fix links/warnings

Author: lgayhardt

articles/ai-studio/how-to/monitor-applications.md

@@ -31,20 +31,20 @@ In this section, learn how to monitor your generative AI applications using Azur
 
 The first step in continuously monitoring your application is to ensure that its telemetry data is captured and stored for analysis. To accomplish this, you'll need to instrument your generative AI application’s code to use the [Azure AI Tracing package](./develop/trace-local-sdk.md) to log trace data to an Azure Monitor Application Insights resource of your choice. This package fully conforms with the OpenTelemetry standard for observability. After you have instrumented your application's code, the trace data will be logged to your Application Insights resource.
 
-After you have included tracing in your application code, you can view the trace data in Azure AI Foundry or in your Azure Monitor Application Insights resource. To learn more about how to do this, see [monitor your generative AI application](monitor-applications.md#monitor-your-generative-ai-application).
+After you have included tracing in your application code, you can view the trace data in Azure AI Foundry or in your Azure Monitor Application Insights resource. To learn more about how to do this, see [monitor your generative AI application](#monitor-your-generative-ai-application).
 
 ### Set up online evaluation
 
-After setting up tracing for your generative AI application, set up [online evaluation with the Azure AI Foundry SDK](./develop/online-evaluation.md) to continuously evaluate your trace data as it is collected. Doing so will enable you to monitor your application's performance in production over time.
+After setting up tracing for your generative AI application, set up [online evaluation with the Azure AI Foundry SDK](./online-evaluation.md) to continuously evaluate your trace data as it is collected. Doing so will enable you to monitor your application's performance in production over time.
 
 > [!NOTE]
-> If you have multiple AI applications logging trace data to the same Azure Monitor Application Insights resource, it's recommended to use the service name to differentiate between application data in Application Insights. To learn how to set the service name, see [Azure AI Tracing](./develop/trace-local-sdk.md). To learn how to query for the service name within your online evaluation configuration, see [using service name in trace data](./develop/online-evaluation.md#using-service-name-in-trace-data).
+> If you have multiple AI applications logging trace data to the same Azure Monitor Application Insights resource, it's recommended to use the service name to differentiate between application data in Application Insights. To learn how to set the service name, see [Azure AI Tracing](./develop/trace-local-sdk.md). To learn how to query for the service name within your online evaluation configuration, see [using service name in trace data](./online-evaluation.md#using-service-name-in-trace-data).
 
 ### Monitor your generative AI application with Azure Monitor Application Insights
 
 In this section, you learn how Azure AI integrates with Azure Monitor Application Insights to give you an out-of-the-box dashboard view that is tailored with insights regarding your generative AI app so you can stay updated with the latest status of your application.
 
-### Insights for your generative AI application  
+#### Insights for your generative AI application  
 
 If you haven’t set this up, here are some quick steps:
 
@@ -80,7 +80,7 @@ You can also share this workbook with your team so they stay informed with the l
 
 ## Related content
 
-- [How to run evaluations online with the Azure AI Foundry SDK](./develop/online-evaluation.md)
+- [How to run evaluations online with the Azure AI Foundry SDK](./online-evaluation.md)
 - [Trace your application with Azure AI Inference SDK](./develop/trace-local-sdk.md)
 - [Visualize your traces](./develop/visualize-traces.md)
 - [Evaluation of Generative AI Models & Applications](../concepts/evaluation-approach-gen-ai.md)

articles/ai-studio/how-to/online-evaluation.md

@@ -320,7 +320,7 @@ project_client.evaluations.disable_schedule(name)
 
 ## Related content
 
-- [Monitor your generative AI applications](./develop/monitor.applications.md)
+- [Monitor your generative AI applications](./monitor.applications.md)
 - [Trace your application with Azure AI Inference SDK](./develop/trace-local-sdk.md)
 - [Visualize your traces](./develop/visualize-traces.md)
 - [Evaluation of Generative AI Models & Applications](../concepts/evaluation-approach-gen-ai.md)