DocumentCode
1640667
Title
Bad Words: Finding Faults in Spirit´s Syslogs
Author
Stearley, Jon ; Oliner, Adam J.
Author_Institution
Sandia Nat. Labs., Albuquerque, NM
fYear
2008
Firstpage
765
Lastpage
770
Abstract
Accurate fault detection is a key element of resilient computing. Syslogs provide key information regarding faults, and are found on nearly all computing systems. Discovering new fault types requires expert human effort, however, as no previous algorithm has been shown to localize faults in time and space with an operationally acceptable false positive rate. We present experiments on three weeks of syslogs from Sandia\´s 512-node "Spirit" Linux cluster, showing one algorithm that localizes 50% of faults with 75% precision, corresponding to an excellent false positive rate of 0.05%. The salient characteristics of this algorithm are (1) calculation of nodewise information entropy, and (2) encoding of word position. The key observation is that similar computers correctly executing similar work should produce similar logs.
Keywords
Linux; entropy; software fault tolerance; system monitoring; Spirit Linux cluster; bad words; false positive rate; fault detection; information entropy; syslogs; Clustering algorithms; Computer science; Fault detection; Grid computing; Humans; Laboratories; Monitoring; Programming profession; Supercomputers; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Cluster Computing and the Grid, 2008. CCGRID '08. 8th IEEE International Symposium on
Conference_Location
Lyon
Print_ISBN
978-0-7695-3156-4
Electronic_ISBN
978-0-7695-3156-4
Type
conf
DOI
10.1109/CCGRID.2008.107
Filename
4534301
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