Merge branch 'main' into release-aisvcs-move-rai-docs

Author: v-alje

articles/ai-foundry/concepts/management-center.md

@@ -2,8 +2,8 @@
 title: Management center overview
 titleSuffix: Azure AI Foundry
 description: "The management center in Azure AI Foundry portal provides a centralized hub for governance and management activities."
-author: Blackmist
-ms.author: larryfr
+author: sdgilley
+ms.author: sgilley
 ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2024

articles/ai-foundry/concepts/resource-types.md

@@ -2,11 +2,11 @@
 title: Choose an Azure resource type for AI foundry
 titleSuffix: Azure AI Foundry
 description: Learn about the supported Azure resource types in Azure AI Foundry portal.
-author: deeikele
-ms.author: deeikele
+reviewer: deeikele
+ms.reviewer: deeikele
 manager: scottpolly
-reviewer: larryfr
-ms.reviewer: larryfr
+author: sgilley
+ms.author: sgilley
 ms.date: 05/18/2025
 ms.service: azure-ai-foundry
 ms.topic: concept-article

articles/ai-foundry/how-to/connections-add.md

@@ -11,9 +11,9 @@ ms.custom:
   - ignite-2024
 ms.topic: how-to
 ms.date: 05/08/2025
-ms.reviewer: larryfr
-ms.author: larryfr
-author: Blackmist
+ms.reviewer: sgilley
+ms.author: sgilley
+author: sdgilley
 zone_pivot_groups: project-type
 # Customer Intent: As an admin or developer, I want to understand how to add new connections in Azure AI Foundry portal.
 

articles/ai-foundry/how-to/deploy-models-serverless.md

@@ -84,13 +84,13 @@ When developing with the OpenAI SDK, you can instrument your code so traces are
     OpenAIInstrumentor().instrument()
     ```
 
-1. Get the connection string to the Azure Application Insights resource associated with your project:
+1. Get the connection string to the Azure Application Insights resource associated with your project. The following line uses the Azure AI Project client, which requires the use of Microsoft Entra ID for authentication:
 
     ```python
     from azure.ai.projects import AIProjectClient
     from azure.identity import DefaultAzureCredential
 
-    project_client = AIProjectClient.from_connection_string(
+    project_client = AIProjectClient(
         credential=DefaultAzureCredential(),
         endpoint="https://<your-resource>.services.ai.azure.com/api/projects/<your-project>",
     )

articles/ai-foundry/how-to/develop/trace-application.md

@@ -0,0 +1,13 @@
+---
+title: Include file
+description: Include file
+ms.author: mopeakande
+author: msakande
+ms.service: azure-ai-foundry
+ms.topic: include
+ms.date: 06/13/2025
+ms.custom: include
+---
+
+> [!NOTE]
+> We recommend that you deploy Azure AI Foundry Models to **Azure AI Foundry resources** so that you can consume your deployments in the resource via a single endpoint with the same authentication and schema to generate inference. The endpoint follows the [Azure AI Model Inference API](/rest/api/aifoundry/modelinference/) which all the Foundry Models support. To learn how to deploy a Foundry Model to the Azure AI Foundry resources, see [Add and configure models to Azure AI Foundry Models](../model-inference/how-to/create-model-deployments.md).