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20 - CHAOS ENGINEERING questions and answers with solutions 2025

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  • Module
  • Chaos
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  • Chaos

Distributed systems are challenging & pervasive - ANSWER - multiple participants - unreliable communication channels - may be allowed to crash - may need to tolerate malicious participants - must eventually agree an some set of decisions In general - failure is always an option - ordering ...

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  • January 7, 2025
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  • Exam (elaborations)
  • Questions & answers
  • Chaos
  • Chaos
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20 - CHAOS ENGINEERING questions
and answers with solutions 2025
Distributed systems are challenging & pervasive - ANSWER - multiple participants

- unreliable communication channels

- may be allowed to crash

- may need to tolerate malicious participants

- must eventually agree an some set of decisions



In general

- failure is always an option

- ordering is hard

- agreement is hard

- the software and what you think it does may differ



chaos engineering - ANSWER experimenting on a system to build confidence in the system's capability to
withstand turbulent conditions in production



- about finding the latent chaos in the system



*goal: manage chaos



- can think about chaos engineering as A/B testing for distributed systems where tests focus on
pathologies of system reliability



instead of looking for improvements, you look for degradation - ANSWER



The 8 fallacies of distributed computing - ANSWER - network is reliable

- latency is 0

- bandwidth is infinity

, - network is secure

- topology doesn't change

- one administrator

- transport cost is 0

- network is homogeneous



originally, experiments targeted these, but others are inspired by fault injection, race conditions, ...



How failure is handled varies depending on a system (5) - ANSWER - logging + continuing

- rerouting

- approximation + quality of service degradation

- error reporting

- terminal failure



(poorly tested + understood in distributed systems)



What impact might fallback strategies have on business performance? - ANSWER - companies don't
make money that day

- customers dislike service --> stop using it



Four common steps for a chaos experiment - ANSWER - measure + define the baseline behaviour of the
system

- hypothesize that the baseline should continue under stress

- simulate pathological behaviours on the deployed system

- try to disprove the hypothesis (show that there is a difference)



* the harder it is to show a difference, the more confidence you have in the robustness of your system



Just as in sequential hypothesis testing, you might want an "early out"

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