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Airbnb Technology Team

Official account of the Airbnb Technology Team, sharing Airbnb's tech innovations and real-world implementations, building a world where home is everywhere through technology.

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Latest from Airbnb Technology Team

55 recent articles

Airbnb Technology Team

Nov 12, 2024 · Mobile Development

Trio Architecture: Building a Compose‑Based Android Framework on Mavericks

Airbnb’s Android team introduced Trio, a Compose‑only framework built atop the Mavericks state‑management library that replaces Fragment‑based navigation with type‑safe, modular page routing, ViewModel‑driven state, compile‑time validation, and dedicated developer tools, now powering the majority of the app’s screens.

AndroidArchitectureJetpack Compose

0 likes · 15 min read

Trio Architecture: Building a Compose‑Based Android Framework on Mavericks

Airbnb Technology Team

Sep 19, 2024 · Mobile Development

How Airbnb Instruments Android Apps to Capture User‑Centric Performance Metrics

Airbnb’s Android Page Performance Score (PPS) framework instruments fragments to collect user‑centric metrics such as TTFL, TTIL, MTH, ALT and RCLT, using a standardized logging config, LoadableView interface, and visibility algorithms, enabling detailed performance analysis and automated alerts for mobile teams.

AndroidPerformance Monitoringinstrumentation

0 likes · 10 min read

How Airbnb Instruments Android Apps to Capture User‑Centric Performance Metrics

Airbnb Technology Team

Sep 9, 2024 · Mobile Development

Implementing Page Performance Score on iOS: PPSStateMachine, Metrics, and Instrumentation

Airbnb’s iOS Page Performance Score implementation introduces a PPSStateMachine that ties a UIViewController’s lifecycle to metric collection—tracking first layout, initial load, scroll thread hangs, additional and rich content load times—using nanosecond timestamps, state‑machine protocols, and view‑responder discovery to emit standardized performance logs.

Page Performance ScoreSwiftiOS

0 likes · 9 min read

Implementing Page Performance Score on iOS: PPSStateMachine, Metrics, and Instrumentation

Airbnb Technology Team

Jul 16, 2024 · Frontend Development

Airbnb Web Performance Metrics and Their Measurement

Airbnb tracks five real‑user performance metrics—Time To First Contentful Paint, Time To First Meaningful Paint, First Input Delay, Total Blocking Time, and Cumulative Layout Shift—using a mix of browser APIs and custom polyfills, combines them into a weighted Page Performance Score, and leverages that score to guide trade‑off decisions and detect regressions.

AirbnbWeb Performancemetrics

0 likes · 11 min read

Airbnb Technology Team

Jul 2, 2024 · Frontend Development

Airbnb Page Performance Score (PPS): Multi‑Platform Metrics, Weighting, and Evolution

Airbnb created the Page Performance Score (PPS), a unified 0‑100 metric that aggregates platform‑specific initial‑load and post‑load user‑centric measurements for Web, iOS, and Android, using weighted curves to enable cross‑page, cross‑team comparisons, track organizational weighted averages, and evolve with new metrics while preserving a stable scale.

AirbnbPage Performance ScoreWeb Performance

0 likes · 10 min read

Airbnb Page Performance Score (PPS): Multi‑Platform Metrics, Weighting, and Evolution

Airbnb Technology Team

Apr 15, 2024 · Artificial Intelligence

Airbnb's Attribute Prioritization System: Machine Learning for Extracting Guest Preferences from Unstructured Text

Airbnb’s Attribute Prioritization System uses a machine‑learning pipeline called LATEX to extract and map guest‑mentioned amenities, activities and places from reviews, messages and tickets, then predicts and ranks the most important attributes per listing, giving hosts personalized suggestions to improve listings and match traveler needs.

AirbnbNERNLP

0 likes · 9 min read

Airbnb's Attribute Prioritization System: Machine Learning for Extracting Guest Preferences from Unstructured Text

Airbnb Technology Team

Mar 1, 2024 · Big Data

Riverbed: A Scalable Data Framework for Real‑time and Batch Processing at Airbnb

Airbnb’s Riverbed framework unifies streaming CDC events and batch Spark jobs behind a GraphQL‑based declarative API to automatically build and maintain distributed materialized views, using Kafka‑partitioned ordering and version control to deliver billions of daily updates with low‑latency reads for features such as payments and search.

AirbnbApache SparkData Engineering

0 likes · 8 min read

Riverbed: A Scalable Data Framework for Real‑time and Batch Processing at Airbnb

Airbnb Technology Team

Jan 31, 2024 · Artificial Intelligence

Airbnb’s Listing Attribute Extraction Platform (LAEP): End-to-End Structured Information Extraction Using Machine Learning and NLP

Airbnb’s Listing Attribute Extraction Platform (LAEP) uses a custom NER model, word‑embedding mapping, and a BERT‑based scorer to automatically pull, normalize, and validate structured attributes from hosts’ unstructured text, boosting coverage for downstream tools and enhancing guest‑host matching at scale.

AirbnbBERTEntity Extraction

0 likes · 11 min read

Airbnb’s Listing Attribute Extraction Platform (LAEP): End-to-End Structured Information Extraction Using Machine Learning and NLP

Airbnb Technology Team

Dec 8, 2023 · Artificial Intelligence

Leveraging Image Aesthetics and Photo Sorting Algorithms to Enhance Airbnb Listings

Airbnb’s new computer‑vision pipeline trains a deep‑learning aesthetic model with an EMD loss to rank photos, automatically sorts new‑listing images by design and room type, and scales real‑time similarity search via HNSW‑based ANN on AWS OpenSearch, boosting click‑through, bookings, and enabling unsupervised visual recommendations.

AirbnbEmbedding SearchPhoto Sorting Algorithm

0 likes · 9 min read

Leveraging Image Aesthetics and Photo Sorting Algorithms to Enhance Airbnb Listings

Airbnb Technology Team

Nov 17, 2023 · Mobile Development

Airbnb’s Journey from Epoxy/UIKit to SwiftUI: Evaluation, Migration, and Lessons Learned

Airbnb’s three‑stage migration from its custom Epoxy/UIKit stack to SwiftUI involved extensive evaluation, rebuilding the design system with flexible style protocols, bridging UIKit and SwiftUI, adopting one‑way data flow, extensive testing and training, resulting in six‑fold code reduction, comparable performance, widespread production adoption, and higher developer productivity despite remaining framework challenges.

AirbnbDeclarative UIEpoxy

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Airbnb’s Journey from Epoxy/UIKit to SwiftUI: Evaluation, Migration, and Lessons Learned