UMBC ebiquity

A Mass Storage System Administrator Autonomic Assistant

Authors: Randy Schauer

Date: December 02, 2005

Abstract: The growing complexity of mass storage systems at major data centers is causing stress on system administrators to keep performance at optimal levels. As storage requirements grow, so does the number of routine tasks that the administrator must perform, as well as the time it takes for these to be executed. The solution being proposed to ease this burden is the Mass Storage System Administrator Autonomic Assistant (MSSAAA). The MSSAAA is a collection of agents that perform some of the more common tasks while the administrators handle higher-level issues. Using the principles of autonomic computing, the MSSAAA is governed by a centralized set of policies that the administrator will review on a regular basis and can adjust as necessary.

The goal is to develop an autonomic assistant to substantially reduce the amount of time it takes to address specific problems in the system. Using tools such as IBM’s Generic Log Adapter, Resource Model Builder, and Autonomic Management Engine, the MSSAAA has been able to (i) quickly determine when tape errors occur and correct them, (ii) monitor the network file system mounts for poor performance and report those, and (iii) correct network file system handle problems through continuous monitoring. The preliminary savings analyses show that the assistant saves the system administrator at least 185 hours per year, and over six thousand dollars in related costs. The results show how efficiently and effectively the MSSAAA handled its assigned tasks, and how it has eased the daily burden of storage system administrators.

Type: MastersThesis

Organization: Computer Science and Electrical Engineering

Publisher: University of Maryland, Baltimore County

Google Scholar: search

Number of downloads: 1939

 

Available for download as


size: 742259 bytes