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Netflix at AWS re:Invent 2019

The Netflix TechBlog

1pm-2pm NFX 207 Benchmarking stateful services in the cloud Vinay Chella , Data Platform Engineering Manager Abstract : AWS cloud services make it possible to achieve millions of operations per second in a scalable fashion across multiple regions. We explore all the systems necessary to make and stream content from Netflix.

AWS 100
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

1pm-2pm NFX 207 Benchmarking stateful services in the cloud Vinay Chella , Data Platform Engineering Manager Abstract : AWS cloud services make it possible to achieve millions of operations per second in a scalable fashion across multiple regions. We explore all the systems necessary to make and stream content from Netflix.

AWS 100
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Friends don't let friends build data pipelines

Abhishek Tiwari

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
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

This talk explores the journey, learnings, and improvements to performance analysis, efficiency, reliability, and security. Netflix runs dozens of stateful services on AWS under strict sub-millisecond tail-latency requirements, which brings unique challenges. In 2019, Netflix moved thousands of container hosts to bare metal.

AWS 37
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Optimizing data warehouse storage

The Netflix TechBlog

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 203
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5 data integration trends that will define the future of ETL in 2018

Abhishek Tiwari

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.