Merge pull request #105141 from mimig1/patch-258

Update hdinsight-autoscale-clusters.md

Author: PRMerger10

articles/hdinsight/hdinsight-autoscale-clusters.md

@@ -7,13 +7,16 @@ ms.reviewer: jasonh
 ms.service: hdinsight
 ms.topic: conceptual
 ms.custom: hdinsightactive
-ms.date: 02/11/2020
+ms.date: 02/21/2020
 ---
 
 # Automatically scale Azure HDInsight clusters
 
 > [!Important]
-> The Autoscale feature only works for Apache Spark, ApacheHive, LLAP and Apache HBase clusters created after May 8th 2019. Autoscale for LLAP and HBase are in preview.
+> The Azure HDInsight Autoscale feature was released for general availability on November 7th, 2019 for Spark and Hadoop clusters and included improvements not available in the preview version of the feature. If you created a Spark cluster prior to November 7th, 2019 and want to use the Autoscale feature on your cluster, the recommended path is to create a new cluster, and enable Autoscale on the new cluster. 
+>
+>Autoscale for Interactive Query (LLAP) and HBase clusters is still in preview. Autoscale is only available on Spark, Hadoop, Interactive Query, and HBase clusters. 
+
 
 Azure HDInsight's cluster Autoscale feature automatically scales the number of worker nodes in a cluster up and down. Other types of nodes in the cluster can't be scaled currently.  During the creation of a new HDInsight cluster, a minimum and maximum number of worker nodes can be set. Autoscale then monitors the resource requirements of the analytics load and scales the number of worker nodes up or down. There's no additional charge for this feature.