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Copy file name to clipboardExpand all lines: articles/machine-learning/concept-hub-workspace.md
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@@ -9,7 +9,7 @@ ms.topic: conceptual
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ms.author: larryfr
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author: Blackmist
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ms.reviewer: namanjoshi
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ms.date: 04/14/2025
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ms.date: 05/12/2025
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monikerRange: 'azureml-api-2 || azureml-api-1'
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#Customer intent: As an IT administrator, I want to understand the purpose of a hub workspace for Azure Machine Learning.
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The goal of hubs is to take away this bottleneck, by letting IT set up a secure, preconfigured, and reusable environment for a team to prototype, build, and operate machine learning models.
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## Interoperability between ML studio and Azure AI Foundry
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Hubs can be used as your team's collaboration environment for both ML studio and [Azure AI Foundry](/azure/ai-studio/what-is-ai-studio). Use ML Studio for training and operationalizing custom machine learning models. Use Azure AI Foundry as experience for building and operating AI applications responsibly.
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| Workspace Kind | ML Studio | Azure AI Foundry |
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| --- | --- | --- |
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| Default | Supported | - |
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| Hub | Supported | Supported |
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| Project | Supported | Supported |
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## Set up and secure a hub for your team
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Create a hub workspace in [Azure portal](how-to-manage-hub-workspace-portal.md), with [Azure Resource Manager templates](how-to-manage-hub-workspace-template.md), or via [Azure Machine Learning SDK/CLI](/azure/ai-foundry/how-to/develop/create-hub-project-sdk). You might customize networking, identity, encryption, monitoring, or tags, to meet compliance with your organization's requirements.
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|BYO virtual network|X|-|-|Use alternative [managed virtual network](how-to-managed-network.md)|
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|Compute clusters|X|-|-|Use alternative [serverless compute](how-to-use-serverless-compute.md)|
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|Parallel run step|X|-|-|-|
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|Batch Endpoints|X|-|-|-|
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All the features which require compute clusters to run will not be supported for hub workspaces (unless the feature is supported on serverless compute).
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## Converting a regular workspace into a hub workspace
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