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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

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
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

by Shefali Vyas Dalal AWS re:Invent is a couple weeks away and our engineers & leaders are thrilled to be in attendance yet again this year! Technology advancements in content creation and consumption have also increased its data footprint. We’ve compiled our speaking events below so you know what we’ve been working on.

AWS 100
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

by Shefali Vyas Dalal AWS re:Invent is a couple weeks away and our engineers & leaders are thrilled to be in attendance yet again this year! Technology advancements in content creation and consumption have also increased its data footprint. We’ve compiled our speaking events below so you know what we’ve been working on.

AWS 100
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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

the order of the rows on your Netflix home page, issuing content licenses when you click play, finding the Open Connect cache closest to you with the content you requested, and many more). All these micro-services are currently operated in AWS cloud infrastructure. Give us a holler if you are interested in a thought exchange.

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Netflix at AWS re:Invent 2019

The Netflix TechBlog

by Shefali Vyas Dalal AWS re:Invent is a couple weeks away and our engineers & leaders are thrilled to be in attendance yet again this year! Technology advancements in content creation and consumption have also increased its data footprint. We’ve compiled our speaking events below so you know what we’ve been working on.

AWS 37
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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

As Big data and ML became more prevalent and impactful, the scalability, reliability, and usability of the orchestrating ecosystem have increasingly become more important for our data scientists and the company. Another dimension of scalability to consider is the size of the workflow.

Java 202