Paper Info
Title
Smarter log analysis
Abstract
Modern computer systems generate an enormous number of logs. IBM Mining Effectively Large Output Data Yield (MELODY) is a unique and innovative solution for handling these logs and filtering out the anomalies and failures. MELODY can detect system errors early on and avoid subsequent crashes by identifying the root causes of such errors. By analyzing the logs leading up to a problem, MELODY can pinpoint when and where things went wrong and visually present them to the user, ensuring that corrections are accurately and effectively done. We present the MELODY solution and describe its architecture, algorithmic components, functions, and benefits. After being trained on a large portion of relevant data, MELODY provides alerts of abnormalities in newly arriving log files or in streams of logs. The solution is being used by IBM services groups that support IBM xSeries® servers on a regular basis. MELODY was recently tested with ten large IBM customers who use zSeries® machines and was found to be extremely useful for the information technology experts in those companies. They found that the solution's ability to reduce extensively large log data to manageable sets of highlighted messages saved them time and helped them make better use of the data.
Year
DOI
Venue
2011
10.1147/JRD.2011.2165675
IBM Journal of Research and Development
Keywords
Field
DocType
relevant data,smarter log analysis,innovative solution,ibm xseries,better use,ibm mining effectively,ibm services group,melody solution,large log data,large ibm customer,large portion
Data mining,Architecture,IBM,Computer science,Information technology,Server,Filter (signal processing)
Journal
Volume
Issue
ISSN
55
5
0018-8646
Citations 
PageRank 
References 
2
0.70
7
Authors
7
Name
Order
Citations
PageRank
E. Aharoni116510.78
Shai Fine21112107.56
Y. Goldschmidt320.70
O. Lavi420.70
O. Margalit5415.75
M. Rosen-Zvi681.78
L. Shpigelman720.70