Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into nw-vnetflow

Author: halkazwini

.openpublishing.redirection.app-service.json

@@ -1850,6 +1850,16 @@
             "redirect_url": "/azure/app-service/scripts/powershell-scale-manual",
             "redirect_document_id": false
         },
+        {
+            "source_path_from_root": "/articles/app-service/get-resource-events.md",
+            "redirect_url": "/azure/app-service/monitor-app-service",
+            "redirect_document_id": false
+        },
+        {
+            "source_path_from_root": "/articles/app-service/overview-monitoring.md",
+            "redirect_url": "/azure/app-service/monitor-app-service",
+            "redirect_document_id": false
+        },
         {
             "source_path_from_root": "/articles/app-service/app-service-security-attributes.md",
             "redirect_url": "/azure/app-service/security-baseline",

.openpublishing.redirection.defender-for-cloud.json

@@ -980,6 +980,11 @@
             "redirect_url": "/azure/defender-for-cloud/view-and-remediate-vulnerability-registry-images",
             "redirect_document_id": false
         },
+        {
+            "source_path_from_root": "/articles/defender-for-cloud/management-groups-roles.md",
+            "redirect_url": "/azure/governance/management-groups/overview",
+            "redirect_document_id": false
+        },
         {
             "source_path_from_root": "/articles/defender-for-cloud/how-to-migrate-to-built-in.md",
             "redirect_url": "/azure/defender-for-cloud/how-to-transition-to-built-in",

.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
         },
         {
@@ -4483,6 +4498,11 @@
             "redirect_url": "/azure/orbital/overview",
             "redirect_document_id": false
         },
+        {
+            "source_path_from_root": "/articles/update-manager/pre-post-events-common-scenarios.md",
+            "redirect_url": "/azure/update-manager/manage-pre-post-events",
+            "redirect_document_id": false
+        },
         {
             "source_path_from_root": "/articles/update-manager/whats-upcoming.md",
             "redirect_url": "/azure/update-manager/whats-new",

articles/ai-services/document-intelligence/concept-custom.md

@@ -54,7 +54,7 @@ To create a custom extraction model, label a dataset of documents with the value
 > Starting with version 4.0 (2024-02-29-preview) API, custom neural models now support **overlapping fields** and **table, row and cell level confidence**.
 >
 
-The custom neural (custom document) model uses deep learning models and  base model trained on a large collection of documents. This model is then fine-tuned or adapted to your data when you train the model with a labeled dataset. Custom neural models support structured, semi-structured, and unstructured documents to extract fields. Custom neural models currently support English-language documents. When you're choosing between the two model types, start with a neural model to determine if it meets your functional needs. See [neural models](concept-custom-neural.md) to learn more about custom document models.
+The custom neural (custom document) model uses deep learning models and  base model trained on a large collection of documents. This model is then fine-tuned or adapted to your data when you train the model with a labeled dataset. Custom neural models support structured, semi-structured, and unstructured documents to extract fields. When you're choosing between the two model types, start with a neural model to determine if it meets your functional needs. See [neural models](concept-custom-neural.md) to learn more about custom document models.
 
 ### Custom template model
 
@@ -131,7 +131,7 @@ The `build custom model` operation adds support for the *template* and *neural*
 
 * Template models only accept documents that have the same basic page structure—a uniform visual appearance—or the same relative positioning of elements within the document.
 
-* Neural models support documents that have the same information, but different page structures. Examples of these documents include United States W2 forms, which share the same information, but vary in appearance across companies. Neural models currently only support English text.
+* Neural models support documents that have the same information, but different page structures. Examples of these documents include United States W2 forms, which share the same information, but vary in appearance across companies.
 
 This table provides links to the build mode programming language SDK references and code samples on GitHub:
 

articles/ai-services/language-support.md

@@ -7,7 +7,7 @@ author: laujan
 manager: nitinme
 ms.service: azure-ai-services
 ms.topic: conceptual
-ms.date: 07/18/2023
+ms.date: 07/08/2024
 ms.author: lajanuar
 ---
 
@@ -25,7 +25,7 @@ The following table provides links to language support reference articles by sup
 |![Document Intelligence icon](~/reusable-content/ce-skilling/azure/media/ai-services/document-intelligence.svg)</br>[Document Intelligence](./document-intelligence/language-support.md) | Turn documents into intelligent data-driven solutions. |
 |![Immersive Reader icon](media/service-icons/immersive-reader.svg)</br>[Immersive Reader](./immersive-reader/language-support.md) | Help users read and comprehend text. |
 |![Language icon](~/reusable-content/ce-skilling/azure/media/ai-services/language.svg)</br>[Language service](./language-service/concepts/language-support.md) | Build apps with industry-leading natural language understanding capabilities. |
-|![Language Understanding icon](media/service-icons/luis.svg)</br>[Language Understanding (LUIS)](./luis/luis-language-support.md) (retired) | Understand natural language in your apps. |
+|![Language Understanding icon](media/service-icons/luis.svg)</br>[Language Understanding (`LUIS`)](./luis/luis-language-support.md) (retired) | Understand natural language in your apps. |
 |![QnA Maker icon](media/service-icons/luis.svg)</br>[QnA Maker](./qnamaker/overview/language-support.md) (retired) | Distill information into easy-to-navigate questions and answers. |
 |![Speech icon](~/reusable-content/ce-skilling/azure/media/ai-services/speech.svg)</br>[Speech Service](./speech-service/language-support.md)| Configure speech-to-text, text-to-speech, translation, and speaker recognition applications. |
 |![Translator icon](~/reusable-content/ce-skilling/azure/media/ai-services/translator.svg)</br>[Translator](./translator/language-support.md) |  Translate more than 100 in-use, at-risk, and endangered languages and dialects.|
@@ -46,4 +46,4 @@ These Azure AI services are language agnostic and don't have limitations based o
 ## See also
 
