Artificial intelligence and tracing-enabled automated healing for mobile device deployments

A non-transitory computer readable storage medium comprising instructions, that when executed by one or more processors of a computing system, cause the computing system to:

• execute, by one or more user devices, a mobile application including a product flow, wherein the product flow includes a flag point comprising a switch configured to enable or disable a corresponding application component;
• determine, by a healing module, a health status of the product flow based on evaluating resource utilization for the one or more user devices executing the mobile application using a machine learning model trained through an iterative supervised learning process using training data comprising past resource utilization values associated with ground truth labels;
• in response to the health status of the product flow indicating a problem with the corresponding application component, produce, by the healing module, a healed product flow by disabling the corresponding application feature using the switch;
• and
• execute, by one or more user devices, the mobile application with the healed product flow.

A system comprising:

• a mobile application distribution platform;
• a healing module;
• and
• a user device in networked communication with the healing module, the user device executing a mobile application received from the mobile application distribution platform, and the mobile application including a product flow, wherein the product flow includes a flag point comprising a switch configured to enable or disable a corresponding application component;
• and wherein:
• the healing module comprises a memory having executable instructions stored thereon;
• and
• one or more processors configured to execute the executable instructions to cause the healing module to:
• determine a health status of the product flow based on evaluating resource utilization for the user device executing the mobile application using a machine learning model trained through an iterative supervised learning process using training data comprising past resource utilization values associated with ground truth labels;
• and
• in response to the health status of the product flow indicating a problem with the corresponding application component, produce a healed product flow by disabling the corresponding application feature using the switch, wherein the user device executes the mobile application with the healed product flow.