✅ C. Cluster pools significantly reduce the start-up time for new clusters.

Cluster pools in Databricks consist of idle, ready-to-use instances. When a new cluster is configured to use a pool, Databricks allocates nodes from the pool, bypassing the need to provision them from scratch. This process drastically cuts down the cluster start-up time.

❌ A. Cluster pools enable load balancing across clusters.

Load balancing is managed by the clusters themselves, not the pools. Pools are about resource availability, not workload distribution.

❌ B. Cluster pools facilitate the creation of clusters.

Pools provide resources for clusters but do not create them. The cluster creation process is separate and must be initiated by the user.

❌ D. Cluster pools are designed for sharing resources among multiple teams.

While pools can be shared, their main goal is to speed up cluster starts, not to manage inter-team resource sharing.

❌ E. Cluster pools ensure all cluster nodes are from a single physical server rack.

The physical location of nodes is managed by Databricks and is not a feature of cluster pools.