Galder Zamarreño | Devoxx

Galder Zamarreño
Galder Zamarreño Twitter

From Red Hat

Galder is one of the founding engineers of Infinispan, Red Hat's distributed in-memory data grid store. He is responsible for the client/server architecture and has recently been implementing a Node.js client. A seasoned conference presenter, Galder is on a mission to promote Infinispan wherever he goes. He's always happy to learn new technologies and programming languages to apply in live coding demos. He's particularly keen on functional programming related technologies, having used Scala since 2009 and Haskell more recently.

Blog: http://galder.zamarreno.com

cldops Cloud, Container et Scalabilité

Introduction to Data Streaming

University

Dealing with real-time, in-memory, streaming data is a unique challenge and with the advent of the smartphone and IoT (trillions of internet connected devices), we are witnessing an exponential growth in data at scale. Learning how to implement architectures that handle real-time streaming data, where data is flowing constantly, and combine it with analysis and instant search capabilities is key for developing robust and scalable services and applications. In this university session, we will look at how to implement an architecture like this, using reactive open source frameworks. An architecture based on the Swiss rail transport system will be used throughout the university.

Technologies: Java (attendees must be comfortable with Java 8), Infinispan, Eclipse Vert.x, Apache Kafka, OpenShift.

bigd Big Data, Machine Learning, IA & Analytics

Real-Time In-Memory Analytics Workshop

Hands-on Labs

Dealing with real-time, in-memory, streaming data is a unique challenge and with the advent of the smartphone and IoT (trillions of internet connected devices), we are witnessing an exponential growth in data at scale. Learning how to implement architectures that handle real-time streaming data, where data is flowing constantly, and combine it with analysis and instant search capabilities is key for developing robust and scalable services and applications.

In this lab session, we will look at how to implement an architecture like this, using reactive open source frameworks. The streaming data architecture has the following tiers: * Data collection tier * Data transport tier * Analysis tier * In-Memory data store tier * Data access tier * Client tier

An architecture based around the Swiss rail transport system will be use throughout the lab. To make it easier to set up the lab environment, we will be running the lab atop of Google Cloud Platform.

Lab session technologies: Java (attendees must be comfortable with Java 8), Infinispan, Vert.x, OpenShift and Google Cloud.

TBA : To be announced / Salle non affectée