Abstract: Various examples are disclosed for generating a prediction of server requirements needed to deploy an application. The application can be deployed in virtualized environment in which virtual machines can execute the application. The predicted server requirements can be generated based upon data from other deployments of the application in other virtualized environments.

Abstract: Various examples are disclosed for generating a prediction of server requirements needed to deploy an application. The application can be deployed in virtualized environment in which virtual machines can execute the application. The predicted server requirements can be generated based upon data from other deployments of the application in other virtualized environments.

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: Systems and techniques are described for generating test cases. In one example, a manual test of code is performed. The manual test uses proxy code to detect at least one input to the code and a data transfer between the code and other code. The data transfer includes an input to the other code and an output from the other code. A file is generated that includes the at least one input to the code, the input to the other code, the output from the other code, and data that specifies that the manual test of the code resulted in an expected output. A mock test automates the manual test of the code based at least in part on the file.

Abstract: Various examples are disclosed for generating a prediction of server requirements needed to deploy an application. The application can be deployed in virtualized environment in which virtual machines can execute the application. The predicted server requirements can be generated based upon data from other deployments of the application in other virtualized environments.

Abstract: Techniques for optimizing resource claims for containers is described. In one example, resource utilization data associated with at least one container may be obtained for a period. A set of forecasting models may be trained based on the resource utilization data associated with a portion of the period. Resource utilization of the at least one container may be predicted for a remaining portion of the period using the set of trained forecasting models. The predicted resource utilization may be compared with the obtained resource utilization data for the remaining portion of the period. A forecasting model may be determined from the set of trained forecasting models based on the comparison to optimize resource claims for the at least one container.

Abstract: Methods and system to calculate a total container cost of each container of a data center are described. Methods compute a direct container cost of each container running in the data center based on container resource utilization and a resource utilization rate of each resource of a host. Methods also compute an indirect container cost of each container is calculated as a sum of indirect cost of each resource of the host used by the container and each resource of the host used by a monitor container that monitors each container utilization of host resources. For each container, a total container cost of the container is calculated as the sum of the direct container cost and the indirect container cost of the container. Total container costs are used to determine the cost of applications miming on the containers.

Abstract: Techniques for optimizing resource claims for containers is described. In one example, resource utilization data associated with at least one container may be obtained for a period. A set of forecasting models may be trained based on the resource utilization data associated with a portion of the period. Resource utilization of the at least one container may be predicted for a remaining portion of the period using the set of trained forecasting models. The predicted resource utilization may be compared with the obtained resource utilization data for the remaining portion of the period. A forecasting model may be determined from the set of trained forecasting models based on the comparison to optimize resource claims for the at least one container.

Abstract: A process of obtaining, in effect, a multi-virtual-machine snapshot by taking a single-virtual-machine snapshot begins with creating, by a host hypervisor, a host virtual machine and a guest hypervisor. The guest hypervisor executes on the host virtual machine. Virtual machines to be included together in an effective multi-virtual-machine snapshot are migrated to the guest hypervisor. A single-virtual-machine snapshot is taken, by the host hypervisor, of the host virtual machine. The snapshot contains the state data for the virtual machines migrated to the guest hypervisor.

Abstract: The present disclosure is related to predicting application response lime based on metrics. An example machine-readable medium may store instructions executable by a processing resource to determine a particular response time and an average response time of an application based on a plurality of relevant performance metrics associated with the application during a first period of time, classify the particular response time into a group based on the average response time, and determine a relationship between the plurality of relevant performance metrics and the particular response time of the application. The example machine-readable medium may further store instructions executable by the processing resource to determine whether a response time of the application is likely to change sufficiently to change the classification to a different group during a second period of time based on the relationship.

Abstract: A process of obtaining, in effect, a multi-virtual-machine snapshot by taking a single-virtual-machine snapshot begins with creating, by a host hypervisor, a host virtual machine and a guest hypervisor. The guest hypervisor executes on the host virtual machine. Virtual machines to be included together in an effective multi-virtual-machine snapshot are migrated to the guest hypervisor. A single-virtual-machine snapshot is taken, by the host hypervisor, of the host virtual machine. The snapshot contains the state data for the virtual machines migrated to the guest hypervisor.

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: User configurations of an installed application are migrated by isolating them from a base application state of the installed application to generate a virtual application package. At runtime, a base virtual application package and a user configurations virtual application package are provisioned from a central repository and executed by the user. The resulting virtualized execution environment merges the application resources contained in the packages such that the user configurations override the base application to make available all of the user configurations. This technique may be used to preserve user configurations during migration of applications, or to maintain user-specific configurations for a particular application across different sessions of a user's virtualized desktop.

Abstract: Systems and techniques are described for generating test cases. In one example, a manual test of code is performed. The manual test uses proxy code to detect at least one input to the code and a data transfer between the code and other code. The data transfer includes an input to the other code and an output from the other code. A file is generated that includes the at least one input to the code, the input to the other code, the output from the other code, and data that specifies that the manual test of the code resulted in an expected output. A mock test automates the manual test of the code based at least in part on the file.

Abstract: Methods and system to calculate a total container cost of each container of a data center are described. Methods compute a direct container cost of each container running in the data center based on container resource utilization and a resource utilization rate of each resource of a host. Methods also compute an indirect container cost of each container is calculated as a sum of indirect cost of each resource of the host used by the container and each resource of the host used by a monitor container that monitors each container utilization of host resources. For each container, a total container cost of the container is calculated as the sum of the direct container cost and the indirect container cost of the container. Total container costs are used to determine the cost of applications miming on the containers.

Abstract: This disclosure presents computational systems and methods that allocate cost of resources of a cluster of server computers used by virtual machines in a virtual data center. In one aspect, a fair unit rate is computed based on the larger of a measured average utilization or an expected utilization of a cluster resource of server computers within a physical data center by virtual machines. The fair unit rate is a cost per unit of resource used over a period of time and is used to compute an allocated cost of the virtual machine usage of the cluster resource.

Abstract: Systems and techniques are described for generating test cases. A described technique includes monitoring a manual test of a code portion. The monitoring can include identifying one or more performed operations performed during the manual test. A seed file can be generated that includes data describing the one or more performed operations. A mock test can be generated for the code portion using the seed file. The mock test can include one or more mock operations that match the one or more performed operations. The mock test can be performed on the code portion, including performing the one or more mock operations using the code portion.

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: Systems and techniques are described for generating test cases. A described technique includes monitoring a manual test of a code portion. The monitoring can include identifying one or more performed operations performed during the manual test. A seed file can be generated that includes data describing the one or more performed operations. A mock test can be generated for the code portion using the seed file. The mock test can include one or more mock operations that match the one or more performed operations. The mock test can be performed on the code portion, including performing the one or more mock operations using the code portion.

Abstract: This disclosure presents computational systems and methods that allocate cost of resources of a cluster of server computers used by virtual machines in a virtual data center. In one aspect, a fair unit rate is computed based on the larger of a measured average utilization or an expected utilization of a cluster resource of server computers within a physical data center by virtual machines. The fair unit rate is a cost per unit of resource used over a period of time and is used to compute an allocated cost of the virtual machine usage of the cluster resource.