Performance Problem Prediction in Transaction Based e-Business Systems

Copyright © (2008) by IEEE. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distrubuted for profit. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee.

Key areas in managing environments that implement e-commerce systems are problem prediction, root cause analysis, and automated problem remediation. Anticipating SLO violations by proactive (rather than reactive) problem determination is particularly important since it can significantly lower the business impact of application performance problems. The approach investigated here is based on two important concepts: dependency graphs and dynamic runtime performance characteristics of resources that comprise an I/T environment. The authors show how one can calculate and use the extent to which supporting resources for a transaction contribute to the end-to-end SLOs for that transaction. An important aspect of this process is the classification of user transactions based on the profile of their resource usage, enabling one to set appropriate thresholds for different classes. Combined with the complete or semi-complete dependency information, our approch confines the scope of potential root causes to a small set of components, thus enabling efficient performance problem anticipation and quick remediation.

By: Manoj K Agarwal; Gautam Kar; Ruchi Mahindru; Anindya Neogi; Anca Sailer

Published in: , volume 5, (no ), pages 1-10 in 2008


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