This disclosure describes techniques that include determining the health of one or more routing engines included within a router. In one example, this disclosure describes a method that includes performing, by a first routing engine included within a router, routing operations, wherein the router includes a plurality of routing engines, including the first routing engine and a second routing engine; receiving, by a computing system, data including health indicators associated with the first routing engine; applying, by the computing system, a machine learning model to the data to determine, from the health indicators, a health status of the first routing engine, wherein the machine learning model has been trained to identify the health status from the health indicators; and determining, by the computing system and based on the health status of the first routing engine, whether to switch routing operations to the second routing engine from the first routing engine.

A system for troubleshooting network problems is disclosed. A model can use demographic information, network usage information, and network membership information to determine an importance of a problem. The importance of the problem for the user who reported the problem, a number of other users affected by the problem, and the importance of the problem to the other users can be used to determine a priority for resolving the problem. Before and after a work order is executed to resolve the problem, network metrics can be gathered, including aggregate network metrics, and automatically presented in various user interfaces. The analysis of the metrics can be used to update a database of which work orders are assigned in response to which problems.

A fault recovery method and apparatus, and a storage medium are provided, and belong to the field of Internet technologies. In the method, network composition information and abnormal event information of a target network are obtained, where the network composition information includes a network topology of the target network and device information of a plurality of network devices on the target network, and the device information includes one or more of interface configuration information, protocol configuration information, and service configuration information; and then a possible root cause of a fault of the target network is determined based on the network composition information and the abnormal event information, where the possible root cause of the fault is used to determine a corresponding fault recovery plan.

A method in which an enterprise switches its devices to various federated network slices across operators based on cost, time, quality, and/or availability parameters defined in flexible rules managed by the enterprise. The method includes obtaining, by a controller of an enterprise, one or more parameters of a device served by a network slice of a core network. The method further includes, based on the one or more parameters of the device and one or more rules, determining, by the controller, whether a triggering event associated with a slice reselection occurred and based on the triggering event and the one or more rules, selecting, by the controller, a federated network slice from among a plurality of network slices provided by a plurality of core networks. The method further includes the controller causing the device to switch from the network slice to the federated network slice.

A wireless device includes a user interface that generates a pairing signal in response to an indication from a user to pair the wireless device to at least one remote device and generates a first location request signal in response to a second indication from a user to locate the at least one remote device. A short-range wireless transceiver communicates RF signals to pair the wireless device to the at least one remote device and that transmits a first RF paging signal to the at least one remote device in response to the location request signal.

Implementations are directed to improving network anti-fragility. In some aspects, a method includes receiving parameter data from a network of nodes, the parameter data comprising attributes, policies, and action spaces for each node in the network of nodes; configuring one or more interruptive events on one or more nodes included in the network of nodes; determining a first action of each node in the network of nodes in response to the one or more interruptive events; determining a first performance metric, for each node, that corresponds to the first action, wherein the first performance matric is determined based on at least a first reward value associated with the first action; continuously updating the first action in an iterative process to obtain a final action, wherein a performance metric corresponding to the final action satisfies a performance threshold, and transmitting the final action for each node to the network of nodes.

Methods and systems are disclosed for configuring a network consisting of an IP Policy Management (IPPM) service and a plurality of distributed network devices supporting DHCP and other service roles wherein network devices are discovered by the IPPM service and the configuration for each of the network devices is determined by the selection of a policy, wherein the policy is made up of a plurality of rules specific to the service roles and capabilities of the network devices, and the configuration of each of the network devices is deployed via the network to the network devices.

A system and method for recommending a similar incident in operations technologies and a related device are provided. The method includes: obtaining alarm information of a to-be-processed incident; obtaining incident diagnosis information of M dimensions based on the alarm information, wherein the M dimensions include M different perspectives of incident diagnosis, and M is an integer greater than 1; performing processing based on the incident diagnosis information of the M dimensions, to obtain a feature of the to-be-processed incident; obtaining a plurality of similarity degrees through calculation based on the feature of the to-be-processed incident and features of a plurality of historical incidents, wherein the plurality of similarity degrees represent respective similarity degrees between the to-be-processed incident and the plurality of historical incidents; and obtaining a similar incident from the plurality of historical incidents through filtering based on the plurality of similarity degrees, and recommending the similar incident.

A system and method for recommending a similar incident in operations technologies and a related device are provided. The method includes: obtaining alarm information of a to-be-processed incident; obtaining incident diagnosis information of M dimensions based on the alarm information, wherein the M dimensions include M different perspectives of incident diagnosis, and M is an integer greater than 1; performing processing based on the incident diagnosis information of the M dimensions, to obtain a feature of the to-be-processed incident; obtaining a plurality of similarity degrees through calculation based on the feature of the to-be-processed incident and features of a plurality of historical incidents, wherein the plurality of similarity degrees represent respective similarity degrees between the to-be-processed incident and the plurality of historical incidents; and obtaining a similar incident from the plurality of historical incidents through filtering based on the plurality of similarity degrees, and recommending the similar incident.

Example techniques for adaptive time window-based log message deduplication are described. In an example, message values are obtained from received log messages. Further, the number of log messages received in a time window having a message value is counted. A log message from which the message value is obtained and the counted number are transmitted upon expiry of the time window. A length of a time window in which a subsequent counting of log messages is to be performed is determined based on various parameters.