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articles/ai-studio/how-to/configure-managed-network.md

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@@ -145,6 +145,7 @@ Before following the steps in this article, make sure you have the following pre
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* Using FQDN outbound rules increases the cost of the managed virtual network because FQDN rules use Azure Firewall. For more information, see [Pricing](#pricing).
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* FQDN outbound rules only support ports 80 and 443.
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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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* If your managed network is configured to __allow only approved outbound__, you cannot use an FQDN rule to access Azure Storage Accounts. You must use a private endpoint instead.
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## Configure a managed virtual network to allow internet outbound
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articles/machine-learning/how-to-managed-network.md

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* When using Managed Vnet, you can't deploy compute resources inside your custom Vnet. Compute resources can only be created inside the managed Vnet.
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* Managed network isolation cannot establish a private connection from the managed virtual network to a user's on-premises resources.
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For the list of supported private connections, see [Private Endpoints](/azure/machine-learning/how-to-managed-network?view=azureml-api-2&tabs=azure-cli&preserve-view=true#private-endpoints).
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* If your managed network is configured to __allow only approved outbound__, you cannot use an FQDN rule to access Azure Storage Accounts. You must use a private endpoint instead.
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### Migration of compute resources
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