Merge pull request #2699 from MicrosoftDocs/main

02/03/2025 AM Publishing

Author: v-alje

articles/ai-services/openai/includes/chatgpt-dotnet.md

@@ -125,4 +125,5 @@ If you want to clean up and remove an Azure OpenAI resource, you can delete the
 
 ## Next steps
 
+* [Get started with the chat using your own data sample for .NET](/dotnet/ai/get-started-app-chat-template?toc=/azure/ai-services/openai/toc.json&bc=/azure/ai-services/openai/breadcrumb/toc.json&tabs=github-codespaces)
 * For more examples, check out the [Azure OpenAI Samples GitHub repository](https://github.com/Azure-Samples/openai)

articles/ai-services/openai/includes/chatgpt-java.md

@@ -180,4 +180,5 @@ If you want to clean up and remove an Azure OpenAI resource, you can delete the
 
 ## Next steps
 
+* [Get started with the chat using your own data sample for Java](/azure/developer/java/ai/get-started-app-chat-template?toc=/azure/ai-services/openai/toc.json&bc=/azure/ai-services/openai/breadcrumb/toc.json&tabs=github-codespaces)
 * For more examples, check out the [Azure OpenAI Samples GitHub repository](https://github.com/Azure-Samples/openai)

articles/ai-services/openai/includes/chatgpt-javascript.md

@@ -178,4 +178,5 @@ If you want to clean up and remove an Azure OpenAI resource, you can delete the
 ## Next steps
 
 * [Azure OpenAI Overview](../overview.md)
+* [Get started with the chat using your own data sample for JavaScript](/azure/developer/javascript/ai/get-started-app-chat-template?toc=/azure/ai-services/openai/toc.json&bc=/azure/ai-services/openai/breadcrumb/toc.json&tabs=github-codespaces)
 * For more examples, check out the [Azure OpenAI Samples GitHub repository](https://github.com/Azure-Samples/openai)

articles/ai-services/openai/includes/chatgpt-python.md

@@ -162,4 +162,5 @@ If you want to clean up and remove an Azure OpenAI resource, you can delete the
 ## Next steps
 
 * Learn more about how to work with GPT-35-Turbo and the GPT-4 models with [our how-to guide](../how-to/chatgpt.md).
+* [Get started with the chat using your own data sample for Python](/azure/developer/python/get-started-app-chat-template?toc=/azure/ai-services/openai/toc.json&bc=/azure/ai-services/openai/breadcrumb/toc.json&tabs=github-codespaces)
 * For more examples, check out the [Azure OpenAI Samples GitHub repository](https://github.com/Azure-Samples/openai)

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

@@ -135,7 +135,7 @@ Before following the steps in this article, make sure you have the following pre
 
 ## Limitations
 
-* Azure AI Foundry currently doesn't support bringing your own virtual network, it only supports managed virtual network isolation.
+* Azure AI Foundry supports managed virtual network isolation for securing your compute resources. Azure AI Foundry does not support bring your own virtual network for securing compute resources. Please note bring your own virtual network for securing computes is different than your Azure virtual network that is required to access Azure AI Foundry from your on-premises network. 
 * Once you enable managed virtual network isolation of your Azure AI, you can't disable it.
 * Managed virtual network uses private endpoint connection to access your private resources. You can't have a private endpoint and a service endpoint at the same time for your Azure resources, such as a storage account. We recommend using private endpoints in all scenarios.
 * The managed virtual network is deleted when the Azure AI is deleted. 

articles/machine-learning/how-to-authenticate-online-endpoint.md

@@ -728,7 +728,7 @@ The __Test__ tab of the deployment's detail page supports scoring for endpoints
 
 ## Log and monitor traffic
 
-To enable traffic logging in the diagnostics settings for the endpoint, follow the steps in [How to enable/disable logs](how-to-monitor-online-endpoints.md#how-to-enabledisable-logs).
+To enable traffic logging in the diagnostics settings for the endpoint, follow the steps in [Turn on logs](how-to-monitor-online-endpoints.md#turn-on-logs).
 
 If the diagnostic setting is enabled, you can check the `AmlOnlineEndpointTrafficLogs` table to see the auth mode and user identity.
 

articles/machine-learning/how-to-autoscale-endpoints.md

@@ -455,7 +455,10 @@ The following steps continue the rule configuration on the __Custom autoscale__
 
 ## Find IDs for supported metrics
 
-If you want to use other metrics in code to set up autoscale rules by using the Azure CLI or the SDK, see the table in [Available metrics](how-to-monitor-online-endpoints.md#available-metrics).
+You can use other metrics when you use the Azure CLI or the SDK to set up autoscale rules.
+
+- For the names of endpoint metrics to use in code, see the values in the __Name in REST API__ column in the table in [Supported metrics for Microsoft.MachineLearningServices/workspaces/onlineEndpoints](monitor-azure-machine-learning-reference.md#supported-metrics-for-microsoftmachinelearningservicesworkspacesonlineendpoints).
+- For the names of deployment metrics to use in code, see the values in the __Name in REST API__ column in the tables in [Supported metrics for Microsoft.MachineLearningServices/workspaces/onlineEndpoints/deployments](monitor-azure-machine-learning-reference.md#supported-metrics-for-microsoftmachinelearningservicesworkspacesonlineendpointsdeployments).
 
 ## Create scale rule based on schedule
 

articles/machine-learning/how-to-deploy-online-endpoints.md

@@ -1230,7 +1230,7 @@ To view metrics and set alerts based on your SLA, complete the steps that are de
 
 ### (Optional) Integrate with Log Analytics
 
-The `get-logs` command for CLI or the `get_logs` method for SDK provides only the last few hundred lines of logs from an automatically selected instance. However, Log Analytics provides a way to durably store and analyze logs. For more information on using logging, see [Monitor online endpoints](how-to-monitor-online-endpoints.md#logs).
+The `get-logs` command for CLI or the `get_logs` method for SDK provides only the last few hundred lines of logs from an automatically selected instance. However, Log Analytics provides a way to durably store and analyze logs. For more information on using logging, see [Monitor online endpoints](how-to-monitor-online-endpoints.md#use-logs).
 
 <!-- [!INCLUDE [Email Notification Include](includes/machine-learning-email-notifications.md)] -->
 

articles/machine-learning/how-to-manage-quotas.md

@@ -123,7 +123,7 @@ Azure Machine Learning online endpoints and batch endpoints have resource limits
 > [!IMPORTANT]
 > These limits are *regional*, meaning that you can use up to these limits per each region you're using. For example, if your current limit for number of endpoints per subscription is 100, you can create 100 endpoints in the East US region, 100 endpoints in the West US region, and 100 endpoints in each of the other supported regions in a single subscription. Same principle applies to all the other limits.
 
-To determine the current usage for an endpoint, [view the metrics](how-to-monitor-online-endpoints.md#metrics). 
+To determine the current usage for an endpoint, [view the metrics](how-to-monitor-online-endpoints.md#use-metrics). 
 
 To request an exception from the Azure Machine Learning product team, use the steps in the [Endpoint limit increases](#endpoint-limit-increases).