Thanks for using Cloudera Community. To your Q, the Driver Cap is the Engine/Resource Profile & the Executor's Resource Usage is defined by the SparkSession or "spark-defaults.conf" file within the Project wherein the Workbench Session is being created.
Your Team can review the Pods in the User's Namespace & see the same i.e. upon a Workbench Session Creation, an Engine Pod is started with "Limits" set toEngine/Resource Profile Settings. After SparkSession is initialised, additional Pods are generated within the User's Namespace based on the Execution's Configs passed via SparkSession or "spark-defaults.conf" file.
You may configure the Executor's Configs as per your usage yet the same depends on the CML Workspace AutoScale Range & InstanceType. Say, an InstanceType supporting 8 vCPU & Executors requesting 8 vCPU won't work. Similarly, AutoScale Max of 5 yet requesting Executors collectively utilising the Resource Limit of 5 Nodes.
Hope the above helps answer your Post's queries. If Yes, Kindly mark the Post as Solved. If No, Feel free to share your concerns & we shall address accordingly.