知鸦日报2023-01-28

本文从最原始的需求出发，结合需求变化，推导出用户系统的演进。

Contract testing has grown in popularity in recent years with the widespread adoption of microservice architectures. In this article, we will share our experiences with contract testing at eBay.

Pinterest has enforced the use of managed and compliant devices in our Okta authentication flow, using a passwordless implementation, so that access to our tools always requires a healthy Pinterest device.

Following the phishing-based attacks against our peers in the tech industry, Pinterest decided to take a two pronged approach to defend against similar attacks. We decided to:

1. Require a managed and healthy Pinterest device be used to access all Pinterest resources, even when in the possession of valid credentials
2. Require FIDO2 credentials for user authentication

In this post, we’ll be focusing on how we required the use of Pinterest managed devices in our Okta authentication flow.

Before jumping into the details of the migration story, we’d like to take a step back and try to explain the motivation and rationale for this migration.

Over time, the data platform has morphed into various forms as the needs of the company have grown. What was a modest data platform in the early days has grown into an exabyte-scale platform. Some systems serving a smaller scale began showing signs of being insufficient for the increased demands that were placed on them. Most notably, we’ve run into some concrete reliability and efficiency issues related to data (de)serialization, which has made us rethink the way we log data and revisit the ideas from first principles to address these pressing issues.

Logger is at the heart of the data platform. The system is used to log analytical and operational data to Scuba, Hive, and stream processing pipelines via Scribe. Every product and data platform team interacts with logging. The data format for logging was either Hive Text Delimited or JSON, for legacy reasons. The limitations of these formats are described in our previous article on Tulip.

There are several online references on how to run Apache Hadoop® (referred to as “Hadoop” in this article) in Docker for demo and test purposes. In a previous blog post, we described how we containerized Uber’s production Hadoop infrastructure spanning 21,000+ hosts.

HDFS NameNode is the most performance-sensitive component within large multi-tenant Hadoop clusters. We had deferred NameNode containerization to the end of our containerization journey to leverage learnings from containerizing other Hadoop components. In this blog post, we’ll share our experience on how we containerized HDFS NameNodes and architected a zero-downtime migration for 32 clusters.

As part of our device authentication and compliance initiative, Pinterest has implemented employee-facing mutual TLS with a custom identity provider in a way that results in a positive user experience.

You may have heard of, or experienced first hand, some unpleasant behavior while attempting to authenticate with a certificate within a browser or application. Even the Wikipedia page for mutual TLS mentions that mTLS is a “..less user-friendly experience, [and] it’s rarely used in end-user applications…”.

At Pinterest, we needed to use Mutual TLS as part of our employee SSO authentication, using a custom identity provider. This means that we needed to support authentication across all major platforms, as well as from within browsers and native applications.

In this blog post, we’ll talk about some of the changes that we’ve made to ensure that user-facing mTLS is a seamless experience for our employees.

Let’s unpack our approach to BFCM Scale Testing to explore some of what it takes to ensure that our ecommerce platform can handle the busiest weekend of the year.

Lyft hosts a dynamic marketplace connecting millions of people to a robust transportation network. In order to offer high value and quality service for both riders and drivers we need to make complex optimization decisions in near-real time. The environment can change quickly with traffic, events and weather, making these decisions even more challenging.

We have employed multi-arm bandits (MAB) algorithms, a common machine learning method for decision making using long-term rewards, to improve our real-time decision making capability. MABs allow us to not only iterate at a faster cadence and lower cost, but also allow for dynamic user experiences and responsive marketplace systems. We will walk through some of our most impactful MAB applications in UI optimization and personalized messaging, concluding with applications in our marketplace algorithms.

In Marken (Scalable Annotation Service at Netflix), an annotation is a piece of metadata which can be attached to an object from any domain.

A deep dive exploration of React server components under the hood.

How Engineering Managers create impact and shape organisational culture.

这个春节档，《满江红》红了。

犹记去年春节档，观众被《狙击手》拉回抗美援朝的战场上，观看了一场紧张刺激的敌我对决。一年过去，随着张艺谋的镜头一转，观众的视线又来到南宋绍兴年间的一座宅院，见证了一场充满悬念的生死局。

在159分钟时间里，张大、孙均的命运几经周折，与秦桧的角力扣人心弦，随着两位主角的终极目标从保命、刺杀变为拿到遗言，影片的情感内核从小人物的热血升格至家国情怀，全军复诵《满江红》的桥段成为被反复回味的名场面。再加上铺陈得恰到好处的喜剧元素，作为一部春节档的主流商业大片，《满江红》成了。

别想干洗店了，他们也水洗。

这些吃的看着像加了色素，长辈还让我吃？

我敢说，这世上没有人皮肤是“无暇”的。不用忙着照镜子，只要仔细看看自己的手臂，就一定会发现好几个小黑点，那就是“痣”。

为什么人身上有这么多痣呢？它们从哪里来？不同的痣可能大小不一，颜色深浅也不同，它们对身体有没有危害？今天我们就来好好聊聊痣。

作为一个北京人，我从小没听说过贡菜，更没见过。近十年随着四川火锅的大行其道，贡菜才出现在我面前。第一次吃就大呼上当——这不就是莴笋条吗！但上网一搜又蒙了，有的说贡菜就是莴笋，有的则言之凿凿说不是。