What is primarily managed by the Databricks control plane?

The Databricks control plane is responsible for managing various essential components of the Databricks environment. This includes workspaces, which serve as organized spaces for collaboration on data projects; notebooks, where users can write and execute code; and configurations, which help in setting up the necessary parameters for running these data tasks. Additionally, the control plane oversees the management of clusters, which are groups of computing resources that perform the actual data processing.

By managing these elements, the control plane facilitates a seamless experience for users as they develop, run, and manage their workflows. It ensures that resources are efficiently allocated and that the overall environment is well-configured for optimal performance.

In contrast, other options focus on aspects that fall under the purview of the data plane or other operational tooling rather than the control plane itself. Data processing tasks, for instance, are executed by the compute resources but are not directly managed by the control plane; it simply facilitates their execution. Similarly, the storage of batch data and data ingestion tools relate more to the data pipeline or analytics layer rather than the core control functionalities managed by Databricks.