Fred Melo introduces Spring Cloud Stream from a Data Microservices perspective.
Gary Russell takes a look at the features of the spring-kafka project as well as the new version (2.0) of spring-integration-kafka which is now based on the Spring for Apache Kafka project.
Thomas Risberg discusses developing big data pipelines with Spring, focusing around the code needed and he also covers how to set up a test environment both locally and in the cloud.
Chris Rawles describes approaches to addressing the concerns around any IoT project through a deep-dive into an interactive demo centered around classification of human activities.
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.
Mark Pollack introduces Spring Cloud Data Flow enabling one to create pipelines for data ingestion, real-time analytics and data import/export, demoing apps that are deployed onto multiple runtimes.
Nivesh Gopathi describes the use cases for dynamic configuration and application secrets management, and how GapTech are solving these at scale using Spring Cloud Config, Vault and Consul.
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.
Kevin Hoffmann and Chris Umbel discuss building .NET microservices and deploying them to the Spring Cloud.
Marcin Grzejszczak and Reshmi Krishna describe how to do distributed tracing with Spring Cloud Sleuth and Zipkin, demoing incorporating these technologies into an existing stock trading application.
Adrian Cole overviews how to debug latency problems using call graphs created by Zipkin, taking a look at the ecosystem, including tools to trace Ruby, C#, Java and Spring Boot apps.