Hewlett-packard Development Company, L.p.

Hewlett Packard Enterprise Development LP

Clifford A McCarthy

Geoffery Schunicht

Abhay Padlia

Rajeev Pandey

Charles S Greenidge

Latha Srinivasan

Subhajit Dasgupta

Jonathan M Sauer

Michelle Catherine Frolik

Charles E Fowler

Gary L Thunquest

Sandesh V Madhyastha

Jerry Harrow

Ludmila Cherkasova

Jerome Rolia

Daniel Edward Herington

Thomas Edwin Turicchi, Jr

Raja Daoud

Canming Jin

Parthasarathy Ranganathan

Vanish Talwar

Alan L Goodrum

Xiaoyun Zhu

Zhikui Wang

Charles W Cochran

William H Blanding

Troy Don Miller

Steven R Landherr

Jerry James Harrow, Jr

Tom Turicchi

Thomas E Turicchi

A system to facilitate infrastructure management is described. The system includes one or more processors and a non-transitory machine-readable medium storing instructions that, when executed, cause the one or more processors to execute an infrastructure management controller to automatically balance utilization of infrastructure resources between a plurality of on-premise infrastructure controllers.

Load balancing of on-premise infrastructure resource controllers

A system to facilitate infrastructure management is described. The system includes one or more processors and a non-transitory machine-readable medium storing instructions that, when executed, cause the one or more processors to execute an infrastructure management controller to receive a request to provide infrastructure management services and generate a mapping between at least one instance of the infrastructure management controller and one or more resource instances at one or more on-premise infrastructure controller instances to provide the cloud based infrastructure management services, wherein the request includes one or more configuration parameters.

Infrastructure resource mapping mechanism based on determined best match proposal for workload deployment

A system to facilitate infrastructure management is described. The system includes one or more processors and a non-transitory machine-readable medium storing instructions that, when executed, cause the one or more processors to execute an infrastructure management controller to receive first monitoring data indicating a first infrastructure condition occurring at an on-premise infrastructure controller, determine a first load state of the on-premise infrastructure controller based on the first infrastructure condition and adjust a consistency level of the on-premise infrastructure controller to a first level of the consistency based on the first state.

Infrastructure adaptive consistency level mechanism

Infrastructure load balancing using software-defined networking controllers

A system to facilitate infrastructure management is described. The system includes a plurality of management controllers each having a control function of a plurality of infrastructure devices and a state cache storing a state of the plurality of infrastructure devices, including a first management controller to initiate an operation to be performed on a first set of resources. The system also includes a plurality of infrastructure controllers, each having a state repository to maintain a state function of the plurality of infrastructure devices, including a first infrastructure controller associated with the first set of resources to perform the operation on the first set of resources, update a first state repository including an updated state of the first set of resources in response to the operation and broadcast the updated state of the first set of resources to each of the plurality of management controllers.

Peer to peer infrastructure management architecture

Fault-tolerant power control in a computer system is described. In an example, a power controller to control power applied to an enclosure having a plurality of computing devices includes: first and second alternating current (AC) primary power meters respectively measuring first and second input power feeds to the enclosure; a first alternative power meter to measuring power supplied by the first input power feed; a second alternative power meter to measure power supplied by the second input power feed; a first controller coupled to the first primary power meter and the second alternative power meter; and a second controller coupled to the second primary power meter and the first alternative power meter; wherein the first controller is coupled to the second controller.

Fault-tolerant power control in a computer system

A system comprises a workload manager evaluator operable to receive a representative workload that is representative of competing workloads that share access to at least one shared computing resource. The workload manager evaluator is operable to evaluate performance of a scheduler that schedules access of the competing workloads to the shared computing resource according to defined control parameter values, wherein the workload manager evaluator evaluates performance of the scheduler under the representative workload for a plurality of different values of the control parameters. In certain embodiments, the workload manager evaluator determines an optimal value for the control parameters of the scheduler for scheduling access to the at least one shared computing resource for the representative workload to satisfy defined performance desires of the system.

