Abstract: Techniques of predictive autoscaling in distributed computing systems are disclosed herein. In one embodiment, a method includes receiving data representing consumption of a computing resource by an application executing on one or more servers in the distributed computing system. The method also includes processing the received data into a time series having multiple resource consumption values by the application with corresponding time stamps and decomposing the time series into a regular component and an irregular component. The method further includes generating a predicted consumption value of the computing resource by the application at a future time point according to the trend, cyclic pattern, or seasonal pattern of the regular component of the time series and causing immediate adjustment of an amount of the computing resource provisioned in the distributed computing system for the application according to the generated predicted consumption value.

Abstract: Techniques of predictive autoscaling in distributed computing systems are disclosed herein. In one embodiment, a method includes receiving data representing consumption of a computing resource by an application executing on one or more servers in the distributed computing system. The method also includes processing the received data into a time series having multiple resource consumption values by the application with corresponding time stamps and decomposing the time series into a regular component and an irregular component. The method further includes generating a predicted consumption value of the computing resource by the application at a future time point according to the trend, cyclic pattern, or seasonal pattern of the regular component of the time series and causing immediate adjustment of an amount of the computing resource provisioned in the distributed computing system for the application according to the generated predicted consumption value.