This session shares many of the production proven methods of running Java on vSphere. Covering how to size JVMs, and VMs for large scale deployments. The session will have a special section on GC tuning and show how a wide range of JVMs can be tuned using a GC recipe developed over the past 15 years of actual field experience in tuning JVMs.

Three key trends and associated tuning techniques are discussed in this session. The key trends are: Consolidation, Elasticity and Flexibility, and Performance

Consolidation Many of our customers find that their middleware deployments have proliferated and are becoming an administrative challenge associated with higher costs. We see a trend across customers who look to virtualization as a way of reducing the number of server instances. At the same time, customers are taking the consolidation opportunity to rationalize the number of middleware components needed to service a particular load. Middleware components most commonly run within a Java Virtual Machine (JVM) with an observed scale of 100 to 1000s of JVM instances and provide many opportunities for JVM instance consolidation. Hence, middleware virtualization provides an opportunity to consolidate twice – once to consolidate server instances, and, secondly, to consolidate JVM instances. This trend is far-reaching, because every IT shop on the planet is considering the cost savings of consolidation. One customer in the hospitality sector went through the process of consolidating their server footprint and at the same time consolidated many smaller JVMs that were less than 1GB heap. They consolidated many of these smaller 1GB JVMs into 2 categories, those that were 4GB, and others that were 6GB. They performed the consolidation in such manner that the net total amount of RAM available to the application was equal to the original amount of RAM, but with fewer JVM instances. They did all of this while improving performance and maintaining good SLAs. They also reduced the cost of administration considerably due to the reduced number of JVM instances they had to manage, and refined environment that helped easily achieve SLA.
Another customer, in the insurance industry, was able to achieve the same as the above customer, but additionally was able to over-commit CPU in development and QA environments in order to save on third party software license costs. On the other hand, sometimes we come across customers that have a legitimate business requirement to maintain one JVM for an application, and/or one JVM per a line of business. In these cases, you cannot really consolidate the JVM instances, as that would cause intermixing of the lifecycle of one application from one line of business with another. However, while such customers don’t benefit from eliminating additional JVM instances through JVM consolidation, they do benefit from more fully utilizing the available compute resource on the server hardware, that otherwise would have been underutilized in a non virtualized environment

Elasticity and Flexibility It is increasingly common to find applications with seasonal demands. For example, many of our customers run various marketing campaigns that drive seasonal traffic towards their application. With VMware, you can handle this kind of traffic burst, by automatically provisioning new virtual machines and middleware components when needed, and then automatically tear down these VMs when the load subsides. In addition, the ability to change updating/patching hardware without causing outage is paramount for middleware that supports the cloud era scale and uptime. VMware VMotion gives you the ability to move VMs around without needing to stop applicators and or the VM. This flexibility alone makes virtualization of middleware worthwhile when managing large-scale middleware deployments. One customer in the financial space, handling millions of transactions per day, used VMotion quite often to schedule their hardware upgrades without any time downtime. What otherwise would be a costly scheduled downtime to their business.

Performance Customers often report improved middleware platform performance when virtualizing. Performance improvements are partly due to the updated hardware that customers will typically refresh during a virtualization project. There is also some performance improvement due to the robust VMware hypervisor. A recent customer that reported a great level of performance provided the following testimony

“With our OrderExpress project we upgraded our Middleware Services, Commerce, Portal, WCM, Service Layer, DB2 Database; migrated from AIX to Linux; virtualized on VMware; moved the application into a three-tier DMZ; increased our transactions by over 150 percent; and added significant new capabilities that greatly improved the customer experience. Changing such a wide range of technology components at once was a huge challenge. However using VMware vSphere and additional architectural changes we were successful in improving performance by over 300 percent; lowered costs in the millions; improved security, availability, and scalability; and how we plan to continue evolving this application to maintain greater than 30 percent yearly growth.”

– Jeff Battisti, Senior Enterprise Architect at Cardinal Health

In this session, I will show some actual JVM and VM sizes for middleware components both small and large JVMs. Will also detail out GC tuning recipe that I have developed over the years,that has been shown to handle JVM heap sizes form 4GB to 88GB+, and higher. Of course the introduction of in-memory databases has driven the trend to have these larger JVMs and hence why we will discuss what is the best way to tune the JVM, VM, and the hardware platform they are deployed on.

I see the sizing question as the most commonly asked question with our customer base,and as a result I plan to focus on it during the session.

Actor based concurrency model is a paradigm shift. What is paradigm shift?

A change in the basic assumptions, or paradigms, within the ruling theory of science. A paradigm shift makes simple ideas hard to grok. Even though Actor model is a simple and revolutionary idea it becomes hard for programmers to see practical benefits and usage. Similarly, the Scala programming language brings a lot to the table in simplifying actor-based design, but comes with a new style of coding. One possible solution to this problem is to evaluate the new paradigm in terms of old paradigm. In this presentation we will take a working Spring based web application and gradually implement it using actors and Scala. We will be skeptical and suspicious of new ideas but at the same time we will be open minded. We will learn about actor based concurrency model using the knowledge of spring. At the same time, we'll learn best practices behind Actors, Scala and combining these with the Spring Framework.

For Modern Applications Many businesses are faced with some new messaging challenges for modern applications, such as horizontal scalability of the messaging tier, heterogeneous messaging systems and access methods, and extreme transaction processing. This presentation/demo will cover how businesses can overcome these messaging challenges with the use of Spring and RabbitMQ technologies.

