FIGURE 3.3. Exposing resource attributes

54 nodes, data storage, and middleware. The middleware virtualizes the cluster into a single system image thus resources such as the CPU can be used without knowing the organization of the cluster. Of interest to this chapter are the components that manage the allocation of jobs to nodes (scheduler) and that monitor the activity of the cluster (monitor. As time progresses, the amount of free memory, disk space, and CPU usage of each cluster node changes. Information about how quickly the scheduler can take a job and start it on the cluster also is vital in choosing a cluster.
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To make information about the cluster publishable, a Publisher Web service and Connector were created using the RVWS framework. The purpose of the publisher Web service was to expose the dynamic attributes of the cluster via the stateful WSDL document. Furthermore, the Publisher service is published to the Dynamic Broker so clients can easily discover the cluster.
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To find clusters, the CaaS Service makes use of the Dynamic Broker. While the Broker is detailed in returning dynamic attributes of matching services, the results from the Dynamic Broker are too detailed for the CaaS Service. Thus another role of the CaaS Service is to summarize the result data so that they convey fewer details.
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Ordinarily, clients could find required clusters but they still had to manually transfer their files, invoke the scheduler, and get the results back. All three tasks require knowledge of the cluster and are conducted using complex tools. The role of the CaaS Service is to i) provide easy and intuitive file transfer tools so clients can upload jobs and download results and ii) offer an easy to use interface for clients to monitor their jobs. The CaaS Service does this by allowing clients to upload files as they would any Web page while carrying out the required data transfer to the cluster transparently.

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Because clients to the cluster cannot knowhow the data storage is managed, the CaaS Service offers a simple transfer interface to clients while addressing the transfer specifics. Finally, the CaaS Service communicates with the clusters scheduler, thus freeing the client from needing to know how the scheduler is invoked when submitting and monitoring jobs.