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. 

Relevance to testing: 

• The case study demonstrates how to perform a system performance test and important parameters to measure. 
• Performance testers can use the PNL to predict the workload at which the system will brake, and therefore test the critical system parameters. 

Slide presentation

E. J. Weyuker and A. Avritzer (2002), "A metric for predicting the performance of an application under a growing workload," IBM Systems Journal 41(1): 45-54.

Reiner Dumke et al. (2001), "Performance Engineering, State of the Art and Current Trends", Springer Verlag

Boudewijn Haverkort et al. (2001), "Performability Modeling, Techniques and Tools", John Wiley & Sons.