Level-up your testing with Chaos Engineering. Learn how pushing your programs to failure can help you plan your improvements.

DevOps for Developers

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.

Kubernetes Chaos Engineering

As you already know, every section that has hands-on exercises is accompanied by a Gist that allows you to copy and paste stuff instead of typing. 

> All the commands from this section are available in the [05-network.sh](https://gist.github.com/455b0321879da7abf4d358a1334fd705) Gist.

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In the next lesson, you will be provided with instructions to create a Kubernetes cluster across different platforms.

The gist containing all the commands from this chapter is given in this lesson.

Before We Begin

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

Conclusion

Gist with Commands