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Webinar: Understanding microservice latency: An introduction to Distributed Tracing and Zipkin

Speakers: Adrian Cole & Marcin Grzejszczak, Pivotal

Latency analysis is the act of blaming components for causing user perceptible delay. In today’s world of microservices, this can be tricky as requests can fan out across polyglot components and even data-centers. In many cases, the root source of latency isn’t a component, but rather a link between components. This session will overview how to debug latency problems, using call graphs created by Zipkin. We’ll use trace zipkin itself, setting up from scratch using docker.

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Spring Roo 2.0.0M2 released

On behalf on the Spring Roo team at DISID Corporation, I’m pleased to announce that Spring Roo 2.0.0.M2 has been released!

The main goal of this Spring Roo version was to update code generation to use latest Spring technologies:

  • Use Spring IO Platform to manage dependency versions and be able to use latest Spring technologies.
  • Update code generation to use the latest Spring framework versions (4.x)
  • Update code generation to include Spring Boot on generated projects.
  • Remove all generated configuration based on XML files and use Spring Boot auto-configuration.
  • Remove Active Record data model in favor of the Repository (Spring Data) based one.
  • Generate application architecture based on service layer pattern by default
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Webinar: Data Microservices with Spring Cloud Data Flow

Speakers: Mark Fisher & Mark Pollack, Pivotal
The future of scalable data processing is microservices! Building on the ease of development and deployment provided by Spring Boot and the cloud native capabilities of Spring Cloud, the Spring Cloud Stream and Spring Cloud Task projects provide a simple and powerful framework for microservice stream and batch processing.
At a higher level of abstraction, Spring Cloud Data Flow is an integrated orchestration layer that provides a highly productive experience for deploying and managing sophisticated data pipelines consisting of standalone microservices. Streams and tasks are defined using a DSL abstraction and can be managed via shell and a web UI. Furthermore, a pluggable runtime SPI allows Spring Cloud Data Flow to coordinate these applications across a variety of distributed runtime platforms such as Cloud Foundry, Apache Mesos and Apache YARN.
During this webinar you’ll see an overview of Spring Cloud Data Flow, with live demos of streaming and batch apps, on different platforms ranging from local cluster to a remote Cloud to show the simplicity of the developer experience.

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Webinar: Introducing Spring Cloud Task

Speaker: Michael Minella, Pivotal

One of the major promises of the cloud is that of flexibility. Today, most applications deployed to the cloud are long running processes that use the flexibility of cloud scaling. But computing is full of short lived tasks that start up, do their work, and then terminate. These tasks are excellent cloud use cases since resources can quickly be provisioned - and reclaimed.

In this webinar, we’ll explore a new project in the Spring Cloud portfolio, Spring Cloud Task, a new framework for developing and orchestrating short-lived microservices. We’ll explore various use cases, build your first task, and discuss how to orchestrate tasks using various techniques. Finally, we’ll peek into the roadmap for the Spring Cloud Task project.

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SpringOne2GX 2015 replay: NoXML - Eliminating XML in Your Spring Projects

Recorded at SpringOne2GX 2015.
Speaker: Matt Raible
Core Spring track
Slides: http://www.slideshare.net/SpringCentral/noxml-eliminating-xml-in-your-spring-projects

Many Spring projects exist that leverage XML for their configuration and bean definitions. Most Java web applications use a web.xml to configure their servlets, filters and listeners. This session shows you how you can eliminate XML by configuring your Spring beans with JavaConfig and annotations. It also shows how you can remove your web.xml and configure your web components with Java.

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SpringOne2GX 2015 replay: Microservices to FastData in the Enterprise with Spring

Recorded at SpringOne2GX 2015.
Speaker: John T Davies
Big Data track
Slides: http://www.slideshare.net/SpringCentral/microservices-to-fastdata-in-the-enterprise-with-spring

How do you deal with massive volumes of data, hundreds of thousands per second? Just chuck it into RAM but what about GC? If we scale to terabytes we need to distribute, what about serialisation costs? How do micro services fit in? In this talk we’ll be using Spring Integration and Spring Boot to ingest gigabytes of complex data into an two different in memory data grids (IMDGs). Based on applications running in production this talk will walk through the design and implementation with several demos.

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SpringOne2GX 2015 replay: High Performance Stream Processing

Recorded at SpringOne2GX 2015.
Speaker: Stephane Maldini, Glenn Renfo, David Turanski
Big Data track
Slides: http://www.slideshare.net/SpringCentral/high-performance-stream-processing-53163754

Making things go fast is harder than it looks. In this talk we dissect a Spring XD application into three areas - message transport, data serialization, and application processing - to show design patterns and techniques that will help you get the highest throughput and lowest resource utilization for your streaming applications. We will compare and contrast in-memory, RabbitMQ, and Kafka transports; Kryo, Protocol Buffers and C24 Simple Data Objects serialization libraries; and processing patterns that use a traditional shared queue and thread pool dispatcher in contrast to a Reactive Streams approach.

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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!

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SpringOne2GX 2015 replay: Reactive Web Applications

Recorded at SpringOne2GX 2015.
Speaker: Stephane Maldini, Rossen Stoyanchev
Web / Javascript track
Slides: http://www.slideshare.net/SpringCentral/reactive-web-applications-53170985
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.

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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
http://www.slideshare.net/SpringCentral/inflight-asset-management-with-spring-data-and-neo4j
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.

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