Assessing the overhead and scalability of system monitors for large data centers

  • Authors:
  • Mauro Andreolini;Michele Colajanni;Riccardo Lancellotti

  • Affiliations:
  • Department of Information Engineering, Modena, Italy;Department of Information Engineering, Modena, Italy;Department of Information Engineering, Modena, Italy

  • Venue:
  • Proceedings of the First International Workshop on Cloud Computing Platforms
  • Year:
  • 2011

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Abstract

Current data centers are shifting towards cloud-based architectures as a means to obtain a scalable, cost-effective, robust service platform. In spite of this, the underlying management infrastructure has grown in terms of hardware resources and software complexity, making automated resource monitoring a necessity. There are several infrastructure monitoring tools designed to scale to a very high number of physical nodes. However, these tools either collect performance measure at a low frequency (missing the chance to capture the dynamics of a short-term management task) or are simply not equipped with instrumentation specific to cloud computing and virtualization. In this scenario, monitoring the correctness and efficiency of live migrations can become a nightmare. This situation will only worsen in the future, with the increased service demand due to spreading of the user base. In this paper, we assess the scalability of a prototype monitoring subsystem for different user scenarios. We also identify all the major bottlenecks and give insight on how to remove them.