Using Multi-System Monitoring Time Series to Predict Performance Events

  • Andreas Schörgenhumer (Speaker)

Activity: Talk or presentationContributed talkscience-to-science

Description

The prediction of failures and other mission-critical events plays an important role in operating today’s software systems and has drawn the attention of many researchers. Event prediction is particularly challenging if multiple systems are involved. In this paper, we thus present an event prediction model which utilizes time series monitoring data from multiple software systems to predict performance events. Our approach incorporates a comprehensive, multi-system data preprocessing framework for creating various feature vector sets, which we then use to train a random forest classifier to evaluate our multi-system event prediction. Our preliminary evaluation based on data from monitoring 250 systems over a period of 20 days shows promising results.
Period09 Nov 2018
Event title9th Symposium on Software Performance (SSP 2018)
Event typeConference
LocationGermanyShow on map

Fields of science

  • 102 Computer Sciences
  • 102022 Software development
  • 102025 Distributed systems

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Engineering and Natural Sciences (in general)