Runtime monitoring tools have become fundamental to assess the correct operation of complex systems and applications. Unfortunately, the more precise is the monitoring (sampling rate, information granularity, and so on), the higher is the overhead introduced in the system itself. In this paper, we propose a new load shedding framework that enables runtime adaptation of monitoring agents under heavy system load, exploiting an heuristic Load Manager to control the agent status and a runtime support for domain-specific policies. We implemented the proposed methodology on Sysdig, with an average control error improvement of 3.51x (12.25x at most), w.r.t. previous solutions.

Performance-aware load shedding for monitoring events in container based environments

Rolando Brondolin;Matteo Ferroni;Marco Santambrogio
2019

Abstract

Runtime monitoring tools have become fundamental to assess the correct operation of complex systems and applications. Unfortunately, the more precise is the monitoring (sampling rate, information granularity, and so on), the higher is the overhead introduced in the system itself. In this paper, we propose a new load shedding framework that enables runtime adaptation of monitoring agents under heavy system load, exploiting an heuristic Load Manager to control the agent status and a runtime support for domain-specific policies. We implemented the proposed methodology on Sysdig, with an average control error improvement of 3.51x (12.25x at most), w.r.t. previous solutions.
Monitoring, Data-stream processing, Load Shedding
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1119788
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