Customer Stories / Media & Entertainment

2019

More Data Science with Less Engineering: ML Infrastructure at Netflix

In this Amazon Web Services (AWS) re:Invent session, Netflix shares its human-centric design principles that provides its engineers with autonomy. Learn how Netflix developed an end-to-end machine learning (ML) infrastructure, Metaflow, using elastic compute, high-throughput storage, and dynamic, scalable notebooks built on AWS using Amazon Simple Storage Service (Amazon S3), Amazon SageMaker, AWS Batch, and Amazon Relational Database Service (Amazon RDS).

AWS Services Used

Amazon S3

Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance.

Amazon SageMaker

Build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows

AWS Batch

AWS Batch lets developers, scientists, and engineers efficiently run hundreds of thousands of batch and ML computing jobs while optimizing compute resources, so you can focus on analyzing results and solving problems.

Amazon RDS

Amazon Relational Database Service (Amazon RDS) is a collection of managed services that makes it simple to set up, operate, and scale databases in the cloud.

Explore Netflix's journey of innovation using AWS

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United States

Global Production ft. Netflix

In this keynote presentation at SIGGRAPH 2021, Laura Teclamariam, director of product and animation at Netflix, and Rahul Dani, director of studio engineering at Netflix, discuss how content production today is truly global and what that means for storytellers.

2020
United States

Designing better ML systems: Learnings from Netflix

In 2019, Netflix open-sourced Metaflow, its human-centric ML platform. In this session, Netflix shares some lessons learned in its multi-year journey building the ML systems that Metaflow incorporates, covering a diverse range of scale from one-time experimentation on laptops to large-scale model training and serving systems on AWS.

2020
United States

Simplifying Delivery as Code with Spinnaker and Kubernetes

In this session, Netflix shares some lessons learned in its multi-year journey building the ML systems that Metaflow incorporates, covering a diverse range of scale from one-time experimentation on laptops to large-scale model training and serving systems on AWS.

2020
United States

Create from Anywhere: The Netflix Workstations Story

In this re:Invent 2022 session, learn how Netflix used AWS services such as NICE DCV, Amazon Elastic Compute Cloud (Amazon EC2) G4 instances, and also the open source continuous delivery platform, Spinnaker, developed by Netflix as its workstation solution.

2022

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