Logging In to a Training Container Using Cloud Shell

Application Scenarios

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

Constraints

The training container must be running in a dedicated resource pool.

Preparation: Assigning the Cloud Shell Permission to an IAM User

1. Log in to the console as a tenant user, click your username in the upper right corner, and choose Identity and Access Management from the drop-down list to switch to the IAM console.
2. On the IAM console, choose Permissions > Policies/Roles from the navigation pane and then click Create Custom Policy in the upper right corner. On the page that appears, configure parameters and click OK.
   • Policy Name: Enter a 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.
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 one, add users to it through user group management, and configure authorization for the user group. If the target user is not in a user group, add the user to a user group through user group management.

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 1 Cloud Shell
   

   If the job is not running or the permission is insufficient, Cloud Shell cannot be used. In this case, locate the fault as prompted.

   Figure 2 Error message