Merge pull request #205534 from Blackmist/identity-warning

adding warning per ask from PG

Author: PRMerger13

articles/machine-learning/how-to-identity-based-data-access.md

@@ -192,12 +192,19 @@ This authentication mode allows you to:
 * Set up fine-grained permissions, where different workspace users can have access to different storage accounts or folders within storage accounts.
 * Audit storage access because the storage logs show which identities were used to access data.
 
-> [!WARNING] 
+> [!IMPORTANT] 
 > This functionality has the following limitations
 > * Feature is only supported for experiments submitted via the [Azure Machine Learning CLI](how-to-configure-cli.md)
 > * Only CommandJobs, and PipelineJobs with CommandSteps and AutoMLSteps are supported 
 > * User identity and compute managed identity cannot be used for authentication within same job.
 
+> [!WARNING]
+> This feature is __public preview__ and is __not secure for production workloads__. Ensure that only trusted users have permissions to access your workspace and storage accounts.
+>
+> Preview features are provided without a service-level agreement, and are not recommended for production workloads. Certain features might not be supported or might have constrained capabilities. 
+>
+> For more information, see [Supplemental Terms of Use for Microsoft Azure Previews](https://azure.microsoft.com/support/legal/preview-supplemental-terms/).
+
 The following steps outline how to set up identity-based data access for training jobs on compute clusters. 
 
 1. Grant the user identity access to storage resources. For example,  grant StorageBlobReader access to the specific storage account you want to use or grant ACL-based permission to specific folders or files in Azure Data Lake Gen 2 storage.

articles/machine-learning/v1/how-to-identity-based-data-access.md

@@ -211,12 +211,19 @@ This authentication mode allows you to:
 * Set up fine-grained permissions, where different workspace users can have access to different storage accounts or folders within storage accounts.
 * Audit storage access because the storage logs show which identities were used to access data.
 
-> [!WARNING] 
+> [!IMPORTANT] 
 > This functionality has the following limitations
 > * Feature is only supported for experiments submitted via the [Azure Machine Learning CLI](../how-to-configure-cli.md)
 > * Only CommandJobs, and PipelineJobs with CommandSteps and AutoMLSteps are supported 
 > * User identity and compute managed identity cannot be used for authentication within same job.
 
+> [!WARNING]
+> This feature is __public preview__ and is __not secure for production workloads__. Ensure that only trusted users have permissions to access your workspace and storage accounts.
+>
+> Preview features are provided without a service-level agreement, and are not recommended for production workloads. Certain features might not be supported or might have constrained capabilities. 
+>
+> For more information, see [Supplemental Terms of Use for Microsoft Azure Previews](https://azure.microsoft.com/support/legal/preview-supplemental-terms/).
+
 The following steps outline how to set up identity-based data access for training jobs on compute clusters. 
 
 1. Grant the user identity access to storage resources. For example,  grant StorageBlobReader access to the specific storage account you want to use or grant ACL-based permission to specific folders or files in Azure Data Lake Gen 2 storage.