Cloud agnostic Big Data platform focusing on scalability and cost-efficiency

Róbert Lovas, Enikő Nagy, József Kovács

Research output: Contribution to journalArticle

2 Citations (Scopus)


Nowadays a significant part of the cloud applications processes a large amount of data to provide the desired analytics, simulation and other results. Cloud computing is becoming a widely used IT model to address the needs of many scientific and commercial Big Data applications. In this paper, we present a Hadoop platform deployment method for various cloud infrastructures with the Occopus cloud orchestrator tool. Our automated solution provides an easy-to-use, portable and scalable way to deploy the popular Hadoop platform with the main goal to avoid vendor locking issues, i.e. there is no dependency on any cloud provider prepared and offered virtual machine image or “black-box” Platform-as-a-Service mechanism. The paper presents promising performance measurements results and cost analysis.

Original languageEnglish
Pages (from-to)167-177
Number of pages11
JournalAdvances in Engineering Software
Publication statusPublished - Nov 2018



  • Big Data
  • Cloud computing
  • Contextualisation
  • Cost analysis
  • Hadoop
  • Occopus
  • Orchestration
  • Scalability

ASJC Scopus subject areas

  • Software
  • Engineering(all)

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