@@ -9,18 +9,23 @@ ms.custom:
   - ignite-2023
   - build-2024
 ms.topic: reference
-ms.date: 08/05/2024
+ms.date: 10/16/2024
 ---
 
 #	Azure OpenAI Embedding skill
 
 The **Azure OpenAI Embedding** skill connects to a deployed embedding model on your [Azure OpenAI](/azure/ai-services/openai/overview) resource to generate embeddings during indexing. Your data is processed in the [Geo](https://azure.microsoft.com/explore/global-infrastructure/data-residency/) where your model is deployed. 
 
+## Prerequisites
+
+Your Azure OpenAI Service must have an associated [custom subdomain](/azure/ai-services/cognitive-services-custom-subdomains). If the service was created through the Azure portal, this subdomain is automatically generated as part of your service setup. Ensure that your service includes a custom subdomain before using it with the Azure AI Search integration.
+
+Azure OpenAI Service resources (with access to embedding models) that were created in AI Studio aren't supported. Only the Azure OpenAI Service resources created in the Azure portal are compatible with the **Azure OpenAI Embedding** skill integration.
+
 The [Import and vectorize data wizard](search-get-started-portal-import-vectors.md) in the Azure portal uses the **Azure OpenAI Embedding** skill to vectorize content. You can run the wizard and review the generated skillset to see how the wizard builds the skill for embedding models. 
 
 > [!NOTE]
 > This skill is bound to Azure OpenAI and is charged at the existing [Azure OpenAI pay-as-you go price](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/#pricing).
->
 
 ## @odata.type  
 

@@ -2,14 +2,13 @@
 title: "Quickstart: Vectorize text and images by using the Azure portal"
 titleSuffix: Azure AI Search
 description: Use a wizard to automate data chunking and vectorization in a search index.
-
 author: HeidiSteen
 ms.author: heidist
 ms.service: azure-ai-search
 ms.custom:
   - build-2024
 ms.topic: quickstart
-ms.date: 08/13/2024
+ms.date: 10/16/2024
 ---
 
 # Quickstart: Vectorize text and images by using the Azure portal
@@ -47,6 +46,10 @@ Key points about the wizard:
   | [Azure AI Studio model catalog](/azure/ai-studio/what-is-ai-studio) |  Azure, Cohere, and Facebook embedding models. |
   | [Azure AI services multiservice account](/azure/ai-services/multi-service-resource) | [Azure AI Vision multimodal](/azure/ai-services/computer-vision/how-to/image-retrieval) for image and text vectorization. Azure AI Vision multimodal is available in selected regions. [Check the documentation](/azure/ai-services/computer-vision/how-to/image-retrieval?tabs=csharp) for an updated list. **To use this resource, the account must be in an available region and in the same region as Azure AI Search**. |
 
+If using the Azure OpenAI Service, it must have an associated [custom subdomain](/azure/ai-services/cognitive-services-custom-subdomains). If the service was created through the Azure portal, this subdomain is automatically generated as part of your service setup. Ensure that your service includes a custom subdomain before using it with the Azure AI Search integration.
+
+Azure OpenAI Service resources (with access to embedding models) that were created in AI Studio aren't supported. Only the Azure OpenAI Service resources created in the Azure portal are compatible with the **Azure OpenAI Embedding** skill integration.
+
 ### Public endpoint requirements
 
 All of the preceding resources must have public access enabled so that the portal nodes can access them. Otherwise, the wizard fails. After the wizard runs, you can enable firewalls and private endpoints on the integration components for security. For more information, see [Secure connections in the import wizards](search-import-data-portal.md#secure-connections).

@@ -94,7 +94,7 @@ Create the data source and provide a system-assigned managed identity.
 
 ### System-assigned managed identity
 
-The [REST API](//rest/api/searchservice/data-sources/create), Azure portal, and the [.NET SDK](/dotnet/api/azure.search.documents.indexes.models.searchindexerdatasourceconnection) support system-assigned managed identity. 
+The [REST API](/rest/api/searchservice/data-sources/create), Azure portal, and the [.NET SDK](/dotnet/api/azure.search.documents.indexes.models.searchindexerdatasourceconnection) support system-assigned managed identity. 
 
 When you're connecting with a system-assigned managed identity, the only change to the data source definition is the format of the "credentials" property. You'll provide an Initial Catalog or Database name and a `ResourceId` that has no account key or password. The `ResourceId` must include the subscription ID of SQL Managed Instance, the resource group of SQL Managed instance, and the name of the SQL database. 
 

@@ -14,7 +14,7 @@ ms.date: 05/23/2024
 
 This article explains how to configure an indexer in Azure AI Search for a private connection to a SQL managed instance that runs within a virtual network. The private connection is through a [shared private link](search-indexer-howto-access-private.md) and Azure Private Link.
 
