Automatic application performance improvements through VM parameter modification after runtime behavior analysis

Abstract

This thesis presents an approach to automatically adjust the parameters of a Java application run on the IBM J9 Virtual Machine in order to improve its performance. It works by analyzing the logfile the VM generates and searching for specific behavioral patterns. These patterns are matched against a list of known patterns for which rules exist that specify how to adapt the VM to the given application. Adapting the application is done by adding parameters and changing existing ones, for example to achieve a better heap usage. The process is fully automated and carried out by a toolkit developed for this thesis. The toolkit iteratively cycles through multiple possible parameter sets, benchmarks them and proposes the best alternative to the user. The user can, without any prior knowledge about the Java application or the VM improve the performance of the deployed application.