Merge pull request #6739 from MicrosoftDocs/main

Auto Publish – main to live - 2025-08-25 17:05 UTC

Author: learn-build-service-prod[bot]

articles/ai-foundry/how-to/create-manage-compute-session.md

@@ -3,17 +3,21 @@ title: Create and manage prompt flow compute sessions
 titleSuffix: Azure AI Foundry
 description: In this article, learn how to create and manage compute sessions to run prompt flows in Azure AI Foundry portal.
 ms.service: azure-ai-foundry
+ms.subservice: azure-ai-prompt-flow
 ms.custom:
   - ignite-2023
   - build-2024
   - ignite-2024
   - hub-only
 ms.topic: how-to
-ms.date: 02/14/2025
+ms.date: 08/25/2025
 ms.reviewer: lochen
 ms.author: sgilley
 author: sdgilley
+ms.collection: ce-skilling-fresh-tier1
+ms.update-cycle: 180-days
 # customer intent: Learn how to create and manage prompt flow compute sessions in Azure AI Foundry portal.
+
 ---
 
 # Create and manage prompt flow compute sessions in Azure AI Foundry portal

articles/ai-foundry/how-to/flow-develop.md

@@ -39,7 +39,7 @@ In this article, you learn how to create and develop your first prompt flow in A
 - You need a deployed model.
 - In your project, configure access control for the blob storage account. Assign the **Storage Blob Data Contributor** role to your user account.
     - In the bottom left of the Azure AI Foundry portal, select **Management center**.
-    - In **Connected resources** for your project, select the link that corresponds to the **Azure Blob Storage** type. 
+    - In **Connected resources** for your hub, select the link that corresponds to the **Azure Blob Storage** type. 
     - Select **View in Azure Portal**
     - In the Azure portal, select **Access control (IAM)**.
     - Select **Add>Add role assignment**.

articles/ai-foundry/includes/deploy-model.md

@@ -27,9 +27,7 @@ To work with a model, you first deploy it into a project.
 
     :::image type="content" source="../media/tutorials/chat/select-model.png" alt-text="Screenshot of the model selection page." lightbox="../media/tutorials/chat/select-model.png":::
 
-1. On the model details page, select **Deploy**.
-
-    :::image type="content" source="../media/tutorials/chat/deploy-model.png" alt-text="Screenshot of the model details page with a button to deploy the model." lightbox="../media/tutorials/chat/deploy-model.png":::
+1. On the model details page, select **Use this model**.
 
 
 1. Leave the default **Deployment name**. Select **Deploy**.

articles/ai-foundry/media/tutorials/chat/deploy-model.png

@@ -60,10 +60,7 @@ In this quickstart, we walk you through setting up your local development enviro
 
 1. Select the **gpt-4o-mini** model from the list of models. You can use the search bar to find it. 
 
-1. On the model details page, select **Deploy**.
-
-    :::image type="content" source="../media/tutorials/chat/deploy-model.png" alt-text="Screenshot of the model details page with a button to deploy the model." lightbox="../media/tutorials/chat/deploy-model.png":::
-
+1. On the model details page, select **Use this model**.
 
 1. Leave the default **Deployment name**. Select **Deploy**.
 

articles/ai-foundry/quickstarts/get-started-code.md

@@ -7,7 +7,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: quickstart
-ms.date: 04/10/2025
+ms.date: 08/25/2025
 ms.reviewer: zuramir
 ms.author: sgilley
 author: sdgilley

articles/ai-foundry/quickstarts/get-started-playground.md

@@ -58,9 +58,7 @@ These steps deploy a model to a real-time endpoint from the Azure AI Foundry por
 
     :::image type="content" source="../media/tutorials/chat/select-model.png" alt-text="Screenshot of the model selection page." lightbox="../media/tutorials/chat/select-model.png":::
 
-1. On the model details page, select **Deploy**.
-
-    :::image type="content" source="../media/tutorials/chat/deploy-model.png" alt-text="Screenshot of the model details page with a button to deploy the model." lightbox="../media/tutorials/chat/deploy-model.png":::
+1. On the model details page, select **Use this model**.
 
 1. Leave the default **Deployment name**. select **Deploy**.  Or, if the model isn't available in your region, a different region is selected for you and connected to your project.  In this case, select **Connect and deploy**.
 

articles/ai-foundry/tutorials/copilot-sdk-create-resources.md

@@ -12,7 +12,7 @@ ms.reviewer: cacrest
 ms.custom:
   - devplatv2
   - ignite-2023
-ms.date: 04/04/2024
+ms.date: 08/25/2025
 #Customer intent: As an MLOps administrator, I want to understand what a managed endpoint is and why I need it.
 ---
 
@@ -32,7 +32,7 @@ Batch endpoints receive pointers to data and run jobs asynchronously to process
 
 ## Batch deployments
 
-A deployment is a set of resources and computes required to implement the functionality that the endpoint provides. Each endpoint can host several deployments with different configurations, and this functionality helps to *decouple the endpoint's interface* from *the implementation details* that are defined by the deployment. When a batch endpoint is invoked, it automatically routes the client to its default deployment. This default deployment can be configured and changed at any time.
+A deployment is a set of resources and computes required to implement the functionality that the endpoint provides. An endpoint can host multiple deployments, each with its own configuration, decoupling the endpoint interface from the deployment implementation details. When a batch endpoint is invoked, it automatically routes the client to its default deployment. This default deployment can be configured and changed at any time.
 
 :::image type="content" source="./media/concept-endpoints/batch-endpoint.png" alt-text="Diagram showing the relationship between a batch endpoint and its deployments." lightbox="media/concept-endpoints/batch-endpoint.png":::