Khun Ban, Robert Scott, Kingsum Chow, Huijun Yan, Intel
We all are witnessing the amazing growth in today’s computing industry. Servers are many times faster and smarter than those of just a few years ago. The need to ensure the applications run well with a large number of users on the Internet has continued and is getting more attention as the move to cloud computing is gaining momentum. To address the question whether the software system can perform under load, we look to performance and load testing. Performance testing is executed to determine how fast a system performs. It is typically done using a particular workload. It can also serve to verify other quality attributes, such as scalability, reliability and resource usage. Load testing is primarily concerned with the ability to operate under a high load such as large quantities of data or a large number of users. We use performance and load testing to evaluate the scalability of a software system.
In this paper, we characterize the challenges in conducting the application performance tests and describe a systematic approach to overcome them. We present a step-by-step data driven and systematic approach to identify performance scalability issues in testing and ensuring software quality through software performance and scalability testing. The approach includes how to analyze multiple pieces of data from multiple sources, and how to determine the configuration changes that are needed to successfully complete the stress tests for scalability. The reader will find it easy to apply our approach for immediate improvement in performance and scalability testing.
Khun Ban, Robert Scott, Kingsum Chow, Huijun Yan, 2011 Technical Paper, Abstract, Paper, Slides
