Ginpex: deriving performance-relevant infrastructure properties through goal-oriented experiments

  • Authors:

  • Michael Hauck;Michael Kuperberg;Nikolaus Huber;Ralf Reussner

  • Affiliations:

  • FZI Research Center for Information Technology, Karlsruhe, Germany;Karlsruhe Institute of Technology, Karlsruhe, Germany;Karlsruhe Institute of Technology, Karlsruhe, Germany;Karlsruhe Institute of Technology, Karlsruhe, Germany

  • Venue:
  • Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS
  • Year:
  • 2011

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Abstract

In software performance engineering, the infrastructure on which an application is running plays a crucial role when predicting the performance of the application. Thus, to yield accurate prediction results, performance-relevant properties and behaviour of the infrastructure have to be integrated into performance models. However, capturing these properties is a cumbersome and error-prone task, as it requires carefully engineered measurements and experiments. Existing approaches for creating infrastructure performance models require manual coding of these experiments, or ignore the detailed properties in the models. The contribution of this paper is the Ginpex approach, which introduces goal-oriented and model-based specification and generation of executable performance experiments for detecting and quantifying performance relevant infrastructure properties. Ginpex provides a metamodel for experiment specification and comes with pre-defined experiment templates that provide automated experiment execution on the target platform and also automate the evaluation of the experiment results. We evaluate Ginpex using two case studies, where experiments are executed to detect the operating system scheduler timeslice length, and to quantify the CPU virtualization overhead for an application executed in a virtualized environment.