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

## The issue we just created

There are a couple of issues that we need to fix to get out of the bad situation we’re in right now. However, before we start solving those, an even bigger problem was created a few moments ago. I will demonstrate the issue by retrieving the nodes.


# The issue we just created

There are a couple of issues that we need to fix to get out of the bad situation we’re in right now. However, before we start solving those, an even bigger problem was created a few moments ago. I will demonstrate the issue by retrieving the nodes.


In this lesson, we will carry out another chaos experiment, which will also include a rollback block so that we can uncordon the node after the experiment.

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?

Uncordoning Worker Nodes

The issue we just created