In many environments, users launch Databricks clusters for development or analysis and forget to shut them down after use. When no auto-termination policy is configured, these clusters remain active indefinitely, incurring unnecessary charges for both Databricks and cloud infrastructure usage. This inefficiency is especially common in interactive clusters that are user-managed, ephemeral, or exploratory in nature. While Databricks provides built-in support for cluster auto-termination, teams often overlook it unless it's enforced through workspace policies. Without this safeguard in place, idle clusters can persist unnoticed for hours or days, leading to avoidable cost.
Databricks clusters accrue cost per second through:
Underlying cloud compute — billed through the host cloud provider (e.g., EC2, Azure VMs) Clusters without auto-termination continue to run — and generate cost — even if idle or abandoned.
