Open Source Resources in Cloud Computing

Eucalyptus: Released as an open-source (under a FreeBSD-style license) infrastructure for cloud computing on clusters that duplicates the functionality of Amazon’s EC2, Eucalyptus directly uses the Amazon command-line tools. Startup Eucalyptus Systems was launched this year with venture funding, and the staff includes original architects from the Eucalyptus project. The company recently released its first major update to the software framework, which is also powering the cloud computing features in the new version of Ubuntu Linux [13].

Red Hat’s Cloud: Linux-focused open-source player Red Hat has been rapidly expanding its focus on cloud computing. At the end of July, Red Hat held its Open Source Cloud Computing Forum, which included a large number of presentations from movers and shakers focused on open-source cloud initiatives. You can find free webcasts for all the presentations here. Stevens’ webcast can bring you up to speed on Red Hat’s cloud strategy. Novell is also an open source-focused company that is increasingly focused on cloud computing, and you can read about its strategy here [13].

Cloudera: The open-source Hadoop software framework is increasingly used in cloud computing deployments due to its flexibility with cluster-based, data-intensive queries and other tasks. It’s overseen by the Apache Software Foundation, and Yahoo has its own time-tested Hadoop distribution. Cloudera is a promising startup focused on providing commercial support for Hadoop [13].

Traffic Server: Yahoo this week moved its open-source cloud computing initiatives up a notch with the donation of its Traffic Server product to the Apache Software Foundation. Traffic Server is used in-house at Yahoo to manage its own traffic, and it enables session management, authentication, configuration management, load balancing, and routing for entire cloud computing software stacks. Acting as an overlay to raw cloud computing services, Traffic Server allows IT administrators to allocate resources, including handling thousands of virtualized services concurrently [13].

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