Jung, Reiner, Heinrich, Robert and Schmieders, Eric (2013) Model-driven Instrumentation with Kieker and Palladio to forecast Dynamic Applications. [Paper] In: Symposium on Software Performance: Joint Kieker/Palladio Days 2013 (KPDAYS 2013). , November 27-29, 2013, Karlsruhe, Germany . Proceedings Symposium on Software Performance: Joint Kieker/Palladio Days 2013 (KPDAYS 2013). ; pp. 99-108 . CEUR Workshop Proceedings, 1083 .

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Abstract

Providing applications in stipulated qualities is a challenging task in today's
cloud environments. The dynamic nature of the cloud requires special runtime models
that reflect changes in the application structure and their deployment. These runtime
models are used to forecast the application performance in order to carry out mitiga-
tive actions proactively. Current runtime models do not evolve with the application
structure and quickly become outdated. Further, they do not support the derivation of
probing information that is required to gather the data for evolving the runtime model.
In this paper, we present the initial results of our research on a forecasting approach
that combines Kieker and Palladio in order to forecast the application performance
based on a dynamic runtime model. To be specific, we present two instrumentation
languages to specify Kieker monitoring probes based on structural information of the
application specified in Palladio component models. Moreover, we sketch a concept
to forward the monitored data to our PCM-based runtime model. This will empower
Palladio to carry out performance forecasts of applications deployed in dynamic envi-
ronments, which is to be tackled in future research steps.

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