Elastic Search
In recent years we have seen massive growth in using Elasticsearch within Netflix. Netflix is running approximately 150 clusters of elastic search and 3, 500 hosts with instances. Netflix is using elastic search for data visualization, customer support, and for some error detection in the system.
For example:
If a customer is unable to play the video then the customer care executive will resolve this issue using elastic search. The playback team goes to the elastic search and searches for the user to know why the video is not playing on the user’s device.
They get to know all the information and events happening for that particular user. They get to know what caused the error in the video stream. Elastic search is also used by the admin to keep track of some information. It is also used to keep track of resource usage and to detect signup or login problems.
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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