Merge branch 'main' into release-movingcycleclouddocs

Author: v-alje

.openpublishing.redirection.json

@@ -4090,36 +4090,6 @@
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articles/app-service/deploy-intelligent-apps-dotnet-to-azure-sql.md

@@ -11,13 +11,13 @@ ms.collection: ce-skilling-ai-copilot
 
 # Deploy a .NET Blazor app connected to Azure SQL and Azure OpenAI on Azure App Service
 
-When creating intelligent apps, you may want to ground the context of your app using your own SQL data. With the recent announcement of [Azure SQL vector support (preview)](https://devblogs.microsoft.com/azure-sql/announcing-eap-native-vector-support-in-azure-sql-database/), you can ground the context using the Azure SQL data you already have with new [vector functions](https://learn.microsoft.com/sql/t-sql/functions/vector-functions-transact-sql) that help manage vector data. 
+When creating intelligent apps, you may want to ground the context of your app using your own SQL data. With the recent announcement of [Azure SQL vector support (preview)](https://devblogs.microsoft.com/azure-sql/announcing-eap-native-vector-support-in-azure-sql-database/), you can ground the context using the Azure SQL data you already have with new [vector functions](/sql/t-sql/functions/vector-functions-transact-sql) that help manage vector data. 
 
 In this tutorial, you'll create a RAG sample application by setting up a Hybrid vector search against your Azure SQL database using a .NET 8 Blazor app. This example builds from the previous documentation to deploy a [.NET Blazor app with OpenAI](/azure/app-service/deploy-intelligent-apps?pivots=openai-dotnet).
 
 ## Prerequisites
 
-- An [Azure OpenAI](https://learn.microsoft.com/azure/ai-services/openai/quickstart?pivots=programming-language-csharp&tabs=command-line%2Ckeyless%2Ctypescript-keyless%2Cpython#set-up) resource with deployed models
+- An [Azure OpenAI](/azure/ai-services/openai/quickstart?pivots=programming-language-csharp&tabs=command-line%2Ckeyless%2Ctypescript-keyless%2Cpython#set-up) resource with deployed models
 - A .NET 8 or 9 Blazor Web App deployed on App Service
 - An Azure SQL database resource with vector embeddings.
 
@@ -135,15 +135,15 @@ In order to prepare your Azure SQL database for vector search, you need to make
 - `text-embedding-ada-002` is used to generate the embeddings
 - `gpt-3.5-turbo` is used for the language model
 
-These two models need to be deployed before continuing the next step. Visit the [documentation](https://learn.microsoft.com/azure/ai-studio/how-to/deploy-models-openai) for deploying models with Azure OpenAI using Azure AI Foundry.
+These two models need to be deployed before continuing the next step. Visit the [documentation](/azure/ai-studio/how-to/deploy-models-openai) for deploying models with Azure OpenAI using Azure AI Foundry.
 
 ## 4. Vectorize your SQL database
 
 To perform a hybrid vector search on your Azure SQL database, you first need to have the appropriate embeddings in your database. There are many ways you can vectorize your database. One option is to use the following [Azure SQL database vectorizer](https://github.com/Azure-Samples/azure-sql-db-vectorizer) to generate embeddings for your SQL database. Vectorize your Azure SQL database before continuing.
 
 ## 5. Create procedure to generate embeddings
 
-With [Azure SQL vector support (preview)](https://devblogs.microsoft.com/azure-sql/announcing-eap-native-vector-support-in-azure-sql-database/), you can create a stored procedure that will use a Vector data type to store generated embeddings for search queries. The stored procedure invokes an external REST API endpoint to get the embeddings. See the [documentation](https://learn.microsoft.com/azure-data-studio/quickstart-sql-database) to use Azure Data Studio to connect to your database before running the query. 
+With [Azure SQL vector support (preview)](https://devblogs.microsoft.com/azure-sql/announcing-eap-native-vector-support-in-azure-sql-database/), you can create a stored procedure that will use a Vector data type to store generated embeddings for search queries. The stored procedure invokes an external REST API endpoint to get the embeddings. See the [documentation](/azure-data-studio/quickstart-sql-database) to use Azure Data Studio to connect to your database before running the query. 
 
