Systems and methods for generating recommendations based on real-time mapping of system components in software applications lineage logs

A method for performing automated software code debugging operations based on real-time mapping of system components in software applications lineage logs, the method comprising:

• executing a first process by one or more components in a first software system;
• accessing, via an application programming interface (“API”) layer, a standardized data representation in a computer programming language of a log of event data of the first process being performed by the one or more components in the first software system;
• parsing the log to extract first event data corresponding to the first process;
• accessing, via the API layer, a first artificial intelligence model, wherein the first artificial intelligence model is trained by:
• electronically indexing first training data based on historical software applications lineage logs that indicate respective time stamps, event names, components, or other data for known software system configurations of the one or more components performing known processes;
• electronically indexing second training data based on historical event data, wherein the historical event data is labeled with the respective time stamps, event names, components, or other data for the known software system configurations of the one or more components performing the known processes;
• and
• training, using the first training data and the second training data, the first artificial intelligence model to label patterns or anomalies between the historical software applications lineage logs and the historical event data;
• determining, by the first artificial intelligence model, a first automated software code debugging operation based on comparing the first event data to the patterns or the anomalies to identify an anomaly in code of the first process;
• and
• executing the first automated software code debugging operation by re-writing code used to execute the first process to remove the anomaly.

One or more non-transitory, computer-readable media, comprising instructions that, when executed by one or more processors, cause operations comprises:

• accessing a first input/output path to retrieve a standardized data representation in a computer programming language of a log of event data of a first process being performed by one or more components in a first software system;
• accessing a second input/output path to retrieve first event data corresponding to the first process;
• accessing, via an API layer, a first artificial intelligence model, wherein the first artificial intelligence model is trained by:
• generating first training data based on historical software applications lineage logs that indicate respective time stamps, event names, components, or other data for known software system configurations of the one or more components performing known processes;
• generating second training data based on historical event data, wherein the historical event data is labeled with the respective time stamps, event names, components, or other data for the known software system configurations of the one or more components performing the known processes;
• and
• training, using the first training data and the second training data, the first artificial intelligence model to similarities or differences between the historical event data and the historical software applications lineage logs;
• determining, by the first artificial intelligence model, a first automated software code debugging operation based on comparing the similarities or the differences to the first event data to identify an anomaly in code of the first process;
• and
• executing the first automated software code debugging operation by re-writing code used to execute the first process to remove the anomaly.