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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. This architecture shift greatly reduced the processing latency and increased system resiliency. Reloaded was well-architected, providing good stability, scalability, and a reasonable level of flexibility.

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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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Stuff The Internet Says On Scalability For December 7th, 2018

High Scalability

It's HighScalability time: This is your 1500ms latency in real life situations - pic.twitter.com/guot8khIPX. Know anyone looking for a simple book explaining the cloud? book: Explain the Cloud Like I'm 10. — Ivo Mägi (@ivomagi) November 27, 2018. Do you like this sort of Stuff? Please support me on Patreon.

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The Netflix Cosmos Platform

The Netflix TechBlog

It supports both high throughput services that consume hundreds of thousands of CPUs at a time, and latency-sensitive workloads where humans are waiting for the results of a computation. The third generation, called Reloaded , has been online for about seven years and has proven to be stable and massively scalable. debian packages).

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Designing Instagram

High Scalability

Generating machine learning based personalized recommendations to discover new people, photos, videos, and stories relevant one’s interest. When a user requests for feed then there will be two parallel threads involved in fetching the user feeds to optimize for latency. Users should be able to like and comment the posts.

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What is real user monitoring (RUM)?

Dynatrace

However, only highly scalable real user monitoring solutions can collect data on all user actions, while less scalable tools have to sample user actions and make inferences from partial data. Providing insight into the service latency to help developers identify poorly performing code. How real user monitoring works.

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Evolution of ML Fact Store

The Netflix TechBlog

Figure 1: Netflix ML Architecture Fact: A fact is data about our members or videos. An example of data about members is the video they had watched or added to their My List. An example of video data is video metadata, like the length of a video. We needed scalability testing and performance testing as well.

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