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To efficiently manage variable workloads by implementing predictive scaling for your Databricks clusters based on historical performance metrics, which combination of Azure services and features would you choose?
A
Azure Logic Apps to monitor Databricks metrics and scale clusters based on predefined rules
B
Utilizing Databricks REST API to dynamically scale clusters in response to Azure Log Analytics alerts
C
Azure Machine Learning to model workload patterns and Azure Function to adjust Databricks cluster size based on predictions
D
Azure Monitor Autoscale to automatically scale Databricks clusters based on CPU and memory utilization
