Tag: Anomaly Detection
Uber’s Observability Applications team overhauled our anomaly detection platform’s workflow to enable the intuitive and performant backfilling of forecasts, paving the way for more intelligent alerting.
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.
In this article, we highlight how Uber leverages machine learning and artificial intelligence to tackle engineering challenges at scale.
Recurrent neural networks equip Uber Engineering's new forecasting model to more accurately predict rider demand during extreme events.
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.
Uber’s mission is transportation as reliable as running water, everywhere, for everyone. Here's the first of a two-part series on the tech stack that Uber Engineering uses to make this happen.
Uber’s mission is transportation as reliable as running water, for everyone, everywhere. This past month, Uber Engineering talked about what it takes to get site reliability engineering right.
Identifying Outages with Argos, Uber Engineering’s Real-Time Monitoring and Root-Cause Exploration Tool
The story of Argos: How Uber Engineering provides highly accurate, real-time alerts on millions of system and business metrics in Uber's fast-paced environment.