Moved the recommendation from AppInsights to Specialized workload-AI

azure-resources/Insights/components/recommendations.yaml

@@ -14,22 +14,3 @@
   learnMoreLink:
     - name: Migrate an Application Insights classic resource to a workspace-based resource
       url: "https://learn.microsoft.com/en-us/azure/azure-monitor/app/convert-classic-resource"
-
-- description: Create Application insights for Machine learning workspace in both the regions
-  aprlGuid: 89928e61-bba8-4c25-99c5-a06a09849ecc
-  recommendationTypeId: null
-  recommendationControl: DisasterRecovery
-  recommendationImpact: Medium
-  recommendationResourceType: Microsoft.Insights/components
-  recommendationMetadataState: Active
-  longDescription: |
-    Create Application Insights for machine learning workspace in both regions. To adjust the data-retention period, update and manage data retention in a Log Analytics workspace.
-  potentialBenefits: Provides monitoring and data retention in DR region
-  pgVerified: false
-  automationAvailable: true
-  tags: null
-  learnMoreLink:
-    - name: Data collection, retention, and storage in Application Insights
-      url: "https://learn.microsoft.com/en-us/azure/azure-monitor/logs/data-retention-configure?tabs=portal-3%2Cportal-1%2Cportal-2"
-    - name: Failover for business continuity and disaster recovery
-      url: "https://learn.microsoft.com/en-us/azure/machine-learning/how-to-high-availability-machine-learning?view=azureml-api-2"

azure-resources/Insights/dataCollectionEndpoints/_index.md

@@ -1,7 +1,7 @@
 ---
 title: dataCollectionEndpoints
 geekdocCollapseSection: true
-geekdocHidden: false
+geekdocHidden: true
 ---
 
 {{< azure-resources-recommendationlist name="azure-resources-recommendationlist" >}}

azure-specialized-workloads/ai/_index.md

@@ -13,8 +13,6 @@ geekdocHidden: false
 | [Deploy a PAYG instance of the model with provisioned throughput to manage overflow effectively](../../../Azure-Proactive-Resiliency-Library-v2/azure-resources/CognitiveServices/accounts/#deploy-a-PAYG-instance-of-the-model-with-provisioned-throughput-to-manage-overflow-effectively) | CognitiveServices  |   accounts    |
 | [Ensure that models are deployed using Global batch for large scale processing](../../../Azure-Proactive-Resiliency-Library-v2/azure-resources/CognitiveServices/accounts/#ensure-that-models-are-deployed-using-global-batch-for-large-scale-processing)                                   | CognitiveServices  |   accounts    |
 | [Ensure AOAI models are deployed using Data Zone Standard for data residency requirements](../../../Azure-Proactive-Resiliency-Library-v2/azure-resources/CognitiveServices/accounts/#ensure-aoai-models-are-deployed-using-data-zone-standard-for-data-residency-requirements)             | CognitiveServices  |   accounts    |
-| [Enable Application insights to monitor online endpoints for Machine learning](../../../Azure-Proactive-Resiliency-Library-v2/azure-resources/Insights/dataCollectionEndpoints/#enable-application-insights-to-monitor-online-endpoints-for-machine-learning)             | Insights  |   dataCollectionEndpoints    |
-| [Create Application insights for Machine learning workspace in both the regions](../../../Azure-Proactive-Resiliency-Library-v2/azure-resources/Insights/components/#create-application-insights-for-machine-learning-workspace-in-both-the-regions)             | Insights  |   components    |
 
 <br>
 

azure-specialized-workloads/ai/recommendations.yaml

@@ -0,0 +1,35 @@
+- description: Enable Application insights to monitor online endpoints for Azure Machine learning
+  aprlGuid: 47176883-2602-455b-97f0-6c6a371bf928
+  recommendationTypeId: null
+  recommendationControl: MonitoringAndAlerting
+  recommendationImpact: Medium
+  recommendationResourceType: Microsoft.Subscription/subscriptions
+  recommendationMetadataState: Active
+  longDescription: |
+    Azure Machine Learning uses integration with Azure Monitor to monitor metrics and logs for online endpoints. Use the built-in features of Application Insights (such as Live metrics, Transaction search, Failures, and Performance) for further analysis.
+  potentialBenefits: Monitoring endpoints gives visibility into metrics and logs
+  pgVerified: false
+  automationAvailable: false
+  tags: AI
+  learnMoreLink:
+    - name: Monitor online endpoints using Application Insights
+      url: "https://learn.microsoft.com/en-us/azure/machine-learning/how-to-monitor-online-endpoints?view=azureml-api-2#using-application-insights"
+
+- description: Create Application insights for Machine learning workspace in both the regions
+  aprlGuid: 89928e61-bba8-4c25-99c5-a06a09849ecc
+  recommendationTypeId: null
+  recommendationControl: DisasterRecovery
+  recommendationImpact: Medium
+  recommendationResourceType: Microsoft.Subscription/subscriptions
+  recommendationMetadataState: Active
+  longDescription: |
+    Create Application Insights for machine learning workspace in both regions. To adjust the data-retention period, update and manage data retention in a Log Analytics workspace.
+  potentialBenefits: Provides monitoring and data retention in DR region
+  pgVerified: false
+  automationAvailable: false
+  tags: AI
+  learnMoreLink:
+    - name: Data collection, retention, and storage in Application Insights
+      url: "https://learn.microsoft.com/en-us/azure/azure-monitor/logs/data-retention-configure?tabs=portal-3%2Cportal-1%2Cportal-2"
+    - name: Failover for business continuity and disaster recovery
+      url: "https://learn.microsoft.com/en-us/azure/machine-learning/how-to-high-availability-machine-learning?view=azureml-api-2"