Abstract:
The current document is directed to automated application-release-management facilities that, in a described implementation, coordinate continuous development and release of cloud-computing applications. The application-release-management process is specified, in the described implementation, by application-release-management pipelines, each pipeline comprising one or more stages, with each stage comprising one or more tasks. The currently described methods and systems employ configuration files to specify configuration of the execution environment for application-release-management pipelines, application-release-management-pipeline stages, and application-release-management-pipeline-stage tasks and apply policies to configuration files to further specify the execution environments for application-release-management pipelines.
Abstract:
Methods and systems assist data center customer to plan virtual data center (“VDC”) configurations, create purchase recommendations to achieve either an expansion or contraction of a VDC, and optimize the data center cost. Methods generate recommendations on lower cost combinations of virtual machine (“VM”) guest OS licenses, server computer hardware and VM software to optimize the costs are generated, generate data center customer plans for additional VMs with Quest OS for a projected period of time, provide recommendations on lower cost combination of guest OS licenses, server hardware, and VM software to optimize the cost. Methods also report any underutilized licensed servers and provide recommendations for cost savings when volume licenses can be replaced by instance based software licenses. Methods may generate VM placement recommendations to data center customers while the customers attempt to manually migrate VMs to different server computers.
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.