Unified Context-Intent Embeddings for Scalable Text-to-SQL
Your Analysts Already Wrote the Perfect PromptAuthors: Keqiang Li, Bin YangIn our previous blog post, we shared how Pinterest built Text-to-SQL with RAG-based table selection (Retrieval-Augmented Generation). That system introduced schema-grounded SQL generation and retrieval-augmented table selecti...
Scaling Global Storytelling: Modernizing Localization Analytics at Netflix
Valentin Geffrier, Tanguy CornuauEach year, we bring the Analytics Engineering community together for an Analytics Summit — a multi-day internal conference to share analytical deliverables across Netflix, discuss analytic practice, and build relationships within the community. This post is one of se...
Optimizing Recommendation Systems with JDK’s Vector API
By Harshad SaneRanker is one of the largest and most complex services at Netflix. Among many things, it powers the personalized rows you see on the Netflix homepage, and runs at an enormous scale. When we looked at CPU profiles for this service, one feature kept standing out: video serendipity scori...
Mount Mayhem at Netflix: Scaling Containers on Modern CPUs
Authors: Harshad Sane, Andrew HalaneyImagine this — you click play on Netflix on a Friday night and behind the scenes hundreds of containers spring to action in a few seconds to answer your call. At Netflix, scaling containers efficiently is critical to delivering a seamless streaming experience to ...
Authors: Junkai Xue | Sr Staff Software Engineer, Big Data Processing Platform; Zheyu Zha | Staff Software Engineer, Big Data Processing Platform; Jia Zhan | Principal Engineer, Online Systems; Alberto Ordonez Pereira | Sr Staff Software Engineer, Online SystemsOverviewA quota is an official limit o...
MediaFM: The Multimodal AI Foundation for Media Understanding at Netflix
Avneesh Saluja, Santiago Castro, Bowei Yan, Ashish RastogiIntroductionNetflix’s core mission is to connect millions of members around the world with stories they’ll love. This requires not just an incredible catalog, but also a deep, machine-level understanding of every piece of content in that cata...
Baolin Li, Lingyi Liu, Binh Tang, Shaojing LiIntroductionPre-training gives Large Language Models (LLMs) broad linguistic ability and general world knowledge, but post-training is the phase that actually aligns them to concrete intents, domain constraints, and the reliability requirements of product...
Automating RDS Postgres to Aurora Postgres Migration
Ram Srivasta Kannan, Wale Akintayo, Jay Bharadwaj, John Crimmins, Shengwei Wang, Zhitaou ZhuIntroductionIn 2024, the Online Data Stores team at Netflix conducted a comprehensive review of the relational database technologies used across the company. This evaluation examined functionality, performanc...