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Auto-Diagnosis and Remediation in Netflix Data Platform

By Vikram Srivastava and Marcelo MaywormNetflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. As our subscribers grow worldwide and Netflix enters the world of gaming, the number of batch workflows and real-time data pipelines increases rapidly. The data platform...

Experimentation is a major focus of Data Science across Netflix

Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, Colin McFarland, Andy Rhines, Sophia Liu, Mihir Tendulkar, Kevin Mercurio, Veronica Hannan, Ting-Po LeeEarlier posts in this series covered the basics of A/B tests (Part 1 and Part 2 ), core statistical concepts (Part 3 and Part 4), and how to build confidence in decisions based on A/B...

Snaring the Bad Folks

Project by Netflix’s Cloud Infrastructure Security team (Alex Bainbridge, Mike Grima, Nick Siow)Cloud security is a hard problem, but an even harder one is cloud security at scale. In recent years we’ve seen several cloud focused data breaches and evidence shows that threat actors are becoming more advanced with their techniques, goals, and tooling....

Building confidence in a decision

Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, Michael Lindon, and Colin McFarlandThis is the fifth post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. Need to catch up? Have a look at Part 1 (Decision Making at Netflix), Part 2 (What is an A/B Test?), Part 3 (False...

Bringing AV1 Streaming to Netflix Members’ TVs

by Liwei Guo, Ashwin Kumar Gopi Valliammal, Raymond Tam, Chris Pham, Agata Opalach, Weibo NiAV1 is the first high-efficiency video codec format with a royalty-free license from Alliance of Open Media (AOMedia), made possible by wide-ranging industry commitment of expertise and resources. Netflix is proud to be a founding member of AOMedia and a key...

Netflix Video Quality at Scale with Cosmos Microservices

by Christos G. Bampis, Chao Chen, Anush K. Moorthy and Zhi LiIntroductionMeasuring video quality at scale is an essential component of the Netflix streaming pipeline. Perceptual quality measurements are used to drive video encoding optimizations, perform video codec comparisons, carry out A/B testing and optimize streaming QoE decisions to mention a...

Data Engineers of Netflix — Interview with Pallavi Phadnis

Data Engineers of Netflix — Interview with Pallavi PhadnisThis post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix.Pallavi Phadnis is a Senior Software Engineer at Netflix.Pallavi Phadnis is a Senior Software Engineer on the Product Data Science and Engineering...

Open-Sourcing a Monitoring GUI for Metaflow

Open-Sourcing a Monitoring GUI for Metaflow, Netflix’s ML Platformtl;dr Today, we are open-sourcing a long-awaited GUI for Metaflow. The Metaflow GUI allows data scientists to monitor their workflows in real-time, track experiments, and see detailed logs and results for every executed task. The GUI can be extended with plugins, allowing the community...

Interpreting A/B test results: false negatives and power

Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, and Colin McFarlandThis is the fourth post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. Need to catch up? Have a look at Part 1 (Decision Making at Netflix), Part 2 (What is an A/B Test?), Part 3 (False positives and...

Revisiting BetterTLS: Certificate Path Building

By Ian HakenLast year the AddTrust root certificate expired and lots of clients had a bad time. Some Roku devices weren’t working right, Heroku had problems, and some folks couldn’t even curl. In the aftermath Ryan Sleevi wrote a really great blog post not just about the issue of this one certificate’s expiry, but the problem that so many TLS implementations...

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