Merge pull request #276855 from msakande/remove-v1-mlflow-concepts-article

remove v1 mlflow concepts article

Author: Court72

articles/machine-learning/.openpublishing.redirection.machine-learning.json

@@ -400,6 +400,11 @@
         "redirect_url": "/azure/machine-learning/v1/how-to-convert-ml-experiment-to-production",
         "redirect_document_id": true
     },
+    {
+        "source_path_from_root": "/azure/machine-learning/v1/concept-mlflow.md",
+        "redirect_url": "/articles/machine-learning/concept-mlflow",
+        "redirect_document_id": true
+    },
     {
         "source_path_from_root": "/articles/machine-learning/tutorial-train-deploy-notebook.md",
         "redirect_url": "/azure/machine-learning/tutorial-azure-ml-in-a-day",

articles/machine-learning/toc.yml

@@ -186,10 +186,6 @@
         items:
           - name: MLflow and Azure Machine Learning
             href: concept-mlflow.md
-          # v1
-          - name: MLflow
-            href: ./v1/concept-mlflow.md
-          # end v1
           - name: MLflow models
             displayName: tracking models, mlflow, custom, flavors
             href: concept-mlflow-models.md

articles/machine-learning/v1/concept-mlflow.md

@@ -17,7 +17,7 @@ ms.custom: UpdateFrequency5, sdkv1
 
 [!INCLUDE [sdk v1](../includes/machine-learning-sdk-v1.md)]
 
-In this article, learn how to deploy your [MLflow](https://www.mlflow.org) model as an Azure web service, so you can leverage and apply Azure Machine Learning's model management and data drift detection capabilities to your production models. See [MLflow and Azure Machine Learning](concept-mlflow.md) for additional MLflow and Azure Machine Learning functionality integrations.
+In this article, learn how to deploy your [MLflow](https://www.mlflow.org) model as an Azure web service, so that you can leverage and apply Azure Machine Learning's model management and data drift detection capabilities to your production models. For more MLflow and Azure Machine Learning functionality integrations, see [MLflow and Azure Machine Learning (v2)](../concept-mlflow.md), which uses v2 SDK.
 
 Azure Machine Learning offers deployment configurations for:
 * Azure Container Instance (ACI) which is a suitable choice for a quick dev-test deployment.