Reactive Summit 2016

Netflix customers stream over two billion hours of content each month, accounting for over a third of downstream Internet traffic during peak hours. At this scale, Netflix's systems generate and collect millions of events every second, such as request traces, streaming client activities, and system metrics. It is essential for engineers to process such data streams efficiently and reliably to support real-time monitoring and alerting, outlier detection, application diagnostics, trend prediction, and many other operations.

This talk will discuss Netflix's stream processing system a.k.a. Mantis that supports a reactive programming model, allows auto scaling, and is capable of processing millions of messages per second with configurable message delivery guarantees.

Mantis is a stream processing framework built on reactive principles using RxJava, Netty and ReactiveSocket. It provides users with the capabilities to write scalable stream processing jobs without having to worry about hard problems such as managing continuous data flow in a distributed environment or ensuring fault tolerance.