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AggMon: Scalable Hierarchical Cluster Monitoring

In: Sustained Simulation Performance 2012

Author

Listed:
  • Erich Focht

    (NEC HPC Europe)

  • Andreas Jeutter

    (NEC HPC Europe)

Abstract

Monitoring and supervising a huge number of compute nodes within a typical HPC cluster is an expensive task. Expensive in the sense of occupying bandwidth, and CPU power that would be better spend for application needs. In this paper, we describe a monitoring framework that is used to supervise thousands of compute nodes in a HPC cluster computer in an efficient way. Within this framework the compute nodes are organized in groups. Groups contain other groups and form a tree-like hierarchical graph. Communication paths are strictly along the edges of the graph. To decouple the components in the network a publish/subscribe messaging system based on AMQP has been chosen. Monitoring data is stored within a distributed time-series database that is located on dedicated nodes in the tree. For database queries and other administrative tasks a synchronous RPC channel, that is completely independent of the hierarchy has been implemented. A browser-based front-end to present the data to the user is currently in development.

Suggested Citation

  • Erich Focht & Andreas Jeutter, 2013. "AggMon: Scalable Hierarchical Cluster Monitoring," Springer Books, in: Michael M. Resch & Xin Wang & Wolfgang Bez & Erich Focht & Hiroaki Kobayashi (ed.), Sustained Simulation Performance 2012, edition 127, pages 51-64, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-32454-3_5
    DOI: 10.1007/978-3-642-32454-3_5
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