TY - GEN
T1 - Detecting performance change in enterprise application versions using resource profiles
AU - Brunnert, Andreas
AU - Krcmar, Helmut
N1 - Publisher Copyright:
© Copyright 2015 ICST.
PY - 2014
Y1 - 2014
N2 - Performance characteristics (i.e., response time, throughput, resource utilization) of enterprise applications change for each version due to feature additions, bug fixes or configuration changes. Therefore, performance needs to be continuously evaluated to detect performance changes (i.e., improvements or regressions). This work proposes a performance change detection process by creating and versioning resource profiles for each application version that is being built. Resource profiles are models that describe the resource demand per transaction for each component of an enterprise application and their control flow. Combined with workload and hardware environment models, resource profiles can be used to predict performance. Performance changes can be identified by comparing the performance metrics resulting from predictions of different resource profile versions (e.g., by observing an increase or decrease of response time). The source of changes in the resulting performance metrics can be identified by comparing the profiles of different application versions. We propose and evaluate an integration of these capabilities into a deployment pipeline of a continuous delivery process.
AB - Performance characteristics (i.e., response time, throughput, resource utilization) of enterprise applications change for each version due to feature additions, bug fixes or configuration changes. Therefore, performance needs to be continuously evaluated to detect performance changes (i.e., improvements or regressions). This work proposes a performance change detection process by creating and versioning resource profiles for each application version that is being built. Resource profiles are models that describe the resource demand per transaction for each component of an enterprise application and their control flow. Combined with workload and hardware environment models, resource profiles can be used to predict performance. Performance changes can be identified by comparing the performance metrics resulting from predictions of different resource profile versions (e.g., by observing an increase or decrease of response time). The source of changes in the resulting performance metrics can be identified by comparing the profiles of different application versions. We propose and evaluate an integration of these capabilities into a deployment pipeline of a continuous delivery process.
KW - Enterprise applications
KW - Java
KW - Palladio component model
KW - Performance change detection
KW - Performance evaluation
UR - http://www.scopus.com/inward/record.url?scp=84962919798&partnerID=8YFLogxK
U2 - 10.4108/icst.valuetools.2014.258184
DO - 10.4108/icst.valuetools.2014.258184
M3 - Conference contribution
AN - SCOPUS:84962919798
T3 - Proceedings of the 8th International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2014
SP - 165
EP - 172
BT - Proceedings of the 8th International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2014
PB - ICST
T2 - 8th International Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2014
Y2 - 9 December 2014 through 11 December 2014
ER -