Abstract
Runtime profiling of Web-based applications and services is an effective method to aid in the provisioning of required resources, for monitoring service-level objectives, and for detecting implementation defects. Unfortunately, it is difficult to obtain accurate profile data on live client workloads due to the high overhead of instrumentation. This paper describes a cloud-based profiling service for managing the tradeoffs between: (i) profiling accuracy, (ii) performance overhead, and (iii) costs incurred for cloud computing platform usage. We validate our cloud-based profiling service by applying it to an open-source e-commerce Web application.
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Kaviani, N., Wohlstadter, E., Lea, R. (2011). Profiling-as-a-Service: Adaptive Scalable Resource Profiling for the Cloud in the Cloud. In: Kappel, G., Maamar, Z., Motahari-Nezhad, H.R. (eds) Service-Oriented Computing. ICSOC 2011. Lecture Notes in Computer Science, vol 7084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25535-9_11
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DOI: https://doi.org/10.1007/978-3-642-25535-9_11
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