Tag: Uber Engineering
Uber's Mobile Engineering team open sources Nanoscope, a new method tracing tool for Android that enables developers to more accurately debug difficult performance issues.
Uber’s Sensing, Inference, and Research team released a software upgrade for GPS on Android phones that significantly improves location accuracy in urban environments.
Uber's Data Infrastructure team overhauled our approach to scaling our storage infrastructure by incorporating several new features and functionalities, including ViewFs, NameNode garbage collection tuning, and an HDFS load management service.
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.
Uber AI Labs introduces Visual Inspector for Neuroevolution (VINE), an open source interactive data visualization tool to help neuroevolution researchers better understand this family of algorithms.
Brought to the US when he was 10 years old, DACA gave Benito Sanchez the security to go to college and get a job in technology.
Written in Haskell, Queryparser is Uber Engineering's open source tool for parsing and analyzing SQL queries that makes it easy to identify foreign-key relationships in large data warehouses.
What do Site Reliability Engineering (SRE) and mentorship have in common? According to Uber SRE manager Sumbry, both areas focus on growth.
Migrating our Schemaless sharding layer from Python to Go while in production demonstrated that it was possible for us to rewrite the frontend of a massive datastore with zero downtime.
The Uber Insurance Engineering team extended Kafka’s role in our existing event-driven architecture by using non-blocking request reprocessing and dead letter queues (DLQ) to achieve decoupled, observable error-handling without disrupting real-time traffic.
Uber Engineering extended our anomaly detection platform's ability to integrate new forecast models, allowing this critical on-call service to scale to meet more complex use cases.
Uber Engineering created Omphalos, our new backtesting framework, to enable efficient and reliable comparison of forecasting models across languages.
To mark the two-year anniversary of Uber Eats, Android engineer Hilary Karls discusses how her team's commitment to "playing the perfect game" resulted in one of Uber’s most successful products.
How do you overcome imposter syndrome? Act with confidence, follow your first instinct, and always be learning and teaching.
In this article, Uber Engineering introduces our Customer Obsession Ticket Assistant (COTA), a new tool that puts machine learning and natural language processing models in the service of customer care to help agents deliver improved support experiences.