Detecting application-level failures in component-based internet services.
Most Internet services (e-commerce, search engines, etc.) suffer faults. Quickly detecting these faults can be the largest bottleneck in improving availability of the system. We present Pinpoint, a methodology for automating fault detection in Internet services by: 1) observing low-level internal structural behaviors of the service; 2) modeling the majority behavior of the system as correct; and 3) detecting anomalies in these behaviors as possible symptoms of failures. Without requiring any a priori application-specific information, Pinpoint correctly detected 89%-96% of major failures in our experiments, as compared with 20%-70% detected by current application-generic techniques.
Kiciman
Emre
E
Department of Computer Science, Stanford University, Stanford, CA 94305, USA. emrek@cs.stanford.edu
Fox
Armando
A
D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003198:Computer Simulation; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D013685:Telecommunications