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Akram RIAHI 

Alexandre KOLACZ

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18:00 - 19:00

Chaos Engineering on Multi-Cloud

Today, Chaos Engineering is becoming more and more prevalent, aiming for stronger resilience in information systems.
The questions about its implementation and integration are numerous and arouse the interest of all!
In this conference, we are going to show you how to make the chaos engineering on multi-cloud possible and easy using Litmus and two public cloud providers.

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Sébastien STOMACQ

17:00 - 18:00

Resiliency and Availability Design Patterns for the Cloud

We have traditionally built robust architectures by trying to avoid mistakes or failures in production, or by testing parts of the system in isolation. However, modern techniques take a very different approach: embracing failure instead of trying to avoid it. Resilient architectures enhance observability, leverage well-known patterns such as graceful degradation, timeouts and circuit breakers but also new patterns like cell-based architecture and shuffle sharding. In this session, will review the most useful patterns for building resilient software systems and especially show the audience how they can benefit from the patterns.

Jason YEE


18:00 - 19:00

Chaos Engineering by Numbers

We've all heard the stories: How Netflix improved reliability with Chaos Monkey, how Amazon saved millions of dollars by practicing failure injection, how big name companies with big budgets and top talent are benefiting from Chaos Engineering. But what about everyone else? Beyond the anecdotal success of a few companies, what does the data show us about the broader range of Chaos Engineering practitioners? In this session I'll share data from the first State of Chaos Engineering report—a survey of hundreds of organizations about how they're practicing Chaos Engineering and the results they're seeing. Then I'll dive into Gremlin's own customer data to share some specifics and case studies. Using this data, you'll be able to build your own successful Chaos Engineering practice.



18:00 - 19:00

Continuous Chaos Testing with Kubernetes and Okteto

Normally, chaos testing is done in isolation, one check right before shipping. By then, developers are working in something else, and fixing a bug becomes expensive and time consuming. In this talk, Ramiro will talk about his experience using  okteto, litmus chaos, and Kubernetes to give teams the ability to continuously Chaos test while writing a feature, not at the end.



19:00 - 20:00

Machine Learning to Predict Chaos

Scientists have been using machine learning for traffic alerts, social media, product recommendations, virtual personal assistants and self driving cars. The applications have the limit of our imagination, so the future evolution of chaotic systems could get a benefit of this practice. In this talk I am going to speak about how can we use machine learning, a computational technique behind artificial intelligence to improve the experiments that we run when we practice chaos engineering. “If you knew the storm was coming, you could just turn off the power and turn it back on later”.

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17:00 - 18:00

Evolution of Cloud Native Chaos Engineering

Cloud native systems are becoming commonplace in modern IT environments. The primary change we see in these environments is the speed at which the changes happen and are expected to happen. Making sure the services are reliable amidst these fast changes is a big challenge. The solution comes in applying chaos engineering into modern DevOps. This new science of reliability engineering can be called Cloud Native Chaos Engineering or CNCE. In this session, we discuss the typical challenges of scale and reliability in cloud native space and the fundamentals of cloud native chaos engineering. We will also touch upon the role of developers and the best practices in increasing the resilience of the applications that they build.

LitmusChaos is a CNCF project that provides an end to end platform to practice or implement cloud native chaos engineering. It implements all the design goals of CNCE. With a large community of users using Litmus, it is well tested and highly scalable. This talk covers the basic architecture and use cases of LitmusChaos.



18:00 - 19:00

Declarative Hypothesis & Observability in Chaos Experiments

In the world of automated chaos experiments, the hypothesis around steady-state is declarative in nature, much in the same way the chaos intent is. Another interesting factor here is the diversity in the way the steady-state is defined. With Litmus (2.0), we can track adherence to SLOs via various probes while also observing the real-time application/platform behavior using the integrated monitoring feature.

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Découvrez le programme de la Chaos week !

Discover The Chaos Week Program !