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

Sometimes, we’re unlucky, and we have partial failures with our network. At other times, we’re incredibly unfortunate, and the network fails entirely, or at least parts of the network related to one or a few of the applications are down. What happens in this case? Can we recuperate from that? Can we make our applications resilient even in those situations?


## Inspecting the definition of `network-abort-100.yaml` and comparing with `network-rollback.yaml`

We can run an experiment that will validate what happens in such a situation. It's going to be an easy one since we already have a very similar experiment.


Sometimes, we’re unlucky, and we have partial failures with our network. At other times, we’re incredibly unfortunate, and the network fails entirely, or at least parts of the network related to one or a few of the applications are down. What happens in this case? Can we recuperate from that? Can we make our applications resilient even in those situations?


# Inspecting the definition of `network-abort-100.yaml` and comparing with `network-rollback.yaml`

We can run an experiment that will validate what happens in such a situation. It's going to be an easy one since we already have a very similar experiment.


In this lesson, we will run a chaos experiment which will simulate what would happen if our application faces a complete network failure.

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?

Aborting All Requests

Inspecting the definition of `network-abort-100.yaml` and comparing with `network-rollback.yaml`