A method for subscriber tier plan adjustment including: monitoring traffic flow for one or more subscriber of a plurality of subscribers on an operator’s network; determining a bandwidth requirement for each of the one or more subscribers; determining a recommended tier plan for each subscriber based on the subscribers’ bandwidth requirement; and providing the recommended tier plan for each of the subscribers to a network operator. A system for subscriber tier plan adjustment including: a learning module configured to monitor traffic flow for one or more subscribers of a plurality of subscribers on a network and determine a bandwidth requirement of each of the one or more subscribers; an analysis module configured to determine a recommended tier plan for each of the subscribers based on each subscriber’s bandwidth requirement; and a notification module configured to provide the recommended tier plan for each subscriber.

Systems and methods for detecting, e.g., that a Network Function (NF) service consumer in a core network of a cellular communications system has restarted are disclosed. In some embodiments, a method of operation of a NF service consumer in a core network of a cellular communications system comprises sending, to a NF service producer, a message comprising information related to a unit of the NF service consumer.

Systems and methods for detecting, e.g., that a Network Function (NF) service consumer in a core network of a cellular communications system has restarted are disclosed. In some embodiments, a method of operation of a NF service consumer in a core network of a cellular communications system comprises sending, to a NF service producer, a message comprising information related to a unit of the NF service consumer.

An apparatus to facilitate telemetry targeted query injection for enhanced debugging in microservices architectures is disclosed. The apparatus includes one or more processors to: identify contextual trace of a previous query recorded in collected data of a service, where microservices of the service responded to the previous query; access an interdependency flow graph representing an architecture and interaction of microservices deployed for a service; retrieve, based on the interdependency flow graph, telemetry data of the microservices corresponding to the contextual trace; identify, based on the telemetry data, an activation profile corresponding to the previous query, the activation profile detailing a response of the microservices to the previous query; compare the activation profile to a correlation profile for the previous query to detect whether an anomaly occurred in the service in response to the previous query; and recommend a modified query based on detection of the anomaly.

An apparatus to facilitate telemetry targeted query injection for enhanced debugging in microservices architectures is disclosed. The apparatus includes one or more processors to: identify contextual trace of a previous query recorded in collected data of a service, where microservices of the service responded to the previous query; access an interdependency flow graph representing an architecture and interaction of microservices deployed for a service; retrieve, based on the interdependency flow graph, telemetry data of the microservices corresponding to the contextual trace; identify, based on the telemetry data, an activation profile corresponding to the previous query, the activation profile detailing a response of the microservices to the previous query; compare the activation profile to a correlation profile for the previous query to detect whether an anomaly occurred in the service in response to the previous query; and recommend a modified query based on detection of the anomaly.

During operation, an electronic device receives, from a second electronic device in a network, a request for testing. In response, the electronic device set ups a video call with a video-call service. Then, the electronic device provides, to the second electronic device, an invitation for the video call. When the electronic device receives a notification (e.g., from the video-call service) that the video call has started, the electronic device provides content via the video-call service for the second electronic device. Next, the electronic device obtains communication-performance metrics associated with communication via the network during the video call and video-service performance metrics associated with the video call. Furthermore, the electronic device diagnoses a type of problem experienced at the second electronic device during the video call based at least in part on the communication-performance metrics, the video-service performance metrics and a pretrained machine-learning model.

Embodiments of the present disclosure provide improved data observability mechanisms. Specifically, embodiments provide for managing event-structured observability data in a federated network and database platform. The improved mechanisms enable improved analysis of data-driven errors and/or storage of associated data for purposes of data observability processing actions and/or rendering for user analysis. Example embodiments are configured for receiving a data stream representing operational engagement of an event-structured service hosted by the federated network and database platform. Some example embodiments are further configured for generating event-structured observability data from the data stream utilizing an event processing pipeline. The example embodiments are further configured for storing the event-structured observability data in at least one event-structured observability data repository of the federated network and database platform. The example embodiments are further configured for initiating an event-driven observability action based on the event-structured observability data.

For example, a network management device performs a method. The network management device collects network data of a current network. Then, the network management device generates a simulation network based on the network data of the current network. When there is a network change requirement, the simulation network can be changed based on a simulation change instruction, to obtain data of a changed simulation network. The network management device obtains a connectivity simulation result based on the data of the changed simulation network and a connectivity simulation input parameter. The network data of the current network is collected, so that restoration is performed and an independent simulation network is additionally generated. The simulation network is changed and the network data generated by the changed simulation network and the connectivity simulation input parameter are used to perform connectivity simulation.

For example, a network management device performs a method. The network management device collects network data of a current network. Then, the network management device generates a simulation network based on the network data of the current network. When there is a network change requirement, the simulation network can be changed based on a simulation change instruction, to obtain data of a changed simulation network. The network management device obtains a connectivity simulation result based on the data of the changed simulation network and a connectivity simulation input parameter. The network data of the current network is collected, so that restoration is performed and an independent simulation network is additionally generated. The simulation network is changed and the network data generated by the changed simulation network and the connectivity simulation input parameter are used to perform connectivity simulation.

Methods are provided for recommending actions to improve operability of a network. In one implementation, a method includes acknowledging a plurality of subnetworks in a whole network, each subnetwork including multiple nodes and being represented by a tunnel group having multiple end-to-end tunnels through the subnetwork. The method also includes selecting a first group of subnetworks from the plurality of subnetworks and generating a Reinforcement Learning (RL) agent for each subnetwork of the first group. Each RL agent is based on observations of end-to-end metrics of the end-to-end tunnels of the respective subnetwork. The observations are independent of specific topology information of the subnetwork. Also, the method includes training a global model based on the RL agents of the first group of subnetworks and applying the global model to an Action Recommendation Engine (ARE) configured for recommending actions that can be taken to improve a state of the whole network.