You have an Azure Databricks workspace named workspace1 in the Standard pricing tier.
You need to configure workspace1 to support autoscaling all-purpose clusters. The solution must meet the following requirements: Automatically scale down workers when the cluster is underutilized for three minutes. Minimize the time it takes to scale to the maximum number of workers. Minimize costs. What should you do first? and why would you do that?
A. Enable container services for workspace1.
B. Upgrade workspace1 to the Premium pricing tier.
C. Set Cluster Mode to High Concurrency.
D. Create a cluster policy in workspace1.
Sophia CarterPosted Feb 18, 2025, 4:03 PM
To configure workspace1 in the Standard pricing tier to support autoscaling all-purpose clusters with the specified requirements, the initial step would be to create a cluster policy in workspace1.
Creating a cluster policy allows you to define the auto scaling behavior for clusters in Azure Databricks. In this case, you can set up the cluster policy to enable automatic scale down of workers when the cluster is underutilized for three minutes. This helps in minimizing costs by terminating unnecessary resources.
Additionally, by configuring a cluster policy correctly, you can optimize the time it takes to scale to the maximum number of workers. This ensures that your cluster scales efficiently based on workload demands.
Before considering other options such as upgrading to the Premium pricing tier or enabling container services, setting up a cluster policy aligns with the specific requirements outlined while also being a cost-effective and efficient approach in managing autoscaling clusters in Azure Databricks.
Once the cluster policy is in place, you can further fine-tune the autoscaling settings based on the workload patterns and resource utilization in your workspace, ensuring an optimal balance between performance, cost, and resource utilization.