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SpringOne2GX 2015 replay: Spring MVC 4.2, New and Noteworthy

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.

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SpringOne2GX 2015 replay: Who needs batch these days?

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.

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SpringOne2GX 2015 replay: Spring Framework - the ultimate configuration battle

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!

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SpringOne2GX 2015 replay: Cloud Native Dataflow Orchestration

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 provides a highly productive deployment and management experience for development and ops. Streams and tasks are defined using the same DSL and shell/UI introduced with Spring XD. Furthermore, a pluggable runtime SPI allows Spring Cloud Data Flow to coordinate these applications across a variety of distributed runtime platforms including Apache YARN, Lattice, and Cloud Foundry.

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SpringOne2GX 2015 replay: Spring Integration Java DSL

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 application using only Spring Java configuration. We will also demonstrate the benefits that Java 8 Lambda support provides, and those additions over the core Spring Integration that the Spring Integration Java DSL implements. We will also discuss concerns and restrictions such as method-chain complexity, pre-Java 8 support etc.

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Webinar Replay: Creating a PageRank Analytics Platform Using Spring Boot Microservices

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. 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.

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Webinar Replay: Spring Boot Authentication... and More!

Guest Speaker: Micah Silverman, Java Developer Evangelist, Stormpath
Slides: http://www.slideshare.net/stormpath/spring-boot-authenticationand-more
Join Stormpath Java Developer Evangelist Micah Silverman for a technical overview of the common pain points with Java authentication. We’ll cover how to solve them with Stormpath in a Spring Boot application, and demonstrate how to quickly add a complete user management system to your Spring Boot app. By the end of this webinar, you’ll be on your way to a fully functioning Spring Boot app backed by Stormpath. Topics Covered: Authentication Pain Points in Java Stormpath, Spring Boot, and Your Architecture Demo: Auth in Spring Boot, with these features: A complete user registration and login system Pre-built login screens Password reset workflows Group-based authorization Advanced user features: API authentication, Single Sign-On, social login, and more Technical Q&A

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SpringOne2GX 2015 replay: Hands on Spring Security 4.1

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.

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SpringOne2GX 2015 replay: Apache Spark for Big Data Processing

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 analysis on large datasets. Furthermore, Spark has a more flexible programming model and gives better performance than Hadoop.

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SpringOne2GX 2015 replay: From Zero to Hero with Spring WebSocket

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 messaging communication style with WebSockets. Going real-time couldn’t be easier with Spring! We will also see the challenges and considerations to take into account when scaling our WebSocket application and deploy it to Cloud Foundry.

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