Merge pull request #259772 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)

Author: Taojunshen

articles/ai-services/speech-service/batch-transcription.md

@@ -36,7 +36,7 @@ To use the batch transcription REST API:
 1. [Get batch transcription results](batch-transcription-get.md) - Check transcription status and retrieve transcription results asynchronously. 
 
 > [!IMPORTANT]
-> Batch transcription jobs are scheduled on a best-effort basis. At pick hours it may take up to 30 minutes or longer for a transcription job to start processing. See how to check the current status of a batch transcription job in [this section](batch-transcription-get.md#get-transcription-status).
+> Batch transcription jobs are scheduled on a best-effort basis. At peak hours it may take up to 30 minutes or longer for a transcription job to start processing. See how to check the current status of a batch transcription job in [this section](batch-transcription-get.md#get-transcription-status).
 
 ## Next steps
 

articles/aks/azure-cni-overlay.md

@@ -169,7 +169,7 @@ The `--pod-cidr` parameter is required when upgrading from legacy CNI because th
 
 [!INCLUDE [preview features callout](includes/preview/preview-callout.md)]
 
-You must register the `Microsoft.ContainerService` `AzureOverlayDualStackPreview` feature flag.
+You must have the latest aks-preview Azure CLI extension installed and register the `Microsoft.ContainerService` `AzureOverlayDualStackPreview` feature flag.
 
 Update an existing Kubenet cluster to use Azure CNI Overlay using the [`az aks update`][az-aks-update] command.
 

articles/cosmos-db/analytical-store-change-data-capture.md

@@ -29,7 +29,7 @@ In addition to providing incremental data feed from analytical store to diverse
 - Supports applying filters, projections and transformations on the Change feed via source query
 - Multiple change feeds on the same container can be consumed simultaneously
 - Each change in container appears exactly once in the change data capture feed, and the checkpoints are managed internally for you
-- Changes can be synchronized "from the Beginning” or “from a given timestamp” or “from now”
+- Changes can be synchronized "from the beginning” or “from a given timestamp” or “from now”
 - There's no limitation around the fixed data retention period for which changes are available
 
 ## Efficient incremental data capture with internally managed checkpoints
@@ -46,7 +46,7 @@ Change data capture in Azure Cosmos DB analytical store supports the following k
 
 ### Capturing changes from the beginning
 
-When the `Start from beginning` option is selected, the initial load includes a full snapshot of container data in the first run, and changed or incremental data is captured in subsequent runs. This is limited by the `analytical TTL` property and documents TTL-removed from analytical store are not included in the change feed. Example: Imagine a container with `analytical TTL` set to 31536000 seconds, what is equivalent to 1 year. If you create a CDC process for this container, only documents newer than 1 year will be included in the initial load.
+When the `Start from beginning` option is selected, the initial load includes a full snapshot of container data in the first run, and changed or incremental data is captured in subsequent runs. This is limited by the `analytical TTL` property and documents TTL-removed from analytical store are not included in the change feed. Example: Imagine a container with `analytical TTL` set to 31536000 seconds, which is equivalent to 1 year. If you create a CDC process for this container, only documents newer than 1 year will be included in the initial load.
 
 ### Capturing changes from a given timestamp
 
@@ -85,7 +85,7 @@ You can create multiple processes to consume CDC in analytical store. This appro
 
 ### Throughput isolation, lower latency and lower TCO
 
-Operations on Cosmos DB analytical store don't consume the provisioned RUs and so don't affect your transactional workloads. change data capture with analytical store also has lower latency and lower TCO. The lower latency is attributed to analytical store enabling better parallelism for data processing and reduces the overall TCO enabling you to drive cost efficiencies in these rapidly shifting economic conditions.
+Operations on Cosmos DB analytical store don't consume the provisioned RUs and so don't affect your transactional workloads. Change data capture with analytical store also has lower latency and lower TCO. The lower latency is attributed to analytical store enabling better parallelism for data processing and reduces the overall TCO enabling you to drive cost efficiencies in these rapidly shifting economic conditions.
 
 ## Scenarios
 
@@ -111,7 +111,7 @@ Change data capture capability enables an end-to-end analytical solution providi
 
 The linked service interface for the API for MongoDB isn't available within Azure Data Factory data flows yet. You can use your API for MongoDB's account endpoint with the **Azure Cosmos DB for NoSQL** linked service interface as a work around until the Mongo linked service is directly supported.
 
