Error log processing for accurate failure prediction
Felix Salfner, Steffen Tschirpke · 2008
Error logs are a fruitful source of information both for di-agnosis as well as for proactive fault handling – however elaborate data preparation is necessary to filter out valu-able pieces of information. In addition to the usage of well-known techniques, we propose three algorithms: (a) assignment of error IDs to error messages based on Lev-enshtein’s edit distance, (b) a clustering approach to group similar error sequences, and (c) a statistical noise filtering algorithm. By experiments using data of a commercial telecommunication system we show that data preparation is an important step to achieve accurate error-based online failure prediction. 1