Merge branch 'main' into release-ignite-document-intelligence-v4

Author: v-alje

articles/ai-services/anomaly-detector/whats-new.md

@@ -84,7 +84,7 @@ We have also added links to some user-generated content. Those items will be mar
 
 ### April 2021
 
-* [IoT Edge module](https://azuremarketplace.microsoft.com/marketplace/apps/azure-cognitive-service.edge-anomaly-detector) (univariate) published.
+* IoT Edge module (univariate) published.
 * Anomaly Detector (univariate) available in Microsoft Azure operated by 21Vianet (China East 2).
 * Multivariate anomaly detector APIs preview in selected regions (West US 2, West Europe).
 

articles/ai-services/content-safety/whats-new.md

@@ -21,7 +21,7 @@ Learn what's new in the service. These items might be release notes, videos, blo
 ### Upcoming deprecations
 
 To align with Content Safety versioning and lifecycle management policies, the following versions are scheduled for deprecation:
-* **Effective October 28, 2024**: All versions except `2024-09-01`, `2024-09-15-preview`, and `2024-09-30-preview` will be deprecated and no longer supported. We encourage users to transition to the latest available versions to continue receiving full support and updates. If you have any questions about this process or need assistance with the transition, please reach out to our support team.
+* **Effective March 1st, 2025**: All versions except `2024-09-01`, `2024-09-15-preview`, and `2024-09-30-preview` will be deprecated and no longer supported. We encourage users to transition to the latest available versions to continue receiving full support and updates. If you have any questions about this process or need assistance with the transition, please reach out to our support team.
 
 ## September 2024
 

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

@@ -4,7 +4,7 @@ titleSuffix: Azure OpenAI
 description: Learn about the different model capabilities that are available with Azure OpenAI.
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 10/25/2024
+ms.date: 12/05/2024
 ms.custom: references_regions, build-2023, build-2023-dataai, refefences_regions
 manager: nitinme
 author: mrbullwinkle #ChrisHMSFT
@@ -388,7 +388,13 @@ All deployments can perform the exact same inference operations, however the bil
 
 ### Data zone standard model availability
 
-[!INCLUDE [Global batch](../includes/model-matrix/datazone-standard.md)]
+[!INCLUDE [Data zone standard](../includes/model-matrix/datazone-standard.md)]
+
+# [Data Zone Provisioned Managed](#tab/datazone-provisioned-managed)
+
+### Data zone provisioned managed model availability
+
+[!INCLUDE [Global data zone provisioned managed](../includes/model-matrix/datazone-provisioned-managed.md)]
 
