Remove Infrastructure Remove Traffic Remove Video
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How To Implement Video Information and Editing APIs in Java

DZone

In the past 15+ years, online video traffic has experienced a dramatic boom utterly unmatched by any other form of content. It must be said that this video traffic phenomenon primarily owes itself to modernizations in the scalability of streaming infrastructure, which simply weren’t present fifteen years ago.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. To that end, the Video and Image Encoding team in Encoding Technologies (ET) has spent the last few years rebuilding the video processing pipeline on our next-generation microservice-based computing platform Cosmos.

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All of Netflix’s HDR video streaming is now dynamically optimized

The Netflix TechBlog

by Aditya Mavlankar , Zhi Li , Lukáš Krasula and Christos Bampis High dynamic range ( HDR ) video brings a wider range of luminance and a wider gamut of colors, paving the way for a stunning viewing experience. 1) depicts the migration of traffic from fixed bitrates to DO encodes. By June 2023 the entire HDR catalog was optimized.

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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 how long it takes for the video to start playing), rebuffer rates, etc.,

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Netflix Video Quality at Scale with Cosmos Microservices

The Netflix TechBlog

Moorthy and Zhi Li Introduction Measuring 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 few.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Investigating a video streaming failure consists of inspecting all aspects of a member account. Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. which is difficult when troubleshooting distributed systems.

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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

We could also swap out the implementation of a field from GraphQL Shim to Video API with federation directives. The control group’s traffic utilized the legacy Falcor stack, while the experiment population leveraged the new GraphQL client and was directed to the GraphQL Shim. How does it work?

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