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Autor Tópico: Kubernetes Chaos Engineering With Chaos Toolkit And Istio  (Lida 191 vezes)

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Kubernetes Chaos Engineering With Chaos Toolkit And Istio
« em: 02 de Julho de 2020, 09:27 »

Kubernetes Chaos Engineering With Chaos Toolkit And Istio
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz
Language: English | Size: 7.46 GB | Duration: 7 hours

What you'll learn
The benefits of chaos engineering
How to be rewarded for destruction
How to test and find limits of a system
How to improve a system based on lessons learned from executing chaos experiments

Requirements
Kubernetes cluster
A few tools installed on a laptop (instructions are provided in the course)
Description
There are very few things as satisfying as destruction, especially true when we're frustrated.

How often did it happen that you have an issue that you cannot solve and that you just want to scream or destroy things? Did you ever have a problem in production that is negatively affecting a lot of users? Were you under a lot of pressure to solve it, but you could not "crack" it as fast as you should. It must have happened, at least once, that you wanted to take a hammer and destroy servers in your datacenter. If something like that never happened to you, then you were probably never in a position under a lot of pressure. In my case, there were countless times when I wanted to destroy things. But I didn't, for quite a few reasons. Destruction rarely solves problems, and it usually leads to negative consequences. I cannot just go and destroy a server and expect that I will not be punished. I cannot hope to be rewarded for such behavior.

What would you say if I tell you that we can be rewarded for destruction and that we can do a lot of good things by destroying stuff? If you don't believe me, you will soon. That's what chaos engineering is about. It is about destroying, obstructing, and delaying things in our servers and in our clusters. And we're doing all that, and many other things, for a very positive outcome.

Chaos engineering tries to find the limits of our system. It helps us deduce what are the consequences when bad things happen. We are trying to simulate the adverse effects in a controlled way. We are trying to do that as a way to improve our systems to make them more resilient and capable of recuperating and resisting harmful and unpredictable events.

That's our mission. We will try to find ways how we can improve our systems based on the knowledge that we will obtain through the chaos.

Who this course is for:
Anyone interested in making the applications and the cluster more resilient

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