 - Use the following to create a stored procedure with your preferred SQL query editor. You need to populate the @url parameter with your Azure OpenAI resource name and populate the rest endpoint with the API key from your text embedding model. You'll notice the model name as part of the @url, which will be populated with your search query.
 
@@ -469,4 +469,4 @@ Here's the full example of the added *OpenAI.razor* page:
 	}
 }
 
-```
+```

articles/app-service/includes/deploy-intelligent-apps/deploy-intelligent-apps-linux-python-pivot.md

@@ -89,7 +89,7 @@ For Azure OpenAI, see [this documentation](/azure/ai-services/openai/quickstart?
 - Model name: The name of the chat completion model, like "gpt-4o".
 - Deployment name: This is sometimes the same as the model name, but you may have chosen to use a different name. This differentiates between different deployments of the same model.
 - Endpoint: A URL like "https://cog-xxk4qzq3tahic.openai.azure.com/"
-- API version: The desired API version, like "2024-10-21". See the [version history documentation](https://learn.microsoft.com/azure/ai-services/openai/api-version-deprecation) for the latest version.
+- API version: The desired API version, like "2024-10-21". See the [version history documentation](/azure/ai-services/openai/api-version-deprecation) for the latest version.
 
 For OpenAI, see this [documentation](https://platform.openai.com/docs/api-reference) to retrieve the API keys. For our application, you need the following values:
 

articles/app-service/overview-hosting-plans.md

@@ -4,7 +4,7 @@ description: Learn how App Service plans work in Azure App Service, how they're
 keywords: app service, azure app service, scale, scalable, scalability, app service plan, app service cost
 ms.assetid: dea3f41e-cf35-481b-a6bc-33d7fc9d01b1
 ms.topic: article
-ms.date: 08/21/2024
+ms.date: 02/28/2025
 ms.author: msangapu
 author: msangapu-msft
 ms.custom: UpdateFrequency3
@@ -105,24 +105,11 @@ If your app is in the same App Service plan with other apps, you may want to imp
 
 ## Should I put an app in a new plan or an existing plan?
 
-Since you pay for the computing resources your App Service plan allocates (see [How much does my App Service plan cost?](#cost)), you can potentially save money by putting multiple apps into one App Service plan. You can continue to add apps to an existing plan as long as the plan has enough resources to handle the load. However, keep in mind that apps in the same App Service plan all share the same compute resources. To determine whether the new app has the necessary resources, you need to understand the capacity of the existing App Service plan, and the expected load for the new app. Overloading an App Service plan can potentially cause downtime for your new and existing apps.
+Since you pay for the computing resources your App Service plan allocates (see [How much does my App Service plan cost?](#cost)), you can potentially save money by putting multiple apps into one App Service plan. You can continue to add apps to an existing plan as long as the plan has enough resources to handle the load. However, keep in mind that apps in the same App Service plan all share the same compute resources. To determine whether the new app has the necessary resources, you need to understand the capacity of the existing App Service plan, and the expected load for the new app. Overloading an App Service plan can potentially cause downtime for your new and existing apps. You can find more comparisons between plans at [App Service limits](../azure-resource-manager/management/azure-subscription-service-limits.md#azure-app-service-limits).
 
 Isolate your app into a new App Service plan when:
 
-- The app is resource-intensive. The number may actually be lower depending on how resource intensive the hosted applications are. However, for general guidance, refer to the table below:
-
-  | App Service Plan SKU | Maximum Apps |
-  |--|--|
-  | B1, S1, P1v2, I1v1 | 8 |
-  | B2, S2, P2v2, I2v1 | 16 |
-  | B3, S3, P3v2, I3v1 | 32 |
-  | P0v3 | 8 |
-  | P1v3, I1v2 | 16 |
-  | P2v3, I2v2, P1mv3 | 32 |
-  | P3v3, I3v2, P2mv3 | 64 |
-  | I4v2, I5v2, I6v2 | Maximum density bound by vCPU usage |
-  | P3mv3, P4mv3, P5mv3 | Maximum density bound by vCPU usage |
-
+- The app is resource-intensive.
 - You want to scale the app independently from the other apps in the existing plan.
 - The app needs resources in a different geographical region.