Pinpoint: Problem Determination in Large, Dynamic Internet Services
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
Performance debugging for distributed systems of black boxes
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Root-cause analysis of performance anomalies in web-based applications
Proceedings of the 2011 ACM Symposium on Applied Computing
Anomaly Detection Techniques for Web-Based Applications: An Experimental Study
NCA '12 Proceedings of the 2012 IEEE 11th International Symposium on Network Computing and Applications
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In this paper we study the performance impact induced by different application-level monitoring tools, targeted for the detection of performance anomalies in Web-based applications. Adaptive and selective algorithms, able to self-adapt the monitoring behavior, are proposed to minimize the performance impact induced by application-level profiling. From the experimental results, becomes clear the usefulness of adaptive and selective monitoring: depending on the system load, the response time latency induced has varied between 0.5 and 14 milliseconds per request; the throughput penalty was inferior to 1%; and the ability to detect and pinpoint the anomalies was not compromised. These outcomes are very favorable to the adoption of application-level profiling and runtime analysis, as a way to detect, pinpoint and repair from anomalies in production systems.