Merge pull request #180538 from jonburchel/2021-11-19-ml-studio-classic-deprecation

ML Studio Classic deprecation

Author: laurabren

articles/data-factory/compute-linked-services.md

@@ -15,6 +15,8 @@ ms.custom: devx-track-azurepowershell, synapse
 
 [!INCLUDE[appliesto-adf-asa-md](includes/appliesto-adf-asa-md.md)]
 
+[!INCLUDE[ML Studio (classic) retirement](../../includes/machine-learning-studio-classic-deprecation.md)] 
+
 This article explains different compute environments that you can use to process or transform data. It also provides details about different configurations (on-demand vs. bring your own) supported when configuring linked services linking these compute environments.
 
 The following table provides a list of supported compute environments and the activities that can run on them. 

articles/data-factory/concepts-pipelines-activities.md

@@ -18,6 +18,8 @@ ms.date: 09/09/2021
 > * [Current version](concepts-pipelines-activities.md)
 [!INCLUDE[appliesto-adf-asa-md](includes/appliesto-adf-asa-md.md)]
 
+[!INCLUDE[ML Studio (classic) retirement](../../includes/machine-learning-studio-classic-deprecation.md)] 
+
 This article helps you understand pipelines and activities in Azure Data Factory and Azure Synapse Analytics and use them to construct end-to-end data-driven workflows for your data movement and data processing scenarios.
 
 ## Overview

articles/data-factory/transform-data-using-machine-learning.md

@@ -19,6 +19,11 @@ ms.date: 09/09/2021
 
 [!INCLUDE[appliesto-adf-asa-md](includes/appliesto-adf-asa-md.md)]
 
+[!INCLUDE[ML Studio (classic) retirement](../../includes/machine-learning-studio-classic-deprecation.md)] 
+
+> [!NOTE] 
+> Since Machine Learning Studio (classic) resources can no longer be created after 1 Dec, 2021, users are encouraged to use [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/) with the [Machine Learning Execute Pipeline activity](transform-data-machine-learning-service.md) rather than using the Batch Execution activity to execute Machine Learning Studio (classic) batches.
+
 [ML Studio (classic)](https://azure.microsoft.com/documentation/services/machine-learning/) enables you to build, test, and deploy predictive analytics solutions. From a high-level point of view, it is done in three steps:
 
 1. **Create a training experiment**. You do this step by using the ML Studio (classic). ML Studio (classic) is a collaborative visual development environment that you use to train and test a predictive analytics model using training data.

articles/data-factory/transform-data.md

@@ -31,6 +31,8 @@ ms.date: 09/09/2021
 
 [!INCLUDE[appliesto-adf-asa-md](includes/appliesto-adf-asa-md.md)]
 
+[!INCLUDE[ML Studio (classic) retirement](../../includes/machine-learning-studio-classic-deprecation.md)] 
+
 ## Overview
 This article explains data transformation activities in Azure Data Factory and Synapse pipelines that you can use to transform and process your raw data into predictions and insights at scale. A transformation activity executes in a computing environment such as Azure Databricks or Azure HDInsight. It provides links to articles with detailed information on each transformation activity.
 

articles/data-factory/update-machine-learning-models.md

@@ -12,10 +12,16 @@ ms.topic: conceptual
 ms.date: 09/09/2021
 ---
 
-# Update  Machine Learning Studio (classic) models by using Update Resource activity
+# Update Machine Learning Studio (classic) models by using Update Resource activity
 
 [!INCLUDE[appliesto-adf-asa-md](includes/appliesto-adf-asa-md.md)]
 
+[!INCLUDE[ML Studio (classic) retirement](../../includes/machine-learning-studio-classic-deprecation.md)] 
+
+> [!NOTE] 
+> Since Machine Learning Studio (classic) resources can no longer be created after 1 Dec, 2021, users are encouraged to use [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/) with the [Machine Learning Execute Pipeline activity](transform-data-machine-learning-service.md) rather than using the Update Resource activity to update Machine Learning Studio (classic) models.
+
+
 This article complements the main Machine Learning Studio (classic) integration article: [Create predictive pipelines using Machine Learning Studio (classic)](transform-data-using-machine-learning.md). If you haven't already done so, review the main article before reading through this article.
 
 ## Overview

articles/data-factory/v1/data-factory-azure-ml-batch-execution-activity.md

@@ -12,6 +12,8 @@ ms.date: 10/22/2021
 
 # Create predictive pipelines using Machine Learning Studio (classic) and Azure Data Factory
 
+[!INCLUDE[ML Studio (classic) retirement](../../../includes/machine-learning-studio-classic-deprecation.md)] 
+
 > [!div class="op_single_selector" title1="Transformation Activities"]
 > * [Hive Activity](data-factory-hive-activity.md)
 > * [Pig Activity](data-factory-pig-activity.md)

articles/data-factory/v1/data-factory-azure-ml-update-resource-activity.md

@@ -12,6 +12,8 @@ ms.date: 10/22/2021
 
 # Updating ML Studio (classic) models using Update Resource Activity
 
+[!INCLUDE[ML Studio (classic) retirement](../../../includes/machine-learning-studio-classic-deprecation.md)] 
+
 > [!div class="op_single_selector" title1="Transformation Activities"]
 > * [Hive Activity](data-factory-hive-activity.md) 
 > * [Pig Activity](data-factory-pig-activity.md)

articles/data-factory/v1/data-factory-compute-linked-services.md

@@ -11,6 +11,9 @@ ms.date: 10/22/2021
 ---
 
 # Compute environments supported by Azure Data Factory version 1
+
+[!INCLUDE[ML Studio (classic) retirement](../../../includes/machine-learning-studio-classic-deprecation.md)] 
+
 > [!NOTE]
 > This article applies to version 1 of Azure Data Factory. If you are using the current version of the Data Factory service, see [Compute linked services in](../compute-linked-services.md).
 

articles/data-factory/v1/data-factory-data-transformation-activities.md

@@ -11,6 +11,9 @@ ms.date: 10/22/2021
 ---
 
 # Transform data in Azure Data Factory version 1
+
+[!INCLUDE[ML Studio (classic) retirement](../../../includes/machine-learning-studio-classic-deprecation.md)] 
+
 > [!div class="op_single_selector"]
 > * [Hive](data-factory-hive-activity.md)  
 > * [Pig](data-factory-pig-activity.md)  

articles/data-factory/v1/data-factory-json-scripting-reference.md

@@ -15,6 +15,7 @@ ms.custom: devx-track-azurepowershell
 > [!NOTE]
 > This article applies to version 1 of Data Factory.
 
+[!INCLUDE[ML Studio (classic) retirement](../../../includes/machine-learning-studio-classic-deprecation.md)] 
 
 This article provides JSON schemas and examples for defining Azure Data Factory entities (pipeline, activity, dataset, and linked service).