Justin Becker & Neeraj Joshi describe Mantis, discuss the challenges associated with designing for the cloud, processing billions of events, all while being cost sensitive.
Udi Dahan takes a look at why different kinds of pub/sub need to be used for specific domains like healthcare, finance, “internet of things”, and some kinds of retail.
Glenn Renfro discusses how to create an application with a scheduler that will retrieve data from a web service, cleanse and emit the data via MQTT, by utilizing Spring Boot and Spring Integration.
Ian Cooper takes a look at two architectural patterns: pipelines for dealing with streams of data effectively, and events which provide significant advantages for loose coupling.
Husain shows the Reactive Extensions (Rx) library which allows one to treat events as collections, how Netflix uses Rx on the client and the server, allowing it to build end-to-end reactive systems.
Neha Narkhede of Kafka fame shares the experience of building LinkedIn's powerful and efficient data pipeline infrastructure around Apache Kafka and Samza to process billions of events every day.
The authors discuss Netflix's new stream processing system that supports a reactive programming model, allows auto scaling, and is capable of processing millions of messages per second.
Gabriel Gonzalez introduces TSAR (TimeSeries AggregatoR), a service for real-time event aggregation designed to deal with tens of billions of events per day at Twitter.
Greg Young discusses unexpected use cases and possible usages of the Event Store.
Ward Cunningham keynotes on how Events, Sockets, CORS, Closures, SVG, DSLs, Canvas, EC2 and Raspberry Pi contribute to a new type of wiki, a federated one.
Paul Buhler provides insight into the development and application of a semantically grounded version of the Workflow Management Coalition's Business Process Analytics Format (BPAF) specification.
Uri Cohen discusses several types of queues with their pros and cons used in financial and trading industries for highly parallelized data processing.