Abstract:
In one embodiment, a method includes storing a cost assigned to a physical computing device in a storage device. The physical computing device is found in a physical infrastructure of a data center. The method determines an instantiation of a virtual machine in a virtual infrastructure. Information for a provisioning of the virtual machine with the physical computing device in the physical infrastructure of the data center is then received. The cost assigned to the physical computing device from the storage device is determined where the cost is used to determine a charge for the virtual machine based on usage of the physical computing device.
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:
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:
Methods and apparatus to select virtualization environments are disclosed. An example method includes determining, via a processor, characteristics of a virtualized application that is deployed in an existing virtualization environment. 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 migrate the virtualized application from the existing virtualization environment to a new virtualization environment based on the scores.
Abstract:
Methods and systems allocate storage costs to virtual machines (“VMs”) in a virtual data center. Methods calculate a datastore-base rate based on datastore utilized-storage capacity in each LD and each LD-base rate when the datastore utilized-storage capacity and each LD-base rate are available. Datastore total cost is calculated by multiplying the datastore-base rate by the datastore utilized-storage capacity. Methods also use graph based methods to calculate datastore-base rates when the datastore utilized-storage capacity is unknown for each LD. The datastore-base rate associated with each datastore may then be used to calculate a VM storage cost of each VM hosted by a datastore.
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:
Some embodiments of the invention provide a method for defining a telecommunications network deployment for a particular geographic region comprised of a set of sub-regions, the telecommunications network including an access network, an edge network and a core network. For each UE of multiple UEs distributed across the particular geographic region, the method selects a traffic category from a set of traffic categories to associate with the UE, and based on the selected traffic category, the method uses an application traffic model to compute an upper threshold limit of an attainable data rate for the UE. For each link of multiple transport links that connect the multiple UEs to the telecommunications network, the method determines a link capacity for each transport link based on the upper threshold limits of the attainable data rates computed for each UE of the multiple UEs. The method simulates performance of the telecommunications network based on the determined link capacities for the multiple transport links. When a set of performance metrics resulting from simulating performance of the telecommunications network meet a performance threshold specified for the telecommunications network, the method uses the determined link capacities to define the telecommunications network deployment for the particular geographic region.
Abstract:
Some embodiments of the invention provide a method for evaluating a deployment of a telecommunications network for a particular geographic area, the telecommunications network including an access network, an edge network, and a core network. The method is performed through a user interface (UI). The method receives a selection to simulate performance of a particular deployment of the access network, the particular deployment including at least (1) configurations for multiple access nodes for providing end-users of the telecommunications network access to the telecommunications network and (2) configurations for multiple transport links that connect the multiple access nodes to the telecommunications network. The method displays a visualization of the particular deployment of the telecommunications network based on the simulated performance, the visualization including (1) representations of multiple components of the telecommunications network including the multiple access nodes, (2) representations of the multiple transport links, (3) indications of performance by the multiple components and the multiple transport links, and (4) a set of selectable UI items for modifying configurations of the multiple access nodes and multiple transport links.
Abstract:
The present disclosure provides example computer-implemented method, medium, and system for managing IP addresses for DPDK enabled network interfaces for cloud native pods. One example method includes creating a pod of one or more containers, where the pod connects to multiple networks through multiple network interfaces. A poll mode driver (PMD) is attached to a first network interface of the multiple network interfaces, where the PMD enables one or more data plane development kit (DPDK) applications inside the pod to manage the first network interface. A first container network interface (CNI) is created to handle the DPDK enabled first network interface. A first Internet protocol (IP) address is allocated to the first network interface using the first CNI. The first IP address is passed to the one or more DPDK applications using the first CNI.
Abstract:
Some embodiments provide a method that generating a host profile for deploying a first network function. the method uses a virtual machine configuration operator in a remote data center to configure one or more virtual machines implementing a workload cluster to perform the first network function based on the host profile. The method uses the virtual machine configuration operator to configure one or more virtual machines implementing a management cluster based on the host profile. The workload cluster is managed by the management cluster.