 # [Standard](#tab/standard)
 

articles/ai-services/openai/concepts/provisioned-reservation-update.md

@@ -0,0 +1,71 @@
+---
+title: 'Azure OpenAI Provisioned December 2024 Update'
+titleSuffix: Azure OpenAI
+description: Learn about new Provisioned skus and commercial changes for Provisioned offers
+manager: chrhoder
+ms.service: azure-ai-openai
+ms.custom:
+ms.topic: how-to
+ms.date: 11/25/2024
+author: sydneemayers
+ms.author: sydneemayers
+recommendations: false
+---
+# Azure OpenAI provisioned December 2024 update 
+
+In early December, 2024, Microsoft launched several changes to the provisioned offering. These changes include:
+- A new deployment type, **data zone provisioned**.
+- Updated hourly pricing for global and data zone provisioned deployment types
+- New Azure Reservations for global and data zone provisioned deployment types
+
+This article is intended for existing users of the provisioned throughput offering. New customers should refer to the [Azure OpenAI provisioned onboarding guide](../how-to/provisioned-throughput-onboarding.md).
+
+## What's changing?
+
+The changes below apply to the global provisioned, data zone provisioned, and provisioned deployment types.
+
+> [!IMPORTANT]
+> The changes in this article do not apply to the older *"Provisioned Classic (PTU-C)"* offering. They only affect the Provisioned (also known as the Provisioned Managed) offering.
+
+### Data zone provisioned
+Data zone provisioned deployments are available in the same Azure OpenAI resource as all other Azure OpenAI deployment types but allow you to leverage Azure's global infrastructure to dynamically route traffic to the data center within the Microsoft defined data zone with the best availability for each request. Data zone provisioned deployments provide reserved model processing capacity for high and predictable throughput using Azure global infrastructure within the Microsoft defined data zone. Data zone deployments are supported for gpt-4o and gpt-4o-mini model families. 
+
+For more information, see the [deployment types guide](https://aka.ms/aoai/docs/deployment-types).
+
+### New hourly pricing for global and data zone provisioned deployments
+In August 2024, Microsoft announced that Provisioned deployments would move to a new [hourly payment model](./provisioned-migration.md) with the option to purchase Azure Reservations to support additional discounts. In December's provisioned update, we will be introducing differentiated hourly pricing across global provisioned, data zone provisioned, and provisioned deployment types. For more information on the hourly price for each provisioned deployment type, see the [Pricing details page](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/). 
+
+### New Azure Reservations for global and data zone provisioned deployments
+In addition to the updates for the hourly payment model, new Azure Reservations will be introduced specifically for global and data zone provisioned deployment types. With these new Azure Reservations, every provisioned deployment type will have a separate Azure Reservation that can be purchased to support additional discounts. The mapping between each provisioned deployment type and the associated Azure Reservation are as follows:
+
+| Provisioned deployment type | Sku name in code  | Azure Reservation product name |
+|---|---|---|
+| Global provisioned | `GlobalProvisionedManaged`  | Provisioned Managed Global  |
+| Data zone provisioned | `DataZoneProvisionedManaged`  | Provisioned Managed Data Zone  |
+| Provisioned | `ProvisionedManaged`  | Provisioned Managed Regional |
+
+> [!IMPORTANT]
+> Azure Reservations for Azure OpenAI provisioned offers are not interchangeable across deployment types. The Azure Reservation purchased must match the provisioned deployment type. If the Azure Reservation purchased does not match the provisioned deployment type, the provisioned deployment will default to the hourly payment model until a matching Azure Reservation product is purchased. For more information, see the [Azure Reservations for Azure OpenAI Service provisioned guidance](https://aka.ms/oai/docs/ptum-reservations).
+
+## Migrating existing deployments to global or data zone provisioned
+Existing customers of provisioned deployments can choose to migrate to global or data zone provisioned deployments to benefit from the lower deployment minimums, granular scale increments, or differentiated pricing available for these deployment types. To learn more about how global and data zone provisioned deployments handle data processing across Azure geographies, see the Azure OpenAI deployment [data processing documentation](https://aka.ms/aoai/docs/data-processing-locations).
+
+Two approaches are available for customers to migrate from provisioned deployments to global or data zone provisioned deployments. 
+
+### Zero downtime migration 
+The zero downtime migration approach allows customers to migrate their existing provisioned deployments to global or data zone provisioned deployments without interrupting the existing inference traffic on their deployment. This migration approach minimizes workload interruptions, but does require a customer to have multiple coexisting deployments while shifting traffic over. The process to migrate a provisioned deployment using the zero downtime migration approach is as follows:
+- Create a new deployment using the global or data zone provisioned deployment types in the target Azure OpenAI resource.
+- Transition traffic from the existing regional provisioned deployment type to the newly created global or data zone provisioned deployment until all traffic is offloaded from the existing regional provisioned deployment.
+- Once traffic is migrated over to the new deployment, validate that there are no inference requests being processed on the previous provisioned deployment by ensuring the Azure OpenAI Requests metric does not show any API calls made within 5-10 minutes of the inference traffic being migrated over to the new deployment. For more information on this metric, [see the Monitor Azure OpenAI documentation](https://aka.ms/aoai/docs/monitor-azure-openai).
+- Once you confirm that no inference calls have been made, delete the regional provisioned deployment.
+
+### Migration with downtime 
+The migration with downtime approach involves migrating existing provisioned deployments to global or data zone provisioned deployments while stopping any existing inference traffic on the original provisioned deployment. This migration approach does not require coexistence of multiple deployments to support but does require workload interruption to complete. The process to migrate a provisioned deployment using the migration with downtime approach is as follows:
+- Validate that there are no inference requests being processed on the previous provisioned deployment by ensuring the Azure OpenAI Requests metric does not show any API calls made within the last 5-10 minutes. For more information on this metric, [see the Monitor Azure OpenAI documentation](https://aka.ms/aoai/docs/monitor-azure-openai).
+- Once you confirm that no inference calls have been made, delete the regional provisioned deployment.
+- Create a new deployment using the global or data zone deployment types in the target Azure OpenAI resource.
+- Once your new deployment has succeeded, you may resume inference traffic on the new global or data zone deployment.
+
+## How do I migrate my existing Azure Reservation to the new Azure Reservation products?
+Azure Reservations for Azure OpenAI Service provisioned offers are specific to the provisioned deployment type. If the Azure Reservation purchased does not match the provisioned deployment type, the deployment will default to the hourly payment model. If you choose to migrate to global or data zone provisioned deployments, you may need to purchase a new Azure Reservation for these deployments to support additional discounts. For more information on how to purchase a new Azure Reservation or make changes to an existing Azure Reservation, see the [Azure Reservations for Azure OpenAI Service Provisioned guidance](https://aka.ms/aoai/reservation-transition).
+

