Abstract:
Techniques for minimizing guest OS licensing costs in a volume based licensing model in a virtual datacenter are described. In one example embodiment, a virtual machine (VM) that requires a license key for a type of guest OS installed in the VM is identified. A license key is then assigned to the VM by first attempting to reassign a license key from an inactive VM, and only if a license key is not available for reassignment, obtaining a new license key for the VM.
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.
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:
Techniques for providing a calendar based provisioning and management for IT administrator/user activities in a virtual datacenter is described. In one example embodiment, an IT task is scheduled as a calendar appointment using an at least one registered calendar application residing in a user device. The at least one registered calendar application is then monitored for the scheduled IT task. The scheduled IT task is then translated into an action/command based on the outcome of the monitoring. The action/command is then issued to manage the scheduled IT task in the datacenter/cloud.
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:
Techniques for managing software licensing cost information are disclosed. In one embodiment, license data including licensing cost information associated with a product may be obtained. A license key for the product may be generated by encrypting the license data using an encryption key. The license key and a decryption key may be provided to a management tool associated with a client device. The management tool may be enabled to decrypt the license key using the decryption key to track the licensing cost information associated with the product.
Abstract:
Methods and systems that automate a DevOps deployment pipeline and optimize DevOps cost are described. Methods generate a deployment pipeline model based on policies associated with each deployment stage and task. Methods optimize cost of the deployment pipeline model based on model combinations of VMs. The deployment pipeline model may be executed on a cloud computing infrastructure in order to develop an application program.
Abstract:
Methods and systems to compute application license costs of a number of applications run on virtual machines of a virtualized data center are described. In one aspect, one or more of the virtual machines (“VMs”) that form the virtual data center are determined. Each VM is created from hardware components specifications of one or more application blueprints stored in a data-storage devices. The one or more blueprints are searched to determine the one more applications that run in each VM. For each VM, a total VM application licensing cost of the one or more applications is computed based on one or more of an application instance license cost, application socket license cost, and application core license of each of the one or more applications associated with each application.
Abstract:
Disclosed are various approaches for remotely hosted management of network virtualization. In one approach, an administrative user at a client device is authenticated by a computing device for access to manage a network located remotely from the computing device. One or more commands are received from the client device to configure a software-defined networking rule for the network. The computing device communicates with one or more services on the network to implement the software-defined networking rule. A status of implementing the software-defined networking rule is reported to the client device.
Abstract:
Some embodiments of the invention provide a method for processing requests for performing operations on resources in a software defined datacenter (SDDC). The resources are software-defined (SD) resources in some embodiments. The method initially receives a request to perform an operation with respect to a first resource in the SDDC. The method identifies a policy that matches (i.e., is applicable to) the received request for the first resource by comparing a set of attributes of the request with sets of attributes of a set of policies that place constraints on operations specified for resources. In some embodiments, several sets of attributes for several policies can be expressed for resources at different hierarchal resource levels of the SDDC. The method rejects the received request when the identified policy specifies that the requested operation violates a constraint on operations specified for the first resource.