Merge branch 'MicrosoftDocs:main' into cosmos-retire-notebooks

Author: seesharprun

.openpublishing.redirection.json

@@ -1242,7 +1242,22 @@
         },
         {
             "source_path_from_root": "/articles/azure-maps/tutorial-creator-feature-stateset.md",
-            "redirect_url": "/azure/azure-maps/how-to-creator-feature-stateset",
+            "redirect_url": "/azure/azure-maps/about-creator",
+            "redirect_document_id": false
+        },
+        {
+            "source_path_from_root": "/articles/azure-maps/schema-stateset-stylesobject.md",
+            "redirect_url": "/azure/azure-maps/about-creator",
+            "redirect_document_id": false
+        },
+        {
+            "source_path_from_root": "/articles/azure-maps/indoor-map-dynamic-styling.md",
+            "redirect_url": "/azure/azure-maps/about-creator",
+            "redirect_document_id": false
+        },
+        {
+            "source_path_from_root": "/articles/azure-maps/how-to-creator-feature-stateset.md",
+            "redirect_url": "/azure/azure-maps/about-creator",
             "redirect_document_id": false
         },
         {

articles/ai-services/document-intelligence/faq.yml

@@ -59,11 +59,11 @@ sections:
           - You can find more details in the [technical community blog](https://techcommunity.microsoft.com/t5/azure-ai-services-blog/document-generative-ai-the-power-of-azure-ai-document/ba-p/3875015).
 
       - question: |
-          Does Document Intelligence offer a semantic chunking solution for retrieval-augmented generation?
+         Can Document Intelligence help with semantic chunking within documents for retrieval-augmented generation?
         answer: |
           **Yes.**
-
-          Semantic chunking is a key step in retrieval-augmented generation (RAG) to ensure its efficient storage and retrieval.
+          
+          Document Intelligence can provide the building blocks to enable semantic chunking. Semantic chunking is a key step in retrieval-augmented generation (RAG) to ensure its efficient storage and retrieval.
 
           - Document Intelligence provides a layout model that segments documents into coherent units based on their semantic content.
 

articles/ai-services/openai/concepts/models.md

@@ -312,7 +312,7 @@ The following Embeddings models are available with [Azure Government](/azure/azu
 
 ### Assistants (Preview)
 
-For Assistants you need a combination of a supported model, and a supported region. Certain tools and capabilities require the latest models. The following models are available in the Assistants API, SDK, Azure AI Studio and Azure OpenAI Studio. The following table is for pay-as-you-go. For information on Provisioned Throughput Unit (PTU) availability, see [provisioned throughput](./provisioned-throughput.md). 
+For Assistants you need a combination of a supported model, and a supported region. Certain tools and capabilities require the latest models. The following models are available in the Assistants API, SDK, Azure AI Studio and Azure OpenAI Studio. The following table is for pay-as-you-go. For information on Provisioned Throughput Unit (PTU) availability, see [provisioned throughput](./provisioned-throughput.md). The listed models and regions can be used with both Assistants v1 and v2.
 
 | Region | `gpt-35-turbo (0613)` | `gpt-35-turbo (1106)`| `fine tuned gpt-3.5-turbo-0125` | `gpt-4 (0613)` | `gpt-4 (1106)` | `gpt-4 (0125)` | `gpt-4o (2024-05-13)` |
 |-----|:---:|:---:|:---:|:---:|:---:|:---:|:---:|

