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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Occasionally, these use cases involve terabytes of data, so we have to pay attention to performance. Instead, in the style of nanoarrow , our Fast Data library only relies on the stable Arrow C data interface , producing a hermetically sealed library with no external dependencies.

Systems 226
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

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. Wednesday?—?December The talk also includes examples of using these tools in the Amazon Elastic Compute Cloud (Amazon EC2) cloud.

AWS 100
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

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. Wednesday?—?December The talk also includes examples of using these tools in the Amazon Elastic Compute Cloud (Amazon EC2) cloud.

AWS 100
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Experimentation is a major focus of Data Science across Netflix

The Netflix TechBlog

Curious to learn about what it’s like to be a Data Engineer at Netflix? Hear directly from Samuel Setegne , Dhevi Rajendran , Kevin Wylie , and Pallavi Phadnis in our “Data Engineers of Netflix” interview series. Growth Advertising At Netflix, we want to entertain the world ! What’s the tradeoff of using those?

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Netflix at AWS re:Invent 2019

The Netflix TechBlog

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. Wednesday?—?December The talk also includes examples of using these tools in the Amazon Elastic Compute Cloud (Amazon EC2) cloud.

AWS 37
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Spice up your Analytics: Amazon QuickSight Now Generally Available in N. Virginia, Oregon, and Ireland.

All Things Distributed

Put simply, data is not always readily available and accessible to organizational end users. The data infrastructure to collect, store, and process data is geared primarily towards developers and IT professionals whereas insights need to be derived by not just technical professionals but also non-technical business users.

Analytics 152