Help Center/ ModelArts/ Best Practices/ Permissions Management/ Configuration Practices in Typical Scenarios/ Logging In to a Training Container Using Cloud Shell
Updated on 2024-03-05 GMT+08:00
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Logging In to a Training Container Using Cloud Shell

Application Scenario

You can use Cloud Shell provided by the ModelArts console to log in to a running training container.

Constraints

You can use Cloud Shell to log in to a running training container using a dedicated resource pool.

Preparation: Assigning the Cloud Shell Permission to an IAM User

  1. Log in to the Huawei Cloud management console as a tenant user, hover the cursor over your username in the upper right corner, and choose Identity and Access Management from the drop-down list to switch to the IAM management console.
  2. On the IAM console, choose Permissions > Policies/Roles from the navigation pane, click Create Custom Policy in the upper right corner, and configure the following parameters.
    • Policy Name: Enter a custom policy name, for example, Using Cloud Shell to access a running job.
    • Policy View: Select Visual editor.
    • Policy Content: Select Allow, ModelArts Service, modelarts:trainJob:exec, and default resources.
      Figure 1 Creating a custom policy
  3. In the navigation pane, choose User Groups. Then, click Authorize in the Operation column of the target user group. On the Authorize User Group page, select the custom policies created in 2, and click Next. Then, select the scope and click OK.

    After the configuration, all users in the user group have the permission to use Cloud Shell to log in to a running training container.

    If no user group is available, create a user group, add users using the user group management function, and configure authorization. If the target user is not in a user group, you can add the user to a user group through the user group management function.

Using Cloud Shell

  1. Configure parameters based on Preparation: Assigning the Cloud Shell Permission to an IAM User.
  2. On the ModelArts console, choose Training Management > Training Jobs. Go to the details page of the target training job and log in to the training container on the Cloud Shell tab.

    Verify that the login is successful, as shown in the following figure.

    Figure 2 Cloud Shell

    If the job is not running or the permission is insufficient, CloudShell cannot be used. Locate the fault as prompted.

    Figure 3 Error message