-In the interface for a new NoSQL linked service, select **Enter Manually** to provide the Azure Cosmos DB account information. Here, use the account's NoSQL document endpoint (ex: `https://<account-name>.documents.azure.com:443/`) instead of the Mongo DB endpoint (ex: `mongodb://<account-name>.mongo.cosmos.azure.com:10255/`)
+In the interface for a new NoSQL linked service, select **Enter Manually** to provide the Azure Cosmos DB account information. Here, use the account's NoSQL document endpoint (Example: `https://<account-name>.documents.azure.com:443/`) instead of the Mongo DB endpoint (Example: `mongodb://<account-name>.mongo.cosmos.azure.com:10255/`)
 
 ## Next steps
 

articles/machine-learning/how-to-setup-authentication.md

@@ -35,7 +35,7 @@ Microsoft Entra Conditional Access can be used to further control or restrict ac
 ## Prerequisites
 
 * Create an [Azure Machine Learning workspace](how-to-manage-workspace.md).
-* [Configure your development environment](how-to-configure-environment.md) or use a [Azure Machine Learning compute instance](how-to-create-compute-instance.md) and install the [Azure Machine Learning SDK v2](https://aka.ms/sdk-v2-install).
+* [Configure your development environment](how-to-configure-environment.md) or use an [Azure Machine Learning compute instance](how-to-create-compute-instance.md) and install the [Azure Machine Learning SDK v2](https://aka.ms/sdk-v2-install).
 
 * Install the [Azure CLI](/cli/azure/install-azure-cli).
 

articles/sap/monitor/provider-ha-pacemaker-cluster.md

@@ -116,7 +116,7 @@ When the provider settings validation operation fails with the code `PrometheusU
 1. Restart the HA cluster exporter agent.
 
     ```bash
-    sstemctl start pmproxy
+    systemctl start pmproxy
     ```
 
 1. Reenable the HA cluster exporter agent.

articles/sentinel/sap/deploy-data-connector-agent-container.md

@@ -231,6 +231,9 @@ In this section, you deploy the data connector agent. After you deploy the agent
     :::image type="content" source="media/deploy-data-connector-agent-container/finish-agent-deployment.png" alt-text="Screenshot of the final stage of the agent deployment.":::
 
 1. Under **Just one step before we finish**, select **Copy** :::image type="content" source="media/deploy-data-connector-agent-container/copy-icon.png" alt-text="Screenshot of the Copy icon." border="false"::: next to **Agent command**.
+
+   The script updates the OS components, installs the Azure CLI and Docker software and other required utilities (jq, netcat, curl). You can supply additional parameters to the script to customize the container deployment. For more information on available command line options, see [Kickstart script reference](reference-kickstart.md).
+   
 1. In your target VM (the VM where you plan to install the agent), open a terminal and run the command you copied in the previous step.
 
     The relevant agent information is deployed into Azure Key Vault, and the new agent is visible in the table under **Add an API based collector agent**. 

articles/storage/files/authorize-oauth-rest.md

@@ -108,7 +108,7 @@ namespace FilesOAuthSample
             string aadEndpoint = "";
             string accountUri = "";
             string connectionString = "";
-            string shareName = "testShare";
+            string shareName = "test-share";
             string directoryName = "testDirectory";
             string fileName = "testFile"; 
 
@@ -124,11 +124,11 @@ namespace FilesOAuthSample
                     AuthorityHost = new Uri(aadEndpoint)
                 });
 
-            ShareClientOptions clientOptions = new ShareClientOptions(ShareClientOptions.ServiceVersion.V2021_12_02);
+            ShareClientOptions clientOptions = new ShareClientOptions(ShareClientOptions.ServiceVersion.V2023_05_03);
 
             // Set Allow Trailing Dot and Source Allow Trailing Dot.
             clientOptions.AllowTrailingDot = true;
-            clientOptions.SourceAllowTrailingDot = true;
+            clientOptions.AllowSourceTrailingDot = true;
 
             // x-ms-file-intent=backup will automatically be applied to all APIs
             // where it is required in derived clients.