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Unpacking The Python Toolkit For Chaos Engineering

Summary

Chaos engineering is the practice of injecting failures into your production systems in a controlled manner to identify weaknesses in your applications. In order to build, run, and report on chaos experiments Sylvain Hellegouarch created the Chaos Toolkit. In this episode he explains his motivation for creating the toolkit, how to use it for improving the resiliency of your systems, and his plans for the future. He also discusses best practices for building, running, and learning from your own experiments.

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  • Your host as usual is Tobias Macey and today I’m interviewing Sylvain Hellegouarch about Chaos Toolkit, a framework for building and automating chaos engineering experiments

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you start by explaining what Chaos Engineering is?
  • What is the Chaos Toolkit and what motivated you to create it?
    • How does it compare to the Gremlin platform?
  • What is the workflow for using Chos Toolkit to build and run an experiment?
    • What are the best practices for building a useful experiment?
    • Once you have an experiment created, how often should it be executed?
  • When running an experiment, what are some strategies for identifying points of failure, particularly if they are unexpected?
    • What kinds of reporting and statistics are captured during a test run?
  • Can you describe how Chaos Toolkit is implemented and how it has evolved since you began working on it?
  • What are some of the most challenging aspects of ensuring that the experiments run via the Chaos Toolkit are safe and have a reliable rollback available?
  • What have been some of the most interesting/useful/unexpected lessons that you have learned in the process of building and maintaining the Chaos Toolkit project and community?
  • What do you have planned for the future of the project?

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The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

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