Baler: deterministic, lossless log message clustering tool

Authors:
Narate Taerat;Jim Brandt;Ann Gentile;Matthew Wong;Chokchai Leangsuksun
Affiliations:
Louisiana Tech University, Ruston, USA;Sandia National Laboratory in California, Livermore, USA;Sandia National Laboratory in California, Livermore, USA;Sandia National Laboratory in California, Livermore, USA;Louisiana Tech University, Ruston, USA
Venue:
Computer Science - Research and Development
Year:
2011

Citing 3
Cited 0

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Clustering event logs using iterative partitioning

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Abstract

The rate of failures in HPC systems continues to increase as the number of components comprising the systems increases. System logs are one of the valuable information sources that can be used to analyze system failures and their root causes. However, system log files are usually too large and complex to analyze manually. There are some existing log clustering tools that seek to help analysts in exploring these logs, however they fail to satisfy our needs with respect to scalability, usability and quality of results. Thus, we have developed a log clustering tool to better address these needs. In this paper we present our novel approach and initial experimental results.