fixes

Author: aahill

articles/ai-foundry/agents/concepts/model-region-support.md

@@ -22,13 +22,13 @@ Azure OpenAI provides customers with choices on the hosting structure that fits
 - **Standard** is offered with a global deployment option, routing traffic globally to provide higher throughput.
 - **Provisioned** is also offered with a global deployment option, allowing customers to purchase and deploy provisioned throughput units across Azure global infrastructure.
 
-All deployments can perform the exact same inference operations, however the billing, scale, and performance are substantially different. To learn more about Azure OpenAI deployment types see [deployment types guide](/azure/ai-services/agents/ai-services/openai/how-to/deployment-types).
+All deployments can perform the exact same inference operations, however the billing, scale, and performance are substantially different. To learn more about Azure OpenAI deployment types see [deployment types guide](../../../ai-services/openai/how-to/deployment-types.md).
 
 Azure AI Foundry Agent Service supports the following Azure OpenAI models in the listed regions.
 
 > [!NOTE]
-> * The following table is for standard deployment availability. For information on Provisioned Throughput Unit (PTU) availability, see [provisioned throughput](/azure/ai-services/agents/ai-services/openai/concepts/provisioned-throughput) in the Azure OpenAI documentation. `GlobalStandard` customers also have access to [global standard models](/azure/ai-services/agents/ai-services/openai/concepts/modelsglobal-standard-model-availability). 
-> * [Hub based projects](/azure/ai-services/agents/ai-foundry/what-is-azure-ai-foundryproject-types) are limited to the following models: gpt-4o, gpt-4o-mini, gpt-4, gpt-35-turbo
+> * The following table is for standard deployment availability. For information on Provisioned Throughput Unit (PTU) availability, see [provisioned throughput](../../../ai-services/openai/concepts/provisioned-throughput.md) in the Azure OpenAI documentation. `GlobalStandard` customers also have access to [global standard models](../../../ai-services/openai/concepts/models.md#global-standard-model-availability). 
+> * [Hub based projects](../../what-is-azure-ai-foundry.md#project-types) are limited to the following models: gpt-4o, gpt-4o-mini, gpt-4, gpt-35-turbo
 
 | REGION           | o1 | o3-mini | gpt-4.1, 2025-04-14 | gpt-4.1-mini, 2025-04-14 | gpt-4.1-nano, 2025-04-14 | gpt-4o, 2024-05-13 | gpt-4o, 2024-08-06 | gpt-4o, 2024-11-20 | gpt-4o-mini, 2024-07-18 | gpt-4, 0613 | gpt-4, turbo-2024-04-09 | gpt-4-32k, 0613 | gpt-35-turbo, 1106 | gpt-35-turbo, 0125 |
 |------------------|----|---------|---------------------|--------------------------|--------------------------|--------------------|--------------------|--------------------|-------------------------|-------------|-------------------------|-----------------|--------------------|--------------------|

articles/ai-foundry/agents/faq.yml

@@ -12,7 +12,7 @@ metadata:
   author: aahill
 title: Azure AI Foundry Agent Service frequently asked questions
 summary: |
-  If you can't find answers to your questions in this document, and still need help check the [Azure AI services support options guide](/azure/ai-services/agents/ai-services/cognitive-services-support-options). Azure AI Foundry Agent Service is part of Azure AI services.
+  If you can't find answers to your questions in this document, and still need help check the [Azure AI services support options guide](../../ai-services/cognitive-services-support-options.md). Azure AI Foundry Agent Service is part of Azure AI services.
 sections:
   - name: General
     questions:

