Introduction to k6 Load Chaos in LitmusChaos

In today's complex digital landscape, application resilience is crucial. Chaos engineering, using tools like LitmusChaos, intentionally introduces faults to uncover systemic issues missed by traditional tests. From now on, we can use k6, a load-testing tool with LitmusChaos. This post explores chaos engineering with LitmusChaos and demonstrates a k6 load chaos experiment.

What are chaos engineering and LitmusChaos
Introduction to k6
Injecting k6 load chaos with LitmusChaos (demo)

What are chaos engineering and LitmusChaos

What if our systems suddenly experience an outage? It's difficult to pinpoint the problem these days, especially since our systems are on Kubernetes, meaning they are microservices. While unit tests and integration tests can detect our application's weaknesses, they cannot detect weaknesses in our overall platform.

Importance of Resilience

The above diagram shows the impact of resilience. Using chaos engineering can be a great way to achieve more than 90% resilience. Chaos Engineering is the discipline of experimenting on a system in order to build confidence in the system’s capability to withstand turbulent conditions in production [1]. Chaos engineering involves intentionally injecting faults into a system to test its resilience. LitmusChaos makes this process easier to implement by simplifying Chaos Engineering.

LitmusChaos (CNCF incubating project) is a Cloud-Native Chaos Engineering Framework with cross-cloud support. You can use Litmus to inject controlled chaos and run chaos experiments in staging and production environments, allowing SREs to identify bugs and vulnerabilities. If you want to know more about Litmuschaos, Check out the documentation!

Introduction to k6

k6 is an open source load testing tool designed for developers to allow teams to create tests-as-code, integrate performance tests as part of the software development lifecycle, and help users test, analyze, and fix application performance issues. k6 supports various types of load testing (ex. spike, smoke, stress).

Now LitmusChaos supports k6 load testing as a chaos fault so that we can simulate load generation to the target application as a part of chaos testing on Kubernetes.

To know more about it, check out this documentation. You can also find our integration in the k6 documentation 🚀

Injecting k6 load chaos with LitmusChaos (demo)

Let us run the k6-loadgen chaos experiment. For simplicity, we will be injecting chaos into an OpenTelemetry Demo.

Prerequisites

Docker, minikube (If you use your k8s cluster, skip this)
Check out the otel-demo's Prerequisites
If you haven't installed LitmusChaos yet, check out this documentation.

Install opentelemetry demo

After installing Minikube and LitmusChaos, We now install the opentelemetry demo. All you have to do is enter the code below.

helm repo add open-telemetry https://open-telemetry.github.io/opentelemetry-helm-charts
helm install my-otel-demo open-telemetry/opentelemetry-demo

If you want to customized a deployment setting, check out this documentation.

We cannot directly access the otel-demo service, so we are using minikube's command to get an external URL

minikube service my-otel-demo-frontendproxy --url

the result is like one below

external url

We now access the frontend service

otel-demo-frontend

You can access Grafana using given URL

http://<<given_url>>/grafana

We will use Home > Dashboards > Demo Dashboard today.

grafana-dashboard

Setup Probes

You can easily create a probe following this documentation. Enter a value like below.

// URL: http://my-otel-demo-frontendproxy.default.svc.cluster.local:8080
// METHOD: GET
// CRITERIA: ==
// Response Code: 200

result

Writing a k6 script

You don't have to install a k6 engine! We just have to write a k6 script. We will use the below code and save it as script.js

import http from 'k6/http';
import { sleep } from 'k6';
export const options = {
  vus: 1000,
  duration: '30s',
};
export default function () {
  http.get('http://my-otel-demo-frontendproxy.default.svc.cluster.local:8080');
  sleep(1);
}

If you'd like to write a more professional script, you can check out this documentation.

and let's make a secret

kubectl create secret generic k6-script \
    --from-file=<<script-path>>/script.js -n <<chaos_infrastructure_namespace>>

Now that all the preliminary work is done, let's create a chaos experiment.

Let's make a chaos experiment

Click Chaos Experiments > + New Experiment to create a new chaos experiment.

int

After clicking the Blank Canvas and Add buttons, we can choose chaos fault in ChaosHub. We use k6-loadgen hub

In the Tune Fault tab, we enter the secret name and key we created before.

tune

Lastly, We add a probe that was created before. probe

Okay, all done! Let's execute a chaos experiment 🚀

A few minutes later, Our chaos experiment succeeded. Congratulations 🎉 result

We can see the load testing result on the Grafana dashboard. Go to Dashboards > Demo Dashboard > Requests Rate for frontend by span name > frontend-proxy. We can see the result below.

chaos-experiment-result

Summary

k6-loadgen fault simulates load generation on the target hosts for a specific chaos duration. The effects of chaos engineering can be maximized by designing experiments with k6-loadgen like other chaos faults in LitmusChaos.

If you are interested in LitmusChaos, Join the community! You can join the LitmusChaos community on GitHub and Slack.

Thank you for reading 🙏

Namkyu Park Maintainer of LitmusChaos LinkedIn | GitHub

Reference

[1] PRINCIPLES OF CHAOS ENGINEERING

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