fixes

Author: aahill

articles/ai-foundry/openai/azure-government.md

@@ -3,6 +3,7 @@ title: Azure OpenAI in Azure Government
 titleSuffix: Azure OpenAI
 description: Learn how to use Azure OpenAI in the Azure Government cloud.
 author: challenp
+ms.author: chaparker
 ms.date: 6/25/2025
 ms.service: azure-ai-openai
 ms.topic: how-to

articles/ai-foundry/openai/concepts/assistants.md

@@ -60,8 +60,6 @@ Before using assistants, you need:
 - A [compatible model](../concepts/models.md#assistants-preview) deployed. For more information about model deployment, see the [resource deployment guide](../how-to/create-resource.md).
 - An [Azure AI project](../../../ai-foundry/how-to/create-projects.md) in Azure AI Foundry portal.
 
-We provide a walkthrough of the Assistants playground in our [quickstart guide](../assistants-quickstart.md). This provides a no-code environment to test out the capabilities of assistants.
-
 ## Assistants components
 
 :::image type="content" source="../media/assistants/assistants-overview.png" alt-text="A diagram showing the components of an assistant." lightbox="../media/assistants/assistants-overview.png":::
@@ -83,7 +81,7 @@ We strongly recommend the following data access controls:
 - Implement authorization. Before performing reads or writes on assistants, threads, messages, and files, ensure that the end-user is authorized to do so.
 - Restrict Azure OpenAI resource and API key access. Carefully consider who has access to Azure OpenAI resources where assistants are being used and associated API keys.
 - Routinely audit which accounts/individuals have access to the Azure OpenAI resource. API keys and resource level access enable a wide range of operations including reading and modifying messages and files.
-- Enable [diagnostic settings](../how-to/monitoring.md#configure-diagnostic-settings) to allow long-term tracking of certain aspects of the Azure OpenAI resource's activity log.
+- Enable [diagnostic settings](../how-to/monitor-openai.md#configure-diagnostic-settings) to allow long-term tracking of certain aspects of the Azure OpenAI resource's activity log.
 
 ## Parameters
 

articles/ai-foundry/openai/concepts/provisioned-throughput.md

@@ -116,7 +116,7 @@ If an acceptable region isn't available to support the desired model, version, a
 
 ### How can I monitor capacity?
 
-The [Provisioned-Managed Utilization V2 metric](../how-to/monitoring.md#azure-openai-metrics) in Azure Monitor measures a given deployments utilization on 1-minute increments. All provisioned deployment types are optimized to ensure that accepted calls are processed with a consistent model processing time (actual end-to-end latency is dependent on a call's characteristics).  
+The [Provisioned-Managed Utilization V2 metric](../how-to/monitor-openai.md#azure-openai-metrics) in Azure Monitor measures a given deployments utilization on 1-minute increments. All provisioned deployment types are optimized to ensure that accepted calls are processed with a consistent model processing time (actual end-to-end latency is dependent on a call's characteristics).  
 
 ### How utilization performance works
 

articles/ai-foundry/openai/faq.yml

@@ -303,7 +303,7 @@ sections:
       - question: |
           What are some examples or other resources I can use to learn about Assistants?  
         answer: |
-          See the [Conceptual](./concepts/assistants.md), [quickstart](./assistants-quickstart.md), [how-to](./how-to/assistant.md) articles for information on getting started and using Assistants. You can also check out Azure OpenAI Assistants code samples on [GitHub](https://github.com/Azure-Samples/azureai-samples/tree/main/scenarios/Assistants).
+          See the [Conceptual](./concepts/assistants.md), [how-to](./how-to/assistant.md) articles for information on getting started and using Assistants. You can also check out Azure OpenAI Assistants code samples on [GitHub](https://github.com/Azure-Samples/azureai-samples/tree/main/scenarios/Assistants).
   - name: Web app
     questions:
       - question: |

articles/ai-foundry/openai/how-to/assistant.md

@@ -67,10 +67,6 @@ An individual assistant can access up to 128 tools including [code interpreter](
 
 Files can be uploaded via Studio, or programmatically. The `file_ids` parameter is required to give tools like `code_interpreter` access to files. When using the File upload endpoint, you must have the `purpose` set to `assistants` to be used with the Assistants API.
 
