Customer Stories / Media & Entertainment
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.
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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. -
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. -
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. -
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.
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