SimianArmy VS litmus

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.

Advanced: set up Hadoop cluster and Latency Monkey https://github.com/Netflix/SimianArmy/wiki/The-Chaos-Monkey-Army to learn about distributed systems resilience

Maybe companies need some kind of "Chaos Monkey" system [0] in place for regular employees. Not in "terminating" random employee's contracts, but a culture were regular, maybe even some kind of random transferals onto other projects, or onto internal work regularly happens.

Everybody knows this and everybody should be prepared to a situation that tomorrow they are not working on the same problem they work on today. How would they structure work? How would they share knowledge? What can the organization to to ensure there always are fallbacks to everybody? At least fallbacks that if not perform at 100% but still on 80 - 90%.

Sadly in my org this would not work of the get go, as we often have personal access tokens to our clients' systems. This is sometimes even a contractual obligation as for specific clients we need to be vetted. But even in these cases we could be reassigned/reshuffled towards a slightly different proposition or at least be reassigned to an internal topic for a few days - just like we would not be able to work if we fell ill.

[0]: https://github.com/Netflix/SimianArmy/wiki/Chaos-Monkey

Maybe. Could also just be a chaos monkey expanding its cage.

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.