Systems and methods for machine learning-based configuration, repair, and execution of software code using log analysis and prior configuration reuse

A system for automated reconfiguration of computing environments, the system comprising processing circuitry configured to:

• execute software code within a computing environment;
• collect a first execution log generated during the execution of the software code;
• process the first execution log with a first trained machine learning model (MLM) to identify configuration-related failures in the computing environment;
• query a database storing a plurality of historical execution logs associated with prior executions and corresponding configuration repair sets to select a historical log having a statistical similarity to the first execution log using a second trained MLM;
• generate a current configuration repair set for the computing environment using a third trained MLM configured to adapt a configuration repair set corresponding to the selected historical log to a current environment state of the computing environment;
• and
• automatically reconfigure the computing environment by applying the current configuration repair set to resolve the identified configuration-related failures.

A non-transitory computer-readable medium storing thereon computer-executable instructions for automated reconfiguration of computing environments, including instructions for:

• executing software code within a computing environment;
• collecting a first execution log generated during the execution of the software code;
• processing the first execution log with a first trained machine learning model (MLM) to identify configuration-related failures in the computing environment;
• querying a database storing a plurality of historical execution logs associated with prior executions and corresponding configuration repair sets to select a historical log having a statistical similarity to the first execution log using a second trained MLM;
• generating a current configuration repair set for the computing environment using a third trained MLM configured to adapt a configuration repair set corresponding to the selected historical log to a current environment state of the computing environment;
• and
• automatically reconfiguring the computing environment by applying the current configuration repair set to resolve the identified configuration-related failures.