TheServerSide Java Symposium is the only conference focused on Enterprise Java worldwide. The conference is held twice a year in the United States and Europe, respectively. TSSJS was hosted this year in Las Vegas, NV and in Prague, Czech Republic, where hundreds of Java professionals met to discuss the latest technologies, methodologies, and trends in the development of robust enterprise applications.
Mission-Critical Cloud/Enterprise Hybrid Deployments
Almost every vendor talks about cloud computing, and "cloud" is becoming the buzzword du jour.
Eugene talks about how to design, implement, and roll-out cloud/enterprise hybrid applications based
on his real-world experiences rolling out production-quality cloud systems. This presentation will
guide you to identify the different cloud architectures that you can combine with your application
(Software as a Service or SaaS, Platform as a Service or PaaS, Infrastructure) and learn how
to define an architecture based on cloud and enterprise components to attain maximum scalability
at a low cost of deployment and operations.
Mission-Critical Cloud/Enterprise Hybrid Deployments (PDF) - 2.2 MB
Google App Engine HOWTO
Google App Engine for Java is the most recent contestant in the war for the low-cost,
high-availability cloud computing environments. This presentation introduces the technology
and its operational model, how it’s alike and how it differs from running Java apps in
traditional app server environments, and what kinds of things developers and app designers
will need to plan, build, deploy, and maintain Java applications that will run on Google’s
App Engine infrastructure.
Google App Engine for Java HOWTO (PDF) - 746 KB
Mule and Hadoop Integration Case Study
This session includes an overview of Hadoop and HDFS for map/reduce and data retrieval operations, as well as advantages of HDFS/Hadoop over RDBMSs queries and data retrieval. It discusses augmenting resource-oriented computing systems with map/reduce capabilities, as well as exposing the map/reduce server farm as services and endpoints, and queries under map/reduce systems. Among the technologies employed in the case study are Hadoop, HDFS, the Mule ESB, Java EE 6, Hive, PIG, and scripting for map/reduce.
Download coming soon! (PDF)
