Examples Of Chaos Engineering

This lesson discusses some of the use-cases for chaos engineering.

Use-cases for chaos engineering

Right now, you might be saying, “okay, I understand that chaos engineering is about learning from the destruction, but what does it really mean?” Let me give you a couple of use-cases for chaos engineering. Although I cannot go through all the permutations of everything we can do, a couple of examples might be in order.

We can validate what happens if you have improper fallback settings when a service is unavailable.

  • What happens when a service is not accessible, one way or another?
  • What happens if an app is retrying indefinitely to reach a service without having properly tuned timeouts?
  • What is the result of outages when an application or a downstream dependency receives too much traffic or when it is not available?
  • Will we experience cascading errors when a single point of failure crashes an app?
  • What happens when our application goes down?
  • What happens when there is something wrong with networking?
  • What happens when a node is not available?
  • Those are just a few of the questions we will explore through practical exercises.

Limitations of the practical examples

There are quite a few reasons we will be unable to explore everything that you can or you should do using chaos engineering. First of all, chaos experiments that we can run depend on a system; not all the experiments apply to everybody. Also, going through all the possible permutations would require too much time. We can even say that the number of experiments and their permutations is infinite. I could write thousands of pages, and I’d still not be able to go through all of them. Instead, I will try to teach you how to think, use some tools, and figure out what makes sense for your organization, your team, and your system.

Now that we mentioned a few examples (more are to come), let’s talk about the principles of chaos engineering.


In the next lesson, we will discuss the process of chaos experiments.

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