Capacity Planning for and Performance Analysis of Large Distributed Transaction Systems


James Aries
Marc Brittan
Eric Dillon
Alan Korncoff
Janusz S. Kowalik
John Lixvar


Every transaction system supporting business processes must satisfy some computational performance requirements. If it does not, the system may have a significantly reduced value or become useless. The number of factors that influence performance of distributed transaction systems is so large, that the traditional capacity planning methods appropriate for centralized mainframe systems are not applicable.

The most cost-effective method has proven to be predictive modeling. A combination of analytic and simulation modeling is most useful for analyzing and tuning performance of systems that have been designed or are in production. The task of designing a system ab initio given expected workloads and required performance/cost constraints is much harder. In this special issue, the paper by Marc Brittan and Janusz Kowalik describes a method for designing initial systems configurations and capacities. This paper focuses on predictive simulation modeling that is used for detailed performance analysis of existing systems. Such analyses may be motivated by "what-if" studies or by a desire to improve system's unsatisfactory performance.


Special Issue