Juergen Hoeller illustrates basic Spring Framework 4.0 concepts and selected Java 8 features within Spring's programming model, exploring the impact on application architectures.
Jeremy Stieglitz discusses best practices for a data-centric security , compliance and data governance approach, with a particular focus on two customer use cases.
Melody Meckfessel explores how Google's engineering teams use CD to build products and scale them, and how their strain of DevOps speeds launches and helps their engineering culture thrive.
The speakers provide insight into design and architectural challenges for creating REST services with Spring Integration with RabbitMQ.
Brian Clozel talks about the newly open-sourced reference application that powers the spring.io site, built with Spring Boot, Spring Framework 4 features, cujoJS, Bower and Gulp.
Dean Wampler argues that Spark/Scala is a better data processing engine than MapReduce/Java because tools inspired by mathematics, such as FP, are ideal tools for working with data.
Matei Zaharia talks about the latest developments in Spark and shows examples of how it can combine processing algorithms to build rich data pipelines in just a few lines of code.
Bob Kelly presents case studies on how Platfora uses Hadoop to do analytics for several of their customers.
Jeff Beck describes how Grails fits into a larger polyglot architecture and goes through his team's experiences building and maintaining these micro services.
Daniel Tunkelang focuses on the data science mindset for successfully applying machine learning to solve problems: express, explain, experiment.
Neha Narkhede of Kafka fame shares the experience of building LinkedIn's powerful and efficient data pipeline infrastructure around Apache Kafka and Samza to process billions of events every day.