Speaker: Kenny Bastani Slides: https://speakerdeck.com/kbastani/creating-a-pagerank-analytics-platform-using-spring-boot-microservices Guided Tutorial from webinar content: http://www.kennybastani.com/2016/01/spring-boot-graph-processing-microservices.html Reference Application from Webinar: https://github.com/kbastani/spring-boot-graph-processing-example Graph processing platform: https://github.com/neo4j-contrib/neo4j-mazerunner

This webinar introduces you to a sample application that combines multiple microservices with a graph processing platform to rank communities of users on Twitter…

Recorded at SpringOne2GX 2015. Presenter: Artem Bilan Data & Integration Slides: http://www.slideshare.net/SpringCentral/spring-integration-java-dsl

Spring Integration Java DSL is an organic extension of the Spring Integration programming model providing an alternative to XML configuration with the fusion of Spring Framework Java & Annotation configuration support, Spring Integration EIP implementation and the Builder pattern.

In this session we will talk about the Spring Integration Java DSL fluent API and how it allows you to easily and quickly add integration capabilities to your…

Recorded at SpringOne2GX 2015. Speakers: Mark Fisher & Patrick Peralta Big Data Track Slides: http://www.slideshare.net/SpringCentral/cloud-native-data-flow-orchestration

The Spring Cloud Stream and Spring Cloud Task projects provide a simple and powerful framework for creating cloud native data microservices for stream and batch processing. Each microservice in these distributed systems consists of a stand-alone Spring Boot application.

While it is possible to define data pipelines across these microservice apps manually, Spring Cloud Data Flow is an integrated orchestration layer that…

Recorded at SpringOne2GX 2015. Speakers: Viktor Gamov, Leonid Igolnik, Baruch Sadogursky Core Spring Track Slides: No slides all demo

Almost every major version of Spring framework introduced a new way to configure the context: XML, Annotations, Java Config, Groovy... What's next, and, more important - why so many?! And how to know what to use and when? In this session Baruch, Viktor and Leonid will try to find the silver bullet, and you will have a chance to vote for the best feature implementations or even make a bet of the winner!

Recorded at SpringOne2GX 2015. Speakers: Gunnar Hillert, Michael Minella Data / Integration Track Slides: http://www.slideshare.net/SpringCentral/who-needs-batch Stream processing gets quite a bit of the press these days. Projects like Spark, Samza/Kafka, Google Cloud Dataflow, Apache Flink, and Amazon Kinesis bring the question of can we accomplish what we need without a batch component. This talk will take a hard look at if we still need batch these days, what that might look like in a modern development platform, and where Spring fits into it all.

Recorded at SpringOne2GX 2015 Presenter: Rossen Stoyanchev Web / Javascript Track Slides: http://www.slideshare.net/SpringCentral/spring-mvc-42-new-and-noteworthy-53171347

This talk provides a practical overview of new features for web applications in Spring Framework 4.2 including the addition of HTTP streaming, Server-Sent Events, a fine-grained model for cross-origin requests, comprehensive HTTP caching updates, and more. There are also plenty of updates for WebSocket-style messaging which this talk will cover.

Recorded at SpringOne2GX 2015 Presenter: Sergi Almar Web /Javascript Track Slides: http://www.slideshare.net/SpringCentral/from-zero-to-hero-with-spring-websocket

Real-time has changed the way we interact with the web, we demand information in real-time. Join Sergi Almar in this presentation to learn how to progressively enhance your traditional Spring MVC application with real-time functionalities for a more interactive and engaging user experience. Starting by adding server push notifications with Server-sent Events (supported in the new Spring 4.2) we will move to a bidirectional…

Recorded at SpringOne2GX 2015 Presenters: Ludwine Probst & Ilayaperumal Gopinathan Big Data Track Slides: http://www.slideshare.net/SpringCentral/apache-spark-for-big-data-processing

Today, we live in the world of Big Data. Hadoop and MapReduce are highly dominant in the domain of large scale data processing. However, the MapReduce model shows its limits for various types of treatment, especially for highly iterative algorithms frequently encountered in the field of Machine Learning.

Spark is an in-memory data processing framework that, unlike Hadoop, provides interactive and real-time…

Recorded at SpringOne2GX 2015 Presenter: Rob Winch Core Spring Track Slides: http://www.slideshare.net/SpringCentral/hands-on-spring-security-41

It can be complicated learning the ins and outs of any technology stack. When this complexity is compounded by needing to understand how to secure our applications, it can be daunting.

In this talk we will discuss how to rapidly and correctly apply Spring Security to an existing application. Along the way we will demo security exploits and see how to mitigate them, answer frequently asked questions, and learn established best practices.

Whether you…