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Improving our video encodes for legacy devices

The Netflix TechBlog

by Mariana Afonso , Anush Moorthy , Liwei Guo , Lishan Zhu , Anne Aaron Netflix has been one of the pioneers of streaming video-on-demand content?—?we we announced our intention to stream video over 13 years ago, in January 2007?—?and and thus fall back to less efficient encode families. 264/AVC Main profile family.

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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

This allows the app to query a list of “paths” in each HTTP request, and get specially formatted JSON (jsonGraph) that we use to cache the data and hydrate the UI. In the snippet above, we’re accessing the detail key for the video object with id 80154610. Instead, it is part of a different path : [videos, <id>, similars].

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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

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ML Platform Meetup: Infra for Contextual Bandits and Reinforcement Learning

The Netflix TechBlog

In this talk, Kinjal used the example of the LinkedIn Feed, to demonstrate how they use bandit algorithms to solve for the optimal parameter selection problem efficiently. He concluded by stressing the efficiency their teams had achieved by doing online parameter exploration instead of the much slower human-in-the-loop manual explorations.

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ML Platform Meetup: Infra for Contextual Bandits and Reinforcement Learning

The Netflix TechBlog

In this talk, Kinjal used the example of the LinkedIn Feed, to demonstrate how they use bandit algorithms to solve for the optimal parameter selection problem efficiently. He concluded by stressing the efficiency their teams had achieved by doing online parameter exploration instead of the much slower human-in-the-loop manual explorations.

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Introducing Netflix TimeSeries Data Abstraction Layer

The Netflix TechBlog

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

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Optimizing Video Streaming CDN Architecture for Cost Reduction and Enhanced Streaming Performance

IO River

Now, with viewers all over the world expecting flawless and high-definition streaming, video providers have their work cut out for them. What Comprises Video Streaming - Traffic CharacteristicsWith the emphasis on a high-quality streaming experience, the optimization starts from the very core. Only overflow will await you.