Palo Alto Networks, Inc.
AUTOSCALING OF DATA PROCESSING COMPUTING SYSTEMS BASED ON PREDICTIVE QUEUE LENGTH

Abstract:

To enhance the scaling of data processing systems in a computing environment, a number of data objects indicated in an allocation queue and a first attribute of the allocation queue are determined, where the allocation queue is accessible to a plurality of data processing systems. A number of data objects indicated in the allocation queue at a subsequent time is predicted based on the determined number of data objects and the first attribute. It is determined whether the active subset of the plurality of data processing systems satisfies a criterion for quantity adjustment based, at least in part, on the predicted number of data objects indicated in the allocation queue and a processing time goal. Based on determining that the active subset of data processing systems satisfies the criterion for quantity adjustment, a quantity of the active subset of data processing systems is adjusted.