Experimentation & Measurement for Search Engine Optimization

Our San Francisco headquarters has it all, from comfy nooks to sunlit views. It’s the… For many of our potential guests, planning a trip starts at the search engine. At Airbnb, we want our product to be painless to find for past guests, and easy to discover for new ones. Search engine optimization (SEO) is the process of improving our site — and more specifically…

Dynein: Building a Distributed Delayed Job Queueing System

An Airbnb Plus listing in Argyll, Scotland Introduction Asynchronous background jobs can often dramatically improve the scalability of web applications by moving time-consuming, resource-intensive tasks to the background. These tasks are often prone to failures, and retrying mechanisms often make it even more expensive…

Moving Lottie Swiftly into the Future

Come and join us in working on Swift development in our gorgeous office! Lottie is a library for Android, iOS, Web, and Windows that parses Adobe After Effects animations exported as JSON with Bodymovin and renders them natively on mobile and on the web. If you haven’t already read Brandon’s post about the Swift rewrite of Lottie on iOS, check it out! We’d…

Amenity Detection and Beyond — New Frontiers of Computer Vision at Airbnb

Authors: Shijing Yao, Dapeng Li, Shawn Chen What amenities are there in this image? Can an algorithm detect them all? How can we train the algorithm effectively? If you are interested in the answers, please read on! Introduction In 2018, we published a blog post titled Categorizing Listing Photos at Airbnb…

On Spark, Hive, and Small Files: An In-Depth Look at Spark Partitioning Strategies

Author: Zachary Ennenga Airbnb’s new office building, 650 Townsend Background At Airbnb, our offline data processing ecosystem contains many mission-critical, time-sensitive jobs — it is essential for us to maximize the stability and efficiency of our data pipeline infrastructure. So, when a few months back, we encountered a recurring issue that caused significant outages of our data…

Sunsetting React Native

This is the fourth in a series of blog posts in which we outline our experience with React Native and what is next for mobile at Airbnb.Where are we today? Although many teams relied on React Native and had planned on using it for the foreseeable future, we were ultimately…

A Deep Dive into Airbnb’s Server-Driven UI System

By Ryan Brooks Background: Server-Driven UI Before we dive into Airbnb’s implementation of server-driven UI (SDUI), it’s important to understand the general idea of SDUI and how it provides an advantage over traditional client-driven…

Building Services at Airbnb, Part 2

By Liang Guo and Frank Lin Vittoria is treating his guests to a tour of the Limoncello factory, where family makes… Airbnb is moving its infrastructure towards SOA. A reliable, performant, and developer-friendly service platform is essential in an architectural evolution. In a previous post, we shared a bird’s-eye view of what we have designed and built to scale the development of services and gave…

Introducing Epoxy for iOS

Epoxy’s story on iOS began in 2016. Swift was still a very new language, and we had recently started to broadly adopt it across our codebase. With the new language, we were still experimenting with how to best build UI. …

Building a faster web experience with the postTask scheduler

When was the last time you opened a page on a website and tried to click on something multiple times for it to work? Or the last time you swiped on an image in a carousel and it stuttered and shifted around unnaturally? While this type of experience happens far…

A “Krispr” Approach to Kubernetes Infrastructure

Introduction Airbnb is built on a service-oriented architecture (SOA). In our production infrastructure, we run hundreds of services that do everything from calculating pricing to returning search results to sending messages to users. To unify and scale our infrastructure, we use Kubernetes, an open source container orchestration engine, to define and…

Data Quality at Airbnb

Authors: Vaughn Quoss, Jonathan Parks, Paul Ellwood Introduction At Airbnb, we’ve always had a data-driven culture. We’ve assembled top-notch data science and engineering teams, built industry-leading data infrastructure, and launched numerous successful open source projects, including Apache Airflow and Apache Superset. Meanwhile, Airbnb has…

WIDeText: A Multimodal Deep Learning Framework

By Wayne Zhang, Mia Zhao, Yuanpei Cao Deep learning (DL) is helping us at Airbnb serve our stakeholders better…

How Airbnb is Boosting Data Literacy With ‘Data U Intensive’ Training

Since we introduced Airbnb’s Data University, the program has continued to thrive and evolve. One improvement has been the addition of team-specific trainings with content tailored to the work of that team. In this post, we describe the impact of this addition and the lessons learned in its implementation. What is Data University? …

Server Rendering, Code Splitting, and Lazy Loading with React Router v4

Challenge accepted. Nicole, one of our hosts, taking some guests on a sunrise walk and picnic above… Some Background on Server Rendering at Airbnb Historically, Airbnb has been a Rails app. A few years back that started to change, we began using Rails simply as a data layer, and all render logic started migrating into JavaScript in…

