Jennifer Anderson, a veteran of Silicon Valley technology companies, leads Uber's Product Platform organization, which hosts our core services. In this interview, she describes her organization and the lessons she has learned.
Uber's Destination:Web meetup series gives great insight about the most current web building tools and techniques. These three videos from Uber presenters offer tips on a mysterious design pattern, the Elm language, and Progressive Enhancement.
A key challenge faced by self-driving vehicles comes during interactions with pedestrians. In our development of self-driving vehicles, the Data Engineering and Data Science teams at Uber ATG (Advanced Technologies Group) contribute to the data processing and analysis that help make these interactions safe.
On May 3, 2019, Uber’s Programming Systems Team hosted the Programming Systems and Tools Track of the company’s Second Uber Science Symposium, featuring a full day of talks by leading researchers and practitioners in the the field.
Uber Technical Writer Shannon Brown offers three tips for creating concise, meaningful documentation.
In this short tutorial, we show you how to build a Hello World! application using Fusion.js, an open source universal web framework suitable for building interactive web applications.
Uber's Maps Collection and Reporting (MapCARs) team shares best practices when choosing which HDFS file formats are optimal for use with Apache Spark.
In this article, Uber’s Marianne Borzic Ducournau discusses why financial planning at Uber presents unique and challenging opportunities for data scientists.
The Uber Beacon leverages visual signaling, an accelerometer, and a gyroscope to improve the accuracy of in-app safety products like our automatic crash detection feature.
Our editors spotlight some of the year's most popular articles, from an overview of our Big Data platform to a first-person account of an engineer's immigrant journey.
Jonathan Levi recounts his experience as an intern at Uber during Summer 2018, including building a useful project for the Uber Eats team.
During a September 2018 meetup, Uber's Payments Platform team discusses how this technology supports our company's growth through an active-active architecture, exactly-once payment processing, and scalability across businesses.
Uber engineers outline how we came to the resource-intensive decision to rewrite, rather than migrate or update, our driver app.
Uber Eats engineers describe how they surface restaurant recommendations in the app using multi-objective optimization to give eaters the most satisfying experience while maintaining the health of the Uber Eats marketplace.
A few of Uber's over 200 engineering interns from this year's summer program talk about the projects they worked on and what their experiences in the office were like.
Facing the need for a resilient data structure over thousands of storage nodes to serve the 15 million rides per day that occur on our platform, Uber engineers developed Herb, our data replication solution. Herb ensures data availability and integrity across our data centers.
Building robust regression analysis not only helps ensure that new feature deployments work properly, but also lets Uber engineers automate deployments.
Maps make up the bedrock of Uber's transportation solutions. Find out how we ensure the quality of our map data through extensive metrics computation, maintaining fidelity to real world locations and pinpointing allowable pick up and drop off locations for riders.
Uber developed its own financial planning software, relying on data science and machine learning, to deliver on-demand forecasting and optimize strategic and operations decisions.
Uber's attorneys explain the intricacies of different types of open source software licenses and intellectual property.
Using GPS and sensor data from Android phones, Uber engineers develop a state model for trips taken by Uber Eats delivery-partners, helping to optimize trip timing for delivery-partners and eaters alike.
To detect and prevent fraud, Uber brings to bear data science and machine learning, analyzing GPS traces and usage patterns to identify suspicious behavior.
Uber engineers share how we process search terms for our Uber Eats service, using query understanding and expansion to find restaurants and menu items that best match what our eaters want.
Making JUMP Bikes' semi-dockless electric bicycles available on Uber's platform not only added a popular new transportation type for Uber riders, but also marked an important step in how we can use our technology to broaden transportation options.
uRate empowers both Uber employees and customers to provide quick and efficient feedback on tools and products, enabling engineers to build more responsive services.
Uber’s Sensing, Inference, and Research team released a software upgrade for GPS on Android phones that significantly improves location accuracy in urban environments.
Matthew Mengerink, Vice President of Engineering for Uber’s Core Infrastructure group, talks about how converging technologies and cloud computing contribute to stable and scalable growth.
Uber's Customer Obsession Engineering team developed new check-in queuing and appointment systems to improve the customer experience for driver-partners at our Greenlight Hubs.
Nicolas Garcia Belmonte, head of visualization, talks about his experience getting started in open source and the role it plays in his work at Uber.
The design of Uber's driver support kiosk drew inspiration from arcade games of the past along with new thinking on how to engage with customers in public spaces.
As we approach the New Year, Uber Open Source revisits some of Uber Engineering's most popular projects from 2017.
To ring in the New Year, the Uber Engineering Blog shares some of our editor's picks for 2017.
Uber Engineering built Denial by DNS, our open source solution for preventing DoS by DNS outages, to facilitate more reliable experiences on Uber's apps, no matter how users choose to access them.
How does Uber keep New Year's Eve and other high traffic events...well, uneventful? By keeping our networks extensible and our services reliable year-round.
Uber’s Customer Obsession team builds tools that make the customer support experience quicker and more seamless for users across our services.
Uber Engineering's On-Call Dashboard provides real-time incident response, shift maintenance, and post-mortem analysis for an improved on-call experience.
Chameleon, a global CMS for Uber.com, enables regional operations and marketing teams at Uber to build and ship customized, on-brand webpages.
In this article, we discuss how Uber Engineering uses Locality Sensitive Hashing on Apache Spark to reliably detect fraudulent trips at scale.
Uber Engineering's data center architecture is adopting IPv6 support to keep pace with the expansion of our services.
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.
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 fraud prevention team built the Mastermind rules engine to detect highly evolved forms of fraud at large scale in a fraction of a second.
An Uber incident response engineer discusses why we built our own custom email IDS to help guard against well executed phishing campaigns.
In this article, we discuss deck.gl, an open sourced, WebGL-powered framework specifically designed for exploring and visualizing data sets at scale.
In this article, we take a look at Euclid, Uber Engineering's Hadoop and Spark-based in-house marketing platform.
Seemingly small inefficiencies are greatly magnified as Uber's business scales. In this article we’ll explore design considerations and unique implementation characteristics of Pyflame, Uber Engineering's high-performance Python profiler implemented in C++.
A behind-the-scenes look at how Uber Engineering continues to develop our virtual onboarding funnel which enables hundreds of thousands of driver-partners to get on the road and start earning money with Uber.
Take a look into uReplicator, Uber’s open source solution for replicating Apache Kafka data in a robust and reliable manner.
The end of a two-part series on the tech stack that Uber Engineering uses to make transportation as reliable as running water, everywhere, for everyone, as of spring 2016.
Uber’s mission is transportation as reliable as running water, everywhere, for everyone. Here's the first of a two-part series on the tech stack that Uber Engineering uses to make this happen.