CPC G06F 9/5005 (2013.01) [G06N 3/08 (2013.01); G06N 7/01 (2023.01)] | 18 Claims |
1. A computer-implemented method for operating applications on a computing system, comprising:
collecting, by a monitoring operator of a workload manager operated by the computing system, a first set of historical workload data generated by operating a first set of one or more applications at a first number of past time instances, wherein the first set of historical workload data are collected for a set of computing nodes within the computing system, and wherein the monitoring operator monitors historical resources used by the set of computing nodes to operate the first set of one or more applications at the first number of past time instances;
predicting, by the workload manager, probability parameters including a probability density function of a second set of future workload data for operating a second set of one or more applications at a second number of future time instances by the set of computing nodes; and
determining, by the workload manager, future resources allocated to operating the second set of one or more applications for the second number of future time instances, based on allocated current resources, a lower bound number of computing nodes to satisfy a quality of service (QOS) for operating the second set of one or more applications, an upper bound number of computing nodes to satisfy the QoS, and the predicted probability parameters, wherein the future resources are determined as a solution for reducing a first probability for allocating a third number of computing nodes over the upper bound number of computing nodes and reducing a second probability for allocating a fourth number of computing nodes below the lower bound number of computing nodes based on an equation related to the first probability and the second probability;
scheduling the determined future resources of the computing system for the second number of future time instances; and
operating the second set of one or more applications on the scheduled future resources to generate workload data.
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