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Copy file name to clipboardExpand all lines: articles/machine-learning/concept-designer.md
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ms.author: lagayhar
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ms.reviewer: lagayhar
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author: lgayhardt
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ms.date: 05/21/2024
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ms.date: 09/09/2025
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ms.custom:
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- designer
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---
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# What is Designer (v2) in Azure Machine Learning?
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Designer in Azure Machine Learning studio is a drag-and-drop user interface for building machine learning pipelines in Azure Machine Learning workspaces.
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Designer in Azure Machine Learning studio is a drag-and-drop interface for building machine learning pipelines in Azure Machine Learning workspaces.
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> [!IMPORTANT]
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> Designer in Azure Machine Learning supports two types of pipelines, which use classic prebuilt (v1) or custom (v2) components. The two component types aren't compatible within pipelines. **This article applies to Designer (v2) with custom components.**
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## Asset libraries
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Designer uses building blocks from Azure Machine Learning asset libraries to create pipelines. The asset libraries include the following pipeline building blocks:
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Designer creates pipelines using building blocks from Azure Machine Learning asset libraries. The asset libraries include these pipeline building blocks:
The **Data**, **Model**, and **Component** tabs on the left side of Designer show assets in your workspace and in all Azure Machine Learning [registries](./how-to-share-models-pipelines-across-workspaces-with-registries.md) that you have access to.
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The **Data**, **Model**, and **Component** tabs on the left side of Designer show assets in your workspace and in all Azure Machine Learning [registries](./how-to-share-models-pipelines-across-workspaces-with-registries.md) that you can access.
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:::image type="content" source="./media/concept-designer/asset-library.png" alt-text="Screenshot of the asset libraries filtered for one registry." lightbox= "./media/concept-designer/asset-library.png":::
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To view assets from specific registries, select the **Registry name** filter. The assets you created in your current workspace are in the **Workspace** registry. The assets provided by Azure Machine Learning are in the **azureml** registry.
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To view assets from specific registries, select the **Registry name** filter. Assets you created in your current workspace are in the **Workspace** registry. Assets provided by Azure Machine Learning are in the **azureml** registry.
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To learn how to create data and component assets in your workspace, see the following articles:
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## Pipelines
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You can use Designer to visually build pipelines with your assets. You can either create new pipelines or clone and build on existing pipeline jobs.
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You can use Designer to visually build pipelines with your assets. Create new pipelines or clone and build on existing pipeline jobs.
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### New pipelines
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Selecting the **+** symbol under **New pipeline** at the top of the Designer screen creates a new pipeline to build from scratch. Be sure to select the **Custom** option so you can use custom components.
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Select the **+** symbol under **New pipeline** at the top of the Designer screen to create a new pipeline from scratch. Be sure to select the **Custom** option so you can use custom components.
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:::image type="content" source="./media/concept-designer/new-pipeline.png" alt-text="Screenshot of selecting new pipeline with custom components." lightbox= "./media/concept-designer/new-pipeline.png":::
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:::image type="content" source="./media/concept-designer/edit-pipeline.png" alt-text="Screenshot of a draft pipeline being edited." lightbox= "./media/concept-designer/edit-pipeline.png":::
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A valid pipeline draft has the following characteristics:
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A valid pipeline draft has these characteristics:
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- Data assets can connect only to components.
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- Components can connect only to either data assets or to other components.
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- Components can connect only to data assets or to other components.
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- All required input ports for components must have some connection to the data flow.
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- All required parameters for each component must be set.
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When you're ready to run your pipeline draft, you save it and submit it as a pipeline job.
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When you're ready to run your pipeline draft, save it and submit it as a pipeline job.
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### Pipeline jobs
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Each time you run a pipeline, the pipeline configuration and results are stored in your workspace as a pipeline job. You can resubmit any past pipeline job, inspect it for troubleshooting or auditing, or clone it to create a new pipeline draft for further editing.
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Each time you run a pipeline, the pipeline configuration and results are stored in your workspace as a pipeline job. You can resubmit any past pipeline job, inspect it for troubleshooting or auditing, or clone it to create a new pipeline draft for editing.
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:::image type="content" source="./media/concept-designer/pipeline-job.png" alt-text="Screenshot of pipeline job list." lightbox= "./media/concept-designer/pipeline-job.png":::
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### Cloned pipeline jobs
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If you want to base a new pipeline on an existing pipeline job in the workspace, you can clone the job into a new pipeline draft to continue editing.
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To base a new pipeline on an existing pipeline job in the workspace, clone the job into a new pipeline draft to continue editing.
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:::image type="content" source="./media/concept-designer/pipeline-clone.png" alt-text="Screenshot of a pipeline job in the workspace with the clone button highlighted." lightbox= "./media/concept-designer/pipeline-clone.png":::
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After cloning, you can find out which pipeline job the new pipeline was cloned from by selecting **Show lineage**.
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After cloning, you can find which pipeline job the new pipeline was cloned from by selecting **Show lineage**.
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:::image type="content" source="./media/concept-designer/draft-show-lineage.png" alt-text="Screenshot showing the draft lineage after selecting Show lineage." lightbox= "./media/concept-designer/draft-show-lineage.png":::
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