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
Netflix Catalogs Objects Across Hybrid Cloud Storage Systems
In this re:Invent 2022 session, learn how Netflix uses a hybrid cloud storage solution that combines Amazon Web Services (AWS) and on-premesis storage. -
United States
Netflix Operates Mission-Critical Data Stores on AWS
Learn how distributed database engineers have established tools, techniques, and approaches on Amazon Web Services (AWS) to debug and mitigate failures. -
United States
Netflix Uses Amazon FSx for Large-Scale Distributed Training of Media Machine Learning
In this AWS re:Invent 2021 session, learn about the challenges of scalable distributed training of media machine learning (ML) models on multi-GPU nodes used by Netflix. -
United States
More Data Science with Less Engineering: ML Infrastructure at Netflix
In this AWS re:Invent session, Netflix shares its human-centric design principles that provides its engineers with autonomy.
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