News

Alfresco Launches Cloud Developer Program

Alfresco, a leading provider of open source enterprise content management software, last week launched a developer program for those looking to build ECM applications that can run in the cloud.

The Alfresco Cloud Developer Program gives participants tools to build cloud-enabled apps that can be used for collaboration and document management. The program also entitles developers access to various content, including training webinars. Developers can also receive 24x7 support.

Many customers are interested in piloting cloud-based applications based on Alfresco's ECM technology, said Ian Howells, the company's chief marketing officer. "I think a high proportion is looking at evaluating the cloud today but I think most will be storing their content internally," he said in an interview.

In conjunction with the new program, the company released an open source tool kit designed to let developers program and deploy to Amazon's EC2 cloud service. Called the Alfresco 3.2 Community Edition, it is built on Ubuntu 9.10, which is installed on a Canonical Partner Repository.

"The reason we've chosen Ubuntu is within the developer community, it's the most widely used platform for us," Howells said. "What we wanted to give them was a way to go to the Amazon AMI [Amazon Machine Images] catalog to kick of an Alfresco instance." Alfresco released a link that directs developers to the AWS console.

The company also released an image that includes Alfresco's core ECM features and APIs based on the Content Management Interoperability Services (CMIS) specification.

CMIS is a standard agreed upon by Alfresco, IBM, EMC (Documentum), Microsoft, OpenText, Oracle and SAP. Intended to provide base interoperability among ECM systems, it is expected to be ratified by the Organization for the Advancement of Structured Information Standards (OASIS) in the first quarter of next year. "What we are targeting to the developer is a way to develop and a way to manage content," Howells said.

Alfresco posted a guide for developers looking to build cloud-enabled applications based on its ECM technology.

About the Author

Jeffrey Schwartz is editor of Redmond magazine and also covers cloud computing for Virtualization Review's Cloud Report. In addition, he writes the Channeling the Cloud column for Redmond Channel Partner. Follow him on Twitter @JeffreySchwartz.

comments powered by Disqus

Featured

  • VS Code v1.99 Is All About Copilot Chat AI, Including Agent Mode

    Agent Mode provides an autonomous editing experience where Copilot plans and executes tasks to fulfill requests. It determines relevant files, applies code changes, suggests terminal commands, and iterates to resolve issues, all while keeping users in control to review and confirm actions.

  • Windows Community Toolkit v8.2 Adds Native AOT Support

    Microsoft shipped Windows Community Toolkit v8.2, an incremental update to the open-source collection of helper functions and other resources designed to simplify the development of Windows applications. The main new feature is support for native ahead-of-time (AOT) compilation.

  • New 'Visual Studio Hub' 1-Stop-Shop for GitHub Copilot Resources, More

    Unsurprisingly, GitHub Copilot resources are front-and-center in Microsoft's new Visual Studio Hub, a one-stop-shop for all things concerning your favorite IDE.

  • Mastering Blazor Authentication and Authorization

    At the Visual Studio Live! @ Microsoft HQ developer conference set for August, Rockford Lhotka will explain the ins and outs of authentication across Blazor Server, WebAssembly, and .NET MAUI Hybrid apps, and show how to use identity and claims to customize application behavior through fine-grained authorization.

  • Linear Support Vector Regression from Scratch Using C# with Evolutionary Training

    Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric value. A linear SVR model uses an unusual error/loss function and cannot be trained using standard simple techniques, and so evolutionary optimization training is used.

Subscribe on YouTube