articles/ai-services/openai/how-to/use-your-data-securely.md

@@ -265,9 +265,10 @@ So far you have already setup each resource work independently. Next you need to
 |--|--|--|--|
 | `Search Index Data Reader` | Azure OpenAI | Azure AI Search | Inference service queries the data from the index. |
 | `Search Service Contributor` | Azure OpenAI | Azure AI Search | Inference service queries the index schema for auto fields mapping. Data ingestion service creates index, data sources, skill set, indexer, and queries the indexer status. |
-| `Storage Blob Data Contributor` | Azure OpenAI | Storage Account | Reads from the input container, and writes the preprocess result to the output container. |
-| `Cognitive Services OpenAI Contributor` | Azure AI Search | Azure OpenAI | Custom skill |
-| `Storage Blob Data Contributor` | Azure AI Search | Storage Account | Reads blob and writes knowledge store. |
+| `Storage Blob Data Contributor` | Azure OpenAI | Storage Account | Reads from the input container, and writes the preprocessed result to the output container. |
+| `Cognitive Services OpenAI Contributor` | Azure AI Search | Azure OpenAI | Custom skill. |
+| `Storage Blob Data Reader` | Azure AI Search | Storage Account | Reads document blobs and chunk blobs. |
+| `Cognitive Services OpenAI User` | Web app | Azure OpenAI | Inference. |
 
 
 In the above table, the `Assignee` means the system assigned managed identity of that resource.

articles/ai-services/openai/includes/api-surface.md

@@ -22,8 +22,8 @@ Each API surface/specification encapsulates a different set of Azure OpenAI capa
 | API | Latest preview release | Latest GA release | Specifications | Description |
 |:---|:----|:----|:----|:---|
 | **Control plane** | `2024-04-01-preview` | [`2023-05-01`](/rest/api/aiservices/accountmanagement/deployments/create-or-update?view=rest-aiservices-accountmanagement-2023-05-01&tabs=HTTP&preserve-view=true) | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/resource-manager/Microsoft.CognitiveServices) | Azure OpenAI shares a common control plane with all other Azure AI Services. The control plane API is used for things like [creating Azure OpenAI resources](/rest/api/aiservices/accountmanagement/accounts/create?view=rest-aiservices-accountmanagement-2023-05-01&tabs=HTTP&preserve-view=true), [model deployment](/rest/api/aiservices/accountmanagement/deployments/create-or-update?view=rest-aiservices-accountmanagement-2023-05-01&tabs=HTTP&preserve-view=true), and other higher level resource management tasks. The control plane also governs what is possible to do with capabilities like Azure Resource Manager, Bicep, Terraform, and Azure CLI.|
-| **Data plane - authoring** | `2024-05-01-preview` | `2024-06-01` | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/authoring) | The data plane authoring API controls [fine-tuning](/rest/api/azureopenai/fine-tuning?view=rest-azureopenai-2024-05-01-preview&preserve-view=true), [file-upload](/rest/api/azureopenai/files/upload?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true), [ingestion jobs](/rest/api/azureopenai/ingestion-jobs/create?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true), and certain [model level queries](/rest/api/azureopenai/models/get?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true)
-| **Data plane - inference** | `2024-05-01-preview` | `2024-06-01` | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference) | The data plane inference API provides the inference capabilities/endpoints for features like completions, chat completions, embeddings, speech/whisper, on your data, Dall-e, assistants, etc. | 
+| **Data plane - authoring** | [`2024-05-01-preview`](/rest/api/azureopenai/operation-groups?view=rest-azureopenai-2024-05-01-preview&preserve-view=true) | [`2024-06-01`](/rest/api/azureopenai/operation-groups?view=rest-azureopenai-2024-06-01&preserve-view=true) | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/authoring) | The data plane authoring API controls [fine-tuning](/rest/api/azureopenai/fine-tuning?view=rest-azureopenai-2024-05-01-preview&preserve-view=true), [file-upload](/rest/api/azureopenai/files/upload?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true), [ingestion jobs](/rest/api/azureopenai/ingestion-jobs/create?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true), and certain [model level queries](/rest/api/azureopenai/models/get?view=rest-azureopenai-2024-05-01-preview&tabs=HTTP&preserve-view=true)
+| **Data plane - inference** | [`2024-05-01-preview`](/azure/ai-services/openai/reference-preview#data-plane-inference) | [`2024-06-01`](/azure/ai-services/openai/reference#data-plane-inference) | [Spec files](https://github.com/Azure/azure-rest-api-specs/tree/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference) | The data plane inference API provides the inference capabilities/endpoints for features like completions, chat completions, embeddings, speech/whisper, on your data, Dall-e, assistants, etc. |
 
