Key performance indicators for traffic intensive web‐enabled business processes
Purpose – Intensive traffic often occurs in web‐enabled business processes hosted by travel industry and government portals. An extreme case for intensive traffic is flash crowd situations when the number of web users spike within a short time due to unexpected events caused by political unrest or extreme weather conditions. As a result, the servers hosting these business processes can no longer handle overwhelming service requests. To alleviate this problem, process engineers usually analyze audit trail data collected from the application server and reengineer their business processes to withstand unexpected surge in the visitors. However, such analysis can only reveal the performance of the application server from the internal perspective. This paper aims to investigate this issue. Design/methodology/approach – This paper proposes an approach for analyzing key performance indicators of traffic intensive web‐enabled business processes from audit trail data, web server logs, and stress testing logs. Findings – The key performance indicators identified in the study's approach can be used to understand the behavior of traffic intensive web‐enabled business processes and the underlying factors that affect the stability of the web server. Originality/value – The proposed analysis also provides an internal as well as an external view of the performance. Moreover, the calculated key performance indicators can be used by the process engineers for locating potential bottlenecks, reengineering business processes, and implementing contingency measures for traffic intensive situations.
Year of publication: |
2012
|
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Authors: | Pun, Ka I. ; Whar Si, Yain ; Chan Pau, Kin |
Published in: |
Business Process Management Journal. - Emerald Group Publishing Limited, ISSN 1758-4116, ZDB-ID 2014421-0. - Vol. 18.2012, 2, p. 250-283
|
Publisher: |
Emerald Group Publishing Limited |
Subject: | Key performance indicators | Traffic intensive web application | Audit trail analysis | Web server log | Stress testing | User studies | World wide web |
Saved in:
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