Cloud native chaos paradigms

Cloud native chaos paradigms

Source: YouTube · Kubesimplify · published Oct 27, 2021 · 1:10:02

Cloud Security
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Description

This session explores cloud-native chaos engineering and Litmus, defining it as "vaccination" through fault injection to build system immunity and resilience 6:12.

Key Takeaways:
• Cloud-native microservices introduce complex third-party dependencies that constitute 80% of a cluster, necessitating targeted chaos testing 12:12.
• Litmus 2.0 evolved to handle complex real-world scenarios by introducing declarative workflows, resiliency scores, and improved visualization 40:31.
• Chaos testing remains critical in managed Kubernetes environments to validate application-level resilience, as providers can't guarantee custom workload behavior 32:05.

Cloud-native chaos engineering is essential for modern infrastructure, helping organizations build resilient systems and prepare for inevitable failures in complex distributed environments.

Sources:

  • 6:12 Definition of chaos engineering as "vaccination"
  • 12:12 Third-party dependencies in cloud-native environments
  • 40:31 Litmus 2.x evolution with workflows and resiliency scores
  • 32:05 Chaos testing in managed Kubernetes environments

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First 800 characters of the transcript

okay uh hello everyone and uh welcome to another live stream uh with another amazing set of folks uh my name is siam pathak and i'm a cncf ambassador working as director of technical evangelism at cevo and uh um we are live again with uh another awesome session and this time it's basically on uh cloud native chaos uh uh paradigms and it's it's it'll be interesting because it's a kind of a journey that we'll be talking about the chaos uh terminologies that have come up uh the chaos uh cloud native chaos stuff that has come up uh so how it has come up or what it is then how litmus has evolved from one dot x to two dot x what was the need to do that and uh then some of the demonstrations of the new set of features uh how uh we can also discuss like depending on the interactions uh definitely …