Jayanta Basak and Randy H. Katz

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2017-123

July 6, 2017

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-123.pdf

Modern datacenters assemble a very large number of disk drives under a single roof. Even if economic and technical factors where to make individual drives more reliable (which is not at all clear, given the commoditization of the technology), their sheer numbers combined with their ever increasing utilization in a well-balanced design makes achieving storage reliability a major challenge. In this paper, we assess the challenge of storage system reliability in the modern datacenter, and demonstrate how good disk failure prediction models can significantly improve the reliability of such systems.

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BibTeX citation:

@techreport{Basak:EECS-2017-123,
    Author= {Basak, Jayanta and Katz, Randy H.},
    Title= {Significance of Disk Failure Prediction in Datacenters},
    Year= {2017},
    Month= {Jul},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-123.html},
    Number= {UCB/EECS-2017-123},
    Abstract= {Modern datacenters assemble a very large number of disk drives under a single roof. Even if economic and technical factors where to make individual drives more reliable (which is not at all clear, given the commoditization of the technology), their sheer numbers combined with their ever increasing utilization in a well-balanced design makes achieving storage reliability a major challenge. In this paper, we assess the challenge of storage system reliability in the modern datacenter, and demonstrate how good disk failure prediction models can significantly improve the reliability of such systems.},
}

EndNote citation:

%0 Report
%A Basak, Jayanta 
%A Katz, Randy H. 
%T Significance of Disk Failure Prediction in Datacenters
%I EECS Department, University of California, Berkeley
%D 2017
%8 July 6
%@ UCB/EECS-2017-123
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-123.html
%F Basak:EECS-2017-123