litmus VS k3s

Litmus, Gremlin, Chaos Mesh, and Chaos Monkey are all popular open-source tools used for chaos engineering. As we will be using AWS cloud infrastructure, we will also explore AWS Fault Injection Simulator (FIS). While they share the same goals of testing and improving the resilience of a system, there are some differences between them. Here are some comparisons:

This LFX quarter I got to get my hands on LitmusChaos, a CNCF incubating opensource project that dives deep on making cloud-native chaos-engineering accessible to multiple developer personas.

In 2010 Netflix developed a tool called "Chaos Monkey", whose goal was to randomly take down compute services (such as virtual machines or containers), part of the Netflix production environment, and test the impact on the overall Netflix service experience. In 2011 Netflix released a toolset called "The Simian Army", which added more capabilities to the Chaos Monkey, from reliability, security, and resiliency (i.e., Chaos Kong which simulates an entire AWS region going down). In 2012, Chaos Monkey became an open-source project (under Apache 2.0 license). In 2016, a company called Gremlin released the first "Failure-as-a-Service" platform. In 2017, the LitmusChaos project was announced, which provides chaos jobs in Kubernetes. In 2019, Alibaba Cloud announced ChaosBlade, an open-source Chaos Engineering tool. In 2020, Chaos Mesh 1.0 was announced as generally available, an open-source cloud-native chaos engineering platform. In 2021, AWS announced the general availability of AWS Fault Injection Simulator, a fully managed service to run controlled experiments.

Litmus Chaos is an open-source Chaos Engineering framework that provides an infrastructure experimental framework to validate the stability of controllers and microservices architectures. It can simulate various environments, such as container-level and application-level environments, natural disasters, faults, and upgrades, to understand how the system responds to these changes. The framework can also explore the behavior changes between controllers and applications, and how controllers respond to challenges in specific states. Litmus Chaos offers convenient observability integration capabilities and is highly extensible.

I am Pratik Singh, a final-year engineering student from Bangalore. I have been alumni of the pilot program of the Github Octernship. Back in 2021, it was called Github Externship. I worked for an organisation LitmusChaos

https://litmuschaos.io/ (open source)

LitmusChaos, is a platform that helps you to run Chaos Engineering in your cluster to identify weaknesses and improvement opportunities.

When the workshop was over, I headed back to the conference pavilion to attend the LitmusChaos Project Office Hours. These discussion events are great because they allow you to learn more about the project ask questions, meet the maintainers, and learn about new features and upcoming updates.

I don't have experience with the solutions you mentioned but I'll add one more to your list. It's Litmus which is open source... https://github.com/litmuschaos/litmus

Implement Chaos Mesh and Litmus chaos engineering framework to understand the behavior and stability of application in real-world use cases.

Opinionated meaning it picks, install, patches your CNI/Ingress/Load Balancer/DNS Server/Metrics Server/Monitoring Setup.

k3s is probably most well known as it ships with bunch of preinstall software: https://github.com/k3s-io/k3s so you can just start throwing yaml files at cluster and handling workloads. It's what I use for my homelab.

Paid things I've heard of include OpenStack and SideroLabs. Haven't used personally by SRE coworkers say good things about them.

For self-hosting I've found https://k3s.io to be really good from the SUSE people. Works on basically any Linux distro and makes self-hosting k8s not miserable.

Yes it’s going to depend on which k8s distribution you’re using. We have work in-progress for k3s to natively support nix-snapshotter: https://github.com/k3s-io/k3s/pull/9319

For other distributions, nix-snapshotter works with official containerd releases so it’s just a matter of toml configuration and a systemd unit for nix-snapshotter.

We run Kubernetes outside of NixOS, but yes the NixOS modules provided by the nix-snapshotter certainly make it simple.

K3S: is a lightweight distribution of Kubernetes that is designed for resource-constrained environments. It is an excellent option for running Kubernetes on a virtual machine or cloud server.

I recently purchased a used Lenovo M900 Think Centre (i7 with 32GB RAM) from eBay to expand my mini-homelab, which was just a single Synology DS218+ plugged into my ISP's router (yuck!). Since I've been spending a big chunk of time at work playing around with Kubernetes, I figured that I'd put my skills to the test and run a k3s node on the new server. While I was familiar with k3s before starting this project, I'd never actually run it before, opting for tools like kind (and minikube before that) to run small test clusters for my local development work.

Kubernetes - k3s distribution

I’ve created a local cluster with K3S and installing Windmill could not be simpler with just one chart to configure, which already has sane defaults to get started. For this demo we will also configure workers to passthrough environment variables to our scripts so that they have access to the Kubernetes API server for later.

You should be familiar with Kubernetes and have set up a Kubernetes cluster. I recommend k3s.