Dynamically Splitting Wide Partitions in Cassandra for Time Series Workloads
By Rajiv Shringi, Kaidan Fullerton, Oleksii Tkachuk and Kartik SathyanarayananIntroductionNetflix’s TimeSeries Abstraction is a scalable system for ingesting and querying petabytes of temporal event data with millisecond latency. We use Apache Cassandra 4.x as the underlying storage for these main r...
By Rajiv Shringi, Kaidan Fullerton, Oleksii Tkachuk and Kartik SathyanarayananIntroductionNetflix’s TimeSeries Abstraction is a scalable system for ingesting and querying petabytes of temporal event data with millisecond latency. We use Apache Cassandra 4.x as the underlying storage for these main r...
From Silos to Service Topology: Why Netflix Built a Real-Time Service Map
By Parth Jain, Rakesh Sukumar, Yingwu Zhao, Renzo Sanchez & Nathan FisherHow we built a living map of our distributed infrastructure to help engineers understand dependencies, troubleshoot faster, and keep Netflix running smoothly for our members around the world.The Puzzle with a Thousand PiecesPic...
Synchronizing the Senses: Powering Multimodal Intelligence for Video SearchBy: Meenakshi Jindal and Munya MarazanyeToday’s filmmakers capture more footage than ever to maximize their creative options, often generating hundreds, if not thousands, of hours of raw material per season or franchise. Extr...
AV1 — Now Powering 30% of Netflix StreamingLiwei Guo, Zhi Li, Sheldon Radford, Jeff WattsStreaming video has become an integral part of our daily lives. At Netflix, our top priority is delivering the best possible entertainment experience to our members, regardless of their devices or network condit...
Post-Training Generative Recommenders with Advantage-Weighted Supervised Finetuning
Author: Keertana Chidambaram, Qiuling Xu, Ko-Jen Hsiao, Moumita Bhattacharya(*The work was done when Keertana interned at Netflix.)IntroductionThis blog focuses on post-training generative recommender systems. Generative recommenders (GRs) represent a new paradigm in the field of recommendation syst...