JUN 17, 2026
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Airbnb Engineering Blog

23 articles on EngBrief

Airbnb Engineering shares how the team builds and scales the world's largest hospitality marketplace. Articles cover frontend architecture, design systems, data science and experimentation, search ranking, machine learning for pricing and recommendations, and the platform infrastructure serving millions of hosts and guests.

FrontendDesign SystemsData ScienceSearch & Ranking
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Latest Articles

Airbnb7d ago

Scaling beyond one: How Airbnb evolved its data architecture for a multi-product world

Airbnb's data engineers and analytics engineers built a flexible data modeling framework to support the company's expansion into multiple products. They defined three foundational principles to ensure consistency and scalability: avoiding hybrid data models, consistent identifier naming, and clear namespace organization. This framework empowered teams to pick the right data model for their specific domain, using shared guidelines that considered factors such as shared product attributes, future evolution, and code maintainability.

FrontendData Science
11 min
Airbnb12d ago

Sitar-agent: Building a reliable dynamic configuration sidecar at scale

Here is a concise summary of the blog post in 3 sentences: Airbnb engineers built Sitar-agent, a lightweight Kubernetes sidecar that delivers dynamic configuration reliably at scale. The sidecar runs alongside every subscribed service pod, synchronizing the latest configurations from the service backend and making them available on the local filesystem for reads. Through key design decisions, including a snapshot-based S3 preload and a pull model with server-side optimization, the Sitar-agent sidecar achieves reliability, performance, scalability, and multi-language support despite the constraints of delivering dynamic configuration at Airbnb's scale.

FrontendData Science
11 min
Airbnb14d ago

When history fails you, borrow from geography

How Airbnb used sequential geographic recovery signals and prior propagation to generate reliable corridor-level forecasts when local data was scarce.By:...

FrontendData Science
12 min
Airbnb28d ago

Scaling Airbnb’s identity graph with a unified knowledge graph infrastructure

How Airbnb shifts from PaaS to an internal knowledge graph infrastructure at scale.By: Lucen Zhao, Shukun Yang, Ashish JainKnowledge graphs offer a natural and...

FrontendData Science
8 min
AirbnbMay 13, 2026

Viaduct 1.0 and the future of Airbnb’s data mesh

Here's a concise 3-sentence summary of the blog post: Airbnb's data-oriented service mesh, Viaduct 1.0, has transitioned from an internal tool to a community-driven, production-ready project with a stable public API. Viaduct solves the problem of decentralized development of a central schema by distributing development through independently developed and tested tenant modules, each owning a portion of the schema. Viaduct complements existing GraphQL Federation approaches and can participate as a subgraph within a federated architecture, offering a flexible solution for teams building a company-wide data API.

FrontendData Science
6 min
AirbnbMay 5, 2026

Monitoring reliably at scale

Here's a summary of the post "Monitoring reliably at scale" from Airbnb Engineering: Airbnb's observability stack depended on the same systems it was intended to monitor, introducing a circular dependency that risked visibility during outages. To break this dependency, the team isolated compute resources and networking layers to provide redundant, highly available paths for collecting metrics. The team created dedicated Kubernetes clusters for observability workloads to minimize shared failure domains and operational overhead. For networking, they built a custom Layer 7 network ingress layer using Envoy to load-balance traffic, isolate observability traffic, and prioritize telemetry.

FrontendData Science
9 min
AirbnbApr 28, 2026

Skipper: Building Airbnb’s embedded workflow engine

Airbnb engineers built Skipper, a lightweight, embedded workflow engine to solve durable execution. It allows teams to write business logic without infrastructure concerns, resulting in a durable, multi-step process expressed as a single workflow class with side effects isolated behind actions. This design enables developers to write readable, maintainable code while promoting the reuse of domain logic, reducing the cost of solving durable execution across the organization.

FrontendData Science
14 min
AirbnbApr 21, 2026

Building a fault-tolerant metrics storage system at Airbnb

How we built a storage system that ingests 50 million samples per second and stores 2.5 petabytes of logical time series data.By: Rishabh KumarModern...

FrontendData Science
10 min
AirbnbApr 14, 2026

Privacy-first connections: Empowering social experiences at Airbnb

Discover how Airbnb prioritizes user privacy while building a more connected community, empowering guests to engage socially, connect confidently, and maintain...

FrontendData Science
8 min
AirbnbApr 7, 2026

Building a high-volume metrics pipeline with OpenTelemetry and vmagent

A production-tested approach for moving a large-scale metrics pipeline from StatsD to OpenTelemetry and Prometheus.By: Eugene Ma, Natasha AleksandrovaWhen...

FrontendData Science
10 min
AirbnbApr 2, 2026

My Journey to Airbnb — Jonathan Woodard

Jonathan Woodard knows defense. After playing professional football as a defensive end for six years, Jonathan knew he wanted a career where he could always...

FrontendData Science
8 min
AirbnbMar 24, 2026

What COVID did to our forecasting models (and what we built to handle the next shock)

How Airbnb built forecasting models resilient enough to survive a global pandemic and whatever shock comes next.By: Harrison KatzThe week everything brokeIn...

FrontendData Science
14 min
AirbnbMar 17, 2026

From vendors to vanguard: Airbnb’s hard-won lessons in observability ownership

How a complex, large-scale migration to an in-house observability platform led to superior tooling, consistent data, and a fundamental reset of the developer...

FrontendData Science
12 min
AirbnbMar 12, 2026

Recommending Travel Destinations to Help Users Explore

How we built a destination recommendation model that helps users spark inspiration and narrow down choices to make journeys smoother.By: Weiwei Guo, Bin Xu,...

FrontendData Science
6 min
AirbnbMar 4, 2026

It Wasn’t a Culture Problem: Upleveling Alert Development at Airbnb

How we changed our Observability as Code alert review process and cut development cycles from weeks to minutes.Observability as Code (OaC) — defining alerts,...

FrontendData Science
9 min
AirbnbFeb 24, 2026

Academic Publications & Airbnb Tech: 2025 Year in Review

2025 was a big year for research at Airbnb, as we made significant progress toward our mission to use AI, data science, and machine learning to become the best...

FrontendData Science
12 min
AirbnbFeb 18, 2026

Safeguarding Dynamic Configuration Changes at Scale

How Airbnb ships dynamic config changes safely and reliablyBy Cosmo Qiu, Bo Teng, Siyuan Zhou, Ankur Soni, Willis HarveyDynamic configuration is a core...

FrontendData Science
9 min
AirbnbFeb 11, 2026

My Journey to Airbnb — Anna Sulkina

Anna Sulkina has always been a traveler, and we’re lucky her travels have brought her to Airbnb. Anna is a Senior Director of Engineering, and she’s...

FrontendData Science
9 min
AirbnbJan 28, 2026

My Journey to Airbnb: Peter Coles

Public school to PhDThe story of Airbnb’s Head Economist for Policy and Director of Data Science involves geology, co-teaching with a Nobel Prize winner, and...

FrontendData Science
9 min
AirbnbJan 12, 2026

Pay As a Local

How Airbnb rolled out 20+ locally relevant payment methods worldwide in just 14 monthsBy: Gerum Haile, Bo Shi, Yujia Liu, Yanwei Bai, Bo Yuan, Rory MacQueen,...

FrontendData Science
13 min