Self-optimizing networks

A non-transitory computer-readable medium storing one or more instructions executable by a computer system to perform operations comprising:

• obtaining, from a distributed computing system servicing requests from user devices of a wireless network, information indicating performance metrics of a first set of computing resources of the distributed computing system;
• generating, based on the information indicating performance metrics of the first set of computing resources, information representing usage of the wireless network at a first point in time;
• providing the information representing usage of the wireless network to a machine-learning model trained to predict, based on usage data, network events at a time subsequent to the first point in time;
• determining, based on an output of the machine-learning model, that at least one particular network event predicted in the output is addressable by using a second set of computing resources of the distributed system, the second set of computing resources being different from the first set of computing resources;
• and
• transmitting, responsive to determining that the at least one particular network event is addressable using the second set of computing resources, a signal configured to adjust the distributed computing system to deploy the second set of computing resources.

A system, comprising:

• one or more processors;
• and
• machine-readable media interoperably coupled with the one or more processors and storing one or more instructions that, when executed by the one or more processors, perform operations comprising:
• obtaining, from a distributed computing system servicing requests from user devices of a wireless network, information indicating performance metrics of a first set of computing resources of the distributed computing system;
• generating, based on the information indicating performance metrics of the first set of computing resources, information representing usage of the wireless network at a first point in time;
• providing the information representing usage of the wireless network to a machine-learning model trained to predict, based on usage data, network events at a time subsequent to the first point in time;
• determining, based on an output of the machine-learning model, that at least one particular network event predicted in the output is addressable by using a second set of computing resources of the distributed system, the second set of computing resources being different from the first set of computing resources;
• and
• transmitting, responsive to determining that the at least one particular network event is addressable using the second set of computing resources, a signal configured to adjust the distributed computing system to deploy the second set of computing resources.