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You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more Machine learning (ML) is widely used across the Uber platform to support intelligent decision making and forecasting for features such as ETA prediction and fraud detection. For optimal results, we invest a lot of resources in developing accurate predictive ML models. I

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more Neural networks, an important tool for processing data in a variety of industries, grew from an academic research area to a cornerstone of industry over the last few years. Convolutional Neural Networks (CNNs) have been particularly useful for extracting information fro

Data / MLUnder the Hood of Uber’s Experimentation PlatformAugust 28, 2018 / Global Experimentation is at the core of how Uber improves the customer experience. Uber applies several experimental methodologies to use cases as diverse as testing out a new feature to enhancing our app design. Uber’s Experimentation Platform (XP) plays an important role in this process, enabling us to launch, debug, me

Introducing Makisu: Uber’s Fast, Reliable Docker Image Builder for Apache Mesos and Kubernetes To ensure the stable, scalable growth of our diverse tech stack, we leverage a microservices-oriented architecture, letting engineers deploy thousands of services on a dynamic, high-velocity release cycle. These services enable new features to greatly improve the experiences of riders, drivers, and eater

EngineeringObservability at Scale: Building Uber’s Alerting EcosystemNovember 20, 2018 / Global Uber’s software architectures consists of thousands of microservices that empower teams to iterate quickly and support our company’s global growth. These microservices support a variety of solutions, such as mobile applications, internal and infrastructure services, and products along with complex confi

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more With the evolution of storage formats like Apache Parquet and Apache ORC and query engines like Presto and Apache Impala, the Hadoop ecosystem has the potential to become a general-purpose, unified serving layer for workloads that can tolerate latencies of a few minutes

EngineeringPeloton: Uber’s Unified Resource Scheduler for Diverse Cluster WorkloadsOctober 30, 2018 / Global Cluster management, a common software infrastructure among technology companies, aggregates compute resources from a collection of physical hosts into a shared resource pool, amplifying compute power and allowing for the flexible use of data center hardware. At Uber, cluster management prov

AIMichelangelo PyML: Introducing Uber’s Platform for Rapid Python ML Model DevelopmentOctober 23, 2018 / Global As a company heavily invested in AI, Uber aims to leverage machine learning (ML) in product development and the day-to-day management of our business. In pursuit of this goal, our data scientists spend considerable amounts of time prototyping and validating powerful new types of ML model

Data / ML, EngineeringUber’s Big Data Platform: 100+ Petabytes with Minute LatencyOctober 17, 2018 / Global Uber is committed to delivering safer and more reliable transportation across our global markets. To accomplish this, Uber relies heavily on making data-driven decisions at every level, from forecasting rider demand during high traffic events to identifying and addressing bottlenecks in our

Marmaray: An Open Source Generic Data Ingestion and Dispersal Framework and Library for Apache Hadoop Connecting users worldwide on our platform all day, every day requires an enormous amount of data management. When you consider the hundreds of operations and data science teams analyzing large sets of anonymous, aggregated data, using a variety of different tools to better understand and maintain

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more To facilitate the growth of Uber’s global operations, we need to be able to quickly store and access billions of metrics on our back-end systems at any given time. As part of our robust and scalable metrics infrastructure, we built M3, a metrics platform that has been i

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more From driver and rider locations and destinations, to restaurant orders and payment transactions, every interaction on Uber’s transportation platform is driven by data. Data powers Uber’s global marketplace, enabling more reliable and seamless user experiences across our

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more A little-known fact is that Uber builds a lot of web-based applications, hundreds of them and counting, in fact. Many of them are internal apps for managing various aspects of the business while others are public facing. A more well-known fact is that web technologies c

Data / ML, EngineeringHerb: Multi-DC Replication Engine for Uber’s Schemaless DatastoreJuly 25, 2018 / Global Schemaless, Uber’s fault-tolerant and scalable datastore, supports the 600-plus cities where we operate and the 15 million rides per day that occur on our platform, not to mention Uber Eats, Uber Freight, and other business lines. Since 2014, we have deployed more than 50 Schemaless instan

An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution Uber uses convolutional neural networks in many domains that could potentially involve coordinate transforms, from designing self-driving vehicles to automating street sign detection to build maps and maximizing the efficiency of spatial movements in the Uber Marketplace. In deep learning, few ideas have experienced

JVM Profiler: An Open Source Tool for Tracing Distributed JVM Applications at Scale Computing frameworks like Apache Spark have been widely adopted to build large-scale data applications. For Uber, data is at the heart of strategic decision-making and product development. To help us better leverage this data, we manage massive deployments of Spark across our global engineering offices. While Spark

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You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more Choice is fundamental to the Uber Eats experience. At any given location, there could be thousands of restaurants and even more individual menu items for an eater to choose from. Many factors can influence their choice. For example, the time of day, their cuisine prefer

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more Data / ML, EngineeringFrom Beautiful Maps to Actionable Insights: Introducing kepler.gl, Uber’s Open Source Geospatial ToolboxMay 29, 2018 / Global Maps are based on our physical world. We create maps using abstract shapes and colors to reveal geographic patterns and te

Data / MLEngineering Data Analytics with Presto and Apache Parquet at UberJuly 11, 2017 / Global From determining the most convenient rider pickup points to predicting the fastest routes, Uber uses data-driven analytics to create seamless trip experiences. Within engineering, analytics inform decision-making processes across the board. As we expand to new markets, the ability to accurately and qui

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more At Uber, we combine real-time systems monitoring with intelligent alerting mechanisms to ensure the availability and reliability of our apps. In our push to empower our engineers to author more accurate alerts, Uber’s Observability Applications team sought to introduce

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more Last October, Uber’s Mobile Engineering team kicked off an effort to improve app performance, and we’ve made great progress so far with speedups of well over 50 percent for some of our key transitions. Early on, we learned that certain classes of performance issues are

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more Location and navigation using global positioning systems (GPS) is deeply embedded in our daily lives, and is particularly crucial to Uber’s services. To orchestrate quick, efficient pickups, our GPS technologies need to know the locations of matched riders and drivers,

EngineeringScaling Uber’s Apache Hadoop Distributed File System for GrowthApril 5, 2018 / Global Three years ago, Uber Engineering adopted Hadoop as the storage (HDFS) and compute (YARN) infrastructure for our organization’s big data analysis. This analysis powers our services and enables the delivery of more seamless and reliable user experiences. We use Hadoop for both batch and streaming analyt

You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more Over the past few decades, the advent of online commerce negatively impacted brick-and-mortar stores, but now the pendulum is swinging back. With millennials seeking more real-world experiences, some companies have evolved how they reach out to consumers in public space

EngineeringIntroducing QALM, Uber’s QoS Load Management FrameworkMarch 22, 2018 / Global Much of Uber’s business involves connecting people with people, making the reliability of our customer platform crucial to our success. The customer platform supports everything from ridesharing and Uber Eats, to Uber Freight and Uber for Business. Our platform team owns four services with thousands of hosts,

Denial By DNS: Uber’s Open Source Tool for Preventing Resource Exhaustion by DNS Outages In June 2016, an unresponsive third-party Domain Name System (DNS) server caused an outage of a legacy login service, affecting riders and drivers trying to access the Uber app. While the issue was mitigated in minutes, discovering why this happened was far more challenging. As part of Uber’s commitment to arc