-On a private connection to a managed instance, the fully qualified domain name (FQDN) of the instance must include the [DNS Zone](/azure/azure-sql/managed-instance/connectivity-architecture-overview#virtual-cluster-connectivity-architecture). Currently, only the Azure AI Search Management REST API provides a `resourceRegion` parameter for accepting the DNS zone specification.
+On a private connection to a managed instance, the fully qualified domain name (FQDN) of the instance must include the [DNS Zone](/azure/azure-sql/managed-instance/connectivity-architecture-overview#virtual-cluster-connectivity-architecture). Currently, only the Azure AI Search Management REST API provides a `dnsZonePrefix` parameter for accepting the DNS zone specification.
 
 Although you can call the Management REST API directly, it's easier to use the Azure CLI `az rest` module to send Management REST API calls from a command line. This article uses the Azure CLI with REST to set up the private link.
 
@@ -57,7 +57,7 @@ For more information about connection properties, see [Create an Azure SQL Manag
        "name": "{{shared-private-link-name}}",
        "properties": {
            "privateLinkResourceId": "/subscriptions/{{target-resource-subscription-ID}}/resourceGroups/{{target-resource-rg}}/providers/Microsoft.Sql/managedInstances/{{target-resource-name}}",
-           "resourceRegion": "a1b22c333d44",
+           "dnsZonePrefix": "a1b22c333d44",
            "groupId": "managedInstance",
            "requestMessage": "please approve",
        }
@@ -66,7 +66,7 @@ For more information about connection properties, see [Create an Azure SQL Manag
 
 1. Provide a meaningful name for the shared private link. The shared private link appears alongside other private endpoints. A name like "shared-private-link-for-search" can remind you how it's used.
 
-1. Paste in the DNS zone name in "resourceRegion" that you retrieved in an earlier step.
+1. Paste in the DNS zone name in "dnsZonePrefix" that you retrieved in an earlier step.
 
 1. Edit the "privateLinkResourceId" to reflect the private endpoint of your managed instance. Provide the subscription ID, resource group name, and object name of the managed instance.
 
@@ -128,7 +128,7 @@ This article assumes a [REST client](search-get-started-rest.md) and uses the RE
 
 1. [Create the data source definition](search-howto-connecting-azure-sql-database-to-azure-search-using-indexers.md) as you would normally for Azure SQL. The format of the connection string is slightly different for a managed instance, but other properties are the same as if you were configuring a data source connection to Azure SQL database.
 
-    Provide the connection string that you copied earlier.
+    Provide the connection string that you copied earlier with an Initial Catalog specified.
 
     ```http
     POST https://myservice.search.windows.net/datasources?api-version=2024-07-01
@@ -139,16 +139,15 @@ This article assumes a [REST client](search-get-started-rest.md) and uses the RE
          "description" : "A database for testing Azure AI Search indexes.",
          "type" : "azuresql",
          "credentials" : { 
-             "connectionString" : "Server=tcp:contoso.public.0000000000.database.windows.net,1433; Persist Security Info=false; User ID=<your user name>; Password=<your password>;MultipleActiveResultsSets=False; Encrypt=True;Connection Timeout=30;" 
+             "connectionString" : "Server=tcp:contoso.public.0000000000.database.windows.net,1433;Persist Security Info=false; User ID=<your user name>; Password=<your password>;MultipleActiveResultsSets=False; Encrypt=True;Connection Timeout=30;Initial Catalog=<your database name>"
             },
          "container" : { 
              "name" : "Name of table or view to index",
              "query" : null (not supported in the Azure SQL indexer)
              },
          "dataChangeDetectionPolicy": null,
          "dataDeletionDetectionPolicy": null,
-         "encryptionKey": null,
-         "identity": null
+         "encryptionKey": null
      }
     ```
 

@@ -2,13 +2,14 @@
 title: Azure OpenAI vectorizer
 titleSuffix: Azure AI Search
 description: Connects to a deployed model on your Azure OpenAI resource at query time.
-author: careyjmac
-ms.author: chalton
+author: HeidiSteen
+ms.author: heidist
+ms.reviewer: chalton
 ms.service: azure-ai-search
 ms.custom:
   - build-2024
 ms.topic: reference
-ms.date: 08/05/2024
+ms.date: 10/16/2024
 ---
 
 # Azure OpenAI vectorizer
@@ -23,7 +24,12 @@ Vectorizers are used at query time, but specified in index definitions, and refe
 
 > [!NOTE]
 > This vectorizer is bound to Azure OpenAI and is charged at the existing [Azure OpenAI pay-as-you go price](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/#pricing).
->
+
+## Prerequisites
+
+Your Azure OpenAI Service must have an associated [custom subdomain](/azure/ai-services/cognitive-services-custom-subdomains). If the service was created through the Azure portal, this subdomain is automatically generated as part of your service setup. Ensure that your service includes a custom subdomain before using it with the Azure AI Search integration.
+
+Azure OpenAI Service resources (with access to embedding models) that were created in AI Studio aren't supported. Only the Azure OpenAI Service resources created in the Azure portal are compatible with the **Azure OpenAI Embedding** skill integration. 
 
 ## Vectorizer parameters