Detection of resource bottlenecks in user devices using artificial intelligence and causal graphs

摘要

Techniques are provided for detection of resource bottlenecks in computing devices. A particular resource bottleneck can be identified as a cause of a current device issue based on a dynamic evaluation, by an anomaly detection module, of performance metrics of a computing device. Once a particular resource bottleneck is identified as anomalous, one or more corresponding adjustments to configuration settings for the computing device can be identified to mitigate the current device issue using a causal graph that represents the dependencies among (i) various issue types for a computing device, (ii) performance metrics of the computing device to evaluate for each issue type, and (iii) one or more resources that may be a cause of a given issue type. The corresponding adjustments to the computing device can be automatically identified based on the resource determined to be the cause of the given device issue type.