To dynamically allow chaining of logical processing units comprising endpoints, at least a type of an endpoint, and address information whereto connect the endpoint is configured, wherein the type of the endpoint is either a host port type or a logical processing unit type. During offloading from a central processing unit one or more functions to be performed by at least one further processing unit, the central processing unit is interacting with the one or more logical processing units via endpoints of the host port type and logical processing units are interacting via endpoints of the logical processing unit port type, the interaction using the address information.

To dynamically allow chaining of logical processing units comprising endpoints, at least a type of an endpoint, and address information whereto connect the endpoint is configured, wherein the type of the endpoint is either a host port type or a logical processing unit type. During offloading from a central processing unit one or more functions to be performed by at least one further processing unit, the central processing unit is interacting with the one or more logical processing units via endpoints of the host port type and logical processing units are interacting via endpoints of the logical processing unit port type, the interaction using the address information.

This document describes modeling and simulation techniques to select a cloud architecture profile based on correlations between application workloads and resource utilization. In some aspects, a method includes obtaining infrastructure data specifying utilization of computing resources of an existing computing system. Application workload data specifying tasks performed by one or more applications running on the existing computing system is obtained. One or more models are generated based on the infrastructure data and the application workload data. The model(s) define an impact on utilization of each computing resource in response to changes in workloads of the application(s). A workload is simulated, using the model(s), on a candidate cloud architecture profile that specifies a set of computing resources. A simulated utilization of each computing resource of the candidate cloud architecture profile is determined based on the simulation. An updated cloud architecture profile is generated based on the simulated utilization.

In one embodiment, dynamic user private networks are virtually segmented within a shared virtual network. A network control system maintains the dynamic logical segmentation of the shared virtual network. User entities (e.g., user devices and/or services) are communicatively coupled to respective personal virtual networks via endpoints of access devices. Each of these endpoints is associated with a corresponding user private network. Responsive in real-time to automated processing of a received electronic particular user request, the network control system automatically modifies the dynamic logical segmentation of the shared virtual network to move a particular user entity on the shared virtual network to newly being on the first dynamic user private network without being disconnected from the shared virtual network. One embodiment uses different user private network identifiers (UPN-IDs) associated with endpoints and received packets to identify their respective user private network.

The subject technology selects a particular zone among multiple zones based on a target skew to meet a global balancing of cluster instances. The subject technology deploys a particular type of cluster instance to the particular zone. The subject technology, for each zone from the multiple zones, determines a respective number of cluster instances. The subject technology identifies a second particular type of cluster instance to remove based on a total number of the second particular type of cluster instance in the multiple zones and a second total number of the particular type of cluster instance in the multiple zones. The subject technology removes the second particular type of cluster instance from a second particular zone to meet the global balancing of cluster instances in the multiple zones.

The present disclosure relates to a baseboard management controller (BMC)-based switch monitoring method, a system, a computer device, and a readable medium thereof. The BMC-based switch monitoring method includes: virtualizing a multi-core BMC into a plurality of logical computers such that each core operates separately; in response to start of a switch, migrating functions of the switch into a first core of the multi-core BMC for start, and monitoring other cores of the multi-core BMC based on a second core of the multi-core BMC; determining, in response to that a new service is received by the switch is detected, whether the new service is a firmware upgrade service; and allocating the new service to the second core in the multi-core BMC for operation, in response to that the new service is the firmware upgrade service.

A service chain accommodation device includes an influence coefficient calculation unit that calculates an influence coefficient indicating that an influence at the time of processing failure of a service chain is greater for a VNF located in a subsequent stage of a service chain and a VNF shared among a plurality of service chains, a residual resource calculation unit that corrects an amount of residual resources that can be accommodated for each of the VNFs through which the service chain passes, and an accommodation design unit that assigns a new service chain on the basis of the amount of the residual resources.

A system and method for a virtual desktop system is disclosed. The system includes a master fabric region including resources for provisioning a desktop. The system includes a plurality of expansion fabric regions. Each of the expansion fabric regions including replicated resources for provisioning the desktop from the master fabric region. The system includes a control plane having a global pool. A client device application operated by a user associated with the global pool accesses a desktop from either the master fabric region or one of the expansion fabric regions. The control plane is operable to add a new expansion fabric region to the plurality of expansion fabric regions or eliminate one of the plurality of expansion fabric regions.

The present disclosure is generally related to edge computing technologies (ECTs), communications networking, network slicing, and in particular, to techniques and technologies for providing flow-specific network slices. In particular, the present disclosure describes mechanisms that expand existing end-to-end architectures in order to include quality of service and monitoring mechanisms that connect network slicing technologies with infrastructure and/or network data center quality of service provider domains. The described mechanisms provide data center bridging to enable network, edge computing, and cloud computing domains.

A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: selecting a service subscription to manage; monitoring asset resource utilization of the subscription service; generating an adaptive service subscription schedule recommendation; and, managing the service subscription based upon the adaptive service schedule recommendation.