Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41196

Collaborative Software Performance Engineering for Enterprise Applications

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Item Summary

Title: Collaborative Software Performance Engineering for Enterprise Applications
Authors: Müller, Hendrik
Bosse, Sascha
Wirth, Markus
Turowski, Klaus
Keywords: Operations analytics
Capacity management
Response time
Monitoring
Prediction
Issue Date: 04 Jan 2017
Abstract: In the domain of enterprise applications, organizations usually implement third-party standard software components in order to save costs. Hence, application performance monitoring activities constantly produce log entries that are comparable to a certain extent, holding the potential for valuable collaboration across organizational borders. Taking advantage of this fact, we propose a collaborative knowledge base, aimed to support decisions of performance engineering activities, carried out during early design phases of planned enterprise applications. To verify our assumption of cross-organizational comparability, machine learning algorithms were trained on monitoring logs of 18,927 standard application instances productively running at different organizations around the globe. Using random forests, we were able to predict the mean response time for selected standard business transactions with a mean relative error of 23.19 percent. Hence, the approach combines benefits of existing measurement-based and model-based performance prediction techniques, leading to competitive advantages, enabled by inter-organizational collaboration.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41196
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.047
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Data Science and Analytics for Collaboration Minitrack



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