Azure Databricks offers autoscaling for catering to dynamic workloads. The amount of dynamic workloads is never the same and has varying spikes in workload volumes. Autoscaling allows Azure clusters to meet variable workloads by automatically scaling up or down as per the amount of workload. Autoscaling not only improves resource utilization but also saves the costs of resources. Resources are scaled up when the volume of the workload rises and scaled down when the volume of the workload drops. Resources are created and destroyed in Azure clusters based on the volume of workloads, so autoscaling is a smart way to manage workloads efficiently.