SimulatedRides:Lyft如何利用负载测试来确保高峰期的可靠服务

Authors: Remco van Bree, Ben Radler

作者:Remco van Bree Remco van Bree,Ben Radler

Contributors: Alex Ilyenko, Ben Radler, Francisco Souza, Garrett Heel, Nathan Hsieh, Remco van Bree, Shu Zheng, Alex Hartwell, Brian Witt

撰稿人Alex Ilyenko,Ben Radler,Francisco Souza,Garrett Heel,Nathan Hsieh,Remco van Bree,Shu Zheng,Alex Hartwell,Brian Witt

“Load testing in production is great.”

"生产中的负载测试很好。"

We know what you’re thinking — testing in production is one of the cardinal sins of software development. However, at Lyft we have come to realize that load testing in production is a powerful tool to prepare systems for unexpected bursty traffic and peak events. We’ll explore why Lyft needed a custom performance testing framework that worked in production, how we built a cross-functional solution, and how we’ve continued to improve this testing platform since its launch in 2016.

我们知道你在想什么--在生产中测试是软件开发的大罪之一。然而,在Lyft,我们已经认识到,在生产中进行负载测试是一个强大的工具,可以让系统为意外的突发流量和峰值事件做好准备。我们将探讨为什么Lyft需要一个在生产中工作的定制性能测试框架,我们如何建立一个跨职能的解决方案,以及自2016年推出以来我们如何继续改进这个测试平台。

What exactly do we mean by “Load Testing”? In the context of this article we mean any tool that creates traffic to stress test systems and see how they perform at the limits of their capacity.

我们所说的 "负载测试 "到底是什么意思?在本文的上下文中,我们指的是创建流量以对系统进行压力测试的任何工具,看看它们在其能力极限下的表现。

Lyft must operate seamlessly even when demand spikes

即使在需求激增时,Lyft也必须无缝运营

It’s imperative for Lyft to be highly available during peak events like Halloween and New Year’s Eve. Riders depend on us for their travel needs, and drivers depend on us to be able to make a living, especially on the busiest days of the year. Historically peak events posed a huge challenge for Lyft, as we would experience unprecedented traffic which was often shaped in unusual patterns compared to a normal work week. Furthermore, due to the tremendous speed at which Lyft was growing, traffic was often interacting with new services that didn’t exist during the previous peak event.

在万圣节和除夕这样的高峰期,Lyft必须保持高度的可用性。乘客依靠我们来满足他们的出行需求,而司机则依靠我们来谋生,尤其是在一年中最繁忙的日子。历史上,高峰期对Lyft...

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