Autoscale for Azure HDInsight is now generally available across all regions for Interactive Query (Apache Hive LLAP) workloads with HDInsight 4.0. Autoscale for Apache Spark and Hadoop workloads was released to General Availability in Nov 2019.
This feature makes it possible to operate your big data analytics workloads in a more cost-efficient and productive way. You can drive higher utilization of your HDInsight clusters and pay only for what you need.
Depending on your requirements, you can choose between load-based and schedule-based autoscaling. Load-based Autoscale can scale the cluster size up and down based on the current resource needs while schedule-based Autoscale can change the cluster size based on the predefined schedule.
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