in your private locations. |
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The managed virtual network is preconfigured with [required default rules](#list-of-required-rules). It's also configured for private endpoint connections to your workspace default storage, container registry and key vault if they're configured as private. After choosing the isolation mode, you only need to consider other outbound requirements you may need to add.
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@@ -87,14 +87,21 @@ Before following the steps in this article, make sure you have the following pre
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```python
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from azure.ai.ml import MLClient
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from azure.ai.ml.entities import Workspace, ManagedNetwork
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from azure.ai.ml.constants._workspace import IsolationMode
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from azure.ai.ml.entities import (
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Workspace,
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ManagedNetwork,
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IsolationMode,
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ServiceTagDestination,
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PrivateEndpointDestination
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)
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from azure.identity import DefaultAzureCredential
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from azure.ai.ml.entities import ServiceTagDestination, PrivateEndpointDestination
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# Replace with the values for your Azure subscription and resource group.
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The following example creates a new workspace named `myworkspace`, with an outbound rule named `myrule` that adds a private endpoint for an Azure Blob store:
> These rules are automatically added to the managed VNet.
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__Private Endpoints__:
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* When the isolation mode for the managed network is `Allow only approved outbound`, Private Endpoint outbound rules will be automatically created as required rules from the managed network for the workspace and associated resources that have public network access disabled (Key Vault, Storage Account, Container Registry, Azure ML Workspace).
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__Outbound__ rules:
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* `AzureActiveDirectory`
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* Once you enable managed virtual network isolation of your workspace, you can't disable it.
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* Managed virtual network uses private endpoint connection to access your private resources. You can't have a private endpoint and a service endpoint at the same time for your Azure resources, such as a storage account. We recommend using private endpoints in all scenarios.
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* The managed network will be deleted and cleaned up when the workspace is deleted.
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