International Business Machines Corporation

Jeffrey Wayne Tenner

Joseph W Cropper

Richard D Dettinger

Richard Joseph Stevens

Daniel Paul Kolz

Kyle Lane Henderson

Eric W Will

Thomas John Eggebraaten

Shannon Everett Wenzel

Gerald Francis McBrearty

Robert J Bestgen

Samuel D Matzek

Taylor D Peoples

Paul Reuben Day

Randy Lynn Egan

David Gerald Herbeck

Jennifer D Mulsow

Robert Douglas Driesch, Jr

Shantan Kethireddy

Christine Iju Wang

Jennifer L LaRocca

Andrew Thomas Thorstensen

Judy Immaculate Tina Djugash

James Buntrock

Serguei V Pakhomov

Christopher Chute

Brian Robert Muras

Mark John Anderson

Peter John Johnson

Hoa Thu Tran

Alwood Patrick Williams, Iii

Travis Michael Drucker

Samuel J Miller

Lynnette Elaine Carston

Carol Ledermann Ramler

Hao Thu Tran

Duy Nguyen

Gary E Rohret

Asset management for a shared pool of configurable computing resources is disclosed. For a set of assets which share a resource on a first compute node, a set of asset weight values is identified. The set of asset weight values indicates a set of utilization shares of the resource by the set of assets. A set of asset priority values is identified with respect to the set of assets on the first compute node. The set of asset priority values indicates a relative status arrangement for the set of assets. Using the set of asset weight values and the set of asset priority values, a determination is made to migrate a first asset of the set of assets from the first compute node to a second compute node. Accordingly, the first asset of the set of assets is migrated from the first compute node to the second compute node.

Asset management with respect to a shared pool of configurable computing resources

As part of a container initialization procedure, a maximum number of hardware threads per processor core in a set of cores of a computer system are enabled, the container initialization procedure configuring an operating system executing on the computer system for container execution and configuring a first container for execution on the operating system. From a set of available cores in the set of cores, an execution core is selected. In the selected execution core, a number of threads per core to be used during execution of the first container is configured, the number of threads per core specified for the container initialization procedure by a first simultaneous multithreading (SMT) parameter. Using the configured execution core, the first container is executed, the executing virtualizing the operating system.

Configuring hardware multithreading in containers

An embodiment includes extracting, by a scheduler, function-tag data associated with a function identified by a deployment request. The embodiment also includes selecting, by the scheduler, a computing device within a server cluster to host the function based at least in part on a comparison of the function-tag data and host-tag data associated with the computing device. The embodiment also includes issuing, by the scheduler, an instruction to the computing device, wherein the issuing of the instruction causes an allocation of resources for hosting execution of the function.

Tag-driven scheduling of computing resources for function execution

Disclosed aspects relate to asset management with respect to a shared pool of configurable computing resources. With respect to a set of assets which share a resource on a first compute node, a set of asset weight values is identified. The set of asset weight values indicates a set of utilization shares of the resource by the set of assets. A set of asset priority values is identified with respect to the set of assets on the first compute node. The set of asset priority values indicates a relative status arrangement for the set of assets. Using the set of asset weight values and the set of asset priority values, a determination is made to migrate a first asset of the set of assets from the first compute node to a second compute node. Accordingly, the first asset of the set of assets is migrated from the first compute node to the second compute node.

A computer in a cloud computing environment includes a virtualization instance (VI) providing cloud services to a consumer device. The computer includes non-virtualizing and self-virtualizing type devices. The VI uses a first virtual device that is a virtual form of one of the non-virtualizing type devices to meet Quality of Service (QoS) objectives. A method for managing the resources of the cloud comprises receiving QoS metrics, determining that the VI cannot meet the QoS objectives using the first virtual device, determining that a second virtual device comprising a virtual form of one of the self-virtualizing type device alternative to that of first virtual device is available and can meet the QoS objectives, and configuring the VI to use the second virtual device in place of the first virtual device. A computer programming product and a system can embody the method.

Swapping non-virtualizing and self-virtualizing devices

Composite virtual machine templates may be used in the deployment of virtual machines into virtualized computing environments. A composite virtual machine template may define a plurality of deployment attributes for use in a virtual machine deployment, and at least some of these deployment attributes may be determined through references to other virtual machine templates and included in the composite virtual machine template.

Composite virtual machine template for virtualized computing environment

A method and system are provided for implementing a policy-driven resource deployment in a cloud environment. A rules-based workflow is used to determine an enhanced deployment option based on requirements of an end user. A policy-driven catalog entry is created including a corresponding set of questions to determine how the end user intends to use their environment. The end user makes a request which contains answers to the set of questions. Answers contained in the end user request are applied to a set of rules for determining a particular deployment option, and resources are deployed using the determined deployment option.

Implementing a policy-driven resource deployment mechanism in a cloud environment

A method for enabling management of cloud resources based on tiered storage data movement includes receiving a request from a cloud computing system to provide the cloud computing system a notification of a data movement initiated by a tiered storage system, where the data movement comprises moving data associated with the cloud computing system from a first storage tier to a second storage tier, and the notification comprises an indication of a condition for initiating the data movement. The method then includes determining that a condition for initiating the data movement was satisfied. The method further includes initiating the data movement in response to determining that the condition was satisfied. The method additionally includes transmitting the notification in response to initiating the data movement.

Policy-based optimization of cloud resources on tiered storage operations

A workload of a virtualized computing environment is rebalanced by resizing and/or moving one or more virtual machines allocated resources from a shared pool of resources in the virtualized computing environment based upon multiple resource capacities specified for each virtual machine and representing different portions of the resources from the shared pool of resources, e.g., minimum and desired resource capacities.

Iterative rebalancing of virtual resources among VMs to allocate a second resource capacity by migrating to servers based on resource allocations and priorities of VMs

One or more concurrency limits may be checked in connection with the performance of a virtual machine management operation such as a virtual machine deploy, resize or migration operation to enable the virtual machine management operation to be scheduled on a host for which no concurrency limits have been met.

Management of a virtual machine in a virtualized computing environment based on a concurrency limit

Temporal dynamic policies may be used to effectively alter the management of a virtual machine in a virtualized computing environment based upon some temporal condition such as how long a virtual machine has been active or idle, how long it has been since the virtual machine was created or deployed, etc. The altered management may be used, for example, to activate various performance and/or reliability-related technologies such as high availability and failover functionality for longer-running virtual machines.

Temporal dynamic virtual machine policies

Disclosed aspects relate to managing link aggregation with respect to a shared pool of configurable computing resources. A set of workloads of the shared pool of configurable computing resources can be monitored to identify a set of networking data. Based on the set of networking data, a link aggregation arrangement for dynamic adjustment may be determined. The link aggregation arrangement may be established by dynamic adjustment with respect to the shared pool of configurable computing resources.

Link aggregation management with respect to a shared pool of configurable computing resources

Disclosed aspects manage a shared pool of configurable computing resources. A set of scaling factor data is monitored. The set of scaling factor data is related to a workload on a configuration of the shared pool of configurable computing resources. A set of workload resource data associated with the workload is ascertained. Using the set of scaling factor data and the set of workload resource data, a triggering event is detected. In response to detecting the triggering event, a configuration action (with respect to the configuration of the shared pool of configurable computing resources) is performed.

Growing community of inventors

Rochester, MN, United States of America

Jeffrey Wayne Tenner