In this presentation we will discuss the options for managing and monitoring applications that use Spring Integration. It will provide a comprehensive overview of the extensive support for JMX provided by Spring Integration, both in terms of providing access to Spring Integration internals, as well as creating a JMX client to interact with local and remote MBeanServers.
In addition, we will show how to use the Spring Integration plugin for Spring Insight to drill down into Spring Integration flow processing to examine application performance.
- Using the Integration MBean Exporter, and the MBeans it registers, for analyzing Messaging Endpoints and Channels.
- Exporting the Integration MBean Exporter itself as an MBean, to gain access to it’s attributes and operations.
- Using the Control Bus to start and stop endpoints.
- Using the Spring Integration plugin for Spring Insight to get a real-time view of your application and its performance.
- Enabling and using Message History
- Using the orderly shutdown mechanism available in Spring Integration 2.2.
- Using JMX endpoints (with local and remote MBeanServers) to monitor attributes. invoke operations, publish notifications, and receive notifications.
About the speaker
Gary has been in software engineering, concentrating on Enterprise Integration, for over 30 years on various platforms, and in the Java space since the late ’90s.
He has been developing with the Spring Framework since 2004 and joined SpringSource/VMware in 2009 in a consulting role. From 2009 until the end of 2011 he taught Core Spring and Enterprise Integration with Spring to several hundred developers, as well as providing Enterprise Integration consulting services with Spring Integration, Spring Batch and Core Spring.
He has been a committer on the Spring Integration project for nearly 3 years and became a full time member of the engineering team in January 2012.
More About Gary »
How to build Big Data Pipelines for Hadoop using OSS
Hadoop is not an island. To deliver a complete Big Data solution, a data pipeline needs to be developed that incorporates and orchestrates many diverse technologies. A Hadoop focused data pipeline not only needs to coordinate the running of multiple Hadoop jobs (MapReduce, Hive, Pig or Cascading), but also encompass real-time data acquisition and the analysis of reduced data sets extracted into relational/NoSQL databases or dedicated analytical engines.
This session looks at the architecture of Big Data pipelines, the challenges ahead and how to build manageable and robust solutions using Open Source software such as Apache Hadoop, Hive, Pig, Spring Hadoop, Batch and Integration.
About the speaker
Costin Leau is an engineer within the SpringSource. His interests include data access and aspect oriented programming. With significant development experience, Costin has worked on various Spring Framework features (cache abstraction, JPA, java config), led the Spring Dynamic Modules (Spring OSGi probject), Spring GemFire and the Spring-inspired, OSGi 4.2 Blueprint Service RI. Currently Costin is working in the NOSQL and Big Data area, leading the Spring integration with Hadoop and Redis.More About Costin »