This Week in Spring - April 5th, 2016

Welcome to another installment of This Week in Spring! As usual, we’ve got a lot to cover so let’s get to it!


SpringOne2GX 2015 replay: Reactive Web Applications

Recorded at SpringOne2GX 2015.
Speaker: Stephane Maldini, Rossen Stoyanchev
Web / Javascript track
In our previous talk “Intro to Reactive Programming” we defined reactive programming and provided details around key initiatives such as Reactive Streams and ReactiveX. In this talk we’ll focus on where we are today with building reactive web applications. We’ll take a look at the choice of runtimes, how Reactive Streams may be applied to network I/O, and what the programming model may look like. While this is a forward looking talk, we’ll spend plenty of time demoing code built with with back-pressure ready libraries available today.


SpringOne2GX 2015 replay: Spring Data Daily Double - Couchbase and Neo4J

Recorded at SpringOne2GX 2015.
Speakers: Michael Wilmes, Lufthansa and Laurent Doguin, Couchbase
Data / Integration Track
We invite you to join these two speakers from the Spring Data community, each speaking about their respective projects for 45 minutes.
Michael Wilmes from Lufthansa Systems will speak about Graph-based Asset Management with the Spring Framework. He is part of a flagship project that brings next-generation Inflight-Entertainment systems onto passenger aircrafts, and tackles the operational aspects of managing IT systems in flight, on ground and anywhere in between. Within his talk he will give insight on how Lufthansa Systems leverages the Spring Stack for solving an asset management problem scope with Spring Data and Neo4j.
Next, Laurent Doguin from Couchbase will tell us how to “Manage Time-base data with Spring Data Couchbase”. A common thing to do in the big data world is store time-based data. It can be logs, user events, social media metrics, market data indicators or even more common now sensor data. You can do that very easily with Spring Data Couchbase. I this talk I will tell you what you need to know before starting to store time-based data. I’ll talk about use cases, data modeling, how Couchbase is a perfect fit for this kind of job and code a little demo that reflects all of this.


1 Stream, 2 Applications, and 3 Dependencies for Spring Cloud Data Flow

I just wanted to register here an experience that made me smile yesterday: making the rapidly improving Spring Cloud Data Flow wiggle from (Spring Boot) start(-ers) to service in a matter of minutes!

The only pre-requisite is that you have a Redis instance runnning. My Redis instance is running on and it required no further configuration for Spring Boot to find and work with it.

We’ll use the epic Spring Initializr to make short work of generating our applications. Remember those silly Apple commercials, “There’s an App For That?” Nevermind that, there’s a checkbox for that! Let’s see if you like the experience as much as I did!