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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. We rolled out encoding innovations such as per-title and per-shot optimizations, which provided significant quality-of-experience (QoE) improvement to Netflix members. This introductory blog focuses on an overview of our journey.

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For your eyes only: improving Netflix video quality with neural networks

The Netflix TechBlog

Bampis , Li-Heng Chen and Zhi Li When you are binge-watching the latest season of Stranger Things or Ozark, we strive to deliver the best possible video quality to your eyes. To do so, we continuously push the boundaries of streaming video quality and leverage the best video technologies.

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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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RSA guide 2024: AI and security are top concerns for organizations in every industry

Dynatrace

Tech Transforms podcast: It’s time to get familiar with generative AI – blog Generative AI can unlock boundless innovation. Hybrid cloud infrastructure explained: Weighing the pros, cons, and complexities – blog While hybrid cloud infrastructure increases flexibility, it also introduces complexity. What is generative AI?

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Ingesting JMeter, temperature and humidity metrics: A Dynatrace innovation day report

Dynatrace

In this blog, I want to give you two examples of internal innovation projects at Dynatrace which leverage this new API, to truly show you the power – and the fun-ness of this new metric ingest ??. The idea was inspired by an innovation day project of our lab in Klagenfurt. There are many use cases for using this API.

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Scaling Media Machine Learning at Netflix

The Netflix TechBlog

Our goal in building a media-focused ML infrastructure is to reduce the time from ideation to productization for our media ML practitioners. In addition, we provide a unified library that enables ML practitioners to seamlessly access video, audio, image, and various text-based assets.

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