Capsule Settings
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To open the Capsule Settings, double click on a capsule or hover over a capsule and click the gear icon.
At the top of the Capsule Settings view the capsule’s description by hovering over the information icon. Open the capsule by clicking Go to this capsule.
Once a capsule is added to a pipeline, it will inherit the resources selected in the capsule's environment editor. The capsule settings menu can then be used to modify the resources allocated to the capsule, independent of those set in the environment editor.
Each CPU based capsule can be allocated a maximum of 192 cores and 4096GB RAM. GPU based capsules can be allocated a maximum of 8 GPUs, 192 cores and 4096GB RAM.
Supplying run script arguments in a pipeline capsule will replace the arguments that are supplied by that capsule’s App Panel. This is a way to customize the inputs to the pipeline capsule without making any changes to the original capsule. Refer to App Panel for more information on how to create an an App Panel.
For a capsule to run successfully in a pipeline, git must be installed. This is dependent on the starter image that is used for each pipeline. If not installed, include it as a package in the capsule's environment editor. A good indication is that if the conda package manager isn’t installed, neither is git.
By default all capsules will run on dedicated machines. Pipelines can be configured to run on spot instances in the .
Arguments must be separated by spaces. If an argument includes a space, such as the title of a plot, it should be in quotes.
