International Business Machines Corporation

Rohith Kottamangalam Ashok

Roy Frank Brabson

Hugh Edward Hockett

Matt Richard Hogstrom

Aaron J Quirk

Matthew J Sheard

Wei Lung Chan

Jose I Ortiz

Aaron Kyle Shook

Ruth Edith Willenborg

Michael John Burr

James K Kochuba

Todd Eric Kaplinger

Daniel Everett Jemiolo

Michael S Law

Bret Ronald Olszewski

Leigh Allen Williamson

Shu Chao Wan

Erik John Burckart

Rahul Ghosh

Thomas M Brey

Ian N Whalley

Antonio Abbondanzio

Andrew Russell Low

Tiia J Salo

Raymond J Harrington

Agustin Mena, Iii

Ivan M Heninger

David Blair Gilgen

Christopher Paul Vignola

Meeta Yadav

Barry P Gower

Wolfgang Segmuller

Douglas Alan Larson

Kristin R Whetstone

Charles James Redlin

Barry Charles Searle

Edward M Howard

David N Nguyen

Thuy B Nguyen

Matthew R Hogstrom

Gerald Francis McBrearty

Lap Thiet Huynh

Steven Dale Ims

Sivaram Gottimukkala

Darryl Edward Gardner

Natasha Pothen

Juniarti A Suryakusuma

Mickael Maison

A method for providing secure access to a virtual machine includes dispensing an image corresponding to a virtual machine from a management appliance to a distributed computing system such that the virtual machine is implemented by at least one of a plurality of interconnected physical computing devices in the distributed computing system; establishing a trusted relationship between the management appliance and the virtual machine; and providing a user with access to the virtual machine from the management appliance without further authentication credentials from the user.

Secure access to a virtual machine

A method and technique for allocation and balancing of storage resources includes monitoring, for each of a plurality of storage controllers, an input/output (I/O) latency value based on an I/O latency associated with each storage volume controlled by a respective storage controller. An I/O latency value threshold is determined. Responsive to a change to the I/O latency value exceeding a threshold, storage volume distribution among the storage controllers is rebalanced.

Allocation and balancing of storage resources

A method and technique for allocation and balancing of storage resources includes monitoring, for each of a plurality of storage controllers, input/output (I/O) latency, network bandwidth utilization, and network latency associated with each storage volume controlled by a respective storage controller. Responsive to receiving a request to allocate a new storage volume, a type of application and an anticipated storage workload level that will utilize one or more of the storage volumes by the application is determined. The I/O latency, network bandwidth utilization, and network latency is analyzed relative to respective thresholds, and the new storage volume is allocated to a selected storage controller based on the analysis and the anticipated storage workload level.

Allocation and balancing of storage resources based on anticipated workload levels

A method and technique for allocation and balancing of storage resources includes monitoring, for each of a plurality of storage controllers, an input/output (I/O) latency value based on an I/O latency associated with each storage volume controlled by a respective storage controller. A network bandwidth utilization value and a network latency value corresponding to each storage controller is also monitored. An I/O latency value threshold, a network bandwidth utilization threshold, and a network latency value threshold is determined. Responsive to at least one of the I/O latency value, the network bandwidth utilization value and the network latency value for at least one storage controller exceeding a respective threshold, storage volume distribution among the storage controllers is rebalanced.

Distribution of middleware binary includes: receiving a request to deploy a workload with middleware service(s); selecting a base operating system (OS) image to host the middleware service(s); determining locations of binary file(s) for the middleware service(s) in a repository on a storage system; cloning a virtual disk containing the base OS image on the storage system; and copying the binary file(s) from the locations in the repository into the cloned virtual disk on the storage system. The binary file(s) are copied onto the virtual disk directly on the storage system, without the need to traverse a network interface. The base OS image is augmented with the binary files just prior to the deployment of the virtual machine (VM).

Method to optimize provisioning time with dynamically generated virtual disk contents

A method, system and computer program product for managing hardware components in a cloud computing environment. A mobile device captures an image of a bar code placed on a rack that is associated with an identifier that references an Internet resource of the management software that manages the rack. The mobile device transmits a request to the management software for information regarding a component in the rack, where the request includes a unique identifier (e.g., serial number) associated with the component. The management software uses the unique identifier to identify the component of interest and transmits information regarding the component of interest to the mobile device. In this manner, the client device can conveniently access the management software as well as conveniently acquire information dynamically from the management software about specific hardware components in these racks while the user is on the floor of the data center.

Acquiring information dynamically regarding a hardware component in the cloud computing system while on the floor of the data center

In an approach to manage isolation requirements of a multi-node workload application, a computer determines one or more first isolation levels for each of a plurality of workload nodes. The computer receives performance data for the plurality of workload nodes and analyzes the performance data for statistical trends in the performance data. The computer identifies an adverse trend in the statistical trends of the performance data and identifies a root cause of the adverse trend in the performance data. The computer then identifies one or more second isolation levels required to meet performance targets, the second isolation levels including an adjustment to the first isolation levels for the plurality of workload nodes.

Managing isolation requirements of a multi-node workload application

A method, data storage device and computer program product for efficiently configuring different types of hardware components. A Universal Serial Bus (USB) key is preloaded with multiple profiles, where each profile contains a configuration file(s) associated with a particular type of hardware component. Upon plugging the USB key into a hardware component, the USB key recognizes the type of hardware component based on the properties of the hardware component available on the USB interface. The USB key identifies a profile containing the configuration file(s) associated with the recognized type of hardware component. The USB key then presents the configuration file(s) contained in the identified profile to the connected hardware component. Such a process may be repeated for configuring another type of hardware component. In this manner, the user is able to efficiently configure different types of hardware by having the USB key function as multiple USB keys.

Universal serial bus (USB) key functioning as multiple USB keys so as to efficiently configure different types of hardware

A method, system and computer program product for selecting hypervisor platforms that are best suited to process application workloads. Attribute requirements for an application workload, such as high CPU capacity, high power and low cost, are received. A ranking algorithm is then applied to a list of pools of compute nodes to identify an ordered list of pools of compute nodes that are best suited for satisfying the attribute requirements of the application workload by comparing hypervisor characteristics of the pools of compute nodes with the attribute requirements of the application workload. Each pool of compute nodes runs on a particular hypervisor platform which has a unique combination of characteristics that correspond to a combination of a set of attribute requirements (e.g., medium CPU/memory/disk capacity; high CPU and memory performance). In this manner, the hypervisor platforms that are best suited for satisfying the application workload requirements are identified.

Selecting optimal hypervisor platforms that satisfy application workload requirements

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Apex, NC, United States of America

Rohith Kottamangalam Ashok