Delve into Kubernetes Chaos Engineering to discover system limits, simulate adverse effects, and improve resiliency. Learn about fault tolerance, high availability, and running experiments in a Kubernetes cluster.

Let’s face it, bad things happen in software engineering, often when you least expect it. Servers go down, there are spikes in traffic, you receive networking errors. Luckily, you can avoid these problems. Enter chaos engineering.
Chaos engineering is where you try to find the limits of a system and simulate adverse effects that might happen. These simulations then help you to determine the best way to improve your system and build up its resiliency.
This course is divided into various sections to get you used to the different types of experiments you can run in chaos engineering. You will start by learning how to destroy application instances in order to show you the importance of scaling, fault tolerance, and high availability.
You will then dive deep into other types of experiments such as destroying a network, draining and deleting nodes, and testing availability. Towards the end of the course, you will learn how to run experiments in a Kubernetes cluster.

The DevOps Toolkit: Kubernetes Chaos Engineering

# Doing it yourself

Here comes your first task. Get a Kubernetes cluster. If you already have one, whichever it is, you can use it for the exercises. If you do not have a Kubernetes cluster, and you know how to create one, just go and create it. However, if you do not have a Kubernetes cluster and you want me to help you create one, then the Gists with the commands for creating a cluster are available below.


You can choose between **Minikube**, **Docker Desktop**, **AKS**, **EKS**, and **GKE**. In other words, the most commonly used Kubernetes flavors are available as Gists. If you don’t like any of them, create your own cluster. As long as you have one, you should be fine.

If you follow my commands to create a cluster, you will see that they’re all single zone clusters, at least those in Google, Amazon, and Azure. They’re running in a single zone, and they have a single node outside the control plane. It’s a very simple cluster, and it’s very small. It’s just big enough for what we need. We’ll see later whether these are well-defined clusters. Chaos experiments will help us with that.

All in all, use my instructions to create a cluster, create a cluster any other way you like, or use an existing cluster. It’s up to you.

# Gists for different Kubernetes flavors

Gists with the commands to create and destroy a Kubernetes cluster are as follows.

* [Docker Desktop](https://gist.github.com/f753c0093a0893a1459da663949df618)
* [Minikube](https://gist.github.com/ddc923c137cd48e18a04d98b5913f64b)
* [GKE](https://gist.github.com/2351032b5031ba3420d2fb9a1c2abd7e)
* [EKS](https://gist.github.com/be32717b225891b69da2605a3123bb33)
* [AKS](https://gist.github.com/c7c9a8603c560eaf88d28db16b14768c)

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There's one more task left for us to do before we start destroying things. We'll need to deploy a demo application. Let’s do that in the next lesson.



This lesson contains instructions regarding creating a Kubernetes cluster.

Introduction To Kubernetes Chaos Engineering

Defining Requirements

Destroying Application Instances

Experimenting with Application Availability

Obstructing and Destroying Network

Draining and Deleting Nodes

Creating Chaos Experiment Reports

Running Chaos Experiments Inside a Kubernetes Cluster

Executing Random Chaos

What’s Next?

Creating a Cluster

Doing it yourself