SimianArmy
ChaosEngineeringPublicStories
| SimianArmy | ChaosEngineeringPublicStories | |
|---|---|---|
| 6 | 1 | |
| 7,755 | 43 | |
| - | - | |
| 0.0 | 5.9 | |
| over 5 years ago | 14 days ago | |
| Java | HTML | |
| Apache License 2.0 | MIT License |
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SimianArmy
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Introduction to Chaos Engineering
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.
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What is the best OS for homelab (Mini PCs)
Advanced: set up Hadoop cluster and Latency Monkey https://github.com/Netflix/SimianArmy/wiki/The-Chaos-Monkey-Army to learn about distributed systems resilience
- AWS Config and orphaned resources
- Teacher pulls the shower head for the first time since she’s worked at the school
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On Being Indispensable at Work
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
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DTCC planning liquidity risk testing on 26th April 21 (4 months early)
Maybe. Could also just be a chaos monkey expanding its cage.
ChaosEngineeringPublicStories
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Introduction to Chaos Engineering
Public Chaos Engineering Stories / Implementations
What are some alternatives?
chaosmonkey - Chaos Monkey is a resiliency tool that helps applications tolerate random instance failures.