Uber Engineering Blog
- Automating Efficiency of Go programs with Profile-Guided Optimizations
- Adopting Arm at Scale: Transitioning to a Multi-Architecture Environment
- Adopting Arm at Scale: Bootstrapping Infrastructure
- MySQL At Uber
- How Uber Uses Ray® to Optimize the Rides Business
- Serving Millions of Apache Pinot™ Queries with Neutrino
- Introducing the Prompt Engineering Toolkit
- The Accounter: Scaling Operational Throughput on Uber’s Stateful Platform
- Unified Checkout: Streamlining Uber’s Payment Ecosystem
- Presto® Express: Speeding up Query Processing with Minimal Resources
- Enabling Infinite Retention for Upsert Tables in Apache Pinot
- Streamlining Financial Precision: Uber’s Advanced Settlement Accounting System
- Open Source and In-House: How Uber Optimizes LLM Training
- Genie: Uber’s Gen AI On-Call Copilot
- Making Uber’s ExperimentEvaluation Engine 100x Faster
- Preon: Presto Query Analysis for Intelligent and Efficient Analytics
- How to Measure Design System at Scale
- QueryGPT – Natural Language to SQL Using Generative AI
- Transforming Executive Travel: Delegate Booking with Uber
- DataMesh: How Uber laid the foundations for the data lake cloud migration
- Lucene: Uber’s Search Platform Version Upgrade
- Pinot for Low-Latency Offline Table Analytics
- Continuous deployment for large monorepos
- Shifting E2E Testing Left at Uber
- Sparkle: Standardizing Modular ETL at Uber
- Upgrading Uber’s MySQL Fleet to version 8.0
- Differential Backups in MyRocks Based Distributed Databases at Uber
- Differential Backups in MyRocks Based Distributed Databases at Uber
- Differential Backups in MyRocks Based Distributed Databases at Uber
- Enabling Security for Hadoop Data Lake on Google Cloud Storage
- Pickup in 3 minutes: Uber’s implementation of Live Activity on iOS
- Odin: Uber’s Stateful Platform
- Navigating the LLM Landscape: Uber’s Innovation with GenAI Gateway
- Introduction to Kafka Tiered Storage at Uber
- Modernizing Logging at Uber with CLP (Part II)
- How Uber ensures Apache Cassandra®’s tolerance for single-zone failure
- Debugging with production neighbors – Powered by SLATE
- Personalized Marketing at Scale: Uber’s Out-of-App Recommendation System
- Flaky Tests Overhaul at Uber
- Modernizing Uber’s Batch Data Infrastructure with Google Cloud Platform
- Uber Becomes Kotlin™ Foundation Silver Member
- How Uber Accomplishes Job Counting At Scale
- Upgrading M3DB from v1.1 to v1.5
- DataK9: Auto-categorizing an exabyte of data at field level through AI/ML
- From Predictive to Generative – How Michelangelo Accelerates Uber’s AI Journey
- DragonCrawl: Generative AI for High-Quality Mobile Testing
- Ensuring Precision and Integrity: A Deep Dive into Uber’s Accounting Data Testing Strategies
- Migrating a Trillion Entries of Uber’s Ledger Data from DynamoDB to LedgerStore
- How LedgerStore Supports Trillions of Indexes at Uber
- Scaling AI/ML Infrastructure at Uber
- Model Excellence Scores: A Framework for Enhancing the Quality of Machine Learning Systems at Scale
- Balancing HDFS DataNodes in the Uber DataLake
- Load Balancing: Handling Heterogeneous Hardware
- Network IDS Ruleset Management with Aristotle v2
- Building Scalable, Real-Time Chat to Improve Customer Experience
- How Uber Serves Over 40 Million Reads Per Second from Online Storage Using an Integrated Cache
- Jupiter: Config Driven Adtech Batch Ingestion Platform