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Copy file name to clipboardExpand all lines: articles/ai-studio/how-to/configure-managed-network.md
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@@ -24,7 +24,6 @@ We have two network isolation aspects. One is the network isolation to access an
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You need to configure following network isolation configurations.
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- Choose network isolation mode. You have two options: allow internet outbound mode or allow only approved outbound mode.
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- Create private endpoint outbound rules to your private Azure resources. Private Azure AI Search isn't supported yet.
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- If you use Visual Studio Code integration with allow only approved outbound mode, create FQDN outbound rules described in the [use Visual Studio Code](#scenario-use-visual-studio-code) section.
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- If you use HuggingFace models in Models with allow only approved outbound mode, create FQDN outbound rules described in the [use HuggingFace models](#scenario-use-huggingface-models) section.
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- If you use one of the open-source models with allow only approved outbound mode, create FQDN outbound rules described in the [curated by Azure AI](#scenario-curated-by-azure-ai) section.
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<sup>1</sup> You can use outbound rules with _allow only approved outbound_ mode to achieve the same result as using allow internet outbound. The differences are:
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* Always use private endpoints to access Azure resources.
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> [!IMPORTANT]
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> While you can create a private endpoint for Azure AI Search, the connected services must allow public networking. For more information, see [Connectivity to other services](#connectivity-to-other-services).
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* You must add rules for each outbound connection you need to allow.
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* Adding FQDN outbound rules __increase your costs__ as this rule type uses Azure Firewall. If you use outbound FQDN rules, charges for Azure Firewall are included in your billing. For more information, see [Pricing](#pricing).
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* The default rules for _allow only approved outbound_ are designed to minimize the risk of data exfiltration. Any outbound rules you add might increase your risk.
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*FQDN outbound rules only support ports 80and443.
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* When using a compute instance with a managed network, use the `az ml compute connect-ssh` command to connect to the compute using SSH.
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### Connectivity to other services
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* Azure AI Search should be public with your provisioned private Azure AI Studio hub.
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* The "Add your data" feature in the Azure AI Studio playground doesn't support using a virtual network or private endpoint on the following resources:
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* Azure AI Search
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* Azure OpenAI
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* Storage resource
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## Configure a managed virtual network to allow internet outbound
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> [!TIP]
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### Scenario: Curated by Azure AI
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These models involve dynamic installation of dependencies at runtime, andreequire outbound _FQDN_ rules to allow traffic to the following hosts:
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These models involve dynamic installation of dependencies at runtime, andrequire outbound _FQDN_ rules to allow traffic to the following hosts:
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*.anaconda.org
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*.anaconda.com
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* Azure Storage (all sub resource types)
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> [!IMPORTANT]
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> While you can create a private endpoint for Azure AI services and Azure AI Search, the connected services must allow public networking. For more information, see [Connectivity to other services](#connectivity-to-other-services).
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When you create a private endpoint, you provide the _resource type_ and _subresource_ that the endpoint connects to. Some resources have multiple types and subresources. For more information, see [what is a private endpoint](/azure/private-link/private-endpoint-overview).
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When you create a private endpoint for hub dependency resources, such as Azure Storage, Azure Container Registry, and Azure Key Vault, the resource can be in a different Azure subscription. However, the resource must be in the same tenant as the hub.
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