Trisha Gee introduces the Disruptor -a parallel messaging framework-, explains how to use it in code, and shows how it was used to solve an application’s messaging needs.Trisha Gee introduces the Disruptor, explains how to use it in code, and shows how it was used to solve an application’s messaging needs.
Robin Zimmermann lays out the broad architectural details of server applications with a web-based client exchanging messages over WebSockets and JMS.
Richard Tibbetts presents a three-tier architecture for real-time data staging analysis, storing the results and delivering them to clients as a service accessible through a variety of interfaces.
Paul Fremantle discusses the evolution of EAI, comparing the latest approaches, suggesting using Async Messaging, EDA, APIs, and doing high volumes, and underlining that evolution is not monotonic.
Kevin Houstoun and Rupert Smith discuss the creation of Java and .NET libraries for a FIX Protocol implementation without generating garbage in order to avoid the latency spikes associated with GC.
Todd Montgomery discusses messaging and how peer-to-peer messaging has changed capital markets, then takes a peek into its future pointing out that queuing is dead.
Ben Stopford, Farzad Pezeshkpour and Mark Atwell discuss: the Manhattan processor – avoiding GC pauses-, beyond messaging with ODC, Risk, data virtualization and collaboration in banking.
Joe Feser discusses how to enhance a legacy application into a disconnected hybrid app using Pub/Sub capabilities of the Windows Azure Service Bus.
Trisha Gee introduces Disruptor, a concurrency framework based on a data structure – a ring buffer – that enables fast message passing in a parallel environment.
Jeff Lindsay discusses creating distributed and concurrent systems using ZeroMQ – a lightweight message queue-, and gevent – a coroutine-based networking library.
Matthew Arrott considers that messaging is at the heart of distributed computing transforming the network into a destination through process choreography and cooperation.
Sid Anand presents the architecture set in place at LinkedIn and the data infrastructure running Java and Scala apps on top of Oracle, Voldemort, DataBus and Kafka.