Minimize costs by under-provisioning resources, accepting that latency SLAs may occasionally not be met during peak loads.

Over-provision resources to guarantee latency SLAs are always met, regardless of the cost implications.

Utilize Azure Databricks' autoscaling feature to dynamically adjust resources based on workload, with real-time monitoring to ensure latency SLAs are met while optimizing for cost.

Manually adjust resources based on predicted workload changes, which may lead to either under-utilization or over-utilization of resources.