Abstract: A computer-implemented method for computing an optimal plan for maximizing availability of the workload balancing of a virtual computing device, in the event of maintenance of the virtual computing device, is provided. The computer-implemented method comprises determining a workload placement plan that migrates a plurality of virtual machines of the virtual computing device to at least one location of a plurality of hypervisors. The computer-implemented method further comprises receiving input parameters for computing the workload placement plan for migrating the plurality of virtual machines. The computer-implemented method further comprises determining the workload placement plan that forms the basis for migrating the plurality of virtual machines, within the virtual computing device, for maximizing operating objectives of the virtual computing device.

Abstract: A computer-implemented method for computing an optimal plan for maximizing availability of the workload balancing of a virtual computing device, in the event of maintenance of the virtual computing device, is provided. The computer-implemented method comprises determining a workload placement plan that migrates a plurality of virtual machines of the virtual computing device to at least one location of a plurality of hypervisors. The computer-implemented method further comprises receiving input parameters for computing the workload placement plan for migrating the plurality of virtual machines. The computer-implemented method further comprises determining the workload placement plan that forms the basis for migrating the plurality of virtual machines, within the virtual computing device, for maximizing operating objectives of the virtual computing device.

Abstract: A method, system and computer program product for optimizing storage system behavior in a cloud computing environment. An Input/Output (I/O) operation data is appended with a tag, where the tag indicates a class of data for the I/O operation data. Upon the storage controller reviewing the tag appended to the I/O operation data, the storage controller performs a table look-up for the storage policy associated with the determined class of data. The storage controller applies a map to determine a storage location for the I/O operation data in a drive device, where the map represents a logical volume which indicates a range of block data that is to be excluded for being stored on the drive device and a range of block data that is to be considered for being stored on the drive device. In this manner, granularity of storage policies is provided in a cloud computing environment.

Abstract: A method, system and computer program product for optimizing storage system behavior in a cloud computing environment. An Input/Output (I/O) operation data is appended with a tag, where the tag indicates a class of data for the I/O operation data. Upon the storage controller reviewing the tag appended to the I/O operation data, the storage controller performs a table look-up for the storage policy associated with the determined class of data. The storage controller applies a map to determine a storage location for the I/O operation data in a drive device, where the map represents a logical volume which indicates a range of block data that is to be excluded for being stored on the drive device and a range of block data that is to be considered for being stored on the drive device. In this manner, granularity of storage policies is provided in a cloud computing environment.