Big data platforms as a service: Challenges and approach

James Horey, Edmon Begoli, Raghul Gunasekaran, Seung Hwan Lim, James Nutaro

Research output: Contribution to conferencePaperpeer-review

18 Scopus citations

Abstract

Infrastructure-as-a-Service has revolutionized the manner in which users commission computing infrastructure. Coupled with Big Data platforms (Hadoop, Cassandra), IaaS has democratized the ability to store and process massive datasets. For users that need to customize or create new Big Data stacks, however, readily available solutions do not yet exist. Users must first acquire the necessary cloud computing infrastructure, and manually install the prerequisite software. For complex distributed services this can be a daunting challenge. To address this issue, we argue that distributed services should be viewed as a single application consisting of virtual machines. Users should no longer be concerned about individual machines or their internal organization. To illustrate this concept, we introduce Cloud-Get, a distributed package manager that enables the simple installation of distributed services in a cloud computing environment. Cloud-Get enables users to instantiate and modify distributed services, including Big Data services, using simple commands. Cloud-Get also simplifies creating new distributed services via standardized package definitions.

Original languageEnglish
StatePublished - 2012
Event4th USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2012 - Boston, United States
Duration: Jun 12 2012Jun 13 2012

Conference

Conference4th USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2012
Country/TerritoryUnited States
CityBoston
Period06/12/1206/13/12

Funding

This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. This research has been made possible by a Lab Directed Research and Development grant at Oak Ridge National Laboratory.

FundersFunder number
United States Government
U.S. Department of Energy
Oak Ridge National Laboratory

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