  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.
