Technologies for dynamically managing resources in disaggregated accelerators include an accelerator. The accelerator includes acceleration circuitry with multiple logic portions, each capable of executing a different workload. Additionally, the accelerator includes communication circuitry to receive a workload to be executed by a logic portion of the accelerator and a dynamic resource allocation logic unit to identify a resource utilization threshold associated with one or more shared resources of the accelerator to be used by a logic portion in the execution of the workload, limit, as a function of the resource utilization threshold, the utilization of the one or more shared resources by the logic portion as the logic portion executes the workload, and subsequently adjust the resource utilization threshold as the workload is executed. Other embodiments are also described and claimed.

A method for end point data communications anonymization for a local communications hub is provided. The method commences with receiving a first request addressed to a server from a computing device. The method further includes selecting a first remote communications hub from a plurality of remote communications hubs. The method continues with modifying the first request to generate a first modified request and sending the first modified request to the first remote communications hub. The first remote communications hub modifies the first modified request to produce a second modified request and forwards the second modified request to the server. The method further includes receiving a first response to the second modified request from the server, modifying the received first response to produce a first modified response, modifying the first modified response to produce a second modified response, and providing the second modified response to the computing device.

A bandwidth sharing method and device based on SDN control of terminal cell are disclosed. The bandwidth sharing method includes: determining, by a SDN controller, whether a trigger request for bandwidth sharing is received; upon receipt of the trigger request, selecting at least one second terminal cell for providing bandwidth sharing to the first terminal cell; controlling the first terminal cell and the at least one second terminal cell to jointly process the target service. The trigger request indicates a need of bandwidth sharing of a first terminal cell from other terminal cells when processing a target service on a backhaul link, and a bandwidth requirement of the target service equals to or exceeds a first predetermined threshold. The SDN controlled bandwidth-sharing scheme may ensure the application of a wireless backhaul sharing mechanism between T-SCs, thereby achieving flexible configuration of bandwidth resources on the backhaul link.

Technologies for switching network traffic include a network switch. The network switch includes one or more processors and communication circuitry coupled to the one or more processors. The communication circuitry is capable of switching network traffic of multiple link layer protocols. Additionally, the network switch includes one or more memory devices storing instructions that, when executed, cause the network switch to receive, with the communication circuitry through an optical connection, network traffic to be forwarded, and determine a link layer protocol of the received network traffic. The instructions additionally cause the network switch to forward the network traffic as a function of the determined link layer protocol. Other embodiments are also described and claimed.

Described herein is a system for automatically capturing configuration changes to the cloud computing resources. The system for automatically capturing configuration changes may detect changes to configurations of cloud computing resources across the geographic regions, in real-time. The changes may be stored in a central data storage device instantiated by a central cloud computing account. Furthermore, a relationship graph indicating the relationships between the different cloud computing resources may be generated.

A device configured to receive a data set and instructions for processing the data set from a network device. The device is further configured to parse the data set into a plurality of data segments to be processed, and generate a plurality of instruction segments from the received instructions. The device is further configured to assign each instruction segment to a resource unit, and to generate control information with instructions for combining processed data segments from the resource units. The device is further configured to receive processed data segments from the resource units, to generate the processed data set, and to output the processed data set to the network device.

A method, a device, and a non-transitory storage medium are described in which a containerized network function (CNF) management service is provided. The service may provide for allocating discrete sets of CNF resources deployed as pods to provide application services to end devices; identifying at least one threshold resource value associated with a first number of the deployed pods which are activated to provide the application services; determining an anticipated nonsatisfaction of the at least one threshold resource value associated with the first number of the deployed pods; and invoking, for a period of time, horizontal pod autoscaling (HPA) via an application programming interface to activate a second number of the deployed pods to provide the application services, wherein the HPA is performed non-incrementally until at least one of the period of time has elapsed or each of the deployed pods has been activated to provide the application services.

A method, a device, and a non-transitory storage medium are described in which a containerized network function (CNF) management service is provided. The service may provide for allocating discrete sets of CNF resources deployed as pods to provide application services to end devices; identifying at least one threshold resource value associated with a first number of the deployed pods which are activated to provide the application services; determining an anticipated nonsatisfaction of the at least one threshold resource value associated with the first number of the deployed pods; and invoking, for a period of time, horizontal pod autoscaling (HPA) via an application programming interface to activate a second number of the deployed pods to provide the application services, wherein the HPA is performed non-incrementally until at least one of the period of time has elapsed or each of the deployed pods has been activated to provide the application services.

A computer system to track and enhance performance of a virtual workspace system is provided. The computer system receives requests to profile phases of a distributed process executed by hosts coupled to one another via a network. Each of phase includes operations executed by processes hosted by the hosts. Each of phase either starts with receipt of a request via a user interface of a virtualization client or ends with provision of a response to the request via the user interface. The computer system identifies event log entries that each include an identifier of an event marking a start or an end of one of the operations, constructs a performance profile based on the event log entries, and transmits the performance profile to the user interface.

A computer system to track and enhance performance of a virtual workspace system is provided. The computer system receives requests to profile phases of a distributed process executed by hosts coupled to one another via a network. Each of phase includes operations executed by processes hosted by the hosts. Each of phase either starts with receipt of a request via a user interface of a virtualization client or ends with provision of a response to the request via the user interface. The computer system identifies event log entries that each include an identifier of an event marking a start or an end of one of the operations, constructs a performance profile based on the event log entries, and transmits the performance profile to the user interface.