Proactive identification of performance problems

Authors:
Songyun Duan;Shivnath Babu
Affiliations:
Duke University;Duke University
Venue:
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Year:
2006

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Abstract

We propose to demonstrate Fa, an automated tool for timely and accurate prediction of Service-Level-Agreement (SLA) violations caused by performance problems in database systems. Fa periodically collects performance data at three levels: applications, database server, and operating system. This data is used to construct probabilistic models for predicting SLA violations. Fa currently uses graphical Bayesian network models because of their ability to support a wide range of inferences, including prediction and diagnosis, as well as their support for interactive visualization and presentation of complex system behavior in intuitive ways.