articles/ai-foundry/agents/how-to/metrics.md

@@ -0,0 +1,97 @@
+---
+title: Monitor Azure AI Foundry Agent Service
+description: Start here to learn how to use Azure Monitor to capture and analyze metrics for your Azure AI Foundry Agent Service.
+ms.date: 06/02/2025
+ms.custom: horz-monitor, subject-monitoring
+ms.topic: conceptual
+author: aahill
+ms.author: aahi
+ms.service: azure-ai-agent-service
+---
+
+# Monitor Azure AI Foundry Agent Service
+
+[!INCLUDE [horz-monitor-intro](~/reusable-content/ce-skilling/azure/includes/azure-monitor/horizontals/horz-monitor-intro.md)]
+
+Monitoring is available for agents in a [standard agent setup](../concepts/standard-agent-setup.md).
+
+> [!IMPORTANT]
+> Monitoring support is currently limited to Azure AI Foundry hubs. Azure AI Foundry projects are not supported.
+
+## Dashboards
+
+Azure AI Foundry Agent Service provides out-of-box dashboards. There are two key dashboards to monitor your resource: 
+
+- The metrics dashboard in the AI Foundry resource view 
+- The dashboard in the overview pane within the Azure portal 
+
+To access the monitoring dashboards, sign in to the [Azure portal](https://portal.azure.com) and then select **Monitoring** in the left navigation menu, then click **Metrics**.
+
+
+:::image type="content" source="../media/monitoring/dashboard.png" alt-text="Screenshot that shows out-of-box dashboards for a resource in the Azure portal." lightbox="../media/monitoring/dashboard.png" border="false":::
+
+## Azure monitor platform metrics
+
+Azure Monitor provides platform metrics for most services. These metrics are:
+
+* Individually defined for each namespace.
+* Stored in the Azure Monitor time-series metrics database.
+* Lightweight and capable of supporting near real-time alerting.
+* Used to track the performance of a resource over time.
+* Collection: Azure Monitor collects platform metrics automatically. No configuration is required.
+
+For a list of all metrics it's possible to gather for all resources in Azure Monitor, see [Supported metrics in Azure Monitor](/azure/azure-monitor/platform/metrics-supported).
+
+## Azure AI Foundry Agent Service metrics
+Azure AI Foundry Agent Service has commonality with a subset of Azure AI services. Here's a list of currently available metrics on Azure Monitor:
+
+| **Metric**      | **Name in REST API** | **Unit** | **Aggregation**                            | **Dimensions**                                         | **Time Grains** | **DS Export** |
+|-----------------|----------------------|----------|--------------------------------------------|--------------------------------------------------------|-----------------|---------------|
+| Agents          | `Agents`             | Count    | Average, Maximum, Minimum, Total (Sum)     | `EventType`                                            | PT1M            | No            |
+| IndexedFiles    | `IndexedFiles`       | Count    | Average, Maximum, Minimum, Total (Sum)     | `ErrorCode`, `Status`, `VectorStoreId`                | PT1M            | No            |
+| Messages        | `Messages`           | Count    | Average, Maximum, Minimum, Total (Sum)     | `EventType`, `ThreadId`                               | PT1M            | No            |
+| Runs            | `Runs`               | Count    | Average, Maximum, Minimum, Total (Sum)     | `AgentId`, `RunStatus`, `StatusCode`, `StreamType`    | PT1M            | No            |
+| Threads         | `Threads`            | Count    | Average, Maximum, Minimum, Total (Sum)     | `EventType`                                            | PT1M            | No            |
+| Tokens          | `Tokens`             | Count    | Average, Maximum, Minimum, Total (Sum)     | `AgentId`, `TokenType`                                | PT1M            | No            |
+| ToolCalls       | `ToolCalls`          | Count    | Average, Maximum, Minimum, Total (Sum)     | `AgentId`, `ToolName`                                 | PT1M            | No            |
+
+
+
+## Analyze monitoring data
+
+There are many tools for analyzing monitoring data.
+
+### Azure Monitor tools
+
+Azure Monitor supports the [metrics explorer](/azure/azure-monitor/essentials/metrics-getting-started), a tool in the Azure portal that allows you to view and analyze metrics for Azure resources. For more information, see Analyze metrics with Azure Monitor metrics explorer.
+
+## Azure Monitor export tools
+
+You can get data out of Azure Monitor into other tools by using the [REST API for metrics](/rest/api/monitor/operation-groups) to extract metric data from the Azure Monitor metrics database. The API supports filter expressions to refine the data retrieved. For more information, see [Azure Monitor REST API reference](/rest/api/monitor/filter-syntax).
+
+To get started with the REST API for Azure Monitor, see [Azure monitoring REST API walkthrough](/azure/azure-monitor/essentials/rest-api-walkthrough).
+
+## Alerts
+
+Azure Monitor alerts proactively notify you when specific conditions are found in your monitoring data. Alerts allow you to identify and address issues in your system before your customers notice them. For more information, see Azure Monitor alerts.
+
+There are many sources of common alerts for Azure resources. [The Azure Monitor Baseline Alerts (AMBA)](https://aka.ms/amba) site provides a semi-automated method of implementing important platform metric alerts, dashboards, and guidelines. The site applies to a continually expanding subset of Azure services, including all services that are part of the Azure Landing Zone (ALZ).
+
+The common alert schema standardizes the consumption of Azure Monitor alert notifications. For more information, see [Common alert schema](/azure/azure-monitor/alerts/alerts-common-schema).
+
+[Metric alerts](/azure/azure-monitor/alerts/alerts-types#metric-alerts) evaluate resource metrics at regular intervals. Metric alerts can also apply multiple conditions and dynamic thresholds.
+
+Every organization's alerting needs vary and can change over time. Generally, all alerts should be actionable and have a specific intended response if the alert occurs. If an alert doesn't require an immediate response, the condition can be captured in a report rather than an alert. Some use cases might require alerting anytime certain error conditions exist. In other cases, you might need alerts for errors that exceed a certain threshold for a designated time period.
+
+Depending on what type of application you're developing with your use of Azure AI Foundry Agent Service, [Azure Monitor Application Insights](/azure/azure-monitor/overview) might offer more monitoring benefits at the application layer.
+
+### Azure AI Foundry Agent Service alert rules
+
+You can set alerts for any metric listed in the [monitoring data reference](../reference/monitor-service.md).
+
+[!INCLUDE [horz-monitor-advisor-recommendations](~/reusable-content/ce-skilling/azure/includes/azure-monitor/horizontals/horz-monitor-advisor-recommendations.md)]
+
+## Related content
+
+- See [Monitoring data reference](../reference/monitor-service.md) for a reference of the metrics and other important values created for Azure AI Foundry Agent Service.
+- See [Monitoring Azure resources with Azure Monitor](/azure/azure-monitor/essentials/monitor-azure-resource) for general details on monitoring Azure resources.

