InfoQ Homepage Uber Content on InfoQ
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Optimizing Uber's Search Infrastructure: Upgrading to Apache Lucene 9.5
Uber Engineering recently announced an upgrade to their search infrastructure, transitioning from Apache Lucene 8.0 to version 9.5. This upgrade improves Uber's search capabilities, performance and efficiency across their various services.
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RAG-Powered Copilot Saves Uber 13,000 Engineering Hours
Uber recently detailed how it built Genie, an AI-powered on-call copilot designed to improve the efficiency of on-call support engineers. Genie leverages Retrieval-Augmented Generation (RAG) to provide accurate real-time responses and significantly enhance the speed and effectiveness of incident response. Since its launch, Genie has answered over 70,000 questions, saving 13,000 engineering hours.
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Uber Completes Major MySQL Fleet Upgrade, Boosting Performance and Security
Uber has detailed improvements to its MySQL database fleet by upgrading from version 5.7 to 8.0. The team wanted to take advantage of performance and concurrency improvements in newer versions of MySQL, and because MySQL 5.7 was reaching end-of-life in October 2023. The work took over a year and involved upgrading more than 2,100 clusters and 16,000 nodes across 19 production zones in 3 regions.
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Uber Drives Apache Kafka's Tiered Storage Feature; Sparks Efficiency Debate
Apache Kafka, the popular distributed event streaming platform, has introduced a new tiered storage feature in version 3.6.0, initially proposed by Uber engineers. This feature, currently in early access, aims to address the scalability and efficiency challenges faced by organizations running large Kafka clusters.
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Uber's CacheFront: Powering 40M Reads per Second with Significantly Reduced Latency
Uber developed an innovative caching solution, CacheFront, for its in-house distributed database, Docstore. CacheFront enables over 40M reads per second from online storage and achieves substantial performance improvements, including a 75% reduction in P75 latency and over 67% reduction in P99.9 latency, demonstrating its effectiveness in enhancing system efficiency and scalability.
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Uber Improves Productivity with Remote Development Environment Devpod
Engineers at Uber created their own remote development environment to improve developer experience and productivity by fixing a number of issues brought about by their adoption of a code monorepo.
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Uber Reduces Logging Costs by 169x Using Compressed Log Processor (CLP)
Uber recently published how it dramatically reduced its logging costs using Compressed Log Processor (CLP). CLP is a tool capable of losslessly compressing text logs and searching them without decompression. It achieved a 169x compression ratio on Uber's log data, saving storage, memory, and disk/network bandwidth.
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Multi-Factor Authentication Fatigue Key Factor in Uber Breach
Earlier this week, Uber disclosed that the recent breach it suffered was made possible through a multi-factor authentication (MFA) fatigue attack where the attacker disguised themselves as Uber IT.
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Uber Open-Sourced Its Highly Scalable and Reliable Shuffle as a Service for Apache Spark
Uber engineering has recently open-sourced its highly scalable and reliable shuffle as a service for Apache Spark. Spark is one of the most important tools and platforms in data engineering and analytics. It is shuffling data on local machines by default and causes challenges while the scale is getting very large. Shuffle as a service is a solution developed at Uber for this problem.
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Uber Introduces a Universal Signup and Login Stack
Uber recently introduced Unified Signup and Login (USL), an effort to consolidate signup and login experiences across all Uber apps and services. USL lowers the engineering complexity and maintenance overhead and allows faster rollout of security policies and fixes. Over the last two years, Uber rolled out USL and currently, more than 78% of Uber's traffic has adopted USL.
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Data Collection, Standardization and Usage at Scale in the Uber Rider App
Uber Engineering recently published how it collects, standardises and uses data from the Uber Rider app. Rider data comprises all the rider's interactions with the Uber app. This data accounts for billions of events from Uber's online systems every day. Uber uses this data to deal with top problem areas such as increasing funnel conversion, user engagement, etc.
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Uber Re-Architected Its Foundational Fulfilment Service
Uber recently shared how it re-architected its fulfilment service, one of Uber's foundational platform services. Following a two-year-long effort involving 30+ teams and hundreds of developers, Uber engineers "built a strong foundation for modelling various types of physical fulfilment categories in the new platform and migrated all existing transportation use cases."
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InfoQ Live July 20th: Software Supply Chain for DevOps & Reducing Feature Flag Debt
How can modern DevOps practices accelerate your software delivery without the quality issues? Learn how automation, continuous testing, and supply management techniques can improve software quality and speed of delivery. Get valuable insights from world-class domain experts at InfoQ Live on July 20th.
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Uber Implements Disaster Recovery for Multi-Region Kafka
In a recent blog post, Uber engineers highlight how they use a replication platform to implement disaster recovery at scale with a multi-region Kafka deployment. Uber has a large deployment of Apache Kafka, processing trillions of messages and multiple petabytes of data per day. Uber's engineers provided business resilience and continuity in the face of natural and human-made disasters.
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Safe and Fast Deploys at Planet Scale: QCon Plus Q&A
Uber has automated the deployment of services using a hybrid cloud model. All services are deployed using the same rollout techniques and workflows, ensuring safe deployment and mitigation of any issues. Abstracting away the differences between clouds supports engineers in building services that run on any platform.