Machine learning-based issue remediation utilizing an application topology graph representation

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:

• to determine an incident associated with an application ecosystem comprising a plurality of applications running on an information technology infrastructure, the incident comprising a natural language description of one or more issues encountered in the application ecosystem;
• to generate an application topology graph representation of the application ecosystem, the application topology graph representation comprising a plurality of nodes each representing one of the plurality of applications and edges connecting the nodes representing dependency relationships between the plurality of applications;
• to detect one or more code changes associated with software code of at least one of the plurality of applications in the application ecosystem;
• to update at least one of the plurality of nodes of the application topology graph representation of the application ecosystem representing the at least one application in the application ecosystem with attention information characterizing the detected one or more code changes associated with the software code of the at least one application;
• to process the natural language description of the one or more issues encountered in the application ecosystem and at least a portion of the application topology graph representation of the application ecosystem utilizing a machine learning model, the machine learning model comprising an attention layer configured to perform a semantic search of the application topology graph representation utilizing the attention information;
• to determine, based at least in part on an output of the machine learning model, (i) a subset of the plurality of applications in the application ecosystem as probable sources of the one or more issues encountered in the application ecosystem and (ii) issue resolution information for remediating the one or more issues in the subset of the plurality of applications in the application ecosystem;
• and
• to remediate, in one or more of the applications in the determined subset of the plurality of applications, the one or more issues encountered in the application ecosystem based at least in part on the determined issue resolution information.

A method comprising:

• determining an incident associated with an application ecosystem comprising a plurality of applications running on an information technology infrastructure, the incident comprising a natural language description of one or more issues encountered in the application ecosystem;
• generating an application topology graph representation of the application ecosystem, the application topology graph representation comprising a plurality of nodes each representing one of the plurality of applications and edges connecting the nodes representing dependency relationships between the plurality of applications;
• detecting one or more code changes associated with software code of at least one of the plurality of applications in the application ecosystem;
• updating at least one of the plurality of nodes of the application topology graph representation of the application ecosystem representing the at least one application in the application ecosystem with attention information characterizing the detected one or more code changes associated with the software code of the at least one application;
• processing the natural language description of the one or more issues encountered in the application ecosystem and at least a portion of the application topology graph representation of the application ecosystem utilizing a machine learning model, the machine learning model comprising an attention layer configured to perform a semantic search of the application topology graph representation utilizing the attention information;
• determining, based at least in part on an output of the machine learning model, (i) a subset of the plurality of applications in the application ecosystem as probable sources of the one or more issues encountered in the application ecosystem and (ii) issue resolution information for remediating the one or more issues in the subset of the plurality of applications in the application ecosystem;
• and
• remediating, in one or more of the applications in the determined subset of the plurality of applications, the one or more issues encountered in the application ecosystem based at least in part on the determined issue resolution information;
• wherein the method is performed by at least one processing device comprising a processor coupled to a memory.