TY - JOUR
T1 - Evolution of storage management
T2 - Transforming raw data into information
AU - Gopisetty, Sandeep
AU - Agarwala, Sandip
AU - Butler, Eric
AU - Jadav, Divyesh
AU - Jaquet, Stefan
AU - Korupolu, Madhukar
AU - Routray, Ramani
AU - Sarkar, Prasenjit
AU - Singh, Aameek
AU - Sivan-Zimet, Miriam
AU - Tan, Chung Hao
AU - Uttamchandani, Sandeep
AU - Merbach, David
AU - Padbidri, Sumant
AU - Dieberger, Andreas
AU - Haber, Eben M.
AU - Kandogan, Eser
AU - Kieliszewski, Cheryl A.
AU - Agrawal, Dakshi
AU - Devarakonda, Murthy
AU - Lee, Kang Won
AU - Magoutis, Kostas
AU - Verma, Dinesh C.
AU - Vogl, Norbert G.
PY - 2008
Y1 - 2008
N2 - Exponential growth in storage requirements and an inereasing number of heterogeneous devices and application policies are making enterprise storage management a nightmare for administrators. Baek-of-the-envelope calculations, rules of thumb, and manual correlation of individual device data are too error prone for the day-to-day administrative tasks of resource provisioning, problem determination, performance management, and impact analysis. Storage management tools have evolved over the past several years from standardizing the data reported by storage subsystems to providing intelligent planners. In this paper, we describe that evolution in the context of the IBM Total Storage® Productivity Center (TPC) - a suite of tools to assist administrators in the day-to-day tasks of monitoring, configuring, provisioning, managing change, analyzing configuration, managing performance, and determining problems. We describe our ongoing research to develop ways to simplify and automate these tasks by applying advanced analytics on the performance statistics and raw configuration and event data collected by TPC using the popular Storage Management Initiative-Specification (SMI-S). In addition, we provide details of SMART (storage management analytics and reasoning technology) as a library that provides a collection of data-aggregation functions and optimization algorithms.
AB - Exponential growth in storage requirements and an inereasing number of heterogeneous devices and application policies are making enterprise storage management a nightmare for administrators. Baek-of-the-envelope calculations, rules of thumb, and manual correlation of individual device data are too error prone for the day-to-day administrative tasks of resource provisioning, problem determination, performance management, and impact analysis. Storage management tools have evolved over the past several years from standardizing the data reported by storage subsystems to providing intelligent planners. In this paper, we describe that evolution in the context of the IBM Total Storage® Productivity Center (TPC) - a suite of tools to assist administrators in the day-to-day tasks of monitoring, configuring, provisioning, managing change, analyzing configuration, managing performance, and determining problems. We describe our ongoing research to develop ways to simplify and automate these tasks by applying advanced analytics on the performance statistics and raw configuration and event data collected by TPC using the popular Storage Management Initiative-Specification (SMI-S). In addition, we provide details of SMART (storage management analytics and reasoning technology) as a library that provides a collection of data-aggregation functions and optimization algorithms.
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U2 - 10.1147/rd.524.0341
DO - 10.1147/rd.524.0341
M3 - Article
AN - SCOPUS:55449118128
SN - 0018-8646
VL - 52
SP - 341
EP - 352
JO - IBM Journal of Research and Development
JF - IBM Journal of Research and Development
IS - 4-5
ER -