Chaos engineering is the discipline of experimenting on a software system in production in order to build confidence in the system's capability to withstand turbulent and unexpected conditions.
- 1 Concept
- 2 History
- 3 Perturbation models
- 4 DevOps
- 5 See also
- 6 Notes and references
In software development, a given software system's ability to tolerate failures while still ensuring adequate quality of service—often generalized as resiliency—is typically specified as a requirement. However, development teams often fail to meet this requirement due to factors such as short deadlines or lack of knowledge of the field. Chaos engineering is a technique to meet the resilience requirement.
Chaos engineering can be used to achieve resilience against:
- Infrastructure failures
- Network failures
- Application failures
While overseeing Netflix's migration to the cloud in 2011, Greg Orzell had the idea to address the lack of adequate resilience testing by setting up a tool that would cause breakdowns in their production environment, the environment used by Netflix customers. The intent was to move from a development model that assumed no breakdowns to a model where breakdowns were considered to be inevitable, driving developers to consider built-in resilience to be an obligation rather than an option:
"At Netflix, our culture of freedom and responsibility led us not to force engineers to design their code in a specific way. Instead, we discovered that we could align our teams around the notion of infrastructure resilience by isolating the problems created by server neutralization and pushing them to the extreme. We have created Chaos Monkey, a program that randomly chooses a server and disables it during its usual hours of activity. Some will find that crazy, but we could not depend on the random occurrence of an event to test our behavior in the face of the very consequences of this event. Knowing that this would happen frequently has created a strong alignment among engineers to build redundancy and process automation to survive such incidents, without impacting the millions of Netflix users. Chaos Monkey is one of our most effective tools to improve the quality of our services."
By regularly "killing" random instances of a software service, it was possible to test a redundant architecture to verify that a server failure did not noticeably impact customers.
Chaos Monkey is a tool invented in 2011 by Netflix to test the resilience of its IT infrastructure. It works by intentionally disabling computers in Netflix's production network to test how remaining systems respond to the outage. Chaos Monkey is now part of a larger suite of tools called the Simian Army designed to simulate and test responses to various system failures and edge cases.
"Imagine a monkey entering a "data center", these "farms" of servers that host all the critical functions of our online activities. The monkey randomly rips cables, destroys devices and returns everything that passes by the hand [i.e. flings excrement]. The challenge for IT managers is to design the information system they are responsible for so that it can work despite these monkeys, which no one ever knows when they arrive and what they will destroy."
Introduces communication delays to simulate degradation or outages in a network.
Performs health checks, by monitoring performance metrics such as CPU load to detect unhealthy instances, for root-cause analysis and eventual fixing or retirement of the instance.
Identifies and disposes unused resources to avoid waste and clutter.
A tool that determines whether an instance is nonconforming by testing it against a set of rules. If any of the rules determines that the instance is not conforming, the monkey sends an email notification to the owner of the instance.
Derived from Conformity Monkey, a tool that searches for and disables instances that have known vulnerabilities or improper configurations.
A tool that detects problems with localization and internationalization (known by the abbreviations "l10n" and "i18n") for software serving customers across different geographic regions.
A "failure-as-a-service" platform built to make the Internet more reliable. It turns failure into resilience by offering engineers a fully hosted solution to safely experiment on complex systems, in order to identify weaknesses before they impact customers and cause revenue loss.
To prepare for the loss of a datacenter, Facebook regularly tests the resistance of its infrastructures to extreme events. Known as the Storm Project, the program simulates massive data center failures.
Days of Chaos
Inspired by AWS GameDays to test the resilience of its applications, teams from Voyages-sncf.com participated in a Day of Chaos. Every 30 minutes, operators simulated failures in pre-production. Teams earned points based on detections, diagnoses, and resolutions. This type of gamified event helps to introduce development teams to the concept of resilience.
ChaoSlingr is the first Open Source application of Chaos Engineering to Cyber Security. ChaoSlingr is focused primarily on performing security experimentation on AWS Infrastructure to proactively discover system security weaknesses in complex distributed system environments. Published on Github in September 2017.
