Assets in deployment spaces

Learn about various ways of adding and promoting assets to a space to support Watson Machine Learning deployments. Find the list of asset types that you can add to a space.

Note these considerations for importing assets into a space:

• Upon import, each asset is automatically assigned a version number, starting with version 1. This to prevent overwriting the asset if you import an updated version later.
• Supporting assets or references required to run jobs in the space must be part of the import package, or added separately, or the jobs will fail.

The way to add an asset to a space depends on the asset type. In case of some assets, you can add them directly to a space (for example a model that was created outside of watsonx). Other asset types originate in a project and have to be transferred from a project to a space. Third class are asset types that you can only add to a space as a dependency of another asset (these asset types are not directly exposed in the Assets tab in the UI). For details, refer to these sections:

• Asset types that you can directly add to a space

• Asset types that are created in projects and can be transferred into a space

• Asset types that can be added to a space only as a dependency

For information about working with Watson Machine Learning assets, refer to:

• Accessing asset details