Designing media optimized byte transfer and storage at Netflix

Track: Cloud Technology

Abstract

Netflix is a media streaming company and a movie studio with data at exabyte scale. Most of the data generated, transferred and stored at Netflix is very media specific, for example, raw camera footage, or data generated as a result of encoding and rendering for different screen types.

In this session, I will throw light on how we design a media aware and optimized transfer, storage and presentation layer for data.

By leveraging this architecture at Netflix scale, we provide a scalable, reliable, and optimized backend layer for media data.

Major takeaways from this session
- Learn about the challenges of designing a scalable object storage layer for data while adhering to the file system POSIX semantics of media applications
- Learn about the optimizations applied to reduce cloud storage footprint, such as chunking, deduplication
- Learn about how different applications expect data to be presented at different locations and in different formats.

Tejas Chopra

Tejas Chopra is a Senior Software Engineer, working in the Data Storage Platform team at Netflix, where he is responsible for architecting storage solutions to support Netflix Studios and Netflix Streaming Platform. Prior to Netflix, Tejas was working on designing and implementing the storage infrastructure at Box, Inc. to support a cloud content management platform that scales to petabytes of storage & millions of users. Tejas has worked on distributed file systems & backend architectures, both in on-premise and cloud environments as part of several startups in his career. Tejas is an International Keynote Speaker and periodically conducts seminars on Micro services, NFTs, Software Development & Cloud Computing and has a Masters Degree in Electrical & Computer Engineering from Carnegie Mellon University, with a specialization in Computer Systems.