TDS Archive

An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

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Chaos in the Calm: What is Chaos Engineering?

Time to be proactive rather than reactive

Niamh Kingsley
TDS Archive
Published in
6 min readAug 24, 2020

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Chaos Engineering isn’t just something that Dr. Robotnik does; it’s a serious and increasingly common part of the development life cycle.

In an ever more dynamic global environment, there is growing pressure to introduce continuous testing to the DevOps toolchain to ensure security and resilience. This is more so the case as the cloud becomes the dominant playground for an increasing number of firms, for where there is emerging tech, there is an emerging threat.

In practice, a system that has not been routinely and effectively tested is more prone to downtime, which can lead to disappointment or even lost customers. In ITIC’s 11th annual Hourly Cost of Downtime Survey, it was found that 87% of organisations are now required to be available 99.99% of the time (which — they note — is up 81% in the past 2.5 years). Incredibly, 40% of enterprise organisations indicated that a single hour of downtime can cost them from $1 million to over $5 million.

So how do you preempt and prepare for the kind of disaster that could cost your company millions? Well, one increasingly popular approach is to productively break your own things before someone else does.

Expose, Improve

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TDS Archive
TDS Archive

Published in TDS Archive

An archive of data science, data analytics, data engineering, machine learning, and artificial intelligence writing from the former Towards Data Science Medium publication.

Niamh Kingsley
Niamh Kingsley

Written by Niamh Kingsley

Passionate about technology, AI, & neuroscience. You can generally find me @nifereum, @niamhkingsley or connect via https://www.linkedin.com/in/niamhkingsley

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