Network resource recommendation using a machine learning model

A computing system comprising:

• one or more processor devices of one or more computing devices, the one or more processor devices configured to:
• receive, from each of a plurality of network devices that compose an access network that is communicatively coupled to a core network, resource utilization information comprising one or more of central processor utilization, memory utilization, and device load values;
• provide the resource utilization information to a machine learning model to receive an output, wherein the machine learning model has been trained with historical resource utilization information associated with network devices that compose an access network, predetermined thresholds, and an impact to the access network of network resources being added to a core network;
• and
• based on the output, send, to a destination a recommended increase in network resources of the core network or the access network.

A non-transitory computer-readable storage medium that includes executable instructions configured to cause one or more processor devices to:

• receive, from each of a plurality of network devices that compose an access network that is communicatively coupled to a core network, resource utilization information comprising one or more of central processor utilization, memory utilization, and device load values;
• provide the resource utilization information to a machine learning model to receive an output, wherein the machine learning model has been trained with historical resource utilization information associated with network devices that compose an access network, predetermined thresholds, and an impact to the access network of network resources being added to a core network;
• and
• based on the output, send, to a destination a recommended increase in network resources of the core network or the access network.