How Does Netflix Onboard a Movie/Video?
Netflix receives very high-quality videos and content from the production houses, so before serving the videos to the users it does some preprocessing.
- Netflix supports more than 2200 devices and each one of them requires different resolutions and formats.
- To make the videos viewable on different devices, Netflix performs transcoding or encoding, which involves finding errors and converting the original video into different formats and resolutions.
Netflix also creates file optimization for different network speeds. The quality of a video is good when you’re watching the video at high network speed. Netflix creates multiple replicas (approx 1100-1200) for the same movie with different resolutions.
These replicas require a lot of transcoding and preprocessing. Netflix breaks the original video into different smaller chunks and using parallel workers in AWS it converts these chunks into different formats (like mp4, 3gp, etc) across different resolutions (like 4k, 1080p, and more). After transcoding, once we have multiple copies of the files for the same movie, these files are transferred to each and every Open Connect server which is placed in different locations across the world.
Below is the step by step process of how Netflix ensures optimal streaming quality:
- When the user loads the Netflix app on his/her device firstly AWS instances come into the picture and handle some tasks such as login, recommendations, search, user history, the home page, billing, customer support, etc.
- After that, when the user hits the play button on a video, Netflix analyzes the network speed or connection stability, and then it figures out the best Open Connect server near to the user.
- Depending on the device and screen size, the right video format is streamed into the user’s device. While watching a video, you might have noticed that the video appears pixelated and snaps back to HD after a while.
- This happens because the application keeps checking the best streaming open connect server and switches between formats (for the best viewing experience) when it’s needed.
User data is saved in AWS such as searches, viewing, location, device, reviews, and likes, Netflix uses it to build the movie recommendation for users using the Machine learning model or Hadoop.
System Design Netflix | A Complete Architecture
Designing Netflix is a quite common question of system design rounds in interviews. In the world of streaming services, Netflix stands as a monopoly, captivating millions of viewers worldwide with its vast library of content delivered seamlessly to screens of all sizes. Behind this seemingly effortless experience lies a nicely crafted system design. In this article, we will study Netflix’s system design.
Important Topics for the Netflix System Design
- Requirements of Netflix System Design
- High-Level Design of Netflix System Design
- Microservices Architecture of Netflix
- Low Level Design of Netflix System Design
- How Does Netflix Onboard a Movie/Video?
- How Netflix balance the high traffic load
- EV Cache
- Data Processing in Netflix Using Kafka And Apache Chukwa
- Elastic Search
- Apache Spark For Movie Recommendation
- Database Design of Netflix System Design
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