 * [What are Azure AI services?](./what-are-ai-services.md)
-* [Create an account](multi-service-resource.md?pivots=azportal)
+* [How to create an account](multi-service-resource.md?pivots=azportal)

articles/ai-services/openai/concepts/model-retirements.md

@@ -4,7 +4,7 @@ titleSuffix: Azure OpenAI
 description: Learn about the model deprecations and retirements in Azure OpenAI.
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 06/19/2024
+ms.date: 07/10/2024
 ms.custom: 
 manager: nitinme
 author: mrbullwinkle
@@ -25,16 +25,43 @@ Azure OpenAI Service models are continually refreshed with newer and more capabl
 * Deprecation
 	* When a model is deprecated, it's no longer available for new customers. It continues to be available for use by customers with existing deployments until the model is retired.
 
-## Preretirement notification
+## Notifications
 
 Azure OpenAI notifies customers of active Azure OpenAI Service deployments for models with upcoming retirements. We notify customers of upcoming retirements as follows for each deployment:
 
-* At least 60 days before retirement 
-* At least 30 days before retirement 
-* At retirement
+1. At model launch, we programmatically designate a "not sooner than" retirement date (typically six months to one year out).
+2. At least 60 days notice before model retirement for Generally Available (GA) models.
+3. At least 14 days notice before preview model version upgrades.  
 
 Retirements are done on a rolling basis, region by region.
 
+## Model availability
+
+1. At least one year of model availability for GA models after the release date of a model in at least one region worldwide
+2. For global deployments, all future model versions starting with `gpt-4o` and `gpt-4 0409` will be available with their (`N`) next succeeding model (`N+1`) for comparison together. 
+1. Customers have 60 days to try out a new GA model in at least one global, or standard region, before any upgrades happen to a newer GA model.  
+
+### Considerations for the Azure public cloud
+
+Be aware of the following: 
+
+1. All model version combinations will **not** be available in all regions.
+2. Model version `N` and `N+1` might not always be available in the same region. 
+3. GA model version `N` might upgrade to a future model version `N+X` in some regions based on capacity limitations, and without the new model version `N+X` separately being available to test in the same region. The new model version will be available to test in other regions before any upgrades are scheduled.   
+4. Preview model versions and GA versions of the same model won't always be available to test together in the same region. There will be preview and GA versions available to test in different regions. 
+5.	We reserve the right to limit future customers using a particular region to balance service quality for existing customers.
+6.	As always at Microsoft, security is of the utmost importance. If a model or model version is found to have compliance or security issues, we reserve the right to invoke the need to do emergency retirements. See the terms of service for more information.
+
+### Special considerations for Azure Government clouds
+
+1.	Global standard deployments won't be available in government clouds.
+2.	Not all models or model versions available in commercial / public cloud will be available in government clouds.
+3.	In the Azure Government clouds, we intend to support only one version of a given model at a time.
+    1. For example only one version of `gpt-35-turbo 0125` and `gpt-4o (2024-05-13)`.
+4.	There will however be a 30 day overlap between new model versions, where more than two will be available.
+    1. For example if `gpt-35-turbo 0125` or `gpt-4o (2024-05-13)` is updated to a future version, or
+    2. for model family changes beyond version updates, such as when moving from `gpt-4 1106-preview` to `gpt-4o (2024-05-13)`. 
+
 ### Who is notified of upcoming retirements
 
 Azure OpenAI notifies those who are members of the following roles for each subscription with a deployment of a model with an upcoming retirement.

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/ai-services/speech-service/how-to-configure-azure-ad-auth.md

@@ -103,7 +103,7 @@ The token context must be set to "https://cognitiveservices.azure.com/.default".
 ::: zone-end
 
 ::: zone pivot="programming-language-python"
-To get a Microsoft Entra access token in Java, use the [Azure Identity Client Library](/python/api/overview/azure/identity-readme).
+To get a Microsoft Entra access token in Python, use the [Azure Identity Client Library](/python/api/overview/azure/identity-readme).
 
 Here's an example of using Azure Identity to get a Microsoft Entra access token from an interactive browser:
 ```Python