Using Cognitive Technologies to Identify and Resolve Issues in a Distributed Infrastructure

A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on at least one processor of a data processing system, causes the data processing system to implement a log error processor, a machine learning model, an operation extraction component, a classifier component, a solution scorer component, and an operation execution engine, wherein the computer readable program causes the data processing system to:

• monitor, by the log error processor, error logs of a plurality of data processing nodes within the distributed infrastructure;
• in response to the log error processor detecting an error in a given node within the distributed infrastructure, provide error data for the error to the machine learning model and receiving from the machine learning model a set of potential solutions and associated confidence values;
• extract, by the operation extraction component from each potential solution in the set of potential solutions, a set of operations to resolve the error;
• map, by the classifier component, each set of operations to a set of executable operations that are executable by the given node;
• determine, by the solution scorer component, whether to perform automatic resolution using a selected potential solution and its corresponding set of executable operations;
• and
• in response to the solution scorer component determining to perform automatic resolution, execute, by the operation execution engine, the corresponding set of executable operations on the given node.

An apparatus comprising:

• a processor;
• and
• a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to implement a log error processor, a machine learning model, an operation extraction component, a classifier component, a solution scorer component, and an operation execution engine, wherein the instructions cause the processor to:
• monitor, by the log error processor, error logs of a plurality of data processing nodes within the distributed infrastructure;
• in response to the log error processor detecting an error in a given node within the distributed infrastructure, provide error data for the error to the machine learning model and receiving from the machine learning model a set of potential solutions and associated confidence values;
• extract, by the operation extraction component from each potential solution in the set of potential solutions, a set of operations to resolve the error;
• map, by the classifier component, each set of operations to a set of executable operations that are executable by the given node;
• determine, by the solution scorer component, whether to perform automatic resolution using a selected potential solution and its corresponding set of executable operations;
• and
• in response to the solution scorer component determining to perform automatic resolution, execute, by the operation execution engine, the corresponding set of executable operations on the given node.