A flexible and scalable approach to navigating measurement data in performance management applications

R.F. Berry, J.L. Hellerstein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Managing the performance of large distributed systems requires flexible and scalable approaches to automating measurement navigation. Unfortunately, existing approaches achieve scalability by severely limiting flexibility. This paper considers an approach that infers navigations from a dimensional representation of the measurement name space. Doing so provides flexible navigation and results in dramatic improvements in scalability, as quantified by analytic models that are developed in this paper. Indeed, our models indicate that it is inherently unscalable to automate navigation by requiring the specification of relationships between measurement names, as is done in existing approaches. In contrast, the dimensional approach is optimal for the class of data sources considered in our models. Exploiting the dimensional approach requires addressing issues such as: irregularities in the measurement name space; mappings between the name space used for measurement collection and storage and the dimensional structured name space; and the efficient storage of measurement names. Solutions are proposed for all of these issues
Original languageEnglish
Title of host publicationProceedings of IEEE Second Internaltional Workshop
PublisherIEEE
Pages92-103
Number of pages12
ISBN (Print)0-8186-7442-3
DOIs
Publication statusPublished - 19 Jun 1996
Event1996 IEEE Second International Workshop on Systems Management - Toronto, Canada
Duration: 19 Jun 199621 Jun 1996

Conference

Conference1996 IEEE Second International Workshop on Systems Management
CountryCanada
CityToronto
Period19/06/9621/06/96

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    Berry, R. F., & Hellerstein, J. L. (1996). A flexible and scalable approach to navigating measurement data in performance management applications. In Proceedings of IEEE Second Internaltional Workshop (pp. 92-103). IEEE. https://doi.org/10.1109/IWSM.1996.534151