Remove Design Remove Efficiency Remove Infrastructure Remove Video
article thumbnail

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.

article thumbnail

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.

Network 292
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

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. This is achieved by more efficiently spacing the ladder points, especially in the high-bitrate region.

article thumbnail

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.

Media 171
article thumbnail

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.

article thumbnail

Scaling Media Machine Learning at Netflix

The Netflix TechBlog

We have been leveraging machine learning (ML) models to personalize artwork and to help our creatives create promotional content efficiently. Our goal in building a media-focused ML infrastructure is to reduce the time from ideation to productization for our media ML practitioners.

Media 290
article thumbnail

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

Dynatrace

Hybrid cloud infrastructure explained: Weighing the pros, cons, and complexities – blog While hybrid cloud infrastructure increases flexibility, it also introduces complexity. Observability is critical for monitoring application performance, infrastructure, and user behavior within hybrid, microservices-based environments.