The way we develop software is changing – and performance engineering is changing too to remain relevant. Integrating into agile development (shift-left / continuous performance testing) becomes a must when performance risks need to be mitigated. Automation and Continuous Integration (CI) become necessary as we get to multiple iterations and shrinking times to verify performance. However, continuous performance testing may be implemented in many different ways and on different levels depending on specific context – what we need to test, how high are performance risks / costs of failure, what technologies we use, etc. There are numerous challenges – and there are different ways to address them. We will discuss several approaches on specific examples – from light-weight solutions to the full-scale implementation at MongoDB.

In particular, the following challenges and ways to address them would be discussed:
-Optimizing cost / benefit ratio: what and when to test
-Integration with other CI / DevOps tools
-Change point detection
-Optimizing test and configuration coverage
-Organization challenges / the role of performance team
-Advanced analysis

Takeaways:

  • Continuous performance testing becomes a must when performance risks need to be mitigated
  • Continuous performance testing may be implemented in many different ways
  • There are numerous challenges to implement continuous performance testing – and there are different ways to address them

INTERVIEW:


About The Speaker:

Alexander Podelko is a Staff Performance Engineer at MongoDB. He has specialized in performance since 1997 – last several years focusing on continuous performance testing.