The Netflix TechBlog

MARCH 7, 2024

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226

Systems Media Cache Open Source 226

The Netflix TechBlog

NOVEMBER 22, 2019

Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Netflix runs dozens of stateful services on AWS under strict sub-millisecond tail-latency requirements, which brings unique challenges. Wednesday?—?December

AWS 100

AWS Entertainment Open Source Benchmarking 100

The Netflix TechBlog

NOVEMBER 22, 2019

Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Netflix runs dozens of stateful services on AWS under strict sub-millisecond tail-latency requirements, which brings unique challenges. Wednesday?—?December

AWS 100

AWS Entertainment Open Source Benchmarking 100

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Latency 63

Latency Analytics Scalability Engineering 63

The Netflix TechBlog

NOVEMBER 22, 2019

Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Netflix runs dozens of stateful services on AWS under strict sub-millisecond tail-latency requirements, which brings unique challenges. Wednesday?—?December

AWS 37

AWS Entertainment Open Source Benchmarking 37

The Netflix TechBlog

DECEMBER 21, 2020

Some of the optimizations are prerequisites for a high-performance data warehouse. Sometimes Data Engineers write downstream ETLs on ingested data to optimize the data/metadata layouts to make other ETL processes cheaper and faster. Both automatic (event-driven) as well as manual (ad-hoc) optimization.

Storage 203

Storage Latency Efficiency Data Engineering 203