Core Java Platform Session Presentations

Analysis of Java support issues reveals that a majority of issues in enterprise Java applications occur not because of bugs in the code or the JRE, but because of incorrect config and absence of manageability tools. In addition, very few enterprises have a well-defined strategy for maintaining security compliance and patch management. If you are an enterprise IT manager responsible for keeping mission-critical apps running, or a systems administrator who manages servers and desktops running Java applications, or a Java applications developer who frequently gets pulled into fighting fires in production environments, then this session is for you.

As the scalable applications need right design, it is assumed that the compromise has to be made on agility. What are the patterns and practices that can be used to bring agility in scalable applications used by millions of users? We take lessons from eBay to form best practices (patterns) to impart agility to scalable application. The patterns cover wide swath including teams composition, development environments, service composition, data persistence, state management, and production set-up.

This evolution has given rise to the growing field of Data Science, which cannot be ignored. It so happens that Java Platform has emerged as a "perfect" platform for practicing Data Science, since many of the tools and technologies needed for Data Science are built in Java. Technologies such as Hadoop, Hive, Pig, HBase, Cassandra, Mahout are prime examples of these. This presentation discusses the field of Data Science and how you can integrate these technologies in your organization to practice Data Science.