International Business Machines Corporation

Joseph W Cropper

Jeffrey Wayne Tenner

John Matthew Santosuosso

Eric L Barsness

James E Carey

Jay Symmes Bryant

Taylor D Peoples

Jennifer D Mulsow

Kyle Lane Henderson

Sadek Jbara

Jason Allan Nikolai

Andrew Thomas Thorstensen

Susan F Crowell

Edward Shvartsman

Christine Iju Wang

Yong Feng

Charles Volzka

Robert Douglas Holt

Ofer Biran

Carlos David Bermudez

Duy Nguyen

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

Disclosed aspects manage a shared pool of configurable computing resources. A resource demand value is identified for a target host. Resource supply values of dynamically-assigned resources are computed for donor hosts. Using the resource demand value and the resource supply values, dynamically-assigned resources are reclaimed from the donor hosts and distributed to the target host.

Dynamically-assigned resource management in a shared pool of configurable computing resources

A method and system are provided for implementing virtual machine (VM) memory right-sizing using VM memory compression. VM memory right-sizing includes monitoring VM memory utilization relative to a memory utilization up-size threshold and a memory utilization down-size threshold for the VM, and a current memory compression factor of total effective memory based on compression. When the VM is above the memory utilization up-size threshold and at a maximum memory allocation, a memory compression factor is increased. When the VM is below the memory utilization down-size threshold and the current memory compression factor is greater than one, the memory compression factor is decreased.

Implementing VM memory right-sizing using VM memory compression

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 processing distributed breakpoints when debugging a distributed application includes establishing a breakpoint in source code of a distributed computer program and executing the distributed computer program. Thereafter, an encountering of the breakpoint is detected in one of the processes, and execution of the one of the processes halted. However, halting execution of any other of the processes is delayed for a delay period during which a list both is generated of others of the processes in which the breakpoint is encountered and also is sorted in accordance with prioritization criteria. Finally, the sorted list is presented after the lapse of the delay period, individual ones of the processes selected in the list, and execution of the selected individual ones of the processes in the sorted list halted while halting of execution of non-selected ones of the processes in the sorted list is bypassed.

Intelligent processing of distributed breakpoints

Placement of virtual machines on physical hosts is based on collocation rules with situational enforcement policies set by a system administrator to increase flexibility in rule enforcement and to more efficiently utilize system resources. A scheduler mechanism allows a system administrator to select different collocation rules and situational enforcement policies for a group of virtual machines. The scheduler mechanism utilizes the collocation rules and the situational enforcement policies to place the virtual machines.

Placement of virtual machines on physical hosts based on collocation rules

A web server includes a client pressure profile sharing and generation mechanism that detects when a user accesses the web server with a first device that does not have a client pressure profile, and automatically generates a client pressure profile for the first device from a client pressure profile for a second device used by the user. Adjustments may be automatically made to the client pressure profile for the first device based on differences in orientation and based on differences in screen size. Changes by the user to the client pressure profile for the first device can be automatically propagated to client pressure profiles for other devices used by the user.

Automatic generation of a client pressure profile for a touch screen device

A processor may determine, using natural language processing, a writing style of content of a composed message written by a composer. The processor may analyze, using natural language processing, a set of previous message written by the composer. The processor may identify, based on the analyzing, writing habits of the composer. The processor may also identify a difference between the writing style of the content and the writing habits of the composer. The processor may display a notification of the difference to the user.

Growing community of inventors

Rochester, MN, United States of America

Joseph W Cropper