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PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING
Edited by: P. Iványi, B.H.V. Topping and G. Várady
Cloud Agnostic Orchestration for Big Data Research Platforms
R. Lovas1,2, E. Nagy1,2 and J. Kovács1
1Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA
SZTAKI), Budapest, Hungary
R. Lovas, E. Nagy, J. Kovacs , "Cloud Agnostic Orchestration for Big Data Research Platforms", in P. Iványi, B.H.V. Topping, G. Várady, (Editors), "Proceedings of the Fifth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 15, 2017. doi:10.4203/ccp.111.15
Keywords: cloud computing, orchestration, Hadoop, Occopus, contextualization.
Nowadays a significant part of the cloud applications process large amount of data to provide the desired analytics, simulation and other results. Cloud infrastructures are becoming an appropriate and widely used solution to address the computation need of many scientific and commercial Big Data applications. In this paper, we present a solution of an automatic Hadoop infrastructure deployment on cloud with the Occopus cloud orchestrator. This solution provides an easy-to-use, portable, scalable, automatic deployment of Hadoop particularly for non-commercial clouds in order to avoid vendor locking issues, i.e. there is no dependency on any provider prepared virtual machine image, etc.
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