Rohit Kelapure provides guidance and best practices in migrating monolithic mainframe apps and data including JCLs wrapped in CICS and IMS using Spring components like Spring Data Flow, Cloud, Batch.
Michael Minella uses Spring XD and Spring Batch to orchestrate the full lifecycle of Hadoop processing and uses Apache Mahout to provide the audience with the recommendation processing.
Gunnar Hillert and Chris Schaefer examine various scalability options in order to improve the robustness and performance of the Spring Batch applications.
Thomas Risberg introduces the Spring for Apache Hadoop project and discusses integration with Spring XD, batch jobs and external data sources.
Gunnar Hillert and Gary Russell introduce Spring Integration and Spring Batch, how they differ, their commonalities, and how you can use them together.
Wayne Lund introduces Java Batch JSR-352 explaining the domain and job specification languages used, the programming model and the runtime specification of the standard.
John Davies examines Visa’s architecture and shows how enterprises have architected complex integrations incorporating Hadoop, memcached, Ruby on Rails, and others to deliver innovative solutions.
David Syer and Mark Fisher on using Spring to develop concurrent and distributed apps, covering topics such as: asynchronous execution, intra-process, inter-process and inter-JVM communication.
Dave Syer and Mark Fisher demo using Spring Batch and Integration for real life situations where automation can save both operators and developers a lot of time by running automated batch jobs.
Dave Syer discusses Spring Batch (SB), batch processing patterns, typical batch processing uses, SB concepts and capabilities, case studies, SB domain details and the SB roadmap.
Wayne Lund discusses batch processing, Spring Batch objectives and features, scenarios for usage, Spring Batch architecture, scaling, example code, failures and retrying, and the future roadmap.