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

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

one or more processors; and

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

executing a first process by one or more components in a first software system;

accessing a first input/output path to retrieve, from a distributed file system, a standardized data representation in a computer programming language of a log of event data of the first process 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 and metadata labels for the first event data, wherein the first event data is generated by the one or more components when performing the first process, wherein the first event data comprises a first subset of data that is output by a first component of the one or more components to a second component of the one or more components, and wherein the first event data comprises a second subset of data that is monitored by a third component that is not one of the one or more components;

transforming the first event data into a structured format for a first artificial intelligence model by normalizing the first event data based on the metadata labels;

transmitting, to an application programming interface (“API”) layer housing the first artificial intelligence model, a first API call comprising the first event data in the structured format, 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 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 performing the known processes; and

training, using the first training data and the second training data, the first artificial intelligence model to generate log templates corresponding to processes performed by different known configurations;

determining, by the first artificial intelligence model, a first automated software code debugging operation for the first process based on comparing one or more of the log templates 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 removing the anomaly in the code corresponding to the first event data.

2 . 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.

3 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining, based on the first event data, a first component of the one or more components;

determining a first expected component output of the first component when performing the first process; and

comparing the first expected component output to the first event data.

4 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining a failure likelihood for the one or more components based on the first event data; and

determining first content for the first automated software code debugging operation based on the failure likelihood.

5 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining a first failure likelihood for the one or more components when performing the first process;

determining a dependent component of the one or more components based on the first event data; and

determining a second failure likelihood for the dependent component based on the first failure likelihood.

6 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining a variance from the log for the one or more components based on the first event data; and

determining an update to the log based on the variance.

7 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining, based on the first event data, a first route through the one or more components when performing the first process;

determining, based on the first event data, a first expected route through the one or more components when performing the first process; and

comparing the first route to the first expected route.

8 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining a first error when performing the first process; and

determining, based on the first event data, a first modification corresponding to the first error.

9 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining a second process dependent on the first process;

determining, based on the first event data, a first effect on the second process; and

determining first content for the first automated software code debugging operation based on the first effect.

10 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining, based on the first event data, an impact radius of the first process; and

determining, based on the impact radius, a second process effected by the first process.

11 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining a first error in the one or more components;

determining, based on the first event data, a modification to the one or more components in response to the first error; and

determining first content for the first automated software code debugging operation based on the modification.

12 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining a first error in the log; and

determining, based on the first event data, to throttle processes performed by the one or more components in response to the first error.

13 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining a first code error when executing the first process;

determining, based on the first event data, a modification to code for the one or more components in response to the first code error; and

determining first content for the first automated software code debugging operation based on the modification.

14 . The method of claim 2 , wherein determining the first automated software code debugging operation further comprises:

determining, based on the first event data, an inconsistency between a determined configuration for a first component of the one or more components and an expected configuration based on the log; and

determining first content for the first automated software code debugging operation based on the inconsistency.

15 . The method of claim 2 , wherein retrieving the log further comprises:

receiving a first criterion for testing the one or more components in the first software system performing the first process; and

determining a first component is included in the one or more components based on the log.

16 . 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.

17 . The one or more non-transitory, computer-readable media of claim 16 , wherein determining, by the first artificial intelligence model, the first automated software code debugging operation further comprises:

determining a first component of the one or more components;

determining a first expected component output of the first component when performing the first process; and

comparing the first expected component output to the first event data.

18 . The one or more non-transitory, computer-readable media of claim 16 , wherein determining, by the first artificial intelligence model, the first automated software code debugging operation further comprises:

determining a failure likelihood for the one or more components based on the first event data; and

determining first content for the first automated software code debugging operation based on the failure likelihood.

19 . The one or more non-transitory, computer-readable media of claim 16 , wherein determining the first automated software code debugging operation further comprises:

determining a first error in the log; and

determining, based on the first event data, to throttle processes performed by the one or more components in response to the first error.

20 . The one or more non-transitory, computer-readable media of claim 16 , wherein determining the first automated software code debugging operation further comprises:

determining, based on the first event data, a first route through the one or more components when performing the first process;

determining, based on the first route, a first expected route through the one or more components when performing the first process; and

comparing the first route to the first expected route.