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describe networking controls
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articles/machine-learning/concept-customer-managed-keys.md

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@@ -51,7 +51,7 @@ In addition to customer-managed keys, Azure Machine Learning also provides a [hb
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## How and what workspace metadata is stored
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When you bring your own encryption key, service metadata will be stored on dedicated resources in your Azure subscription. Microsoft creates a seperate resource group in your subscription for this named *"azureml-rg-workspacename_GUID"*. Resource in this managed resource group can only be modified by Microsoft. Additional networking controls are configured when you create a private link endpoint on your workspace.
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When you bring your own encryption key, service metadata will be stored on dedicated resources in your Azure subscription. Microsoft creates a seperate resource group in your subscription for this named *"azureml-rg-workspacename_GUID"*. Resource in this managed resource group can only be modified by Microsoft.
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The following resources are created and store metadata for your workspace:
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Your Azure Machine Learning workspace reads and writes data using its managed identity. This identity is granted access to the resources using a role assignment (Azure role-based access control) on the data resources. The encryption key you provide is used to encrypt data that is stored on Microsoft-managed resources. It's also used to create indices for Azure AI Search, which are created at runtime.
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Additional networking controls are configured when you create a private link endpoint on your workspace to allow for inbound connectivity. In this configuration, a private link endpoint connection will be created to the CosmosDB instance and network access will be restricted to only trusted Microsoft services.
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## Customer-managed keys
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When you __don't use a customer-managed key__, Microsoft creates and manages these resources in a Microsoft owned Azure subscription and uses a Microsoft-managed key to encrypt the data.

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