Minerva: An automated resource provisioning tool for large-scale storage systems

  • Authors:

  • Guillermo A. Alvarez;Elizabeth Borowsky;Susie Go;Theodore H. Romer;Ralph Becker-Szendy;Richard Golding;Arif Merchant;Mirjana Spasojevic;Alistair Veitch;John Wilkes

  • Affiliations:

  • Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA;Hewlett--Packard Laboratories, Palo Alto, CA

  • Venue:
  • ACM Transactions on Computer Systems (TOCS)
  • Year:
  • 2001

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Abstract

Enterprise-scale storage systems, which can contain hundreds of host computers and storage devices and up to tens of thousands of disks and logical volumes, are difficult to design. The volume of choices that need to be made is massive, and many choices have unforeseen interactions. Storage system design is tedious and complicated to do by hand, usually leading to solutions that are grossly over-provisioned, substantially under-performing or, in the worst case, both.To solve the configuration nightmare, we present minerva: a suite of tools for designing storage systems automatically. Minerva uses declarative specifications of application requirements and device capabilities; constraint-based formulations of the various sub-problems; and optimization techniques to explore the search space of possible solutions.This paper also explores and evaluates the design decisions that went into Minerva, using specialized micro- and macro-benchmarks. We show that Minerva can successfully handle a workload with substantial complexity (a decision-support database benchmark). Minerva created a 16-disk design in only a few minutes that achieved the same performance as a 30-disk system manually designed by human experts. Of equal importance, Minerva was able to predict the resulting system's performance before it was built.