Performance problem prediction in transaction-based e-business systems
| Autor: | Anindya Neogi, Ruchi Mahindru, Gautam Kar, Anca Sailer, Manoj K. Agarwal |
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| Rok vydání: | 2008 |
| Předmět: |
Dependency (UML)
Electronic business Computer Networks and Communications Computer science Process (engineering) computer.software_genre Resource (project management) Risk analysis (engineering) Anticipation (artificial intelligence) Data mining Electrical and Electronic Engineering Root cause analysis computer Database transaction Electronic data interchange |
| Zdroj: | IEEE Transactions on Network and Service Management. 5:1-10 |
| ISSN: | 1932-4537 |
| DOI: | 10.1109/tnsm.2008.080101 |
| Popis: | Key areas in managing e-commerce systems are problem prediction, root cause analysis, and automated problem remediation. Anticipating SLO violations by proactive problem determination (PD) is particularly important since it can significantly lower the business impact of application performance problems. The main contribution of this paper is to investigate proactive PD 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 contribution of all supporting resources for a transaction to the end-to-end SLO for that transaction. Higher order moments of these components' contributions are further tracked for proactive alerting. 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 the different classes only. Combined with the complete or semi-complete dependency information, our approach confines the scope of potential root causes to a small set of components, thus enabling efficient performance problem anticipation and quick remediation. |
| Databáze: | OpenAIRE |
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