Merge pull request #292354 from Padmalathas/UUF-DecemberFixes-Patch

UUF Updates and Fixes

Author: prmerger-automator[bot]

articles/batch/managed-identity-pools.md

@@ -2,8 +2,9 @@
 title: Configure managed identities in Batch pools
 description: Learn how to enable user-assigned managed identities on Batch pools and how to use managed identities within the nodes.
 ms.topic: conceptual
-ms.date: 08/12/2024
+ms.date: 12/23/2024
 ms.devlang: csharp
+ai-usage: ai-assisted
 ms.custom:
 ---
 # Configure managed identities in Batch pools
@@ -13,6 +14,10 @@ complicated identity and credential management by providing an identity for the
 (Azure AD ID). This identity is used to obtain Microsoft Entra tokens to authenticate with target
 resources in Azure.
 
+When adding a User-Assigned Managed Identity to a Batch Pool, it is crucial to set the *Identity* property in your configuration. This property links the managed identity to the pool, enabling it to access Azure resources securely. Incorrect setting of the *Identity* property can result in common errors, such as access issues or upload errors.
+
+For more information on configuring managed identities in Azure Batch, please refer to the [Azure Batch Managed Identities documentation](/troubleshoot/azure/hpc/batch/use-managed-identities-azure-batch-account-pool).
+
 This topic explains how to enable user-assigned managed identities on Batch pools and how to use managed identities within the nodes.
 
 > [!IMPORTANT]
@@ -106,6 +111,23 @@ ArmOperation<BatchAccountPoolResource> armOperation = batchAccount.GetBatchAccou
 BatchAccountPoolResource pool = armOperation.Value;
 ```
 
+> [!NOTE]
+> To include the *Identity* property use the following example code:
+```csharp
+   var pool = batchClient.PoolOperations.CreatePool(
+       poolId: "myPool",
+       virtualMachineSize: "STANDARD_D2_V2",
+       cloudServiceConfiguration: new CloudServiceConfiguration(osFamily: "4"),
+       targetDedicatedNodes: 1,
+       identity: new PoolIdentity(
+           type: PoolIdentityType.UserAssigned,
+           userAssignedIdentities: new Dictionary<string, UserAssignedIdentity>
+           {
+               { "/subscriptions/{subscription-id}/resourceGroups/{resource-group}/providers/Microsoft.ManagedIdentity/userAssignedIdentities/{identity-name}", new UserAssignedIdentity() }
+           }
+       ));
+   ```
+
 ## Use user-assigned managed identities in Batch nodes
 
 Many Azure Batch functions that access other Azure resources directly on the compute nodes, such as Azure Storage or

articles/batch/tutorial-run-python-batch-azure-data-factory.md

@@ -3,7 +3,8 @@ title: 'Tutorial: Run a Batch job through Azure Data Factory'
 description: Learn how to use Batch Explorer, Azure Storage Explorer, and a Python script to run a Batch workload through an Azure Data Factory pipeline.
 ms.devlang: python
 ms.topic: tutorial
-ms.date: 03/01/2024
+ms.date: 12/23/2024
+ai-usage: ai-assisted
 ms.custom: mvc, devx-track-python
 ---
 
@@ -82,8 +83,10 @@ Paste the connection string into the following script, replacing the `<storage-a
 
 ``` python
 # Load libraries
-from azure.storage.blob import BlobClient
+# from azure.storage.blob import BlobClient
+from azure.storage.blob import BlobServiceClient
 import pandas as pd
+import io
 
 # Define parameters
 connectionString = "<storage-account-connection-string>"
@@ -93,8 +96,16 @@ outputBlobName	= "iris_setosa.csv"
 # Establish connection with the blob storage account
 blob = BlobClient.from_connection_string(conn_str=connectionString, container_name=containerName, blob_name=outputBlobName)
 
+# Initialize the BlobServiceClient (This initializes a connection to the Azure Blob Storage, downloads the content of the 'iris.csv' file, and then loads it into a Pandas DataFrame for further processing.)
+blob_service_client = BlobServiceClient.from_connection_string(conn_str=connectionString)
+blob_client = blob_service_client.get_blob_client(container_name=containerName, blob_name=outputBlobName)
+
+# Download the blob content
+blob_data = blob_client.download_blob().readall()
+
 # Load iris dataset from the task node
-df = pd.read_csv("iris.csv")
+# df = pd.read_csv("iris.csv")
+df = pd.read_csv(io.BytesIO(blob_data))
 
 # Take a subset of the records
 df = df[df['Species'] == "setosa"]
@@ -106,6 +117,8 @@ with open(outputBlobName, "rb") as data:
     blob.upload_blob(data, overwrite=True)
 ```
 
+For more information on working with Azure Blob Storage, refer to the [Azure Blob Storage documentation](/azure/storage/blobs/storage-blobs-introduction). 
+
 Run the script locally to test and validate functionality. 
 
 ``` bash