Abstract: A method, system and computer program product for selecting hypervisor platforms that are best suited to process application workloads. Attribute requirements for an application workload, such as high CPU capacity, high power and low cost, are received. A ranking algorithm is then applied to a list of pools of compute nodes to identify an ordered list of pools of compute nodes that are best suited for satisfying the attribute requirements of the application workload by comparing hypervisor characteristics of the pools of compute nodes with the attribute requirements of the application workload. Each pool of compute nodes runs on a particular hypervisor platform which has a unique combination of characteristics that correspond to a combination of a set of attribute requirements (e.g., medium CPU/memory/disk capacity; high CPU and memory performance). In this manner, the hypervisor platforms that are best suited for satisfying the application workload requirements are identified.

Abstract: A method, system and computer program product for selecting hypervisor platforms that are best suited to process application workloads. Attribute requirements for an application workload, such as high CPU capacity, high power and low cost, are received. A ranking algorithm is then applied to a list of pools of compute nodes to identify an ordered list of pools of compute nodes that are best suited for satisfying the attribute requirements of the application workload by comparing hypervisor characteristics of the pools of compute nodes with the attribute requirements of the application workload. Each pool of compute nodes runs on a particular hypervisor platform which has a unique combination of characteristics that correspond to a combination of a set of attribute requirements (e.g., medium CPU/memory/disk capacity; high CPU and memory performance). In this manner, the hypervisor platforms that are best suited for satisfying the application workload requirements are identified.

Abstract: Embodiments of the invention relate to a primary system instance to operate as a foreground process and creation of one or more shadow system instances to operate as a background process. The background instances yield information and performance data. Performance data associated with the foreground and background processes are generated and compared. One of the background instances may be converted to a new primary system instance as an alternative instance configuration.

Abstract: A method, system and computer program product for selecting hypervisor platforms that are best suited to process application workloads. Attribute requirements for an application workload, such as high CPU capacity, high power and low cost, are received. A ranking algorithm is then applied to a list of pools of compute nodes to identify an ordered list of pools of compute nodes that are best suited for satisfying the attribute requirements of the application workload by comparing hypervisor characteristics of the pools of compute nodes with the attribute requirements of the application workload. Each pool of compute nodes runs on a particular hypervisor platform which has a unique combination of characteristics that correspond to a combination of a set of attribute requirements (e.g., medium CPU/memory/disk capacity; high CPU and memory performance). In this manner, the hypervisor platforms that are best suited for satisfying the application workload requirements are identified.

Abstract: A method, system and computer program product for selecting hypervisor platforms that are best suited to process application workloads. Attribute requirements for an application workload, such as high CPU capacity, high power and low cost, are received. A ranking algorithm is then applied to a list of pools of compute nodes to identify an ordered list of pools of compute nodes that are best suited for satisfying the attribute requirements of the application workload by comparing hypervisor characteristics of the pools of compute nodes with the attribute requirements of the application workload. Each pool of compute nodes runs on a particular hypervisor platform which has a unique combination of characteristics that correspond to a combination of a set of attribute requirements (e.g., medium CPU/memory/disk capacity; high CPU and memory performance). In this manner, the hypervisor platforms that are best suited for satisfying the application workload requirements are identified.