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To improve search and recommendation user experiences, Uber migrated from Apache Lucene to Amazon OpenSearch to support large-scale vector search and better capture search intent. This transition introduced several infrastructure challenges, which Uber engineers addressed with targeted solutions.
Uber’s Ceilometer framework automates infrastructure performance benchmarking beyond applications. It standardizes testing across servers, workloads, and cloud SKUs, helping teams validate changes, identify regressions, and optimize resources. Future plans include AI integration, anomaly detection, and continuous validation.
Beth Anderson discusses the "power distance index" and its critical role in communication. Using the Korean Air Flight 801 tragedy as a case study, she explains the dangers of hierarchy-driven silence. She shares actionable frameworks for building the 4 stages of psychological safety, implementing reverse mentoring, and using PRs as tools for knowledge sharing rather than gatekeeping.
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Gilad Shoham about building effective mentorship relationships, leading fully distributed teams and the evolving role of developers in an AI-augmented future.
Spotify has introduced the Experiments with Learning (EwL) metric on top of its Confidence experimentation platform to measure how many tests deliver decision-ready insights, not just how many “win.” EwL captures both the quantity and quality of learning across product teams, helping them make faster, smarter product decisions at scale. The outcome must support one action: ship, abort, or iterate.
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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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Uber Adopts Amazon OpenSearch for Semantic Search to Better Capture User Intent
To improve search and recommendation user experiences, Uber migrated from Apache Lucene to Amazon OpenSearch to support large-scale vector search and better capture search intent. This transition introduced several infrastructure challenges, which Uber engineers addressed with targeted solutions.
By Sergio De SimoneBenchmarking Beyond the Application Layer: How Uber Evaluates Infrastructure Changes and Cloud Skus
Uber’s Ceilometer framework automates infrastructure performance benchmarking beyond applications. It standardizes testing across servers, workloads, and cloud SKUs, helping teams validate changes, identify regressions, and optimize resources. Future plans include AI integration, anomaly detection, and continuous validation.
By Leela KumiliPresentation: Changing Power Dynamics: What Senior Engineers Can Learn From Junior Engineers
Beth Anderson discusses the "power distance index" and its critical role in communication. Using the Korean Air Flight 801 tragedy as a case study, she explains the dangers of hierarchy-driven silence. She shares actionable frameworks for building the 4 stages of psychological safety, implementing reverse mentoring, and using PRs as tools for knowledge sharing rather than gatekeeping.
By Beth AndersonPodcast: Effective Mentorship and Remote Team Culture with Gilad Shoham
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Gilad Shoham about building effective mentorship relationships, leading fully distributed teams and the evolving role of developers in an AI-augmented future.
By Gilad ShohamBeyond Win Rates: How Spotify Quantifies Learning in Product Experiments
Spotify has introduced the Experiments with Learning (EwL) metric on top of its Confidence experimentation platform to measure how many tests deliver decision-ready insights, not just how many “win.” EwL captures both the quantity and quality of learning across product teams, helping them make faster, smarter product decisions at scale. The outcome must support one action: ship, abort, or iterate.
By Olimpiu Pop