articles/ai-services/openai/how-to/content-filters.md

@@ -1,22 +1,26 @@
 ---
-title: 'Use content filters (preview) with Azure OpenAI Service'
+title: 'Use content filters (preview) with Azure AI Foundry'
 titleSuffix: Azure OpenAI
-description: Learn how to use and configure the content filters that come with Azure OpenAI Service, including getting approval for gated modifications.
+description: Learn how to use and configure the content filters that come with Azure AI Foundry, including getting approval for gated modifications.
 #services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 10/04/2024
+ms.date: 12/05/2024
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
 ms.custom: FY25Q1-Linter
-# customer intent: As a developer, I want to learn how to configure content filters with Azure OpenAI Service so that I can ensure that my applications comply with our Code of Conduct.
+# customer intent: As a developer, I want to learn how to configure content filters with Azure AI Foundry so that I can ensure that my applications comply with our Code of Conduct.
 ---
 
-# How to configure content filters with Azure OpenAI Service
+# How to configure content filters with Azure AI Foundry
 
-The content filtering system integrated into Azure OpenAI Service runs alongside the core models, including DALL-E image generation models. It uses an ensemble of multi-class classification models to detect four categories of harmful content (violence, hate, sexual, and self-harm) at four severity levels respectively (safe, low, medium, and high), and optional binary classifiers for detecting jailbreak risk, existing text, and code in public repositories. The default content filtering configuration is set to filter at the medium severity threshold for all four content harms categories for both prompts and completions. That means that content that is detected at severity level medium or high is filtered, while content detected at severity level low or safe is not filtered by the content filters. Learn more about content categories, severity levels, and the behavior of the content filtering system [here](../concepts/content-filter.md). Jailbreak risk detection and protected text and code models are optional and off by default. For jailbreak and protected material text and code models, the configurability feature allows all customers to turn the models on and off. The models are by default off and can be turned on per your scenario. Some models are required to be on for certain scenarios to retain coverage under the [Customer Copyright Commitment](/legal/cognitive-services/openai/customer-copyright-commitment?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext).
+The content filtering system integrated into Azure AI Foundry runs alongside the core models, including DALL-E image generation models. It uses an ensemble of multi-class classification models to detect four categories of harmful content (violence, hate, sexual, and self-harm) at four severity levels respectively (safe, low, medium, and high), and optional binary classifiers for detecting jailbreak risk, existing text, and code in public repositories. 
+
+The default content filtering configuration is set to filter at the medium severity threshold for all four content harms categories for both prompts and completions. That means that content that is detected at severity level medium or high is filtered, while content detected at severity level low or safe is not filtered by the content filters. Learn more about content categories, severity levels, and the behavior of the content filtering system [here](../concepts/content-filter.md). 
+
+Jailbreak risk detection and protected text and code models are optional and off by default. For jailbreak and protected material text and code models, the configurability feature allows all customers to turn the models on and off. The models are by default off and can be turned on per your scenario. Some models are required to be on for certain scenarios to retain coverage under the [Customer Copyright Commitment](/legal/cognitive-services/openai/customer-copyright-commitment?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext).
 
