Emc IP Holding Company LLC

Shamail Tahir

Kenneth Durazzo

Yu Cao

Sanping Li

Ryan Wallner

Workload data associated with past execution of an application by a computing system is obtained. Two or more prediction models are trained using the obtained past workload data. A weight is assigned to each of the two or more trained prediction models. The two or more weighted prediction models are combined to form an ensemble prediction model configured to predict, in real-time, workload associated with future execution of the application by the computing system.

Adaptive ensemble workload prediction model based on machine learning algorithms

A current workload associated with a computing infrastructure is monitored for a change in the current workload. A first cost value is computed wherein the first cost value indicates a cost associated with scaling a current resource configuration for the computing infrastructure to respond to the change to the current workload. A second cost value is computed wherein the second cost value indicates a cost associated with ignoring the change to the current workload and maintaining the current resource configuration for the computing infrastructure. The first cost value and the second cost value are compared. A determination is made whether to scale or maintain the current resource configuration based on the comparison of the first cost value and the second cost value.

Resource scaling in computing infrastructure

An apparatus comprises container host devices each implementing one or more containers, at least one storage platform coupled to the plurality of container host devices and implementing storage resources for utilization by processes running in the containers, and a controller associated with at least a subset of the container host devices and the storage platform. The containers implemented by the container host devices are arranged in container groups and the storage resources implemented by the storage platform are arranged in storage groups. The controller is configured to coordinate establishment of container host resource allocations for one or more of the container groups with establishment of storage resource allocations for one or more of the storage groups. Portions of the container groups may be arranged with corresponding portions of the storage groups into container-storage groups, with the controller generating information indicative of relative levels of resource utilization across the container-storage groups.

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North Grafton, MA, United States of America

Shamail Tahir