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.
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Notes
- 1.
The development and investigation described in this paper were done as part of the TIMACS project and were sponsored by NEC and the German Bundesministerium für Bildung und Forschung.
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Focht, E., Jeutter, A. (2013). AggMon: Scalable Hierarchical Cluster Monitoring. In: Resch, M., Wang, X., Bez, W., Focht, E., Kobayashi, H. (eds) Sustained Simulation Performance 2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32454-3_5
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DOI: https://doi.org/10.1007/978-3-642-32454-3_5
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