 ## Authentication
 

articles/aks/dapr-settings.md

@@ -6,15 +6,15 @@ ms.author: hannahhunter
 ms.topic: article
 ms.custom: build-2023, devx-track-azurecli, linux-related-content
 ms.subservice: aks-developer
-ms.date: 04/01/2024
+ms.date: 07/09/2024
 ---
 
 # Configure the Dapr extension for your Azure Kubernetes Service (AKS) and Arc-enabled Kubernetes project
 
-Once you've [created the Dapr extension](./dapr.md), you can configure the [Dapr](https://dapr.io/) extension to work best for you and your project using various configuration options, like:
+After [creating the Dapr extension](./dapr.md), you can configure the [Dapr](https://dapr.io/) extension to work best for you and your project using various configuration options, like:
 
 - Limiting which of your nodes use the Dapr extension
-- Setting automatic CRD updates
+- Setting automatic custom resource definition (CRD) updates
 - Configuring the Dapr release namespace
 
 The extension enables you to set Dapr configuration options by using the `--configuration-settings` parameter in the Azure CLI or `configurationSettings` property in a Bicep template. 
@@ -137,7 +137,7 @@ properties: {
 
 ## Install Dapr in multiple availability zones while in HA mode
 
-By default, the placement service uses a storage class of type `standard_LRS`. It is recommended to create a **zone redundant storage class** while installing Dapr in HA mode across multiple availability zones. For example, to create a `zrs` type storage class, add the `storageaccounttype` parameter: 
+By default, the placement service uses a storage class of type `standard_LRS`. It's recommended to create a **zone redundant storage class** while installing Dapr in HA mode across multiple availability zones. For example, to create a `zrs` type storage class, add the `storageaccounttype` parameter: 
 
 ```yaml
 kind: StorageClass
@@ -186,7 +186,7 @@ You can configure the release namespace.
 
 # [Azure CLI](#tab/cli)
 
-The Dapr extension gets installed in the `dapr-system` namespace by default. To override it, use `--release-namespace`. Include the cluster `--scope` to redefine the namespace.
+The Dapr extension gets installed in the `dapr-system` namespace by default. To override it, use `--release-namespace`. To redefine the namespace, include the cluster `--scope`.
 
 ```azurecli
 az k8s-extension create \
@@ -218,7 +218,7 @@ properties: {
 
 ---
 
-[Learn how to configure the Dapr release namespace if you already have Dapr installed](./dapr-migration.md).
+[Learn how to configure the Dapr release namespace when migrating from Dapr open source to the Dapr extension](./dapr-migration.md).
 
 ## Show current configuration settings
 
@@ -240,7 +240,7 @@ az k8s-extension show --cluster-type managedClusters \
 >
 > HA is enabled by default. Disabling it requires deletion and recreation of the extension.
 
