Danny Yuan discusses how Uber builds its next generation of stream processing system to support real-time analytics as well as complex event processing.
Akshat Vig and Khawaja Shams discuss DynamoDB Streams and what it takes to build an ordered, highly available, durable, performant, and scalable replicated log stream.
Marius Bogoevici demonstrates how to create complex data processing pipelines that bridge the big data and enterprise integration together and how to orchestrate them with Spring Cloud Data Flow.
Neha Narkhede shares the experience at LinkedIn moving from ETL to real-time streams, the challenges of scaling Kafka to hundreds of billions of events/day, supporting thousands of engineers, etc.
Sebastian von Conrad and James Ross explain how to use event sourcing in order to keep the cost of change lower.
Jessica Kerr introduces Elm, focusing on its architecture: how it overturns what is essential in object-oriented and even back-end functional programming.
Tim Wagner defines server-less computing, examines the key trends and innovative ideas behind the technology, and looks at design patterns for big data, event processing, and mobile using AWS Lambda.
Neville Li and Igor Maravić cover the evolution of Spotify’s event delivery system, discussing lessons learned moving it into the cloud using Scio, a high level Scala API for the Dataflow SDK.
Neha Narkhede explains how Apache Kafka was designed to support capturing and processing distributed data streams by building up the basic primitives needed for a stream processing system.
Martin Kleppmann explores using event streams and Kafka for keeping data in sync across heterogeneous systems, and compares this approach to distributed transactions.
Peter Bakas presents in detail how Netflix has used Kafka, Samza, Docker, and Linux to implement a multi-tenant pipeline processing 700B events/day in the Amazon AWS cloud.
Ned Twigg discusses using RxJava to wrap SWT events, looking at a few simple SWT UI's, and coding them using raw SWT and then again using RxJava.