爱彼迎自主开发的页面性能评分（PPS）旨在通过收集多种以用户为中心的性能指标，并将它们转化为一个 0-100 的综合评分，来描述丰富复杂的性能。在本文中，我们将深入介绍如何在Android 上定义和实现这些指标。请确保首先阅读

A deep dive into the streaming aspect of the Lambda architecture framework of Riverbed.

爱彼迎上的整个用户旅程被划分为不同的页面，每个页面都有自己的页面性能分数(PPS)。为了支持这个基于页面的性能跟踪系统，我们建立了一个标准化的基础设施，使工程师能够配置页面和功能的对应关系。

在 iOS 上，页面与 UIViewController相关联。我们在 UIViewController 的生命周期中收集性能数据，在 viewDidDisappear 时发送收集到的日志。我们使用 PageName 作为全局的页面标识符，日志必须存在 PageName 时才能创建或发送。

How the Airbnb Media team built group travel Postcards for the 2024 Summer Release by leveraging a novel destination matching algorithm while advancing the platform’s image & localized text processing capabilities.

An Important Foundation For Security, Privacy, and Compliance at Airbnb.

At Airbnb, Apache Flink was introduced in 2018 as a supplementary solution for stream processing. It ran alongside Apache Spark™ Streaming for several years before transitioning to become the primary stream processing platform. In this blog post, we will delve into the evolution of Flink architecture at Airbnb and compare our prior Hadoop Yarn platform with the current Kubernetes-based architecture. Additionally, we will discuss the efforts undertaken throughout the migration process and explore the challenges that arose during this journey. In the end we will summarize the impact, learnings along the way and future plans.

Incrementally modernizing our frontend infrastructure to roll out the latest React features without downgrades.

Airbnb has made significant strides in improving web accessibility for Hosts and guests who require larger text sizes.

How Airbnb enabled hosts and guests to connect and introduce themselves through the Host Passport.

At Airbnb, we have developed Brandometer, a state-of-the-art natural language understanding (NLU) technique for understanding brand perception based on social media data. Brand perception refers to…

Part three on how we built a Compose based architecture with Mavericks in the Airbnb Android app.

A feature platform that offers observability and management tools, allows ML practitioners to use a variety of data sources, while handling the complexity of data engineering, and provides low latency streaming.

Part two on how we built a Compose based architecture with Mavericks in the Airbnb Android app.

A three part series on how we built a Compose based architecture with Mavericks in the Airbnb Android app

用于加快和提高读取密集型工作负载可靠性的爱彼迎数据框架的概述。

How Airbnb achieved a smooth and transparent migration from Buck to Bazel on iOS, with minimal interference to developer workflows.