Prediction of Hard Drive Failures Via Rule Discovery From AutoSupport Data

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The ability to accurately predict an impending hard disk failure is important for reliable storage system design. The facility provided by most hard drive manufacturers, called S.M.A.R.T. (self-monitoring, analysis and reporting technology), has been shown by current research to have poor predictive value. The problem of finding alternatives to S.M.A.R.T. for predicting disk failure is an area of active research. This paper presents a rule discovery methodology, and show that it is possible to construct decision support systems that can detect such failures using information recorded in the AutoSupport database. The paper demonstrates the effectiveness of the system by evaluating it on disks that were returned to NetApp from the field.