-## Assistants playground
-
-We provide a walkthrough of the Assistants playground in our [quickstart guide](../assistants-quickstart.md). This provides a no-code environment to test out the capabilities of assistants.
-
 ## Assistants components
 
 | **Component** | **Description** |

articles/ai-foundry/openai/how-to/dynamic-quota.md

@@ -70,6 +70,6 @@ dynamic quota is less likely to be engaged for your deployment if it runs in hea
 ## Next steps
 
 * Learn more about how [quota works](./quota.md).
-* Learn more about [monitoring Azure OpenAI](./monitoring.md).
+* Learn more about [monitoring Azure OpenAI](./monitor-openai.md).
 
 

articles/ai-foundry/openai/how-to/latency.md

@@ -141,12 +141,12 @@ We recommend measuring your overall throughput on a deployment with two measures
 -	Calls per minute: The number of API inference calls you're making per minute. This can be measured in Azure-monitor using the Azure OpenAI Requests metric and splitting by the ModelDeploymentName
 -	Total Tokens per minute: The total number of tokens being processed per minute by your deployment. This includes prompt & generated tokens. This is often further split into measuring both for a deeper understanding of deployment performance. This can be measured in Azure-Monitor using the Processed Inference tokens metric. 
 
-You can learn more about [Monitoring the Azure OpenAI](./monitoring.md).
+You can learn more about [Monitoring the Azure OpenAI](./monitor-openai.md).
 
 ## How to measure per-call latency
 The time it takes for each call depends on how long it takes to read the model, generate the output, and apply content filters. The way you measure the time will vary if you're using streaming or not. We suggest a different set of measures for each case. 
 
-You can learn more about [Monitoring the Azure OpenAI](./monitoring.md).
+You can learn more about [Monitoring the Azure OpenAI](./monitor-openai.md).
 
 ### Non-Streaming:
 -	 End-to-end Request Time: The total time taken to generate the entire response for non-streaming requests, as measured by the API gateway. This number increases as prompt and generation size increases.

articles/ai-foundry/openai/how-to/provisioned-get-started.md

@@ -201,7 +201,7 @@ You can find the utilization measure in the Azure-Monitor section for your resou
 
 :::image type="content" source="../media/provisioned/azure-monitor-utilization.jpg" alt-text="Screenshot of the provisioned managed utilization on the resource's metrics blade in the Azure portal." lightbox="../media/provisioned/azure-monitor-utilization.jpg":::
 
-For more information about monitoring your deployments, see the [Monitoring Azure OpenAI](./monitoring.md) page.
+For more information about monitoring your deployments, see the [Monitoring Azure OpenAI](./monitor-openai.md) page.
 
 
 ## Handling high utilization

articles/ai-foundry/openai/index.yml

@@ -50,8 +50,6 @@ landingContent:
              url: whisper-quickstart.md
            - text: Text to speech (preview)
              url: text-to-speech-quickstart.md
-           - text: Assistants
-             url: assistants-quickstart.md 
       - linkListType: tutorial
         links:
          - text: Embeddings

articles/ai-foundry/openai/overview.md

@@ -44,7 +44,7 @@ Start with the [Create and deploy an Azure OpenAI resource](./how-to/create-reso
     - Try out the [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) playgrounds to explore the capabilities of the models. 
     - You can also just start making API calls to the service using the REST API or SDKs.
 
-    For example, you can try [real-time audio](./realtime-audio-quickstart.md) and [assistants](./assistants-quickstart.md) in the playgrounds or via code.
+    For example, you can try [real-time audio](./realtime-audio-quickstart.md) in the playgrounds or via code.
 
 > [!NOTE]
 > A Limited Access registration form is required to access some Azure OpenAI models or features. Learn more on the [Azure OpenAI Limited Access page](/azure/ai-foundry/responsible-ai/openai/limited-access).