Capacity units per hour for notebooks

The rate of capacity units per hour consumed is determined for:

• Default Python or R environments by the hardware size and the number of users in a project using one or more runtimes

  For example: The IBM Runtime 24.1 on Python 3.10 XS with 2 vCPUs will consume 1 CUH if it runs for one hour. If you have a project with 7 users working on notebooks 8 hours a day, 5 days a week, all using the IBM Runtime 24.1 on Python 3.10 XS environment, and everyone shuts down their runtimes when they leave in the evening, runtime consumption is 5 x 7 x 8 = 280 CUH per week.

  The CUH calculation becomes more complex when different environments are used to run notebooks in the same project and if users have multiple active runtimes, all consuming their own CUHs. Additionally, there might be notebooks, which are scheduled to run during off-hours, and long-running jobs, likewise consuming CUHs.

• Default Spark environments by the hardware configuration size of the driver, and the number of executors and their size.

Capacity units per hour for notebooks with Decision Optimization

The rate of capacity units per hour consumed is determined by the hardware size and the price for Decision Optimization.

Capacity units per hour for notebooks with Watson Natural Language Processing

The rate of capacity units per hour consumed is determined by the hardware size and the price for Watson Natural Language Processing.

Capacity units per hour for SPSS Modeler flows

Capacity units per hour for Data Refinery and Data Refinery flows

Capacity units per hour for RStudio

Capacity units per hour for GPU environments

Learn more

• For information on monitoring your account's resource usage, see Monitoring account resource usage.
• For details on computing resource allocation and consumption, see wastonx.ai Studio environments compute usage

Parent topic: watsonx.ai Studio plans