articles/ai-foundry/agents/how-to/tools/azure-functions.md

@@ -27,7 +27,7 @@ To use all features of function calling including parallel functions, you need t
 ## Prerequisites
 
 * [Azure Functions Core Tools v4.x](/azure/azure-functions/functions-run-local)
-* [A deployed agent with the standard setup](/../../environment-setup.md#choose-your-setup)
+* [A deployed agent with the standard setup](../../environment-setup.md#choose-your-setup)
     > [!NOTE] 
     > The basic agent setup is not supported.
 * [Azurite](https://github.com/Azure/Azurite)

articles/ai-foundry/agents/how-to/triggers.md

@@ -60,13 +60,13 @@ Start by adding the Azure AI Foundry Agent service connectors to your workflow.
 
 1. Depending on your use-case, choose the actions you need. 
 
-    If you want to create a new [thread](./concepts/threads-runs-messages/md#threads) for each new event of your trigger, add the following in sequence: 
+    If you want to create a new [thread](../concepts/threads-runs-messages/md#threads) for each new event of your trigger, add the following in sequence: 
     1. Create thread 
     1. Create run 
     1. Get run 
     1. List messages 
 
-    If you want to create a new [run](./concepts/threads-runs-messages.md#runs) in the same thread for each new event, add the following in sequence: 
+    If you want to create a new [run](../concepts/threads-runs-messages.md#runs) in the same thread for each new event, add the following in sequence: 
 
     1. Create run 
     1. Get run
@@ -91,7 +91,7 @@ The **List Agent** connector only lists all the agents you have in your AI proje
 
 ## Configure the "create thread" connector
 
-The **create thread** connector creates a new [thread](./concepts/threads-runs-messages.md#threads), which is a conversation session between an Agent and a user. Threads store [messages](./concepts/threads-runs-messages.md#messages) and automatically handle truncation to fit content into a model's context. You can configure the **create thread** connector with the following:
+The **create thread** connector creates a new [thread](../concepts/threads-runs-messages.md#threads), which is a conversation session between an Agent and a user. Threads store [messages](../concepts/threads-runs-messages.md#messages) and automatically handle truncation to fit content into a model's context. You can configure the **create thread** connector with the following:
 
 **messages (optional)**: You can add the message you want the AI agent to respond to. Add the role as **user** for the message you want the agent to respond to. It can be the event payload from the trigger, for example a form response field. It can also be a constant message, for example always triggering with the phrase "*what is the latest AI news this week?*"  
 
@@ -120,7 +120,7 @@ The **create thread** connector creates a new [thread](./concepts/threads-runs-m
 
 ## Configure the "create run" connector
 
-The **create run** connector creates a new [run](./concepts/threads-runs-messages.md#runs), which is an activation of an Agent to begin running based on the contents of the thread. The agent uses its configuration (such as tool resources) and the thread's messages to perform tasks by calling models and tools. As part of a run, the agent appends messages to the thread. 
+The **create run** connector creates a new [run](../concepts/threads-runs-messages.md#runs), which is an activation of an Agent to begin running based on the contents of the thread. The agent uses its configuration (such as tool resources) and the thread's messages to perform tasks by calling models and tools. As part of a run, the agent appends messages to the thread. 
 
 To configure the **create run** connector, click on it and provide the following information:
 

