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Engineering, Backend

Ceilometer: Uber’s Adaptive Benchmarking Framework

Dig into Ceilometer, Uber’s adaptive benchmarking framework for ensuring system performance and reliability at scale. Learn how it automates performance testing while providing production-like insights and continuous validation.

November 20 / Global

Engineering, Data / ML, Uber AI

Enhancing Uber’s Guidance Heatmap with Deep Probabilistic Models

November 18 / Global

Case study: How Bloomington Transit broadens reach without breaking the budget

November 13 / Global

Backend, Data / ML, Engineering, Uber AI

I/O Observability for Uber’s Massive Petabyte-Scale Data Lake

November 13 / Global

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Data / ML, Engineering

Building Zone Failure Resilience in Apache Pinot™ at Uber

November 6 / Global

Raising the Bar on ML Model Deployment Safety

October 30 / Global

Engineering, Data / ML

Enabling Deep Model Explainability with Integrated Gradients at Uber

October 23 / Global

Higher Education

Game changers: how Lafayette College balances academics and athletics with Uber

October 22 / Global

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Requirement Adherence: Boosting Data Labeling Quality Using LLMs

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Rebuilding Uber’s Apache Pinot™ Query Architecture

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Uber’s Strategy to Upgrading 2M+ Spark Jobs

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Higher Education

How the University of Illinois streamlines faculty travel with Uber

September 19 / Global

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