Method and system for validating root cause analysis in an information technology infrastructure

A system for validating a root cause analysis in an Information Technology (IT) infrastructure, comprising:

• a processor;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which when executed by the processor, cause the processor to:
• receive a topology graph corresponding to a root cause of an issue in the IT infrastructure,
• wherein the topology graph comprises a causal node connected to a plurality of impacted nodes, wherein:
• the causal node corresponds to a causal event,
• each of the plurality of impacted nodes correspond to one of a plurality of impacted events;
• determine a relevance classification information and a confidence score for each of the plurality of impacted nodes using a pre-trained multi-class classification model,
• wherein the relevance classification information comprises one of a relevant label or a not-relevant label,
• wherein the multi-class classification model is pre-trained using domain knowledge related to IT infrastructure and historical data, and
• wherein the historical data comprises a set of historically validated topology graphs corresponding to a set of root causes of a set of historical issues in the IT infrastructure;
• and
• determine a validated topology graph corresponding to the root cause based on one or more impacted nodes from the plurality of impacted nodes having the relevant label and the confidence score greater than a predefined threshold.

A non-transitory computer-readable medium storing computer-executable instructions for validating a root cause analysis in an Information Technology (IT) infrastructure, the computer-executable instructions configured for:

• receiving a topology graph corresponding to a root cause of an issue in the IT infrastructure,
• wherein the topology graph comprises a causal node connected to a plurality of impacted nodes, wherein:
• the causal node corresponds to a causal event,
• each of the plurality of impacted nodes correspond to one of a plurality of impacted events;
• determining a relevance classification information, and a confidence score for each of the plurality of impacted nodes using a pre-trained multi-class classification model,
• wherein the relevance classification information comprises one of a relevant label or a not-relevant label,
• wherein the multi-class classification model is pre-trained using domain knowledge related to IT infrastructure and historical data, and
• wherein the historical data comprises a set of historically validated topology graphs corresponding to a set of root causes of a set of historical issues in the IT infrastructure;
• and
• determining a validated topology graph corresponding to the root cause based on one or more impacted nodes from the plurality of impacted nodes having the relevant label and the confidence score greater than a predefined threshold.