Abstract: Virtualized applications are autoscaled by receiving performance data in time-series format from a running virtualized application, computationally analyzing the performance data to determine a pattern therein, and extending the performance data to a time in the future based at least on the determined pattern. The extended performance data is analyzed to determine if resources allocated to the virtualized application are under-utilized or over-utilized, and a schedule for re-allocating resources to the virtualized application based at least in part on a result of the analysis of the extended performance data is created.

Abstract: Virtualized applications are autoscaled by receiving performance data in time-series format from a running virtualized application, computationally analyzing the performance data to determine a pattern therein, and extending the performance data to a time in the future based at least on the determined pattern. The extended performance data is analyzed to determine if resources allocated to the virtualized application are under-utilized or over-utilized, and a schedule for re-allocating resources to the virtualized application based at least in part on a result of the analysis of the extended performance data is created.

Abstract: Virtualized applications are autoscaled by receiving performance data in time-series format from a running virtualized application, computationally analyzing the performance data to determine a pattern therein, and extending the performance data to a time in the future based at least on the determined pattern. The extended performance data is analyzed to determine if resources allocated to the virtualized application are under-utilized or over-utilized, and a schedule for re-allocating resources to the virtualized application based at least in part on a result of the analysis of the extended performance data is created.

Abstract: Virtualized applications are autoscaled by receiving performance data in time-series format from a running virtualized application, computationally analyzing the performance data to determine a pattern therein, and extending the performance data to a time in the future based at least on the determined pattern. The extended performance data is analyzed to determine if resources allocated to the virtualized application are under-utilized or over-utilized, and a schedule for re-allocating resources to the virtualized application based at least in part on a result of the analysis of the extended performance data is created.

Abstract: A host for a virtual machine is selected by first electronically receiving (i) a virtual-machine allocation request for resources in a cluster of servers upon which a plurality of virtual machines are executing and (ii) performance data related to the execution of the plurality of virtual machines. The effect of executing a new virtual machine associated with the request on each server using on the gathered performance data is simulated, and a server is selected based on a result of the simulation; the new virtual machine is caused to execute on the selected server.