Recorded at SpringOne Platform 2016. Speaker: Andreas Evers, Ordina JWorks Slides: http://www.slideshare.net/SpringCentral/writing-comprehensive-and-guaranteed-uptodate-rest-api-documentation

RESTful APIs are eating the world, yet all too often the documentation can cause indigestion for the APIs' developers and their users. Developers have to deal with annotation overload, repetition, and an unpleasant writing environment. Users are then left with documentation that's inaccurate and difficult to use. It doesn't have to be this way.

This talk will introduce Spring REST Docs and its test…

Recorded at SpringOne Platform 2016. Speaker: Oleg Zhurakousky Slides: http://www.slideshare.net/SpringCentral/spring-with-apachenifi

Spring Integration has long captured the hearts and minds of the developers world wide for its emphasis on simplicity, modularity and productivity when it comes to all things related to work-flow orchestration and complex event processing and is successfully used in a variety of Big Data solutions. Apache NiFi, on the other hand, is a new addition to the already rich Big Data technology stack.

Can the two complement one another?

This hands-on talk, based on…

Recorded at SpringOne Platform 2016. Slides: http://www.slideshare.net/SpringCentral/streaming-live-data-and-the-hadoop-ecosystem

It’s not always easy to get the data you need for analysis. And it becomes even more challenging if it is live streaming data you are working with. Learn how you can make Hadoop work for you in the most effective way possible, especially when it comes to adapting to the agile business requirements of today’s competitive environment. We will cover the Hadoop ecosystem – what is Hadoop, HDFS, MapReduce, Yarn, and then how leading open source projects such as Hive…

Recorded at SpringOne Platform 2016. Speaker: Victor Gamov, Neil Stevenson, Hazelcast Slides: http://www.slideshare.net/SpringCentral/spring-data-hazelcast-fluently-accessing-distributed-repositories

The primary goal of the Spring Data project is to make it easier to build Spring-powered applications that use data access technologies.

In this talk, Neil and Viktor will present using a new Spring Data for Hazelcast project and demonstrate how using the Spring Data paradigm gains the power of a distributed data repository.

The implementation is built on the new Spring Data KeyValue module and…

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…

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…

Recorded at SpringOne Platform 2016. Speakers: Gary Russell Slides: http://www.slideshare.net/SpringCentral/spring-for-apache-kafka

With the advent of the Kafka 0.9+ pure Java client, the Spring Team has created the new spring-kafka project with familiar Spring abstractions such as the KafkaTemplate, message listener container and POJO listener annotation @KafkaListener.

In this talk we'll take a look at the features of the project as well as the new version (2.0) of spring-integration-kafka which is now based on the Spring for Apache Kafka project.

Recorded at SpringOne Platform 2016. Speaker: Fred Melo Slides: http://www.slideshare.net/SpringCentral/architecting-for-cloud-native-data-data-microservices-done-right-using-spring-cloud-64889916

Microservices are definitely offering best practice guidance for those architecting cloud native applications. The ability to quickly create small services that can be individually deployed, configured and scaled, as building blocks for scalable, highly distributed and fault-tolerant systems has been causing every company to rethink on how to architect modern systems and making Spring Boot shine in…

Recorded at SpringOne Platform 2016. Speaker: Joe Kutner, Confluent Slides: http://www.slideshare.net/SpringCentral/i-cant-believe-its-not-a-queue-using-kafka-with-spring

Your existing message system is great, until it gets overloaded. Then what? That's when you should try Kafka.

Kafka is designed to be resilient. It takes the stress out of moving from a Spring monolith into a scalable system of microservices. Since you can capture every event that happens in your app, it's great for logging. You can even use Kafka's distributed, ordered log to simulate production load in your staging…