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Webinar Replay: 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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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 Replay: 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.

Read more...

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.

Read more...

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.

Read more...

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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