International Business Machines Corporation

Google Inc.

Peng Ye

Noshir Cavas Wadia

Lance Warren Russell

Joseph L Hellerstein

Maheswaran Surendra

Todd W Mummert

Steven E Froehlich

Mukund Raghavachari

Jayashree Subrahmonia

Luis J Ostdiek

Edwin Richie Lassettre

Lawrence S Hsiung

Lawrence Shun-mok Hsiung

David Wiley Coleman

Rahul Jain

Dikran S Meliksetian

Michael Ignatowski

Harold Hershey Hall, Jr

Catherine Cuong Diep

Rekha Devi Garapati

Sandra Sheu Chang

Cynthia Ferne Craine

Todd William Mummert

An apparatus, system, and method are disclosed for logically packaging and delivering a service offering. A set of service implementation artifacts, a service ordering process, and a service provisioning process are selected and configured to implement a service offering. A requirements specification for the set of service implementation artifacts is defined. Logical associations between parameters are defined such that a change of a parameter for a first component triggers a change for a parameter of a second component. Beneficially, such an apparatus, system, and method accelerates the self-service ordering and deployment of service offerings.

Apparatus, system, and method for logically packaging and delivering a service offering

Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.

Managing computing deployment in presence of variable workload

Techniques are provided for automating allocation of resources based on business decisions. An impact of a business decision is quantified in terms of information technology (IT) metrics. The resources that may be needed to address the impact are estimated. The estimated resources are provisioned.

Integrating performance, sizing, and provisioning techniques with a business process

Techniques are provided for allocating resources. Performance metrics for a transaction are received. It is determined whether one or more service level objectives are being violated based on the received performance metrics. In response to determining that the one or more service level objectives are being violated, additional resources are allocated to the transaction. In response to allocating the additional resources, a resource allocation event is published.

Peer to peer resource negotiation and coordination to satisfy a service level objective

Provided are a method, system, and program for distributing application transactions among work servers. Application transaction rates are determined for a plurality of applications supplying transactions to process. For each application, available partitions in at least one server are assigned to process the application transactions based on partition transaction rates of partitions in the servers. For each application, a determination is made of weights for each server including partitions assigned to the application based on a number of partitions in the server assigned to the application. The determined weights for each application are used to distribute application transactions among the servers including partitions assigned to the application.

Method, system, and program for distributing application transactions among work servers

The present invention discloses a method, system and article of manufacture for autonomic identification of an optimum hardware configuration for a Web infrastructure. A plurality of performance objectives and a plurality of best practice rules for the Web infrastructure are established first. Then, a search space and a current configuration performance index within the search space are established. Next, a database of available hardware models is searched for a best-fit configuration based on the established plurality of best practice rules and the established current configuration performance index. The performance data of the found best-fit configuration is calculated using a performance simulator and then compared to the established plurality of performance objectives. If the calculated performance data meet the established plurality of performance objectives, then the best-fit configuration is designated as the optimum hardware configuration. Otherwise, the search space is narrowed and searching is continued until such optimum hardware configuration is found.

Autonomic computing algorithm for identification of an optimum configuration for a web infrastructure

Methods and apparatus for managing computing deployment in presence of variable workload

The present invention discloses a method, system and article of manufacture for performing analytic modeling on a computer system by handling a plurality of predefined system criteria directed to a modeled computer system. The present invention provides means for the user of an analytic model to specify (i.e. enable) any number of predefined system criteria that must all be simultaneously satisfied. The modeling methodology uses a variation of the well-known Mean Value Analysis technique in its calculations. Response times, resource utilizations, and resource queue lengths are initially estimated for a small user arrival rate. An iterative method is used to gradually increase the user arrival rate by a constant value. For each iteration, response times, resource utilizations, and resource queue lengths are calculated. Then for all the criteria, which have been enabled, it is checked to see if the value limits specified for those criteria have exceeded. If not, the model calculation results are saved and next iteration is started. The model iterations continue with a gradually increasing user arrival rate until one or more of the modeling criteria are exceeded. At that time the model outputs the results from the previous iteration (i.e. the saved results where all the criteria were still satisfied), and the modeling calculations are finished. The model results may be used as input for further processing.

Method, system and article of manufacture for an analytic modeling technique for handling multiple objectives

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Fremont, CA, United States of America

Peng Ye