Our backend infrastructure at Tinder relies on Redis-based caching to fulfill the requests generated by more than 2 billion uses of the Swipe® feature per day and hosts more than 30 billion matches to 190 countries globally. Most of our data operations are reads, which motivates the general data flow architecture of our backend microservices.
Source: medium.com
This year provedonce againthat IT-related failures “are universally unprejudiced: they happen in every country; to large companies and small; in commercial, nonprofit, and governmental organizations; and without regard to status or reputation.” Below is a review that just scratches the surface of the sundry failures, glitches, and other IT hiccups that made the news in 2018. This year saw a slight reduction in the number of flight cancellations and delays due to computer-related problems as compared with the past three years, especially in the United States.
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In 5 years, the number of endpoints consumed by Lyft’s mobile apps grew to over 500, and the size of our mobile engineering team increased by more than 15x. To scale with this growth, our infrastructure had to evolve dramatically to utilize new advances in modern networking in order to continue to provide benefits for our users. This post describes the journey through the evolution of Lyft’s mobile networking: how it’s changed, what we’ve learned, and why it’s important for us as a growing business.
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I started to compile a list of public failure/horror stories related to Kubernetes. It should make it easier for people tasked with operations to find outage reports to learn from. Since we started with Kubernetes at Zalando in 2016, we collected many internal postmortems.
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