A Scalable Platform for Monitoring Data Intensive Applications

Latest advances in information technology and the widespread growth in different areas are producing large amounts of data. Consequently, in the past decade a large number of distributed platforms for storing and processing large datasets have been proposed. Whether in development or in production,...

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Bibliographic Details
Published inJournal of grid computing Vol. 17; no. 3; pp. 503 - 528
Main Authors Drăgan, Ioan, Iuhasz, Gabriel, Petcu, Dana
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.09.2019
Springer Nature B.V
Subjects
Big Data
Computer Science
Data management
Management of Computing and Information Systems
Monitoring
Platforms
Processor Architectures
User Interfaces and Human Computer Interaction
Cloud computing
Scalable monitoring
Big data
Monitoring big data applications
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Summary:Latest advances in information technology and the widespread growth in different areas are producing large amounts of data. Consequently, in the past decade a large number of distributed platforms for storing and processing large datasets have been proposed. Whether in development or in production, monitoring the applications running on these platforms is not an easy task, dedicated tools and platforms were proposed for this task yet none are specially designed for Big Data frameworks. In this paper we present a distributed, scalable, highly available platform able to collect, store, query and process monitoring data obtained from multiple Big Data frameworks. Alongside the architecture we experimentally show that the solution proposed is scalable and can handle a substantial quantity of monitoring data.
ISSN:1570-7873
1572-9184
DOI:10.1007/s10723-019-09483-1