Merge pull request #209204 from santiagxf/santiagxf/aml-mlflow-azurechina

Update how-to-use-mlflow-azure-databricks.md

Author: prmerger-automator[bot]

articles/machine-learning/how-to-use-mlflow-azure-databricks.md

@@ -54,16 +54,19 @@ By default, dual-tracking is configured for you when you linked your Azure Datab
 
 Linking your ADB workspace to your Azure Machine Learning workspace enables you to track your experiment data in the Azure Machine Learning workspace and Azure Databricks workspace at the same time. This is referred as Dual-tracking.
 
+> [!WARNING]
+> Dual-tracking in a [private link enabled Azure Machine Learning workspace](how-to-configure-private-link.md) is not supported by the moment. Configure [exclusive tracking with your Azure Machine Learning workspace](#tracking-exclusively-on-azure-machine-learning-workspace) instead.
+> 
+> [!WARNING]
+> Dual-tracking in not supported in Azure China by the moment. Configure [exclusive tracking with your Azure Machine Learning workspace](#tracking-exclusively-on-azure-machine-learning-workspace) instead.
+
 To link your ADB workspace to a new or existing Azure Machine Learning workspace, 
 1. Sign in to [Azure portal](https://portal.azure.com).
 1. Navigate to your ADB workspace's **Overview** page.
 1. Select the **Link Azure Machine Learning workspace** button on the bottom right. 
 
  ![Link Azure DB and Azure Machine Learning workspaces](./media/how-to-use-mlflow-azure-databricks/link-workspaces.png)
 
-> [!WARNING]
-> Dual-tracking in a [private link enabled Azure Machine Learning workspace](how-to-configure-private-link.md) is not supported by the moment. Configure [exclusive tracking with your Azure Machine Learning workspace](#tracking-exclusively-on-azure-machine-learning-workspace) instead.
-
 After you link your Azure Databricks workspace with your Azure Machine Learning workspace, MLflow Tracking is automatically set to be tracked in all of the following places:
 
 * The linked Azure Machine Learning workspace.