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The Lifecycle of LLM-as-a-Judge: Building, Aligning, and Monitoring at scale
By Emma Yanyang Kong, JJ Tan, Ishan Gupta, Lars Olds, Claire Campbell, David Fagnan, Ratna Kavuri, Rohan Gosain, Veli Balin, Minsu Jang, Louis Garcia ### Introduction Any team generating text with an LLM at scale hits t…
Trading a Cloud Identity for Your Own: Workload Attestation on Managed Compute
By Dhruv Pratap Introduction Organizations that have been around for a while usually run two identity systems side by side. One belongs to the cloud provider: IAM roles, instance profiles, execution roles. The other is …
29 分钟 · Netflix TechBlog
Leave the Class Path in the Rearview Mirror
Introducing composable, module system native and agent friendly command line tools for modern Java development By Danny Thomas, JVM Ecosystem Team Recent work on the Java language to pave the on-ramp has made it easier …
19 分钟 · Netflix TechBlogLATEST STORIES
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MAPS: Netflix’s Multimodal Asset Personalization at Scale精选导读
By Emma Yanyang Kong, Aditya Deshpande, Asad Abbasi, Bowei Yan, David Fagnan, Ashish Rastogi, Dhaval Patel, Ray Zhang Introduction The Netflix experience is a journey of discovery. Every visual cue, from the artwork on …
A Tale of Two Flink Autoscalers精选导读
Samuel Yeboah, Francesco Di Chiara and Mingliang Liu Today, Netflix runs two Flink autoscalers. That is exactly one more than we want. We built the first one in-house years ago, when there was no mature option suited to…
How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC…精选导读
How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC execution API Authors: Nilesh Mishra and Ajit Koti This is the third entry of a multi-part blog series describing how we bui…
Modeling Device Capabilities for Analytics精选导读
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 ga…
GenRec: Towards LLM-Native Recommendation at Netflix精选导读
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, and intera…
In-House LLM Serving at Netflix精选导读
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, i…
Building Service Topology at Scale: Architecture, Challenges, and Lessons Learned精选导读
By Parth Jain, Rakesh Sukumar, Yingwu Zhao, Renzo Sanchez-Silva & Nathan Fisher A deep dive into the engineering challenges of building a real-time service dependency map at Netflix scale: from streaming architectures a…