nfs-ganesha-server-and-external-provisioner VS litmus

Now, for the purposes of this article, in case you don't have an NFS server available, we will use a simple NFS Server Provisioner, which we'll use only for example purposes. As mentioned before, using a managed solution from a cloud provider or a properly configured HA NFS server in your infrastructure is highly recommended. We'll install not the most up-to-date solution, but it should work for example purposes. We will follow the Quickstart found in the repo, mixed with this repo which does some small tweaks to make it work with K3d, which is summarized in the following commands run from the helm folder:

Some people just setup an NFS share. There's one that uses existing NFS and another that also provides NFS. This becomes a single point of failure though.

Conceptually to attach your storage to your pod, you have to go through 2 objects, the PVC that attaches to the PV, which itself must have a physical support, so the nfs mount on your nodes in hostpath, which is globally disgusting, it is better to inform the NFS server in your PV. Maybe I'm wrong but it seems clear to me. However, if you ask this kind of questions, you might be missing two or three things about K8. I advise you to read the documentation about PV, PVC, SC etc... Also NFS is not POSIX and by nature slow, which can cause inconsistencies in your data, but this is an extreme case. In a logic of automation you can use this: https://github.com/kubernetes-sigs/nfs-ganesha-server-and-external-provisioner Help yourself with this . https://www.linuxtechi.com/configure-nfs-persistent-volume-kubernetes/

I found something similar that seems to be a continuation of the nfs-server-provisioner- https://github.com/kubernetes-sigs/nfs-ganesha-server-and-external-provisioner

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.