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Flipr: Making Changes Quickly and Safely at Scale

Introduction Uber’s many software systems require a high volume of changes every day. Because of our systems’ size and complexity, it is a significant challenge to implement these changes without unintended consequences, ultimately slowing down developer productivity. Flipr is a … The post Flipr: Making Changes Quickly and Safely at Scale appeared...

Uber’s Journey Toward Better Data Culture From First Principles

Data powers Uber Uber has revolutionized how the world moves by powering billions of rides and deliveries connecting millions of riders, businesses, restaurants, drivers, and couriers. At the heart of this massive transportation platform is Big Data and Data Science … The post Uber’s Journey Toward Better Data Culture From First Principles appeared...

Navigating to the Technical Program Management and Learning Team

Spread across 4 continents, the Technical Strategy, Program Management, and Learning team is composed of Technical Program Managers (TPMs), Technical Writers, Technical Strategists, and Technical Training Program Managers. Uber TPMs play a critical role in executing high-impact, company-wide initiatives and … The post Navigating to the Technical...

Elastic Deep Learning with Horovod on Ray

Introduction In 2017, we introduced Horovod, an open source framework for scaling deep learning training across hundreds of GPUs in parallel.  At the time, most of the deep learning use cases at Uber were related to the research and … The post Elastic Deep Learning with Horovod on Ray appeared first on Uber Engineering Blog.

Applying Machine Learning in Internal Audit with Sparsely Labeled Data

As machine learning continues to evolve, transforming the various industries it touches, it has only begun to inform the world of audit. As a data scientist and former CPA Auditor, I can understand why this is the case. By nature, … The post Applying Machine Learning in Internal Audit with Sparsely Labeled Data appeared first on Uber Engineering Blog.

How Uber Deals with Large iOS App Size

The App Size Problem Uber’s iOS mobile Apps for Rider, Driver, and Eats are large in size. The choice of Swift as our primary programming language, our fast-paced development environment and feature additions, layered software and its dependencies, and statically … The post How Uber Deals with Large iOS App Size appeared first on Uber Engineering...

Evolving Schemaless into a Distributed SQL Database

Introduction In 2016 we published blog posts (I, II) about Schemaless – Uber Engineering’s Scalable Datastore. We went over the design of Schemaless as well as explained the reasoning behind developing it. In this post today we … The post Evolving Schemaless into a Distributed SQL Database appeared first on Uber Engineering Blog.

Fast and Reliable Schema-Agnostic Log Analytics Platform

At Uber, we provide a centralized, reliable, and interactive logging platform that empowers engineers to work quickly and confidently at scale. The logs are tagged with a rich set of contextual key value pairs, with which engineers can slice and … The post Fast and Reliable Schema-Agnostic Log Analytics Platform appeared first on Uber Engineering...

Uber’s Real-time Data Intelligence Platform At Scale: Improving Gairos Scalability/Reliability

Background Real-time data (# of ride requests, # of drivers available, weather, game) enables operations teams to make informed decisions like surge pricing, maximum dispatch ETA calculating, and demand/supply forecasting about our services that improve user experiences on the … The post Uber’s Real-time Data Intelligence Platform At Scale: Improving...

The Journey Towards Metric Standardization

At Uber, business metrics are vital for discovering insights about how we perform, gauging the impact of new products, and optimizing the decision making process. The use cases for metrics can range from an operations member diagnosing a fares issue … The post The Journey Towards Metric Standardization appeared first on Uber Engineering Blog.

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