Evaluating performance of workload manager based on QoS to representative workload and usage efficiency of shared resource for plurality of minCPU and maxCPU allocation values

When the maximum power consumption of a computer exceeds a currently selected power-consumption cap, a cap setting corresponding to the currently selected power-consumption cap is reduced. In addition, power-cap settings corresponding to power-consumption caps between said currently selected power-consumption cap and said maximum power consumption are reduced.

Decrementing settings for a range of power caps when a power cap is exceeded

Apparatus, methods, and other embodiments associated with providing a correlation between a power distribution unit(s) and a device(s) are described. One example method includes storing first time series data that identifies, on a per power distribution unit (PDU) basis, current drawn from a set of PDUs. The example method may include storing second time series data that identifies, on a per device basis, power used by a set of related devices. With the two time series data available, the method may then provide a PDU-device correlation signal that identifies a correlation between current drawn from a PDU and power used by a device.

Power distribution unit-device correlation

A method comprises defining a scheduler parameter for a maximum allocation of capacity of a shared resource to a consumer for a scheduling interval. Utilization of an allocated capacity of the shared resource by the consumer during a given scheduling interval is measured, and when the allocated capacity of the shared resource is completely utilized by the consumer during the given scheduling interval, the scheduler increases the allocated capacity of the shared resource to the defined maximum allocation for the consumer for a next scheduling interval. Thus, rather than gradually increasing the allocation of capacity over many intervals, the scheduler immediately increases the allocation to a predefined maximum amount in response to an allocated amount of capacity being completely utilized during a scheduling interval.

System and method for allocating capacity of shared resources to a workload

Power consumption of a group of computer systems is managed based on a maximum power consumption for the group. A power budget is determined from the power consumption of each computer system and the maximum power consumption for the group. The power budget identifies a power cap for each computer system in the group. The power caps in the power budget are distributed to the computer systems in the group.

Power budgeting for a group of computer systems using utilization feedback for manageable components

A computer system characterized by a container hierarchy uses a workload manager to allocate computing resources to workloads. The workload manager can allocate resources as a function of aggregate characteristics of a group of workloads, even where the group does not conform to the container hierarchy.

Workload management for computer system with container hierarchy and workload-group policies

A system comprises a workload evaluator that is operable to receive a representative workload that is representative of competing demands for capacity of at least one shared computing resource. The workload evaluator evaluates the representative workload and computes a metric representing a degree of burstiness of demands present in the representative workload. The metric representing degree of burstiness of the representative workload may be used for estimating an upper bound on quality of service provided by a workload manager to the representative workload. The metric may also be used for evaluating at least one scheduler parameter setting of the workload manager to aid in determining an optimal parameter setting based at least in part on the estimated impact of the representative workload on QoS provided by the workload manager.

System and method for evaluating a workload and its impact on performance of a workload manager

A method is disclosed for allocating computer system resources, such as memory, among applications. Input parameters are received for applications. The parameters include a minimum entitlement value, a maximum entitlement value, and a weight. The minimum entitlement is the minimum amount of resources that the application should receive. The maximum entitlement is the maximum amount of resources that the application should receive. The weight specifies the priority of the application relative to other applications, for purposes of distributing system resources. Computer system resources are then allocated among applications based on the parameters.

Allocation of system resources among applications using predefined entitlement values and weight associated with each of the applications

In one embodiment, a system comprises a plurality of partitions that provide isolated operating environments for execution of software processes, wherein the plurality of partitions are arranged in a tiered manner with different partition types at different tiers, a data structure for representing the plurality of partitions, wherein the data structure comprises multiple nodes corresponding to the plurality of partitions and links between the nodes representing how the plurality of partitions are arranged in the tiers, and an arbiter software module for allocating resources between the plurality of partitions, wherein the arbiter software module receives requests to allocate resources to the plurality of partitions and traverses the data structure to determine which requests to satisfy.

Growing community of inventors

Plano, TX, United States of America

Clifford A McCarthy