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Using Models at Runtime to Support Adaptable Monitoring of Multi-clouds Applications

Abstract

The ability to run and manage multi-clouds applications (i.e., Applications that run on multiple clouds) allows exploiting the peculiarities of each cloud solution and hence improves non-functional aspects such as availability, cost, and scalability. Monitoring such multi-clouds applications is fundamental to track the health of the applications themselves and of their underlying infrastructures as well as to decide when and how to adapt their behaviour and deployment. It is clear that, not only the application but also the corresponding monitoring infrastructure should dynamically adapt in order to (i) be optimized to the application context (e.g., Adapting the frequency of monitoring to reduce network load), (ii) to enable the co-evolution of the monitoring platform together with the cloud application (e.g., If a service migrates from one provider to another, the monitoring activities have to be adapted accordingly). In this paper, we present a model-based platform for the dynamic provisioning, deployment, and monitoring of multi-clouds applications whose monitoring activities can be automatically and dynamically adapted to best fit with the actual deployment of the application.

Category

Academic chapter/article/Conference paper

Language

English

Author(s)

  • Lorenzo Cianciaruso
  • Francesco di Forenza
  • Elisabetta Di Nitto
  • Marco Miglierina
  • Nicolas Ferry
  • Arnor Solberg

Affiliation

  • Politecnico di Milano University
  • SINTEF Digital / Sustainable Communication Technologies

Year

2014

Publisher

IEEE (Institute of Electrical and Electronics Engineers)

Book

SYNASC 2014 - 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing

ISBN

978-1-4799-8447-3

Page(s)

401 - 408

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