KeenTune: Automated Tuning Tool for Cloud Application Performance Testing and Optimization

PROCEEDINGS OF THE 32ND ACM SIGSOFT INTERNATIONAL SYMPOSIUM ON SOFTWARE TESTING AND ANALYSIS, ISSTA 2023(2023)

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摘要
The performance testing and optimization of cloud applications is challenging since manual tuning of software stacks is tedious while automated tuning tools are rarely used for cloud services. To address this, we introduce KeenTune, an auto-tuning tool designed to optimize application performance and facilitate performance testing. KeenTune is a lightweight and flexible tool that can be deployed with target applications with negligible impact on their performance. Specifically, KeenTune uses a surrogate model that can be implemented with machine learning models to filter out less relevant parameters for efficient tuning. Our empirical evaluation shows that KeenTune significantly enhances the throughput performance of Nginx web servers, resulting in improvements of up to 90.43% and 117.23% in certain cases. This highlights the benefits of using KeenTune for achieving efficient and effective performance testing of cloud applications. The video and source code for KeenTune are provided as supplementary materials.
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关键词
Performance testing,automated tuning,machine learning
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