Recorded at SpringOne2GX 2015. Presenters: Fred Melo & William Markito Oliveira Big Data Track Slides: http://www.slideshare.net/SpringCentral/implementing-a-highly-scalable-stock-prediction-system-with-r-apache-geode-and-spring-xd

Finance market prediction has always been one of the hottest topics in Data Science and Machine Learning. However, the prediction algorithm is just a small piece of the puzzle. Building a data stream pipeline that is constantly combining the latest price info with high volume historical data is extremely challenging using traditional platforms, requiring a lot of…

Recorded at SpringOne2GX 2015. Presenters:Yann Cébron - JetBrains, Stéphane Nicoll, Pivotal Core Spring Track Slides: no slides all demo

For many years, IntelliJ IDEA has been widely used in projects employing the Spring Framework. The latest version of the IDE (14.1) now ships with dedicated Spring Boot support. In this practical presentation we're going to look at some features from IntelliJ IDEA that will help you not only get started with Spring Boot but also guide you along the way, helping with coding and configuration management for your application. As a bonus, we'll also discover…

Recorded at SpringOne2GX 2015 Presenter: Mark Pollack Big Data Track Slides: http://www.slideshare.net/SpringCentral/spring-xd-today-and-tomorrow In this talk we will cover the major new features added to Spring XD since last year as well as upcoming changes for the next major version. Key integrations driven by the Big Data ecosystem at large such as Kafka, Spark, functional programming, integration with Python, and designer/monitoring UIs will be introduced and demonstrated. The next major version of XD will shift to a foundation based on Cloud-Native architectural principles, where each…

Recorded at SpringOne2GX 2015 Presenters: Sam Brannen & Nicolas Fränkel Core Spring Track Slides: http://www.slideshare.net/SpringCentral/get-the-most-out-of-testing-with-spring-42-53128369

Join Sam Brannen and Nicolas Fränkel to discover what's new in Spring Framework 4.2's testing support and learn tips and best practices for testing modern, Spring-based applications. Sam Brannen is the Spring Test component lead and author of the Spring TestContext Framework, and Nicolas Fränkel is the author of the book "Integration Testing from the Trenches".

In this session, Sam and Nicolas will cover…

Speaker: Oliver Gierke

A year has passed and the Spring Data shipped two release train iterations packed with interesting features. This talk will give a broad overview of the most important introduced in the Fowler and Gosling release trains. We will cover recent additions and improvements in Spring Data Commons - the module that's shared amongst the store specific ones. We'll then delve into the latest and greatest features of individual store modules, like JPA, MongoDB and the community ones as well.

Tuesday, Jan 26th, 2016 10:00AM PST (San Francisco GMT-08:00) Register

Speaker: Kenny Bastani

This webinar introduces you to a sample application that combines multiple microservices with a graph processing platform to rank communities of users on Twitter. The problem we’re going to solve is how to discover communities of influencers on Twitter using a set of seed profiles as inputs.

To solve this problem without a background in machine learning or social network analytics might be a bit of a stretch, but we’re going to take a stab at it using a little bit of computer science history. We’re going to use a collection of popular tools as a part of this article’s sample application. The tools we’ll use, in the order of importance, will be: Spring Boot Neo4j Apache Spark Docker RabbitMQ While there are some missing pieces, such as securing REST API access, and mapping device volumes to the containers, these kinds of important topics will be covered in future webinars.

Recorded at SpringOne2GX 2015. Track: Web / Javascript track Speaker: Rob Winch Slides: http://www.slideshare.net/SpringCentral/state-of-securing-restful-apis-with-spring The many benefits of a RESTful architecture has made it the standard way in which to design web based APIs. For example, the principles of REST state that we should leverage standard HTTP verbs which helps to keep our APIs simple. Server components that are considered RESTFul should be stateless which help to ensure that they can easily scale. We can leverage caching to gain further performance and scalability benefits.

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Recorded at SpringOne2GX 2015. Track: Big Data Speaker: Marius Bogoevici Slides: http://www.slideshare.net/SpringCentral/stream-processing-at-scale-with-spring-xd-and-kafka In the recent years, drastic increases in data volume, as well as a greater demand for low latency have led to a radical shift in business requirements and application development methods. Near-realtime data processing has started to become more prevalent, and high-throughput messaging systems such as Apache Kafka have emerged as key building blocks. Focusing on developer experience and productivity, Spring XD makes it…

Recorded at SpringOne2GX 2015. Track: Web / Javascript Track Speaker: Andy Wilkinson Slides: http://www.slideshare.net/SpringCentral/documenting-restful-apis An API's documentation is a vital part of making it easy to understand and easy to use. RESTful APIs are no different. In this talk we'll look at what should be included in your RESTful API's documentation and, just as importantly, what should be omitted. Using real-word examples, both good and bad, we'll discuss how the documentation should be structured so that it's informative, succinct, and easy to read. Having identified what…