Hewlett-packard Development Company, L.p.

Hewlett Packard Enterprise Development LP

Bryan L Backer

Jerome Alexander Rolia

Daniel Edward Herington

Thomas Edwin Turicchi, Jr

William H Blanding

Jerry James Harrow, Jr

Dan Herington

A scale out workload management system executing on a computer system controls simultaneous execution of multiple workloads. The computer system includes multiple nodes, where each node defines computer resources consumable by a workload. The scale out workload management system includes an application manager coupled to the nodes. The application manager controls start up and shut down of the nodes based on demands placed on the workloads. The scale out workload management system further includes a workload manager coupled to the application manager. The workload manager includes a monitor module that collects performance information from nodes on which the workloads are executing, an aggregator module that collects the performance information and aggregates the performance information from all nodes supporting the workloads, and a comparator module that compares aggregated performance information for the workloads to a performance target and determines if an allocation of nodes to the workloads should be changed.

Management of multiple scale out workloads

A computer utilization report presents utilization data in tabular form so that utilization data for different time frames can be readily compared. The time frames include long and short continuous time frames, as well as at least one periodic discontinuous time frame.

Utilization reporting with multiple time frames

In one representative embodiment, a system for operating load balancers for multiple instance applications comprises a plurality of cluster nodes for executing applications, wherein at least a subset of the plurality of cluster nodes executes multiple applications and includes respective resource allocation modules for assigning resources between the multiple applications in response to performance data associated with the multiple applications, a plurality of load balancers for distributing application transactions between the plurality of cluster nodes, and a configuration process that analyzes performance data associated with the multiple applications and dynamically configures the plurality of load balancers in response to the analysis.

System and method for dynamically configuring a plurality of load balancers in response to the analyzed performance data

In one embodiment, jobs requiring short processing time are given preference over jobs requiring long processing time by processing to completion all jobs for the first N seconds of the job. Jobs requiring longer than N seconds to complete are given a lower priority than a newly arriving job can and continue being processed, but are subject to reduction in resources by new jobs as each new job arrives.

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Altadena, CA, United States of America

Bryan L Backer