Managing Images

Notes and Constraints

• System images are built-in images and cannot be modified or deleted.
• You can create and manage all custom images only if you are a workspace administrator or developer, or if you have the DAYU Administrator or Tenant Administrator permissions. As a developer, you can only create and manage custom images for yourself. As an operator or viewer, you can only view images.
• You can create up to 100 custom images in a workspace.
• The name of a custom image must be unique in a workspace.
• You can create custom images only from built-in system images.

Viewing System Images

1. Log in to the DataArts Studio console by following the instructions in Accessing the DataArts Studio Instance Console.
2. On the DataArts Studio console, locate a workspace and click Management Center.
3. In the navigation pane on the left, choose Images.
4. Click the System Images tab to view system images.
   Figure 1 Viewing system images
   

Creating a Custom Image

1. Log in to the DataArts Studio console by following the instructions in Accessing the DataArts Studio Instance Console.
2. On the DataArts Studio console, locate a workspace and click Management Center.
3. In the navigation pane on the left, choose Images. On the displayed page, click the Custom Images tab.
   Figure 2 Creating a custom image
   

4. Click Create Image and configure the parameters listed in Table 1 to create a custom image.

   Table 1 Parameters for creating a custom image

   Parameter	Description
   Basic Information
   Image Name	Image name
   Visible To	To whom the image is visible. Select All or Only myself. NOTE: If you select Only myself, the image is visible only to you, the workspace administrator, and users with the DAYU Administrator or Tenant Administrator permissions.
   Description	Description. A maximum of 1,000 characters are allowed.
   Basic Image Source	Source of the basic image. Only System is supported.
   Basic Image	Basic image. If you select System for Basic Image Source, select a system image.
   Dependency Configuration
   Python	Python dependency packages, with one package in each line Two formats are supported: Package name, for example, Shapely. By default, the latest version of the dependency package is used. Package name==Version number, for example, Shapely==2.1.2
   Yum	Yum dependency packages. Enter packages according to repository rules, with one package in each line. Example: gcc-4.8.5-44.el7
   Script	Script installation information, for example, pip install Shapely==2.1.2

5. Click Save to finish creating a custom image.

   A custom image must be published so that it can be used for scheduling or used in runtime environments (for creating notebook instances in the development environment). Publish the custom image by performing 6 or by referring to publishing a custom image.

6. (Optional) Click Publish to publish the custom image.

Managing Custom Images

• Publishing a custom image: Click Publish in the Operation column to publish an image. You can view the versions of the published image by referring to viewing image versions.
• Modifying a custom image: Click Modify in the Operation column of a custom image to modify it.

  You can modify an unpublished image in its current version. If you modify a published image, a new image version will be generated, which does not affect the published historical versions.

• Deleting a custom image: Click More in the Operation column and select Delete to delete a custom image.
  

  When a custom image is deleted, its published version will also be deleted. Deleted images cannot be restored. Exercise caution when performing this operation.

• Viewing image versions: Click More in the Operation column of an image and select View Version to view the published versions of the image.

  Published image versions cannot be modified or deleted. They can only be rolled back.

• Rolling back an image version: Click More in the Operation column of an image and select View Version. Then, click Roll Back in the Operation column to roll back the image version to a specified historical version.

  After the rollback, a new image version is generated. It must be published again before it can be used for scheduling or in runtime environments (creation of notebook instances in the development environment).