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

For now, we’re going to focus on one-shot experiments that we’ll run manually, or through pipelines, or any other means that we might see fit.

## Inspecting the `once.yaml` file

Let's take a look at yet another Kubernetes YAML file.

For now, we’re going to focus on one-shot experiments that we’ll run manually, or through pipelines, or any other means that we might see fit.

# Inspecting the `once.yaml` file

Let's take a look at yet another Kubernetes YAML file.

In this lesson, we will learn about Kubernetes jobs and apply a job to our cluster for one-shot experiments.

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?

Running One-Shot Experiments

Inspecting the `once.yaml` file