Tom will build a case for AMQP, explain how SpringSource is providing AMQP support via Spring AMQP and Spring Integration, explain how RabbitMQ is a modern messaging solution that offers a reliable, highly available, scalable and portable messaging system with predictable and consistent throughput and latency, and demonstrate how Spring Integration and RabbitMQ can be progressively introduced into a standard Spring web application.

In this session you will learn what Spring Integration and Spring Batch are all about, how they differ, their commonalities, and how you can use Spring Batch and Spring Integration together.

We will provide a short overview of the Enterprise Integration Patterns (EIP) as described in the highly influential book of the same name. Based on these patterns, we will then see how Spring Integration enables the development of Message-driven applications. This allows you to not only modularize new or existing applications but also makes it easy to integrate with external systems.

This session will also introduce Spring Batch. Spring Batch addresses the needs of any batch process, be it complex calculations in large financial institutions or simple data migration tasks as they exist in many software development projects. We will cover what Spring Batch is, how Spring approaches the concepts of batch and how Spring handles scaling batch processes to be able to handle any volume of data.

You will also see how Spring Integration and Spring Batch maximize the reuse of the integration support provided by the core Spring Framework. In addition to providing a robust, proven foundation, this also flattens the learning curve considerably to all developers already familiar with Spring.

The repository abstraction layer is one of the core pieces of the Spring Data projects. It provides a consistent, interface-based programming model to allow implementing data access layers easily. The talk will start with a brief introduction and dive into best practices and implementation patterns later one.

We will conclude the session with an overview over what can actually be built on top of this generic repository abstraction and discuss integration hooks into Spring MVC and REST webservices.

Introduction to Cascading, an application framework for Java developers to deploy robust, enterprise-grade applications on Apache Hadoop. We'll start with the simplest Cascading program possible (file copy in a distributed file system) and progress in small steps to show a Java-based social recommender system based on Twitter feeds.

Introduction to Cascading, an application framework for Java developers to deploy robust, enterprise-grade applications on Apache Hadoop. We'll start with the simplest Cascading program possible (file copy in a distributed file system) and progress in small steps to show a Java-based social recommender system based on Twitter feeds.

The objective is to show how to work with “Big Data”, starting on a laptop with sample data sets, to generate JAR-based apps which can be deployed on very large clusters.

We'll show best practices for scalable apps in Cascading, how to leverage TDD features, etc.

Alternative data persistence approaches are all the rage these days. Transitioning our skill sets and legacy applications to these new and promising technologies though can be problematic. Spring Data is an exciting solution to persistence proliferation. It brings the flexibility and familiarity of the Spring Framework and adds the concepts of Repositories which allow developers to write their programs to using familiar methods such as save, update, delete, and dynamic finders.

In this presentation we will introduce Spring Data for GemFire and how it leverages your existing Spring Framework skills to create generic Spring style interfaces which will make it more efficient to transition to distributed data grids such as GemFire.

When applications grow bigger, modularity becomes a key aspect regarding maintainability. Design decisions made in the early days are hardly discoverable in the codebase, inter-module dependencies grow a lot. The talk introduces means and approaches to connect logical architecture to the codebase. Beyond that we discuss patterns and best practices around general code organization, package structures to build a solid foundation for Java applications and in how far Spring can help creating loosely coupled components and dedicated points to extend applications.

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.

Topics include:

• 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.

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.

Customer interest in virtualizing Java workloads has been growing exponentially year on year. For the last few years, the focus has been largely around looking for best practice guidance to mitigate concerns around virtualizing Java workloads, particularly in the area of performance. Since joining VMware, SpringSource has been investing in providing first class support for the Java runtime on vSphere with products such as EM4J. Combined with the industry-leading capabilities of the vSphere platform and the growing product portfolio around the Java ecosystem, there are many great reasons to virtualize Java.

So rather than continuing to ask the question, is it OK to virtualize Java, this session boldly aims to suggest that you would be crazy not to!

Come to this session to get an in-depth view of the latest and greatest in Cloud Foundry. It's easier than ever before to build and deploy your distributed polyglot applications. You will see some exciting new options, including new Java and Node runtimes and support for background workers and container-less web apps. These features allow you to create distributed apps comprised of many smaller, focused apps each written in the framework that fits its purpose best. We will also explore the latest in tooling, including new features in the STS plugin and the brand new "next gen" VMC client. We will peek under the hood to see what's new in the Cloud Foundry architecture. From Cloud Foundry beginner to expert, this session has something for everyone.

The modern web is rich with APIs that can be consumed by other applications, enabling an integrated experience for the users who hold accounts on the websites that front those APIs. Many of these APIs are secured with OAuth, an authorization specification for securing REST APIs. Spring Social is an extension to the Spring Framework that enables Spring applications to establish connections with those APIs on behalf of their users with little or no need to muck about in the intricacies of OAuth.

In this session, we'll explore how Spring Social brings API connectivity to Spring applications. We'll also uncover the newest features of Spring Social that make it easier than ever to link your application's users to the identities they maintain on various sites across the web.

In the modern web, user interfaces are expected to be rich, highly responsive, and available anytime, anywhere, and on any device. Round-trip server-side HTML rendering doesn't fit the bill any longer and numerous JavaScript frameworks have stepped forward to simplify development of client-side user-interfaces. With so many great options available, we now face a paradox of choice and it can be difficult to decide which UI framework best suits our needs.

In this session we'll explore a handful of the most popular client-side UI frameworks, including Backbone, Knockout, Sammy, and Spine (and others) weighing their strengths and weaknesses and helping decide which framework is most suitable for a given set of UI goals.