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A metric for predicting the performance of an application under a growing workload

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2 Author(s)
Weyuker, E.J. ; AT&T Research Laboratories, 180 Park Avenue, Florham Park, New Jersey 07932, USA ; Avritzer, A.

A new software metric, designed to predict the likelihood that the system will fail to meet its performance goals when the workload is scaled, is introduced. Known as the PNL (Performance Nonscalability Likelihood) metric, it is applied to a study of a large industrial system, and used to predict at what workloads bottlenecks are likely to appear when the presented workload is significantly increased. This allows for intelligent planning in order to minimize disruption of acceptable performance for customers. The case study also outlines our performance testing approach and presents the major steps required to identify current production usage and to assess the software performance under current and future workloads.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Systems Journal  (Volume:41 ,  Issue: 1 )