Reference | Leveraging fully managed elastic AI compute#

Elastic AI compute can be used to execute:

  • Python code recipes

  • Any visual recipe you want to run using Spark

  • Visual or code-based ML model training

  • Notebooks

  • Webapps

  • Code Studios

To leverage elastic AI compute, you have to choose a container configuration in the Advanced tab of a recipe or Runtime Environment panel of a visual analysis task.

You can choose the container’s capacity in terms of CPU and RAM, as well as the code environment to include. For some advice on what container you should choose, see Tip | Choosing container sizes.

Choosing a container in this way leverages a container that is apart from the rest of your application and dedicated to this task. This behavior ensures that it won’t interfere with other processes.

Dataiku screenshot of the container configuration selection behavior dropdown.