 > [!NOTE]
 > All customers have the ability to modify the content filters and configure the severity thresholds (low, medium, high). Approval is required for turning the content filters partially or fully off. Managed customers only may apply for full content filtering control via this form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR). At this time, it is not possible to become a managed customer.
@@ -37,7 +41,7 @@ You can configure the following filter categories in addition to the default har
 
 |Filter category  |Status |Default setting  |Applied to prompt or completion?  |Description  |
 |---------|---------|---------|---------|---|
-|Prompt Shields for direct attacks (jailbreak)     |GA|    On     |   User prompt      |   Filters / annotates user prompts that might present a Jailbreak Risk. For more information about annotations, visit [Azure OpenAI Service content filtering](/azure/ai-services/openai/concepts/content-filter?tabs=python#annotations-preview). |
+|Prompt Shields for direct attacks (jailbreak)     |GA|    On     |   User prompt      |   Filters / annotates user prompts that might present a Jailbreak Risk. For more information about annotations, visit [Azure AI Foundry content filtering](/azure/ai-services/openai/concepts/content-filter?tabs=python#annotations-preview). |
 |Prompt Shields for indirect attacks  | GA| Off | User prompt | Filter / annotate Indirect Attacks, also referred to as Indirect Prompt Attacks or Cross-Domain Prompt Injection Attacks, a potential vulnerability where third parties place malicious instructions inside of documents that the generative AI system can access and process. Requires: [Document embedding and formatting](/azure/ai-services/openai/concepts/content-filter?tabs=warning%2Cuser-prompt%2Cpython-new#embedding-documents-in-your-prompt). |
 | Protected material - code |GA| On | Completion | Filters protected code or gets the example citation and license information in annotations for code snippets that match any public code sources, powered by GitHub Copilot. For more information about consuming annotations, see the [content filtering concepts guide](/azure/ai-services/openai/concepts/content-filter#annotations-preview) |
 | Protected material - text | GA| On | Completion | Identifies and blocks known text content from being displayed in the model output (for example, song lyrics, recipes, and selected web content).  |
@@ -60,5 +64,5 @@ We recommend informing your content filtering configuration decisions through an
 ## Related content
 
 - Learn more about Responsible AI practices for Azure OpenAI: [Overview of Responsible AI practices for Azure OpenAI models](/legal/cognitive-services/openai/overview?context=/azure/ai-services/openai/context/context).
-- Read more about [content filtering categories and severity levels](../concepts/content-filter.md) with Azure OpenAI Service.
+- Read more about [content filtering categories and severity levels](../concepts/content-filter.md) with Azure AI Foundry.
 - Learn more about red teaming from our: [Introduction to red teaming large language models (LLMs) article](../concepts/red-teaming.md).

articles/ai-services/openai/how-to/dall-e.md

@@ -24,13 +24,13 @@ OpenAI's DALL-E models generate images based on user-provided text prompts. This
 #### [DALL-E 3](#tab/dalle3)
 
 - An Azure subscription. You can [create one for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?icid=ai-services).
-- An Azure OpenAI resource created in the *Sweden Central* region. For more information, see [Create and deploy an Azure OpenAI Service resource](../how-to/create-resource.md).
-- Deploy a *dall-e-3* model with your Azure OpenAI resource.
+- An Azure OpenAI resource created in a supported region. See [Region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability).
+- - Deploy a *dall-e-3* model with your Azure OpenAI resource.
 
 #### [DALL-E 2 (preview)](#tab/dalle2)
 
 - An Azure subscription. You can [create one for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?icid=ai-services).
-- An Azure OpenAI resource created in the *East US* region. For more information, see [Create and deploy an Azure OpenAI Service resource](../how-to/create-resource.md).
+- An Azure OpenAI resource created in a supported region. See [Region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability). For more information, see [Create and deploy an Azure OpenAI Service resource](../how-to/create-resource.md).
 
 ---