%0 Journal Article %1 eichelberger2015adaptive %A Eichelberger, Holger %A Qin, Cui %A Schmid, Klaus %A Niederée, Claudia %D 2015 %J Softwaretechnik-Trends %K adaptation myown qualimaster %N 3 %P 35-37 %T Adaptive Application Performance Management for Big Data Stream Processing %V 35 %X Big data applications with their high-volume and dynamically changing data streams impose new challenges to application performance management. Efficient and effective solutions must balance performance versus result precision and cope with dramatic changes in real-time load and needs without over-provisioning resources. Moreover, a developer should not be burdened too much with addressing performance management issues, so he can focus on the functional perspective of the system For addressing these challenges, we present a novel comprehensive approach, which combines software configuration, model-based development, application performance management and runtime adaptation.

@article{eichelberger2015adaptive, abstract = {Big data applications with their high-volume and dynamically changing data streams impose new challenges to application performance management. Efficient and effective solutions must balance performance versus result precision and cope with dramatic changes in real-time load and needs without over-provisioning resources. Moreover, a developer should not be burdened too much with addressing performance management issues, so he can focus on the functional perspective of the system For addressing these challenges, we present a novel comprehensive approach, which combines software configuration, model-based development, application performance management and runtime adaptation.}, added-at = {2016-03-08T09:47:48.000+0100}, author = {Eichelberger, Holger and Qin, Cui and Schmid, Klaus and Niederée, Claudia}, biburl = {https://www.bibsonomy.org/bibtex/2275b302cbcb3dd463ac687357f5d7ec4/eichelbe}, description = {Special part: Proceedings of the Symposium on Software Performance (SSP) 2015, 4.-6. November, 2015, Munich, Germany}, interhash = {3fc2f9bd2595e65f4f558910d078b8f2}, intrahash = {275b302cbcb3dd463ac687357f5d7ec4}, journal = {Softwaretechnik-Trends}, keywords = {adaptation myown qualimaster}, month = nov, number = 3, pages = {35-37}, timestamp = {2016-03-09T16:22:16.000+0100}, title = {Adaptive Application Performance Management for Big Data Stream Processing}, volume = 35, year = 2015 }