The Airbnb Talent Directory

The past few months have been hard for all of us, but it has been inspiring to see everyone, especially the Airbnb community, support each other during an unprecedented time. Our CEO, Brian Chesky, recently announced the departure of nearly 1,900 employees. Among these employees are incredibly talented Engineers and Data Scientists who have contributed to Airbnb in uncountable ways. To support our teammates departing Airbnb, we launched the Alumni Talent Directory, an opt-in directory which lists valued employees and contingent workers who have recently departed Airbnb. If you’re currently hiring or looking for incredible talent, the Talent Directory is full of amazing Engineers and Data Scientists, among others. We hope we can connect these individuals with new opportunities. It’s been an honor to work with such a talented team committed to our mission of belonging, and we’re confident any company would be lucky to have them. We’d also like to thank the cross-functional team that created the site in an extremely short period of time. We are all grateful for their hard work: Chris Arrington, Gina Groom, Noor Malik, Derek Southard, Parag Hardas, Robin Foyle, Mike Fowler, Christian Williams, Megan Gebhart, Alex Cheng, Steve Rafferty, Sonia Yang, Andy Tran, Angela Wu, Linsey Jackson, James Deslonde, Kelly Coldwell, as well as Joe Gebbia for inspiring the idea. Airbnb Alumni Talent Directory

How Druid enables analytics at Airbnb

By Pala Muthiah and Jinyang Li Wikipedia: A druid was a member of the high-ranking professional class in ancient Celtic cultures… Airbnb serves millions of guests and hosts in our community. Every second, their activities on Airbnb.com, such as searching, booking, and messaging, generate a huge amount of data we anonymize and use to improve the community’s experience on our platform. The Data Platform Team…

Inside Connect: Airbnb’s Engineering Apprenticeship Program

by Beti Gathegi & Jacqui Watts Hello! We’re excited that you’re here to learn more about the Connect program. Before we share details, though, we’d like to introduce ourselves. We’re Beti Gathegi and Jacqui Watts — a team of two whose purpose at Airbnb is to help bring this program…

How Airbnb Standardized Metric Computation at Scale

Part II: The six design principles of Minerva compute infrastructure By: Amit Pahwa, Cristian Figueroa, Donghan Zhang, Haim Grosman, John Bodley, Jonathan Parks, Maggie Zhu, Philip Weiss, Robert Chang, Shao Xie, Sylvia Tomiyama, Xiaohui Sun Introduction As described in the first post of this series, Airbnb invested significantly in building Minerva, a single source of truth metric platform that standardizes the…

Enzyme’s Next Phase

In 2016, Airbnb released Enzyme, our React component testing library. In the following 4 years, the project has amassed more than 18,000 stars, and over 340 contributors. GitHub also tells us that Enzyme is used by over 230,000 repos and 24,000 packages, and npm reports that it is downloaded around 2 million times each week. The community’s response to this project has been astounding, to say the least. Much of Enzyme’s success is the result of the vibrant React community opening and commenting on actionable issues and submitting quality pull requests. All of your contributions have directly contributed to this project’s success—we could not have done this without you. This community is largely the reason why we are excited to announce that we will transfer ownership of Enzyme to the new enzymejs GitHub organization. We believe that this new home will help the project continue to support the community’s needs well into the future. The success here has moved beyond Airbnb as a single org and it’s time for our baby to be launched as a successful adult. Internally at Airbnb, Enzyme has been a catalyst for better frontend test coverage and is currently used in over 17,000 tests. While other options like React Testing Library have gained traction within Airbnb, we will still be using and contributing to Enzyme for the foreseeable future. If you want to help Enzyme grow, please check out the open issues and pull requests — the “help wanted” tag is a great starting point.

Inside Connect: Supporting Apprentices as an Engineering Leader

As an engineering leader with 15+ years of industry experience, I am currently head of engineering for the Marketing Technology Platform at Airbnb. Our goal is to build world-class technology systems and tools that power the unique blend of performance and brand marketing strategies at Airbnb. In this post, I’d…

Fighting Financial Fraud with Targeted Friction

The piano in our “Vienna” meeting room in San Francisco has an easter egg. Move… On any given night, nearly two million people are staying in Airbnb listings in 191 countries around the world. The rapid growth of our global community is predicated on one thing: trust. We take a comprehensive approach to trust, which consists of both robust proactive measures and reactive support, but…

Scaling a Mature Data Pipeline — Managing Overhead

Author: Zachary Ennenga The view from the third floor at Airbnb HQ! Background There is often a natural evolution in the tooling, organization, and technical underpinning of data pipelines. Most data teams and data pipelines are born from a monolithic collection of queries. As the pipeline grows in its complexity, it becomes sensible to leverage the Java or Python Spark…

Detecting Vulnerabilities With Vulnture

Introduction Securing assets and data is a challenging and important task, regardless of your industry or company size. On Airbnb’s InfoSec team, we are constantly thinking about how to quickly and effectively detect and remediate…

Building an Effective Test Pipeline in a Service Oriented World

This staircase connects several floors of our beautiful new San Francisco office, 650 Townsend. Context Over the past 2 years, Airbnb engineering has been working on a major initiative to migrate from a gigantic Rails Application to a decoupled service-oriented architecture, or SOA…