42 posts
Modeling Device Capabilities for Analytics -- Listen Share by Aarti Laddha, Richard Diaz-Cool, Rishika Idnani, Venkatesh Selveraj Netflix supports a vast and evolving set of features and content types, ranging from 4K streaming and immersive audio to live streaming and cloud gam…
GenRec: Towards LLM-Native Recommendation at Netflix -- 2 Listen Share Authors: Ying Li, Arjun Rao, Shradha Sehgal Introduction Recommendations sit at the heart of the Netflix experience. Our current production models rely on thousands of hand‑crafted features over users, items,…
In-House LLM Serving at Netflix -- 2 Listen Share By AI Platform’s Model Runtime team and Inference team Introduction Most organizations consume LLMs through hosted APIs. Netflix went further — we run the full stack ourselves, from model deployment through inference, inside our…
Featured Building Service Topology at Scale: Architecture, Challenges, and Lessons Learned -- Listen Share By Parth Jain, Rakesh Sukumar, Yingwu Zhao, Renzo Sanchez-Silva & Nathan FisherA deep dive into the engineering challenges of building a real-time service dependency map at…
Featured GenPage: Towards End-to-End Generative Homepage Construction at Netflix -- 6 Listen Share Authors: Lequn Wang, Jiangwei Pan, and Linas Baltrunas Introduction The Netflix homepage is the first thing users see when they open the app and the primary way they discover conte…
Toward More Controllable AI Video Editing: An Early Research Exploration at Netflix -- 5 Listen Share By Zhuoning Yuan, Ta-Ying Cheng, Benjamin Klein, Bahareh Azarnoush Introduction At Netflix, we build technology to help storytellers bring their creative visions to life and to…
How Netflix Simplified Batch Compute with Kueue -- Listen Share By Alvin Bao, Alex Petrov, Jennifer Lai, Aidan Sherr, and Samartha Chandrashekar As a part of the journey to transition Netflix’s compute infrastructure to be more Kubernetes-native, we have leaned into incorporatin…
The Data Canary: How Netflix Validates Catalog Metadata -- 1 Listen Share By Celina Amados At Netflix, our catalog metadata is crucial to our member experience, and a single corrupted data state can impact millions of viewers immediately. To protect streaming reliability, we bui…
Data Projects: Managing Data Assets at Netflix Scale By Amer Hesson, Marcelo Mayworm, James Mulcahy, and Brittany Truong -- 7 Listen Share The Problem: Managing Assets at Netflix Scale Netflix’s Data Platform is vast. We have millions of tables in our data warehouse and tens of…
Predicting Risk in Content Launches: How Data-Driven Insights can Transform Launch Planning -- Listen Share by Emily Gill Each year, we bring the Analytics Engineering community together for an Analytics Summit — a multi-day internal conference to share analytical deliverables a…
The Evolution of Cassandra Data Movement at Netflix -- 4 Listen Share By Guil Pires, Jennifer Prince, Jose Camacho, Ken Kurzweil, Phanindra Chunduru Background In a previous post, we introduced Data Bridge, a unified management plane for batch Data Movement at Netflix. Historica…
Thinking Fast & Slow for a Personalized Notification System -- 5 Listen Share by Matthew Wood, Ishan Gupta, Kevin Mercurio, Devon Bryant, and Claire Dorman In his seminal book “Thinking, Fast and Slow,” Daniel Kahneman describes two systems that drive human cognition: System 1,…
A Human-Augmenting Agentic Workflow for Causal Inference -- 8 Listen Share By Winston Chou, Adrien Alexandre, Lars Olds, Yi Zhang, Garrett Hagemann, and Nathan Kallus Introduction Imagine asking a data agent to analyze the causal relationship between two variables, such as the e…
Dynamic Repartitioning for Time Series Workloads -- Listen Share By Rajiv Shringi, Kaidan Fullerton, Oleksii Tkachuk and Kartik Sathyanarayanan Introduction Netflix’s TimeSeries Abstraction is a scalable system for ingesting and querying petabytes of temporal event data with mil…
High-Throughput Graph Abstraction at Netflix: Part I -- 3 Listen Share By Oleksii Tkachuk, Kartik Sathyanarayanan, Rajiv Shringi Introduction Netflix has a diverse range of graph use cases, each serving specific business needs with unique functionality and performance requiremen…