2025-06-17 –, Palais Atelier
Search is integral to Uber's core business and user experience. In this talk, we’ll explore the unique challenges of Search at Uber and chart the evolution of Uber’s Search Platform—from leveraging Elasticsearch to developing an in-house solution, and finally, innovating in collaboration with the OpenSearch community.
Search powers critical functionality across all Uber products, including product discovery in the Uber Eats app, seamless pickup and drop-off experiences in Uber Rides, and real-time geospatial matching for drivers and riders. However, this comes with unique technical challenges such as real-time updates, geospatial awareness, and semantic search at scale.
Over the years, Uber’s Search Platform has undergone significant transformation:
- Initially built entirely on Elasticsearch, we faced challenges related to scalability and feature limitations.
- To address these, Uber developed a custom, in-house solution tailored to meet our unique needs.
- Recognizing the importance of open standards and community-driven innovation, we later embraced OpenSearch, collaborating with its vibrant community to contribute enhancements and ensure long-term sustainability.
In this talk, we will discuss:
- The unique technical requirements of Search at Uber.
- The architectural evolution of our platform in response to business growth and new challenges.
- The strategic shift toward collaborating with the open-source ecosystem to foster innovation and scalability.
Search, Scale, People & Community
Level:Intermediate
Yupeng Fu is a Principal Engineer in the Platform Engineering organization at Uber. He leads the Search and Real-time Data Platforms. Yupeng is also an active contributor to open-source projects. He is an OpenSearch TSC member and Apache Pinot PMC.