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Platform For AI:Manage workspaces

Last Updated:Apr 07, 2024

After you create a workspace in Platform for AI (PAI), you can view and modify workspace configurations, such as computing resources, members, and storage settings, on the Workspace Details page.

Limits

Only the administrator or owner of a workspace can modify workspace configurations.

View the details of a workspace

  1. Log on to the PAI console.

  2. In the left-side navigation pane, click Workspaces. On the Workspaces page, click the name of the workspace that you want to view.

  3. On the right side of the Workspace Details page, you can view information about the workspace, such as the workspace name, workspace ID, and associated computing resources.

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Modify the description of a workspace

  1. In the Details section on the right side of the Workspace Details page, click Modify.

  2. In the Workspace Basic Configuration panel, modify the Description field and click OK.

    修改工作空间描述

Manage the computing resources of a workspace

Note

If no computing resources are associated with a workspace, an error may occur when you train a model in Machine Learning Designer or submit a training job.

View computing resources

  1. In the Computing Resources section on the right side of the Workspace Details page, click Resources.

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  2. In the Workspace Resource Configuration panel, you can view the associated resources, such as MaxCompute Resources, General Computing Resources, and Fully Managed Flink Resources. You can also view information about the associated resources, such as Quota Name and Billing Method. image.png

Associate computing resources

In the Workspace Resource Configuration panel, you can associate the computing resources of the current Alibaba Cloud account with the workspace. The following figure shows how to associate MaxCompute Resources.

Important

To disassociate computing resources, contact your account manager.

When you associate MaxCompute resources, pay-as-you-go GPU-accelerated computing is automatically enabled. You can modify the settings based on your business requirements. image.png

Add GPU resources

You can use GPU resources to build models for audio, visual, and textual perception training in Machine Learning Designer.

  1. In the Workspace Resource Configuration panel, click the MaxCompute Resources tab.

  2. Find the resource item for which you want to add GPU resources and click Modify in the Actions column.

  3. In the Resource Settings dialog box, select Pay-as-you-go from the GPU drop-down list and then click OK.

Configure the default storage path of a workspace

  1. In the Storage Settings section on the right side of the Workspace Details page, click Settings.

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  2. In the Storage Settings panel, specify an Object Storage Service (OSS) path in the Workspace Default Storage field and then click OK.

    Important

    Members who are assigned the Algorithm Developer role in the workspace must have read and write permissions on the specified OSS path.

    存储路径

    Note

    The specified OSS path can be used by the pipelines in Machine Learning Designer. If you specify another storage path when you create a pipeline in Machine Learning Designer, the specified OSS path in the Workspace Default Storage field becomes invalid.

Manage the members of a workspace

In the Members section on the right side of the Workspace Details page, you can view the members of a workspace and their roles. Click Manage to add or remove members or modify member roles. For more information, see Manage members of the workspace. image

Configure SLS for a workspace

You can send logs that are generated for the Data Science Workshop (DSW) instances and Deep Learning Containers (DLC) jobs in the current workspace to Simple Log Service (SLS) for custom analysis. Perform the following steps to configure SLS:

  1. In the Log Service section on the right side of the Workspace Details page, click Settings.

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  2. In the SLS Logs panel, configure the following parameters and click OK:

    Parameter

    Description

    SLSProject

    The SLS project. SLS projects are used to isolate and manage resources. If no projects are available in the drop-down list, click Create SLS Project to create a project. For more information, see Manage a project.

    LogStore

    The SLS Logstore. Logstores are used to collect, store, and query logs. If no Logstores are available in the drop-down list, click Create Logstore to create a Logstore. For more information, see Manage a Logstore.

    Modules that require SLS storage

    Valid options: Distributed Training (DLC) and Interactive Modeling (DSW). You can select both options.

    image

Reference

  • Machine Learning Designer is a visual tool for machine learning modeling that uses the cloud-native PAIFlow engine to facilitate end-to-end machine learning development. For more information, see Overview of Machine Learning Designer.

  • You can create a notification rule to monitor the status of pipelines in Machine Learning Designer or DLC jobs or trigger related events based on the approval status of model versions. For more information, see Create a notification rule.