What are "resource pools" used for in Databricks?

Resource pools in Databricks are designed specifically to provide fine-grained control over resource allocation. This capability allows organizations to manage computational resources more effectively by grouping resources into pools that can be allocated to different users or workloads based on specific needs.

Using resource pools, administrators can specify the maximum number of concurrent jobs, control the overall capacity for various workloads, and ensure that resources are distributed fairly among users or projects. This level of control is crucial in a collaborative environment where multiple users and processes may compete for resources, as it helps to optimize performance and maintain stability across the Databricks platform.

In contrast to this, limiting data access to users is primarily managed through permissions and access controls rather than resource pools. Simplifying notebook sharing pertains more to collaboration features rather than resource management. Enhancing user experience generally refers to the overall usability and design of the platform, which is separate from the technical management of resources.