In this article, we discuss how Uber Engineering uses Locality Sensitive Hashing on Apache Spark to reliably detect fraudulent trips at scale.
Composed of a staged rollout and intelligent analytics tool, Uber Engineering's experimentation platform is capable of stably deploying new features at scale across our apps. In this article, we discuss the challenges and opportunities we faced when building this product.
How Uber Engineering re-architected the content delivery feed and backend ecosystem of our new driver app to deliver an enhanced user experience.
Uber Engineering's data center architecture is adopting IPv6 support to keep pace with the expansion of our services.
Uber Engineering built a custom stack that generates AutoValue models using immutable collections to stably migrate Android apps at scale.
Get to know Uber Engineering New York City and the exciting work we do on UberEATS, UberRUSH, and Uber's Observability platform.
The Uber Developer Platform empowers engineers worldwide to build moving in-app experiences for riders and drivers through integrations with Uber's Trip Experience API.
A daylong event at Uber’s Palo Alto office, sponsored by our LadyEng group, showcased the technical work across Uber Engineering as well as the people who are leading and building these projects. Here are some of the resulting presentations.
Uber Engineering debuts deck.gl 4.0, the latest version of our open source data visualization framework featuring enhanced geospatial exploration, a re-architected codebase, and more comprehensive documentation.
A recipe for success: how Uber Engineering used React Native to optimize UberEATS' Restaurant Dashboard app for mobile.
Although an untraditional choice for building mobile architectures, deep scope hierarchies are a key component of Uber's new Android rider app that enable the quick and seamless rollout of new features.
Say cheese! To better identify driver fraud, Uber Engineering's safety team developed Real-Time ID Check, a face verification solution that uses Face API.
Uber Engineering's data processing platform team recently built and open sourced Hoodie, an incremental processing framework that supports our business critical data pipelines. In this article, we see how Hoodie powers a rich data ecosystem where external sources can be ingested into Hadoop in near real-time.
Uber Engineering's fraud prevention team built the Mastermind rules engine to detect highly evolved forms of fraud at large scale in a fraction of a second.
The Uber Engineering mobile team migrates to a monorepo that uses Buck to test and deploy iOS and Android code faster and more efficiently than ever before.
This article is about developing Uber Engineering's open source distributed tracing system, Jaeger.
Meet Uber Engineering's Ohana. Meaning family in Hawaiian, Ohana is an open sourced, iOS framework for retrieving and formatting contact information.
An Uber incident response engineer discusses why we built our own custom email IDS to help guard against well executed phishing campaigns.
In November 2016 Uber unveiled a sleek new rider app. The app implements a new mobile architecture across both iOS and Android. In this article, Uber Engineering discusses why we felt the need to create a new architecture pattern, and how it helps us reach our goals.
Uber Engineering explains why and how we built Chaperone, our in-house auditing system for monitoring Kafka pipeline health.