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Money Heist - A Stream Processing Original!

Netflix will spend roughly 19B+ on content in 2021 over 100 countries to entertain over 200M subscribers. With this scale of investment in internationalized productions, it is essential to intelligently invest and track the movement of cash, in near-real-time, from pre-production to launch. This involves complex near real time financial calculations, data movement, consistent data views of transactional data of the present and the cash predictions of the future. It needs exactly once processing semantics and idempotency while guaranteeing a low latency serving layer. We leverage kafka to build a scalable and fault tolerance event-based processing engine to provide the right SLA guarantees. We also embrace event-driven data materialization to provide low latency lookups at scale. The aim of this talk is to provide an insight into how we built such a scalable system while embracing a full blown Kappa architecture, with Kafka at the heart of it all.


Meha Pandey

Meha is a Senior Software Engineer at Netflix. She is responsible for designing and building systems at scale to optimize content spend in Netflix Studios. She has experience building search and messaging infrastructure for large scale financial applications.

Shengze Yu

Shengze is currently Senior Software Engineers at Netflix. His team is responsible for building tools to process financial data for Netflix’s studio. He has experience building and running large scale systems like datastores, search platforms, stream processing applications and messaging infrastructure for consumer and enterprise applications.