Application-level performance monitoring of cloud services based on the complex event processing paradigm

Authors:
Philipp Leitner;Christian Inzinger;Waldemar Hummer;Benjamin Satzger;Schahram Dustdar
Affiliations:
Distributed Systems Group, Vienna University of Technology, Argentinierstrasse 8/184-1, 1040, Austria;Distributed Systems Group, Vienna University of Technology, Argentinierstrasse 8/184-1, 1040, Austria;Distributed Systems Group, Vienna University of Technology, Argentinierstrasse 8/184-1, 1040, Austria;Distributed Systems Group, Vienna University of Technology, Argentinierstrasse 8/184-1, 1040, Austria;Distributed Systems Group, Vienna University of Technology, Argentinierstrasse 8/184-1, 1040, Austria
Venue:
SOCA '12 Proceedings of the 2012 5th IEEE International Conference on Service-Oriented Computing and Applications (SOCA)
Year:
2012

Citing 0
Cited 2

Monitoring and Autoscaling IaaS Clouds: A Case for Complex Event Processing on Data Streams

UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
A Framework and Middleware for Application-Level Cloud Bursting on Top of Infrastructure-as-a-Service Clouds

UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Monitoring of applications deployed to Infrastructure-as-a-Service clouds is still an open problem. In this paper, we discuss an approach based on the complex event processing paradigm, which allows application developers to specify and monitor high-level application performance metrics. We use the case of a Web 2.0 sentiment analysis application to illustrate the limitations we currently experience with regard to cloud monitoring, and show how our approach allows for more expressive definitions of monitored metrics. Furthermore, we indicate how the higher-level metrics produced by our approach can be used to increase application elasticity in an existing cloud middleware.