-To update your Dapr configuration settings, recreate the extension with the desired state. For example, assume we've previously created and installed the extension using the following configuration:
+To update your Dapr configuration settings, recreate the extension with the desired state. For example, let's say you previously created and installed the extension using the following configuration:
 
 ```azurecli-interactive
 az k8s-extension create --cluster-type managedClusters \
@@ -368,14 +368,13 @@ properties: {
 
 ## Meet network requirements
 
-The Dapr extension for AKS and Arc for Kubernetes requires the following outbound URLs on `https://:443` to function:
+The Dapr extension requires the following outbound URLs on `https://:443` to function on AKS and Arc for Kubernetes:
 1. `https://mcr.microsoft.com/daprio` URL for pulling Dapr artifacts.
-2. `https://linuxgeneva-microsoft.azurecr.io/` URL for pulling some Dapr dependencies.
-3. The [outbound URLs required for AKS or Arc for Kubernetes](../azure-arc/kubernetes/network-requirements.md). 
+1. The [outbound URLs required for AKS or Arc for Kubernetes](../azure-arc/kubernetes/network-requirements.md). 
 
 ## Next Steps
 
-Once you have successfully provisioned Dapr in your AKS cluster, try deploying a [sample application][sample-application].
+Once you successfully provisioned Dapr in your AKS cluster, try deploying a [sample application][sample-application].
 
 <!-- LINKS INTERNAL -->
 [deploy-cluster]: ./tutorial-kubernetes-deploy-cluster.md

articles/app-service/environment/ase-multi-tenant-comparison.md

@@ -21,7 +21,7 @@ An App Service Environment is an Azure App Service feature that provides a fully
 |Dedicated host group|[Available](overview.md#dedicated-environment) |No |
 |Remote file storage|Fully dedicated to the App Service Environment |Remote file storage for the application is dedicated, but the storage is hosted on a shared file server |
 |Private inbound configuration|Yes, using ILB App Service Environment variation |Yes, via private endpoint |
-|Planned maintenance|[Manual upgrade preference is available](how-to-upgrade-preference.md) |The platform handles maintenance. [Service health notifications are available](../../app-service/routine-maintenance.md). |
+|Planned maintenance|[Manual upgrade preference is available](how-to-upgrade-preference.md) |[The platform handles maintenance](../../app-service/routine-maintenance.md) |
 |Aggregate remote file share storage limit|1 TB for all apps in an App Service Environment v3|250 GB for all apps in a single App Service plan. 500 GB for all apps across all App Service plans in a single resource group.|
 
 ### Scaling

articles/azure-arc/edge-storage-accelerator/create-pv.md

@@ -19,7 +19,7 @@ This section describes the prerequisites for creating a persistent volume (PV).
 1. Create a storage account [following the instructions here](/azure/storage/common/storage-account-create?tabs=azure-portal).
 
     > [!NOTE]
-    > When you create your storage account, create it under the same resource group and region/location as your Kubernetes cluster.
+    > When you create your storage account, create it under the same resource group as your Kubernetes cluster. It is recommended that you also create it under the same region/location as your Kubernetes cluster.
 
 1. Create a container in the storage account that you created in the previous step, [following the instructions here](/azure/storage/blobs/storage-quickstart-blobs-portal#create-a-container).
 
@@ -65,8 +65,6 @@ Note the `metadata: name:` as you must specify it in the `spec: volumeName` of t
    metadata:
        ### Create a name here ###
        name: CREATE_A_NAME_HERE
-       ### Use a namespace that matches your intended consuming pod, or "default" ###
-       namespace: INTENDED_CONSUMING_POD_OR_DEFAULT_HERE
    spec:
        capacity:
            ### This storage capacity value is not enforced at this layer. ###

articles/azure-arc/edge-storage-accelerator/create-pvc.md

@@ -36,11 +36,6 @@ This size does not affect the ceiling of blob storage used in the cloud to suppo
        volumeMode: Filesystem
        ### This name references your PV name in your PV config ###
        volumeName: INSERT_YOUR_PV_NAME
-   status: 
-       accessModes: 
-           - ReadWriteMany 
-       capacity: 
-           storage: 5Gi
    ```
 
    > [!NOTE]

articles/azure-arc/edge-storage-accelerator/release-notes.md

@@ -16,6 +16,11 @@ This article provides information about new features and known issues in Edge St
 
 - Kernel versions: the minimum supported Linux kernel version is 5.1. Currently there are known issues with 6.4 and 6.2.
 
+## Version 1.2.0-preview
+
+- Extension identity and OneLake support: ESA now allows use of a system-assigned extension identity for access to blob storage or OneLake lake houses.
+- Security fixes: security maintenance (package/module version updates).
+
 ## Next steps
 
 [Edge Storage Accelerator overview](overview.md)