Uber Movement: Let's find smarter ways forwardLet’s find smarter ways forwardUber Movement provides anonymized data from over two billion trips to help urban planning around the world
Building Reliable Reprocessing and Dead Letter Queues with Kafka
EngineeringBuilding Reliable Reprocessing and Dead Letter Queues with Apache KafkaFebruary 16, 2018 / Global In distributed systems, retries are inevitable. From network errors to replication issues and even outages in downstream dependencies, services operating at a massive scale must be prepared to encounter, identify, and handle failure as gracefully as possible. Given the scope and pace at whi
Code Migration in Production: Rewriting the Sharding Layer of Uber’s Schemaless Datastore
Code Migration in Production: Rewriting the Sharding Layer of Uber’s Schemaless Datastore In 2014, Uber Engineering built Schemaless, our fault-tolerant and scalable datastore, to facilitate the rapid growth of our company. For context, we deployed more than 40 Schemaless instances and many thousands of storage nodes in 2016 alone. As our business grew, so did our resource utilization and latencie
Year in Review: 2017 Highlights from Uber Open Source
Since the beginning, Uber has relied on open source technologies to build reliable, production-hardened systems that can grow at scale. In this spirit, Uber Engineering has given back several technologies to the open source community, ranging from a data visualization framework and an iOS contacts library, to a signature rendering tool and even a new programming language. As we ring in the New Yea
Building an Intelligent Experimentation Platform with Uber Engineering
You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more During our inaugural Uber Technology Day, data scientist Eva Feng delivered a presentation on Uber’s experimentation platform (XP). In this article, she and colleague Zhenyu Zhao detail how Uber engineered an XP capable of rolling out new features stably and quickly at
Uber Newsroom
Map beacon indicating location switcherMagnifying glass indicating a search icon 日本 | 2017 年 10 月 31 日UberEATS、横浜でサービス開始!! 〜 HELLO YOKOHAMA! キャンペーン実施〜記事作成者: Kay Hattori Uber のテクノロジーを活用したフードデリバリーサービス「UberEATS （読み方：ウーバーイーツ）」 は 2017年11月1日 (水) 10時より、横浜でサービスを開始いたします。 港町として発展してきた横浜ならではの多国籍料理や日本で独自に進化してきた洋食、そして日本三大中華街のひとつ、横浜中華街からは本格的な中華料理など、UberEATS の GPS を利用したマッチングテクノロジーで、ご自宅や職場、公園などご指定の場所に出来立ての料理をお届けしま
Uber Help
In October 2016, Uber experienced a data security incident that resulted in a breach of information related to rider and driver accounts. For riders, this information included the names, email addresses, and mobile phone numbers related to accounts globally. Our outside forensics experts have not seen any indication that trip location history, credit card numbers, bank account numbers, or dates of
Uber Newsroom
Map beacon indicating location switcherMagnifying glass indicating a search icon US | Nov 21, 20172016 Data Security IncidentWritten byDara Khosrowshahi, CEO As Uber’s CEO, it’s my job to set our course for the future, which begins with building a company that every Uber employee, partner and customer can be proud of. For that to happen, we have to be honest and transparent as we work to repair ou
Uber AI Labs Open Sources Pyro, a Deep Probabilistic Programming Language
EngineeringUber AI Labs Open Sources Pyro, a Deep Probabilistic Programming LanguageNovember 3, 2017 / Global Achieving Uber’s goal of bringing reliable transportation to everyone requires effortless prediction and optimization at every turn. Opportunities range from matching riders to drivers, to suggesting optimal routes, finding sensible pool combinations, and even creating the next generation
Meet Horovod: Uber's Open Source Distributed Deep Learning Framework for TensorFlow
Data / ML, EngineeringMeet Horovod: Uber’s Open Source Distributed Deep Learning Framework for TensorFlowOctober 17, 2017 / Global Over the past few years, advances in deep learning have driven tremendous progress in image processing, speech recognition, and forecasting. At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep l
Introducing AthenaX, Uber Engineering’s Open Source Streaming Analytics Platform
EngineeringIntroducing AthenaX, Uber Engineering’s Open Source Streaming Analytics PlatformOctober 9, 2017 / Global Uber facilitates seamless and more enjoyable user experiences by channeling data from a variety of real-time sources. These insights range from in-the-moment traffic conditions that provide guidance on trip routes to the Estimated Time of Delivery (ETD) of an UberEATS order—and every
Engineering Uncertainty Estimation in Neural Networks for Time Series Prediction at Uber
Data / MLEngineering Uncertainty Estimation in Neural Networks for Time Series Prediction at UberSeptember 6, 2017 / Global Accurate time series forecasting during high variance segments (e.g., holidays and sporting events) is critical for anomaly detection, resource allocation, budget planning, and other related tasks necessary to facilitate optimal Uber user experiences at scale. Forecasting the
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