litmus VS kubernetes

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.

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.

"You are holding it wrong", huh?

From the homepage https://kubernetes.io/:

"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."

Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.

Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.

If you do kubectl explain deployment than (surprise!) you'll get a description for extensions/v1beta1. Because kubectl explain works the same way, just like kubectl get:

Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).

In this project, you will understand and get hands on experience around the entire concept around CI/CD from applications perspective. To fully gain real expertise around this idea, it is best to see it in action across different programming languages and from the platform perspective too. From the application perspective, we will be focusing on PHP here; there are more projects ahead that are based on Java, Node.js, .Net and Python. By the time you start working on Terraform, Docker and Kubernetes projects, you will get to see the platform perspective of CI/CD in action.

The single most important development in hosting since the invention of EC2 is defined by its own 3-letter acronym: k8s. Kubernetes has won the “container orchestrator” space, becoming the default way that teams across industries are managing their compute nodes and scheduling their workloads, from data pipelines to web services.