Discovery troubleshooting based on machine learning

A non-transitory computer-readable medium, having stored thereon program instructions that, upon execution by a computing system, cause the computing system to perform operations comprising:

• obtaining a discovery pattern that indicates a plurality of operations configured to acquire information about a corresponding computing resource type of a plurality of computing resource types;
• identifying a variable parameter value that is associated with and affects execution of the discovery pattern with respect to a computing resource of the corresponding computing resource type;
• determining, prior to execution of the discovery pattern with respect to the computing resource, an error value by using a machine learning model to process the variable parameter value, wherein the error value indicates a likelihood that execution of the discovery pattern, when associated with the variable parameter value, with respect to the computing resource results in a corresponding error type, and wherein occurrence of an error of the corresponding error type during the execution of the discovery pattern prevents the discovery pattern from obtaining at least some of the information about the computing resource;
• and
• receiving, based on the error value, an input comprising one or more of (i) an instruction to execute the discovery pattern or (ii) a modification applicable to the variable parameter value.

A system comprising:

• one or more processors;
• and
• memory, containing program instructions that, upon execution by the one or more processors, cause the system to perform operations comprising:
• obtaining a discovery pattern that indicates a plurality of operations configured to acquire information about a corresponding computing resource type of a plurality of computing resource types;
• identifying a variable parameter value that is associated with and affects execution of the discovery pattern with respect to a computing resource of the corresponding computing resource type;
• determining, prior to execution of the discovery pattern with respect to the computing resource, an error value by using a machine learning model to process the variable parameter value, wherein the error value indicates a likelihood that execution of the discovery pattern, when associated with the variable parameter value, with respect to the computing resource results in a corresponding error type, and wherein occurrence of an error of the corresponding error type during the execution of the discovery pattern prevents the discovery pattern from obtaining at least some of the information about the computing resource;
• and
• receiving, based on the error value, an input comprising one or more of (i) an instruction to execute the discovery pattern or (ii) a modification applicable to the variable parameter value.