Mike Gehard takes the journey from monolith to microservices.
Eric Bottard and Ilayaperumal Gopinathan discuss easy composition of microservices with Spring Cloud Data Flow.
Gil Tene presents the current state of Java SE and OpenJDK, the role of Java in the Big Data and Infrastructure components, JCP, the ecosystem, trends, etc.
Nikhil Garg talks about the various Machine Learning problems that are important for Quora to solve in order to keep the quality high at such a massive scale.
Bo Peng goes over how Datascope iterated on the major pieces of the Expert Finder application project to produce actionable insights and recommendations on methodologies.
Rajini Sivaram talks about Kafka and reactive streams and then explores the development of a reactive streams interface for Kafka and the use of this interface for building robust applications.
Fred Melo introduces Spring Cloud Stream from a Data Microservices perspective.
Vinicius Carvalho talks about the role of a centralized Schema repository, and how can we work with different data models and protocols to achieve schema evolution.
Michael Minella and Glenn Renfro introduce Spring Cloud Task providing capabilities for building short lived, cloud-native microservices, as well as look at example applications.
Marcin Grzejszczak shows how to use the Spring Cloud Contract Verifier to stub HTTP / Messaging collaborators, faking microservices with stubs that were tested against their producer.
Sharma Podila reviews the state of containers usage in Netflix, discussing projects Titus and Mantis, AWS integration, and using Fenzo to run an elastic infrastructure for a varied mix of workloads.
Jie Yu discusses how containers are managed in Mesos, the future of container support in Mesos, and shows some of the new container networking and storage features.