Abstract: A request to execute a recurring job is received by a cloud computing environment. Thereafter, available computing resources available to execute the job are determined based on historical resource consumption trends. A resource prediction for the job is then generated using an ensemble model ((S)ARIMA model) that combines an autoregressive moving average (ARMA) model and an autoregressive moving average (ARIMA) prediction models. The resource prediction characterizes resources to be consumed for successfully executing the job. Execution of the job can then be scheduled by the cloud computing environment based on the resource prediction and the available computing resources. Related apparatus, systems, techniques and articles are also described.

Abstract: A request to execute a recurring job is received by a cloud computing environment. Thereafter, available computing resources available to execute the job are determined based on historical resource consumption trends. A resource prediction for the job is then generated using an ensemble model ((S)ARIMA model) that combines an autoregressive moving average (ARMA) model and an autoregressive moving average (ARIMA) prediction models. The resource prediction characterizes resources to be consumed for successfully executing the job. Execution of the job can then be scheduled by the cloud computing environment based on the resource prediction and the available computing resources. Related apparatus, systems, techniques and articles are also described.