articles/ai-foundry/agents/overview.md

@@ -103,7 +103,7 @@ Azure AI Foundry Agent Service provides a production-ready foundation for deploy
 | **2. Multi-agent coordination** | Built-in support for agent-to-agent messaging. |
 | **3. Tool orchestration** | Server-side execution and retry of [tool calls](how-to\tools\overview.md) with structured logging. No manual orchestration required. |
 | **4. Trust and safety** | Integrated [content filters](/azure/ai-services/agents/ai-services/openai/how-to/content-filters) help prevent misuse and mitigate prompt injection risks (XPIA). all outputs are policy-governed. |
-| **5. Enterprise integration** | Bring your own [storage](/azure/ai-services/agents/ai-services/agents/how-to/use-your-own-resourcesuse-an-existing-azure-cosmos-db-for-nosql-account-for-thread-storage), [Azure AI Search index](/azure/ai-services/agents/ai-services/agents/how-to/use-your-own-resourcesuse-an-existing-azure-ai-search-resource), and [virtual network](how-to\virtual-networks.md) to meet compliance needs. |
+| **5. Enterprise integration** | Bring your own [storage](./how-to/use-your-own-resources.md#use-an-existing-azure-cosmos-db-for-nosql-account-for-thread-storage), [Azure AI Search index](./how-to/use-your-own-resources.md#use-an-existing-azure-ai-search-resource), and [virtual network](how-to\virtual-networks.md) to meet compliance needs. |
 | **6. Observability and debugging** | Threads, tool invocations, and message traces are [fully traceable](concepts\tracing.md); [Application Insights integration](./how-to/metrics.md) for telemetry |
 | **7. Identity and policy control** | Built on Microsoft Entra with full support for RBAC, audit logs, and enterprise conditional access. |
 

articles/ai-foundry/agents/quotas-limits.md

@@ -30,7 +30,7 @@ The 2,000,000 agent limit refers to the maximum number of distinct Agent resourc
 
 ## Quotas and limits for Azure OpenAI models
 
-See the [Azure OpenAI](/azure/ai-services/agents/ai-services/openai/quotas-limits) for current quotas and limits for the Azure OpenAI models that you can use with Azure AI Foundry Agent Service. 
+See the [Azure OpenAI](../../ai-services/openai/quotas-limits.md) for current quotas and limits for the Azure OpenAI models that you can use with Azure AI Foundry Agent Service. 
 
 ## Next steps
 

articles/ai-foundry/agents/reference/monitor-service.md

@@ -0,0 +1,36 @@
+---
+title: Monitoring data reference for Azure AI Foundry Agent Service
+description: This article contains important reference material you need when you monitor Azure AI Foundry Agent Service by using Azure Monitor.
+ms.date: 05/05/2025
+ms.custom: horz-monitor, subject-monitoring
+ms.topic: reference
+author: aahill
+ms.author: aahi
+ms.service: azure-ai-agent-service
+---
+
+# Azure AI Foundry Agent Service monitoring data reference
+
+[!INCLUDE [horz-monitor-ref-intro](~/reusable-content/ce-skilling/azure/includes/azure-monitor/horizontals/horz-monitor-ref-intro.md)]
+
+See [Monitor Azure AI Foundry Agent Service](../how-to/metrics.md) for details on the data you can collect on your agents.
+
+## Metrics
+
+Here are the most important metrics we think you should monitor for Azure AI Foundry Agent Service. Later in this article is a longer list of all available metrics which contains more details on metrics in this shorter list. _See the below list for most up to date information. We're working on refreshing the tables in the following sections._
+
+- [Category: Agents](#category-agents)
+<!-- - Indexed files -->
+
+## Supported metrics
+
+This section lists all the automatically collected platform metrics for this service. These metrics are also part of the global list of [all platform metrics supported in Azure Monitor](/azure/azure-monitor/reference/supported-metrics/metrics-index#supported-metrics-per-resource-type).
+
+[!INCLUDE [horz-monitor-ref-metrics-tableheader](~/reusable-content/ce-skilling/azure/includes/azure-monitor/horizontals/horz-monitor-ref-metrics-tableheader.md)]
+[!INCLUDE [Microsoft.MachineLearningServices/workspaces](~/reusable-content/ce-skilling/azure/includes/azure-monitor/reference/metrics/microsoft-machinelearningservices-workspaces-metrics-include.md)]
+
+
+## Related content
+
+- See [Monitor Azure AI Foundry Agent Service](../how-to/metrics.md) for a description of monitoring Azure AI Foundry Agent Service.
+- See [Monitor Azure resources with Azure Monitor](/azure/azure-monitor/essentials/monitor-azure-resource) for details on monitoring Azure resources.

articles/ai-foundry/agents/whats-new.md

@@ -78,7 +78,7 @@ You can now use the Azure AI Foundry Agent Service in the [Azure AI Foundry](htt
 
 ### Azure AI Service public preview
 
-Azure AI Service is now available in preview. The service builds off of the [Assistants API](/azure/ai-services/agents/ai-services/openai/how-to/assistant) in Azure OpenAI, and offers several additional features, such as:
+Azure AI Service is now available in preview. The service builds off of the Assistants API in Azure OpenAI, and offers several additional features, such as:
 
 * Several [additional tools](how-to\tools\overview.md) to enhance your AI agents' functionality, such as the ability to use Bing and as a knowledge source and call functions. 
 * The ability to use non Azure OpenAI [models](concepts\model-region-support.md):