Express Remote Managed Infrastructure Services Case Study
We have presented a new remote management service offering called Express Remote Managed Infrastructure Services (ERMIS). Since this class of offerings provides an opening into the SMB market for IBM, it was imperative to build the differential artifacts to lower costs and enhance the global appeal and reach of RIM via automation. To that end, we described two areas of research: service catalog and PD. Automation of management tasks for such commonly requested services helps in lowering costs while quickly delivering leading edge services to customers. As software solutions become more complex, it becomes impossible for the administrator of the data center to master the skill of each solution and learn the complex dependency relationships among the components in different solutions. The ERMIS service catalog aids in providing functionality across different ITIL processes such as service catalog management
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RIM can reduce the costs of operations, thus enabling IT managers to consider investing in new technology. Matching IT infrastructure with the needs of a business is a CIO’s biggest challenge. The increasing complexity of IT infrastructure and the constant pressure to reduce its costs, forces CIOs to maximize the use of existing resources and to enhance productivity of key technical people. Downtime, however brief, can result in revenue losses, unhappy customers and a loss of productivity. Instead of using productive time to making strategic decisions, key personnel are forced to spend it in routine operations management of IT infrastructure. The objective of this paper is focused on Artificial Neural Networks (ANN) based system to verify whether a RIM will ultimately lead to improvement in Software Process. Predicting success or failure of RIM & achieving maximum accuracy by changing number of neurons in ANN system is one of the main conclusion (Pal,
RIM can reduce the costs of operations, thus enabling IT managers to consider investing in new technology. Matching IT infrastructure with the needs of a business is a CIO’s biggest challenge. The increasing complexity of IT infrastructure and the constant pressure to reduce its costs, forces CIOs to maximize the use of existing resources and to enhance productivity of key technical people. Downtime, however brief, can result in revenue losses, unhappy customers and a loss of productivity. Instead of using productive time to making strategic decisions, key personnel are forced to spend it in routine operations management of IT infrastructure. The objective of this paper is focused on Artificial Neural Networks (ANN) based system to verify whether a RIM will ultimately lead to improvement in Software Process. Predicting success or failure of RIM & achieving maximum accuracy by changing number of neurons in ANN system is one of the main conclusion (Pal,