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Fabric3 is a platform for developing, assembling, and managing composite applications. Fabric3 provides the following features:

  • A programming model based on Service Component Architecture (SCA) and Spring that is specifically designed for building and integrating loosely-coupled systems.
  • The ability to use a variety of remote wire services and support for dependency injection whether they are local or remote. Think of Spring or Guice for distributed, loosely coupled services.
  • Support for a range of communication protocols and messaging patterns in a unified, consistent manner without tying application logic to specific transport APIs. Use ZeroMQ, REST, messaging middleware (JMS), and Web Services, and file-based transports without polluting application code with complex APIs and configuration.
  • A cross-application policy framework for implementing and enforcing policies such as security, reliability, and SLAs throughout an organization.
  • A management framework for provisioning, controlling, and monitoring production deployments via a RESTful API.
  • Portability across a variety of middleware environments including Tomcat, and WebLogic.

 

Info
titleFabric3 Benefits

If you would like a hands-on example of how Fabric3 simplifies application development and the advantages it brings, please look at the BigBank sample application.

 

In this chapter, we cover the basics of setting up and deploying an application using Fabric3.

The documentation assumes a basic understanding of SCA concepts. Before proceeding, if you have not done so, we recommend familiarizing yourself with SCA. The specifications themselves (http://www.oasis-opencsa.org) are generally not the most accessible source of introductory information. We recommend:

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For projects that intend to use Spring, Fabric3 also ships with a set of dedicated Spring samples. These samples are ports a subset of the SCA Java samples described in this chapter, with SCA Java components replaced by Spring beans. Basic layout, configuration and deployment remain the same across both sets of samples.

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