First introduced by Uber in November 2018, Peloton manages resources across large-scale, distinct workloads, combining separate compute clusters.
In this article, we highlight how Uber leverages machine learning and artificial intelligence to tackle engineering challenges at scale.
A daylong event at Uber’s Palo Alto office, sponsored by our LadyEng group, showcased the technical work across Uber Engineering as well as the people who are leading and building these projects. Here are some of the resulting presentations.
The details and examples of Schemaless triggers, a key feature of the datastore that’s kept Uber Engineering scaling since October 2014. This is the third installment of a three-part series on Schemaless; the first part is a design overview and the second part is a discussion of architecture.
The making of Schemaless, Uber Engineering’s custom designed datastore using MySQL, which has allowed us to scale from 2014 to beyond. This is part one of a three-part series on Schemaless.
Kate Park's Uber internship experience on the Supply Engine team. The first of a series of articles on what it's like to intern at Uber Engineering.
Here’s a look inside the world of Supply Engineering at Uber, obsessed with creating the best, most scalable earnings platform for our partners in over 330 cities.