A system and method for recovering application authentication with an application server by using an exponential back-off procedure via push notifications is discussed herein. The system allows for authentication of a user account after network outages or service disruptions without traffic overload during recovery. A user equipment (UE) receives a failed registration notification after a failed registration attempt of the user account with an application server associated with the application. A push notification includes an instruction that causes the application to switch from an inactive state to a temporary active state. The push notification is sent from a push notification service in response to a push request from a notification server based on a recovery request from the UE due to the failed registration notification. While the application is in the temporary active state, the instruction further causes the application to request registration with the application server.

Techniques for automated incident triage and diagnosis are described. A method of automated incident triage and diagnosis may include receiving incident data associated with an incident, identifying one or more mitigation actions to resolve the incident using at least one machine learning model based at least on the incident data, and automatically executing the one or more mitigation actions to mitigate the incident.

Architectures and techniques are presented that provide an improved mechanism for a subscriber entity to report to a network provider a network issue that affects the performance of an application that uses a service provided by the network provider. The improved mechanism can enable fine granularity with respect to the network issue by identifying the issue on a per-session basis. In response to feedback data that is reported by the subscriber entity, the network provider can perform self-healing or other upgrade techniques to rapidly remedy the network issue.

A device is configured to detect a triggering event within a network that is associated with a communication error between a first network device and a second network device. The device is further configured to identify a first node in a computer network map corresponding with the first network device and to identify node properties for the first node. The device is further configured to identify the error correction instructions in the node properties for the first node that include an address for rerouting data traffic to a third network device. The device is further configured to apply the error correction instructions where applying the error correction instructions suspends data traffic to the second network device and reroutes data traffic to the third network device.

A device is configured to detect a triggering event within a network that is associated with a communication error between a first network device and a second network device. The device is further configured to identify a first node in a computer network map corresponding with the first network device and to identify node properties for the first node. The device is further configured to identify the error correction instructions in the node properties for the first node that include an address for rerouting data traffic to a third network device. The device is further configured to apply the error correction instructions where applying the error correction instructions suspends data traffic to the second network device and reroutes data traffic to the third network device.

An endpoint computing device multi-network slice remediation/productivity system includes a core network system coupled to a RAN system and configured to allocate network slices and make them available for use in wireless communications via the RAN system. While operating in a pre-boot environment, an endpoint computing device determines that it is unable to transition to operating in a runtime environment and, in response, establishes a remediation network connection with a first network slice, and establishes a productivity network connection with a second network slice. While operating in a pre-boot environment and performing the remediation operations, the endpoint computing device then performs remediation operations via remediation wireless communications over the remediation network connection with the first network slice, and provides access to productivity application(s) that are configured to allow a user to perform productivity operations via productivity wireless communications over the productivity network connection with the second network slice.

An endpoint computing device multi-network slice remediation/productivity system includes a core network system coupled to a RAN system and configured to allocate network slices and make them available for use in wireless communications via the RAN system. While operating in a pre-boot environment, an endpoint computing device determines that it is unable to transition to operating in a runtime environment and, in response, establishes a remediation network connection with a first network slice, and establishes a productivity network connection with a second network slice. While operating in a pre-boot environment and performing the remediation operations, the endpoint computing device then performs remediation operations via remediation wireless communications over the remediation network connection with the first network slice, and provides access to productivity application(s) that are configured to allow a user to perform productivity operations via productivity wireless communications over the productivity network connection with the second network slice.

Disclosed here is a system to automatically predict and resolve issues within a telecommunication network. Initially, the system builds a service registry to store dependence information within the network, which can include software components and hardware components. Various components of the network create logs of their operations. Machine learning models examine the logs and detect any issues. Upon detecting an issue or abnormal event, the system can automatically resolve the issue by determining the most similar issue occurring previously and determining a solution that resolved the previous most similar issue. In addition, the system can propagate the fix to dependent systems and/or notify the dependent systems of the issue.

Disclosed here is a system to automatically predict and resolve issues within a telecommunication network. Initially, the system builds a service registry to store dependence information within the network, which can include software components and hardware components. Various components of the network create logs of their operations. Machine learning models examine the logs and detect any issues. Upon detecting an issue or abnormal event, the system can automatically resolve the issue by determining the most similar issue occurring previously and determining a solution that resolved the previous most similar issue. In addition, the system can propagate the fix to dependent systems and/or notify the dependent systems of the issue.

Methods and systems for autonomous computing comprising processing historical data to analyze a past performance, collecting data from a plurality of connected devices over a network, synchronizing the collected data from the plurality of connected devices with the processed historical data. Based on the synchronized data, methods and systems disclosed include detecting an alert (error/fault) condition in one or more of the plurality of connected devices, based on the detected alert condition, triggering the delivery of the detected alert condition to an automated network operations center (NOC), and matching the determined alert condition to a historical alert condition by the network operations center. Based on the matching, methods and systems include determining a corrective action, and based on the determined corrective action, assigning a virtual self-healing module from a plurality of virtual self-healing modules. Finally, a trigger to performance of the determined corrective action by the assigned virtual self-healing module is initiated.