Pinpoint: Problem Determination in Large, Dynamic Internet Services
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
Automatic Failure-Path Inference: A Generic Introspection Technique for Internet Applications
WIAPP '03 Proceedings of the The Third IEEE Workshop on Internet Applications
A Methodology for Detection and Estimation of Software Aging
ISSRE '98 Proceedings of the The Ninth International Symposium on Software Reliability Engineering
HOTOS '01 Proceedings of the Eighth Workshop on Hot Topics in Operating Systems
AspectJ in Action: Practical Aspect-Oriented Programming
AspectJ in Action: Practical Aspect-Oriented Programming
Autonomous recovery in componentized Internet applications
Cluster Computing
Magpie: online modelling and performance-aware systems
HOTOS'03 Proceedings of the 9th conference on Hot Topics in Operating Systems - Volume 9
Detection of Performance Anomalies in Web-Based Applications
NCA '10 Proceedings of the 2010 Ninth IEEE International Symposium on Network Computing and Applications
Memory performance prediction of web server applications based on grey system theory
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
Adaptive monitoring of web-based applications: a performance study
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Workload-aware anomaly detection for Web applications
Journal of Systems and Software
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The complexity behind current business-critical applications leads many times to performance problems difficult to anticipate and analyze. In our previous work we described a framework for detection of performance anomalies in web-based and component-based applications. It provides low overhead monitoring, correctly distinguishes performance anomalies from common workload variations and also presents initial information for system or application server changes related with an application performance anomaly. In this paper we present a framework extension devised to offer root-cause failure analysis for a given performance anomaly. The monitoring module enables application profiling and ANOVA analysis is used to verify if a performance anomaly is due to internal changes within the application (e.g., application updates) or to external changes (e.g., remote services changes, system/application server change). The paper includes some experimental results that show the effectiveness of our approach to pinpoint the root-cause for different types of performance anomalies and remarks its potential to avoid a considerable number of service failures.