Abstract:
System and method for deploying an application in a computer system automatically extend an application topology of virtual computing resources of the computer system and application components of the application to be executed on the virtual computing resources to include an affinity-type rule for the virtual computing resources of the computer system based on at least one predefined policy of the application topology and deploy the application in the computer system by provisioning the virtual computing resources to the physical devices in the computer system based on the extended application topology.
Abstract:
The present disclosure is related to methods, systems, and machine-readable media for information technology (IT) cost calculation in a software defined data center. A cost of infrastructure IT objects in a software defined data center can be calculated. The infrastructure IT objects can be mapped to an IT service construct over time, during runtime of the infrastructure IT objects. A portion of the cost of the infrastructure IT objects can be allocated to the IT service construct according to the map. A non-infrastructure IT cost can be allocated to the IT service construct. A total cost of the IT service construct can be calculated based on the allocations.
Abstract:
Techniques for optimizing guest operating system (OS) utilization cost in a processor based licensing model in a virtual datacenter are described. In one example embodiment, a virtual machine (VM) that has or is scheduled to have an instance of an operating system (OS) that requires a license is identified. Availability of a physical processor of a first host computing system that is licensed to execute the OS based on the computing resource requirements of the VM, the physical processor based license, author assigned affinity to physical processors in the first host computing. system is determined. The VM is then migrated/placed to/on the physical processor of the first host computing system or migrated/placed to/on a physical processor of a second host computing system based on the outcome of the determination.
Abstract:
A method for scheduling computing resources with container migration includes determining a resource availability for one or more hosts, a resource allocation for one or more virtual machines (VMs), and a resource usage for one or more containers. The method includes identifying the hosts on which VMs and containers can be consolidated based on resource availability. The method also includes calculating a target resource configuration for one or more VMs. The method further includes removing or adding resources to the VMs for which a target resource configuration was calculated to achieve the target resource configuration. The method further includes allocating the one or more VMs on the one or more hosts based on the resource availability of the one or more hosts, and allocating the one or more containers on the one or more VMs based on the resource configuration of each VM and the resource usage of each container.
Abstract:
Methods and apparatus to select virtualization environments are disclosed. An example method includes determining, via a processor, characteristics of a virtualized application that is awaiting deployment, analyzing, via the processor, the characteristics of the virtualized application to select a subset of virtualization environments that are capable of executing the virtualized application, the subset of virtualization environments selected from a set of virtualization environments of different virtualization environment types used in the datacenter, comparing, via the processor, the characteristics of the virtualized application to the virtualization environments of the subset of virtualization environments to determine scores for the virtualization environments, and deploying the virtualized application in the virtualization environment based on the scores.
Abstract:
Systems and methods of allocating network cost of a physical data center to data center tenants are disclosed. In one aspect, the systems and methods compute a total cost of the physical data center devices and networks and other operational expenditures over a period of time. The systems and methods compute local network and Internet utilization for each VM over the full period. Network utilization is computed for each VM as a fraction of the total cost. The cost allocated to each tenant is computed as a sum of the total cost of all VMs used by the tenant.
Abstract:
The present disclosure describes methods and systems that monitor the utilization of computational resources. In one implementation, a system periodically measures the utilization of computational resources, determines an amount of computational-resource wastage, identifies the source of the wastage, and generates recommendations that reduce or eliminate the wastage. In some implementations, recommendations are generated based on a cost of the computational-resource wastage. The cost of computational-resource wastage can be determined from factors that include the cost of providing a computational resource, an amount of available computational resources, and the amount of actual computational-resource usage. Methods of presenting and modeling computational-resource usage and methods that associate an economic cost with resource wastage are presented.
Abstract:
Methods and systems of determining an optimum power-consumption profile for virtual machines running in a data center are disclosed. In one aspect, a power-consumption profile of a virtual machine and a unit-rate profile of electrical power cost over a period are received. The methods determine an optimum power-consumption profile based on the power-consumption profile and the unit-rate profile. The optimum power-consumption profile may be used reschedule the virtual machine over the period.
Abstract:
This disclosure presents computational systems and methods for calculating the cost of vCPUs from the cost of CPU computing cycles. In one aspect, a total number of computing cycles used by one or more virtual machines (“VMs”) is calculated based on utilization measurements of a multi-core processor for each VM over a period of time. The method also calculates a total number of virtual CPUs (“vCPUs”) used by the one or more VMs based on vCPU counts for each VM over the period of time. A cost per vCPU is calculated based on the total number of computing cycles, the total number of vCPUs, and cost per computing cycle. The cost per vCPU is stored in a data-storage device. The cost per vCPU can be used to calculate the cost of a VM that uses one or more of the vCPUs.
Abstract:
Methods and systems that allocate the total cost of virtual storage created from hard disk drives (“HDDs”) and solid state drives (“SSDs”) of server computers and mass-storage devices of a cloud-computing facility are described. The virtual storage is used to form virtual disks (“VDs”) of virtual machines (“VMs”) comprising a virtual datacenter (“VDC”). Methods calculate a total virtual storage cost of the virtual storage from hardware costs and other costs such as labor, maintenance, facilities and licensing costs, which is used to calculate an HDD cost rate and an SSD cost rate. A cost of each VD is calculate based on virtual storage policy parameters, the HDD cost rate, and the SSD cost rate. The costs of the VDs associated with a VM are combined to obtain a VM storage cost. The VM storage costs may be combined to obtain the virtual storage cost of the VDC.