Machine learning monitoring of wireless network infrastructure application servers

A system comprising:

• one or more processors;
• and
• one or more non-transitory computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• receiving a first server performance metric associated with a first application server of a wireless communication network, wherein the first server performance metric is associated with a plurality of network service requests processed by the wireless communication network;
• receiving a second server performance metric associated with a second application server of the wireless communication network, wherein the second server performance metric is associated with the plurality of network service requests;
• providing the first server performance metric and the second server performance metric as input to a first machine learning model associated with service degradation and to a second machine learning model associated with anomaly detection or prediction;
• determining a third application server of the wireless communication network, based at least in part on an output of the first machine learning model or the second machine learning model;
• and
• initiating a network operations process associated with the third application server.

One or more non-transitory computer-readable media storing instructions executable by a processor, wherein the instructions, when executed, cause the processor to perform operations comprising:

• receiving a first server performance metric associated with a first charging system node of a wireless communication network, wherein the first server performance metric is associated with a plurality of network service requests processed by the wireless communication network;
• receiving a second server performance metric associated with a second charging system node of the wireless communication network, wherein the second server performance metric is associated with the plurality of network service requests;
• providing the first server performance metric and the second server performance metric as input to a first machine learning model associated with service degradation and to a second machine learning model associated with anomaly detection or prediction;
• determining a third charging system node of the wireless communication network, based at least in part on an output of the first machine learning model or the second machine learning model;
• and
• initiating a network operations process associated with the third charging system node.