How is Performance Addressed in DevOps?

C. Bezemer, Simon Eismann, Vincenzo Ferme, Johannes Grohmann, R. Heinrich, Pooyan Jamshidi, Weiyi Shang, A. Hoorn, M. Villavicencio, J. Walter, Felix Willnecker
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引用次数: 53

Abstract

DevOps is a modern software engineering paradigm that is gaining widespread adoption in industry. The goal of DevOps is to bring software changes into production with a high frequency and fast feedback cycles. This conflicts with software quality assurance activities, particularly with respect to performance. For instance, performance evaluation activities --- such as load testing --- require a considerable amount of time to get statistically significant results. We conducted an industrial survey to get insights into how performance is addressed in industrial DevOps settings. In particular, we were interested in the frequency of executing performance evaluations, the tools being used, the granularity of the obtained performance data, and the use of model-based techniques. The survey responses, which come from a wide variety of participants from different industry sectors, indicate that the complexity of performance engineering approaches and tools is a barrier for wide-spread adoption of performance analysis in DevOps. The implication of our results is that performance analysis tools need to have a short learning curve, and should be easy to integrate into the DevOps pipeline in order to be adopted by practitioners.
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如何在DevOps中解决性能问题?
DevOps是一种现代软件工程范例,在业界得到了广泛的采用。DevOps的目标是以高频率和快速的反馈周期将软件更改引入生产。这与软件质量保证活动相冲突,特别是在性能方面。例如,性能评估活动——例如负载测试——需要相当多的时间来获得统计上有意义的结果。我们进行了一项行业调查,以深入了解如何在工业DevOps设置中解决性能问题。特别是,我们对执行性能评估的频率、使用的工具、获得的性能数据的粒度以及基于模型的技术的使用感兴趣。来自不同行业部门的各种各样的参与者的调查反馈表明,性能工程方法和工具的复杂性是DevOps中广泛采用性能分析的障碍。我们的结果的含义是,性能分析工具需要有一个短的学习曲线,并且应该很容易集成到DevOps管道中,以便被实践者采用。
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