Hardware performance counter-based problem diagnosis for e-commerce systems
Keith A. Barea b, Soila P. Kavulyaa b, Priya Narasimhana b
- aElectrical & Computer Engineering Department, Carnegie Mellon University, Pittsburgh, PA, USA
- bElectrical & Computer Engineering Department, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, Pennsylvania, 15213-3890, USA
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Abstract
Black-box instrumentation can support problem diagnosis in distributed systems without the need to modify the application code or to understand its semantics. We explore a novel, low-overhead black-box instrumentation source - CPU/hardware performance counters - for problem diagnosis. Based on our hypothesis that performance problems manifest as observable, anomalous changes in CPU performance counter-values collected across the nodes of a distributed system, we develop a diagnosis approach that is able to detect and localize performance problems injected into RUBiS, a three-tier e-commerce system.

