Abstract: The system and method for structuring self-provisioning workloads deployed in virtualized data centers described herein may provide a scalable architecture that can inject intelligence and embed policies into managed workloads to provision and tune resources allocated to the managed workloads, thereby enhancing workload portability across various cloud and virtualized data centers. In particular, the self-provisioning workloads may have a packaged software stack that includes resource utilization instrumentation to collect utilization metrics from physical resources that a virtualization host allocates to the workload, a resource management policy engine to communicate with the virtualization host to effect tuning the physical resources allocated to the workload, and a mapping that the resource management policy engine references to request tuning the physical resources allocated to the workload from a management domain associated with the virtualization host.

Abstract: The system and method for structuring self-provisioning workloads deployed in virtualized data centers described herein may provide a scalable architecture that can inject intelligence and embed policies into managed workloads to provision and tune resources allocated to the managed workloads, thereby enhancing workload portability across various cloud and virtualized data centers. In particular, the self-provisioning workloads may have a packaged software stack that includes resource utilization instrumentation to collect utilization metrics from physical resources that a virtualization host allocates to the workload, a resource management policy engine to communicate with the virtualization host to effect tuning the physical resources allocated to the workload, and a mapping that the resource management policy engine references to request tuning the physical resources allocated to the workload from a management domain associated with the virtualization host.

Abstract: The system and method for structuring self-provisioning workloads deployed in virtualized data centers described herein may provide a scalable architecture that can inject intelligence and embed policies into managed workloads to provision and tune resources allocated to the managed workloads, thereby enhancing workload portability across various cloud and virtualized data centers. In particular, the self-provisioning workloads may have a packaged software stack that includes resource utilization instrumentation to collect utilization metrics from physical resources that a virtualization host allocates to the workload, a resource management policy engine to communicate with the virtualization host to effect tuning the physical resources allocated to the workload, and a mapping that the resource management policy engine references to request tuning the physical resources allocated to the workload from a management domain associated with the virtualization host.

Abstract: The system and method for structuring self-provisioning workloads deployed in virtualized data centers described herein may provide a scalable architecture that can inject intelligence and embed policies into managed workloads to provision and tune resources allocated to the managed workloads, thereby enhancing workload portability across various cloud and virtualized data centers. In particular, the self-provisioning workloads may have a packaged software stack that includes resource utilization instrumentation to collect utilization metrics from physical resources that a virtualization host allocates to the workload, a resource management policy engine to communicate with the virtualization host to effect tuning the physical resources allocated to the workload, and a mapping that the resource management policy engine references to request tuning the physical resources allocated to the workload from a management domain associated with the virtualization host.

Abstract: The system and method for structuring self-provisioning workloads deployed in virtualized data centers described herein may provide a scalable architecture that can inject intelligence and embed policies into managed workloads to provision and tune resources allocated to the managed workloads, thereby enhancing workload portability across various cloud and virtualized data centers. In particular, the self-provisioning workloads may have a packaged software stack that includes resource utilization instrumentation to collect utilization metrics from physical resources that a virtualization host allocates to the workload, a resource management policy engine to communicate with the virtualization host to effect tuning the physical resources allocated to the workload, and a mapping that the resource management policy engine references to request tuning the physical resources allocated to the workload from a management domain associated with the virtualization host.