Bank of America Corporation

Vijay B Akella

Susan McClung

Rajat Wadhwani

Michael J Ragunas

Cheryl Robinson

Kevin R Davis

Steve A Erickson

Nicholas G Hesse

Leigh Anne Whitlock

Matthew S Kukielski

Bryant Lee Osborn

Heidi Jane Johnson

Thomas A Wheeler

James E Dunevant

Angela K Workman

Christian P Selmi

Embodiments of the invention relate to systems, methods, and computer program products that provide for a technological infrastructure consumption index. The index is instrumental in measuring and managing technological infrastructure consumption. The consumption index is generated on a predetermined schedule as indicator of a business entity's volume of infrastructure consumption. The consumption index tracks key consumption elements, which are within the control of application teams, thereby insuring that the consumption of the key elements are being managed on an ongoing basis. Additionally, the consumption index provides for drill-down capabilities for the purpose of readily accessing data associated with specific key consumption elements of interest and specific teams/organizations within the business entity.

Technological infrastructure consumption index

Embodiments of the present invention provide apparatuses and methods for a capacity model run-time estimator that determines the transactional capacity of an application. The capacity model run-time estimator is based on a model that includes at least one job with various steps within a run-time window. One or more windows make up shifts and one or more shifts make up a day. Historical data is used to estimate various run-times for each of the steps in a window. If the steps are dependent on transaction characteristics a statistical analysis is used to determine a run-time window estimator model that is dependent on the transaction characteristics. Constraints are placed on the run-time and transaction capacity of the windows, intra-windows, and shifts. The capacity model uses the run-time window estimators and constraints to determine the transaction capacity for an application across various periods and compares the results to forecasted capacity.

Capacity modeling system

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Charlotte, NC, United States of America

Vijay B Akella