The Chaos Toolkit was born from the desire to simplify access to the discipline of chaos engineering and demonstrate that the experimentation approach can be done at different levels: infrastructure, platform but also application. The Chaos Toolkit is an open-source tool, licensed under Apache 2, published in October 2017.
Mangle enables you to run chaos engineering experiments seamlessly against applications and infrastructure components to assess resiliency and fault tolerance. It is designed to introduce faults with very little pre-configuration and can support any infrastructure that you might have including K8S, Docker, vCenter or any Remote Machine with ssh enabled. With its powerful plugin model, you can define a custom fault of your choice based on a template and run it without building your code from scratch.
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The rapid pace of the DevOps methodology of software deployment makes it challenging to ensure a sufficient level of confidence in the face of frequent releases. A key element to address this is for monitoring and testing to be done throughout the development and release cycle. Integrating chaos engineering into the DevOps toolchain contributes to the goal of continuous testing.
- Fault tolerance
- Fault-tolerant computer system
- Data redundancy
- Error detection and correction
- Fall back and forward
- Resilience (network)
- Robustness (computer science)
Notes and references
- "Principles of Chaos Engineering". principlesofchaos.org. Retrieved 2017-10-21.
- "The Netflix Simian Army". Netflix Tech Blog. Medium. 2011-07-19. Retrieved 2017-10-21.
- US20120072571 A1, Orzell, Gregory S. & Yury Izrailevsky, "Validating the resiliency of networked applications"
- "Netflix Chaos Monkey Upgraded". Netflix Tech Blog. Medium. 2016-10-19. Retrieved 2017-10-21.
- "SimianArmy: Tools for your cloud operating in top form. Chaos Monkey is a resiliency tool that helps applications tolerate random instance failures". Netflix, Inc. 2017-10-20. Retrieved 2017-10-21.
- SimianArmy: Tools for keeping your cloud operating in top form. Chaos Monkey is a resiliency tool that helps applications tolerate random instance failures, Netflix, Inc., 2017-11-07, retrieved 2017-11-07
- SemiColonWeb (2015-12-08). "Infrastructure : quelles méthodes pour s'adapter aux nouvelles architectures Cloud ? - D2SI Blog". D2SI Blog (in French). Retrieved 2017-11-07.
- "Netflix libère Chaos Monkey dans la jungle Open Source - Le Monde Informatique". LeMondeInformatique (in French). Retrieved 2017-11-07.
- "Mais qui sont ces singes du chaos ?" [But who are these monkeys of chaos?]. 15marches (in French). 2017-07-25. Retrieved 2017-10-21.
- "The Netflix Simian Army", medium.com, retrieved 2017-12-12
- "Security Monkey monitors AWS, GCP, OpenStack, and GitHub orgs for assets and their changes over time.: Netflix/Security_monkey". 2019-06-22.
- "GitHub repo of Byte-Monkey". GitHub. 2019-06-20.
- "GitHub repo of Chaos Machine". GitHub. 2019-05-29.
- Zhang, Long; Morin, Brice; Haller, Philipp; Baudry, Benoit; Monperrus, Martin (2018). "A Chaos Engineering System for Live Analysis and Falsification of Exception-handling in the JVM". arXiv:1805.05246 [cs.SE].
- "Gremlin raises $18 million to expand 'failure-as-a-service' testing platform". VentureBeat. 2018-09-28. Retrieved 2018-10-24.
- Hof, Robert (2016-09-11), "Interview: How Facebook's Storm Heads Off Project Data Center Disasters", Forbes, retrieved 2017-10-21
- SemiColonWeb (2016-07-04). "GameDay AWS: test the resilience of your applications Cloud". D2SI Blog. Retrieved 2017-10-21.
- "DevOps: feedback from Voyages-sncf.com - Blog du Moderator", Moderator's Blog (in French), 2017-03-17, retrieved 2017-10-21
- "Days of Chaos: the development of the devops culture at Voyages-Sn ..." Slideshare. 2017-10-03. devops REX.
- Miles, Russ (2017-10-06). "Introducing and Extending the Chaos Toolkit". Russ Miles (the Geek on a Harley). Retrieved 2017-10-23.