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Detalle de: IaaSMon: Monitoring Architecture for Public Cloud Computing Data Centers

Title IaaSMon: Monitoring Architecture for Public Cloud Computing Data Centers
Abstract

Monitoring of cloud computing infrastructures is an imperative necessity for cloud providers and administrators to analyze, optimize and discover what is happening in their own infrastructures. Current monitoring solutions do not fit well for this purpose mainly due to the incredible set of new requirements imposed by the particular requirements associated to cloud infrastructures. This paper describes in detail the main reasons why current monitoring solutions do not work well. Also, it provides an innovative monitoring architecture that enables the monitoring of the physical and virtual machines available within a cloud infrastructure in a non-invasive and transparent way making it suitable not only for private cloud computing but also for public cloud computing infrastructures. This architecture has been validated by means of a prototype integrating an existing enterprise-class monitoring solution, Nagios, with the control and data planes of OpenStack, a well-known stack for cloud infrastructures. As a result, our new monitoring architecture is able to extend the exiting Nagios functionalities to fit in the monitoring of cloud infrastructures. The proposed architecture has been designed, implemented and released as open source to the scientific community. The proposal has also been empirically validated in a production-level cloud computing infrastructure running a test bed with up to 128 VMs where overhead and responsiveness has been carefully analyzed.

Apa Reference Gutierrez-Aguado, J., Alcaraz Calero, J. M., & Diaz Villanueva, W. (2016). IaaSMon: Monitoring Architecture for Public Cloud Computing Data Centers. Journal of Grid Computing, 14(2), 283–297. 10.1007/s10723-015-9357-4
Doi 10.1007/s10723-015-9357-4
Publication Date 4 Mar 2016
Publication Type Article
Researcher Wladimiro Diaz Villanueva
Ontology Cloud Computing
Research Groups Theory, Bioinformatics and Computation
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