Second Workshop on Real, Large Distributed SystemsPreliminary Abstract
Pp. 4348 of the Proceedings
Detecting Performance Anomalies in Global Applications
Terence Kelly, Hewlett-Packard Laboratories
Understanding real, large distributed systems can be as
difficult and important as building them. Complex modern
applications that span geographic and organizational
boundaries confound performance analysis in challenging
new ways. These systems clearly demand new analytic
methods, but we are wary of approaches that suffer
from the same problems as the systems themselves (e.g.,
complexity and opacity).
This paper shows how to obtain valuable insight
into the performance of globally-distributed applications
without abstruse techniques or detailed application
knowledge: Simple queueing-theoretic observations
together with standard optimization methods yield remarkably
accurate performance models. The models can
be used for performance anomaly detection, i.e., distinguishing
performance faults from mere overload. This
distinction can in turn suggest both performance debugging
tools and remedial measures.
Extensive empirical results from three production
systems serving real customerstwo of which are
globally distributed and span administrative domains
demonstrate that our method yields accurate performance
models of diverse applications. Our method furthermore
flagged as anomalous an episode of a real performance
bug in one of the three systems.
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