A method (100) for managing resource usage across domains in a communication network is disclosed. The communication network comprises a radio access domain, a core domain and a transport domain providing connectivity between the radio access domain and the core domain. The method comprises receiving from the core domain an indication of load status of gateway nodes in the core domain (110), receiving from the transport domain an indication of load status of transport resources in the transport domain (120), normalising across the core and transport domain a cost of using resources in each domain (130), calculating, on the basis of the normalised costs, optimal chains of resources in the core and transport domains for providing a service from different radio access nodes to different possible Access Point Names (APNs) (140), and sending to the core and transport domains information about the calculated optimal resource chains (150). Also disclosed are methods for managing resource usage in a core domain, a transport domain and a radio access domain of a communication network, together with cross domain, core domain, transport domain and radio access domain control elements.

Embodiments of the present application provide an acceleration management node. The acceleration management node separately receives acceleration device information of all acceleration devices. The acceleration device information includes an algorithm type, an acceleration bandwidth or non-uniform memory access architecture (NUMA). The acceleration management node obtains an invocation request from a client. The acceleration management node queries the acceleration device information to determine, from all the acceleration devices of the at least one acceleration node, a target acceleration device matching the invocation request. The acceleration management node further instructs a target acceleration node to respond to the invocation request.

A method and network node are provided for dimensioning a network service (NS). The method comprises calculating, based on given capacity requirements of the NS, a required number of virtual network functions component (VNFC) instances of each of a plurality of virtual network function (VNF) in the NS; selecting a VNF deployment flavor (VnfDf) for each of the plurality of VNFs in the NS, based on the calculated required number of VNFC instances; generating a network service deployment flavor (NsDf) including the selected VnfDfs; and onboarding a network service descriptor (NSD), which includes the NsDf, for use for instantiating the dimensioned NS.

A method and network node are provided for dimensioning a network service (NS). The method comprises calculating, based on given capacity requirements of the NS, a required number of virtual network functions component (VNFC) instances of each of a plurality of virtual network function (VNF) in the NS; selecting a VNF deployment flavor (VnfDf) for each of the plurality of VNFs in the NS, based on the calculated required number of VNFC instances; generating a network service deployment flavor (NsDf) including the selected VnfDfs; and onboarding a network service descriptor (NSD), which includes the NsDf, for use for instantiating the dimensioned NS.

A method includes creating a package of an application, registering the package with an orchestrator, triggering instantiation of the application in the orchestrator, generating initial configuration files for the instantiation of the application, changing an application state of the application to a planned state, changing the application state to a Keycloak state in response to obtaining client identification of the Keycloak information for the application, changing the application state to an instantiated state in response to deploying the application on the set of target servers, changing the application state to a configured state in response applying daily configuration files to perform daily configuration of the application in the set of target servers, and changing the application state to a monitored state in response to monitoring the application in the set of target servers by an observability framework tool.

A computer-implemented method includes receiving a request to provision a set of storage volumes for a server cluster, wherein the request includes an identifier for the server cluster and generating a provisioning work ticket for each storage volume in the set of storage volumes, each provisioning work ticket including the identifier for the server cluster. The provisioning work tickets are provided to a message broker. Multiple volume provisioning instances are executed such that at least two of the volume provisioning instances operate in parallel with each other and such that each volume provisioning instance receives a respective provisioning work ticket from the message broker and attempts to provision a respective storage volume of the set of storage volumes for the server cluster in response to receiving the volume provisioning work ticket.

Techniques are described for sharing prepopulated container image caches among container execution environments to improve the performance of container launches. The container images used to prepopulate such a cache at a computing device supporting one or more container execution environments can include various container images that are used as the basis for a wide range of user-created containers such as, for example, container images representing popular operating system distributions, database servers, web-application frameworks, and so forth. Existing systems typically obtain these container images as needed at runtime when launching containers (for example, from a container registry or other external source), often incurring significant overhead in the container launch process. The use of a prepopulated container image cache can significantly improve the performance of container launches by making such commonly used container images available to container execution environments running at a computing device ahead of time.

Techniques discussed herein relate to providing composable edge devices. In some embodiments, a user request specifying a set of services to be executed at a cloud-computing edge device may be received by a computing device operated by a cloud computing provider. A manifest may be generated in accordance with the user request. The manifest may specify a configuration for the cloud-computing edge device. Another request can be received specifying the same or a different set of services to be executed at another edge device. Another manifest which specifies the configuration for that edge device may be generated and subsequently used to provision the request set of services on that device. In this manner, manifests can be used to compose the platform to be utilized at any given edge device.

In general, techniques are described for network connectivity for non-colocated customers of a cloud exchange. A programmable network platform for the cloud exchange comprises processing circuitry configured to: configure a virtual network device in the data center to run a network service for a customer; receive, from the customer, a request for a remote port and network information for a network service provider connectivity service for the customer; assign, in response to receiving the request for the remote port, a remote port of the cloud exchange to the customer; and configure, in response to receiving the request for the remote port using the network information, the cloud exchange to connect the network service provider connectivity service to the virtual network device via the remote port of the cloud exchange.

Various systems and methods for implementing an edge computing system to realize 5G network slices with blockchain traceability for informed 5G service supply chain are disclosed. A system configured to track network slicing operations includes memory and processing circuitry configured to select a network slice instance (NSI) from a plurality of available NSIs based on an NSI type specified by a client node. The available NSIs uses virtualized network resources of a first network resource provider. The client node is associated with the selected NSI. The utilization of the network resources by the plurality of available NSIs is determined using an artificial intelligence (AI)-based network inferencing function. A ledger entry of associating the selected NSI with the client node is recorded in a distributed ledger, which further includes a second ledger entry indicating allocations of resource subsets to each of the NSIs based on the utilization.