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SpringOne Platform 2016 Replay: Spring and Big Data

Recorded at SpringOne Platform 2016.
Speaker: Thomas Risberg
Slides: http://www.slideshare.net/SpringCentral/spring-and-big-data

In this talk we will discuss ways to develop big data pipelines using Spring technologies. Learn how we can stream data into HDFS, run a Spark or a Hive job and extract the results from HDFS or Cassandra for presentation. The solution we develop will be a cloud-native pipeline that we will be able to run both locally and in the cloud.

The presentation focuses around the code for our solution and we also cover how to set up a test environment both locally and in the cloud. While building our solution using Spring Boot and Spring for Apache Hadoop we’ll cover how this app can be integrated in a larger context such as Spring Cloud Stream and Spring Cloud Data Flow. We will also discus configuration solutions for running our app in a variety of environments.

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SpringOne Platform 2016 Replay: Building resilient and evolutionary data microservices

Recorded at SpringOne Platform 2016.
Speaker: Vinicius Carvalho
Slides: http://www.slideshare.net/SpringCentral/building-resilient-and-evolutionary-data-microservices

How can we build data pipelines that are resilient to change? Data usually outlives application code, and we have to be prepared to deploy streams that can cope with the evolution of that data that is in motion. This talk will discuss the approach and supporting patterns to write resilient data microservices with Spring Cloud Stream and Spring Cloud Dataflow. We will discuss the role of a centralized Schema repository, and how can we work with different data models and protocols to achieve schema evolution. A centralized schema service will also help us understand what kind of data is currently being served and consumed by the different parts of our distributed system.

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Spring Team at Devnexus 2017

If you are joining the Spring Team at the SOLD OUT DevNexus 2017 event in Atlanta, GA on February 22-24 2017, here’s where you can find us and other Pivotal experts!

Pivotal is sponsoring and will be at booth # 7 from 9am-3pm on Thursday Feb 23, and 9am - 6pm on Friday Feb 24.

We will have experts available at the booth to talk to you about Spring Boot, Spring Cloud, Spring Cloud Data Flow, Cloud Foundry, and much more. Don’t miss these talks and workshops from Spring & Pivotal leaders on Cloud-Native, Reactive Spring, and much more!

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Webinar: Spring Boot 1.5 and Pivotal Cloud Foundry

Spring Boot and Pivotal Cloud Foundry users won’t want to miss Spring team’s Madhura Bhave and Pieter Humphrey as they tour through the Spring Boot 1.5 release.

Inspired in part by cool community open source work from codecentric.de, one of the hottest new directions that the two teams are working on is the integration of Spring Boot Actuators with Pivotal Cloud Foundry.

Attendees will be given direct linkage to product management - this is your chance to influence future integration direction! You’ll also walk away understanding all the highlights of the Spring Boot 1.5 release, including exciting improvements in Kafka and Pivotal Cloud Foundry support.

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SpringOne Platform 2016 Replay: Migrating from Spring XD to Spring Data Cloud Flow

Recorded at SpringOne Platform 2016.
Speakers: Katie Mooney; Director, Marketing Operations, zData; Cahlen Humphreys; Big Data Solutions Architect, zData & Dillon Woods; Chief Technology Officer, zData
Slides: http://www.slideshare.net/SpringCentral/lessons-learned-migrating-from-spring-xd-to-spring-data-cloud-flow-katie-mooney-dillon-woods-cahlen-humphreys

The goal of this session is to teach companies how they can use real-time data to make predictions with Spring Cloud Data Flow, Spark 2.0 and Spark ML. It will cover how to train your model using Spark ML in Spark 2.0. Once trained we will show you how to make real-time predictions using the model and Spring Cloud Data Flow.

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SpringOne Platform 2016 Replay: Reactive Kafka

Recorded at SpringOne Platform 2016.
Speaker: Rajini Sivaram
Slides: http://www.slideshare.net/SpringCentral/reactive-kafka

Apache Kafka is a distributed, scalable, high-throughput messaging bus. Over the last few years, Kafka has emerged as a key building block for data-intensive distributed applications. As a high performance message bus, Kafka enables the development of distributed applications using the microservices architecture.

Reactive Streams simplifies the development of asynchronous systems using non-blocking back pressure. The reactive framework enables the development of asynchronous microservices by providing a side-effect free functional API with minimal overhead that supports low latency, non-blocking end-to-end data flows.

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SpringOne Platform 2016 Replay: Task Madness - Modern on demand processing

Recorded at SpringOne Platform 2016.
Speakers: Michael Minella,Glenn Renfro
Slides: http://www.slideshare.net/SpringCentral/task-madness-modern-on-demand-processing

The flexibility promised by cloud computing is something that hasn’t been fully available in many use cases yet. Most application models are still based on long running containers, robbing users of that very flexibility. Spring Cloud Task, a new project in the Spring portfolio provides both functional and non-functional capabilities for building short lived, cloud-native, microservices. This talk will introduce the project as well as look at example applications. Since we’re in Vegas, we’re going to put that on demand processing to good use by demonstrating how we used it to generate a March Madness NCAA Men’s Basketball Tournament bracket. We’ll review how it worked, why Spring Cloud Task was the best fit for this type of application, and how we did this past March!

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SpringOne Platform 2016 Replay: Secure & Dynamic App Config at GapTech with Spring Cloud, Vault and Consul

Recorded at SpringOne Platform 2016.
Speaker: Nivesh Gopathi, Gap Tech
Slides: http://www.slideshare.net/SpringCentral/secure-dynamic-app-config-at-gaptech

As organizations move to audit trails over managed processes, continuous delivery with aggressive MTTR, security first doctrines and ephemeral instances, a key enabler is a platform ability for dynamic application configuration and securely bootstrapping application secrets. In this session, we will go over what the use cases for dynamic configuration and application secrets management are with some high level requirements, how we are collaboratively solving for these at enterprise scale using Spring Cloud Config, Vault and Consul and what’s coming next.

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Spring Team at Devoxx US 2017

Join the Spring Team at the 1st ever Devoxx event in the United States on March 21-23, 2017!
Pivotal is sponsoring and will be at booth # 104 from 10am-8pm on Tuesday March 21st, and 9:45am - 4:30pm on Wednesday March 22rd.

We will have experts available to talk to you about Spring Boot, Spring Cloud, Spring Cloud Data Flow, Cloud Foundry, and much more. Stop by and learn about Cloud Native Java from the leaders at Pivotal.

Don’t miss talks from Spring leaders on Cloud-Native, Reactive Spring, Eclipse and Big Data!

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SpringOne Platform 2016 Replay: Putting a SpEL on Spinnaker: Evolving an Expression Language for Continuous Delivery

Recorded at SpringOne Platform 2016.
Speaker: Tomas Lin, Netflix
Slides: http://www.slideshare.net/SpringCentral/putting-a-spel-on-spinnaker-evolving-an-expression-language-for-continuous-delivery-at-netflix

Spinnaker is an open source, multi-cloud continuous delivery platform. It is used by over 90% of cloud deployments at Netflix. The Spring Expression Language (SpEL) is heavily leveraged to fully articulate and extend Spinnaker’s automated deployment pipelines. SpEL is used heavily to interact with pipeline stages and triggers for variable substitution, information retrieval and conditional evaluation. This session will walk through the evolution of Spinnaker’s use of SpEL over two years of active development. We will share the code, features and wisdom gained from helping the Netflix and open source community adopt SpEL. You should attend if you are interested in the Spinnaker platform and the continuous delivery pipelines feature, or wish to learn how to fully harness SpEL for your own tools.

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