Component monitoring framework

1. A method, comprising:

collecting data corresponding to a plurality of components in a system, wherein the data comprises information about one or more issues associated with the plurality of components;

using one or more machine learning models to analyze the data and categorize the data based at least in part on the analysis to determine at least one component type and issue type for the one or more issues associated with the plurality of components;

selecting from a plurality of application programming interfaces (APIs) two or more APIs that are configured to monitor respective statuses of the plurality of components, wherein the selection is based at least in part on the APIs of the plurality of APIs which correspond to the categorized data, the determined component type, and the issue type for the one or more issues associated with the plurality of components;

pushing portions of the data to corresponding ones of the two or more selected APIs;

retrieving code associated with one or more of the plurality of components, wherein the code is associated with the one or more issues associated with the plurality of components;

parsing the code;

generating a graphical representation of the code for display on a user interface based at least in part on the parsing, wherein the two or more selected APIs are used to generate the graphical representation of the code, and wherein the graphical representation of the code illustrates one or more connections and one or more data transfers between at least two elements caused by execution of the code;

identifying one or more anticipated failures associated with one or more of the plurality of components identified in the one or more issues; and

facilitating reprocessing of transactions associated with the anticipated failures;

wherein the steps of the method are executed by a processing device operatively coupled to a memory.

2. The method of claim 1 , wherein the plurality of components comprise one or more applications, one or more instances of middleware and one or more servers.

3. The method of claim 1 , wherein the plurality of components further comprise one or more virtual machines.

4. The method of claim 1 , further comprising:

receiving the respective statuses of the one or more components; and generating one or more visualizations depicting one or more of the respective statuses.

5. The method of claim 4 , wherein the one or more respective statuses comprise an operating status of one or more applications.

6. The method of claim 4 , wherein the one or more respective statuses comprise a number of queues and a number of consumers corresponding to message-oriented-middleware.

7. The method of claim 6 , wherein the one or more respective statuses further comprise an operating status of one or more message channels used by the message-oriented-middleware.

8. The method of claim 4 , wherein the one or more respective statuses comprise an operating status of one or more databases.

9. The method of claim 4 , wherein the one or more respective statuses comprise at least one of an amount and a type of data flowing into and out of a given component of the one or more components.

10. The method of claim 4 , wherein the one or more respective statuses comprise real- time statuses.

11. The method of claim 1 , wherein the at least two elements comprise a source system and a target system.

12. The method of claim 1 , wherein the data is collected from one or more electronic mail messages sent in response to the one or more issues.

13. The method of claim 1 , wherein the data is collected from one or more component logs.

14. The method of claim 1 , further comprising:

receiving the respective statuses of the one or more components; and

identifying a given one of the one or more components missing a service level agreement (SLA) based at least in part on the received respective statuses.

15. The method of claim 1 , further comprising:

receiving the respective statuses of the one or more components; and

identifying one or more redundant transactions associated with the one or more components based at least in part on the received respective statuses.

16. An apparatus comprising:

a processing device operatively coupled to a memory and configured to:

collect data corresponding to a plurality of components in a system, wherein the data comprises information about one or more issues associated with the plurality of components;

use one or more machine learning models to analyze the data and categorize the data based at least in part on the analysis to determine at least one component type and issue type for the one or more issues associated with the plurality of components;

select from a plurality of application programming interfaces (APIs) two or more APIs that are configured to monitor respective statuses of the plurality of components, wherein the selection is based at least in part on the APIs of the plurality of APIs which correspond to the categorized data, the determined component type, and the issue type for the one or more issues associated with the plurality of components;

push portions of the data to corresponding ones of the two or more selected APIs;

retrieve code associated with one or more of the plurality of components, wherein the code is associated with the one or more issues associated with the plurality of components;

parse the code;

generate a graphical representation of the code for display on a user interface based at least in part on the parsing, wherein the two or more selected APIs are used to generate the graphical representation of the code, and wherein the graphical representation of the code illustrates one or more connections and one or more data transfers between at least two elements caused by execution of the code;

identify one or more anticipated failures associated with one or more of the plurality of components identified in the one or more issues; and

facilitate reprocessing of transactions associated with the anticipated failures.

17. The apparatus of claim 16 , wherein the processing device is further configured to:

receive the respective statuses of the one or more components; and

generate one or more visualizations depicting one or more of the respective statuses.

18. An article of manufacture 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 said at least one processing device to perform the steps of:

collecting data corresponding to a plurality of components in a system, wherein the data comprises information about one or more issues associated with the plurality of components;

using one or more machine learning models to analyze the data and categorize the data based at least in part on the analysis to determine at least one component type and issue type for the one or more issues associated with the plurality of components;

selecting from a plurality of application programming interfaces (APIs) two or more APIs that are configured to monitor respective statuses of the plurality of components, wherein the selection is based at least in part on the APIs of the plurality of APIs which correspond to the categorized data, and the determined component type and the issue type for the one or more issues associated with the plurality of components;

pushing portions of the data to corresponding ones of the two or more selected APIs;

retrieving code associated with one or more of the plurality of components, wherein the code is associated with the one or more issues associated with the plurality of components;

parsing the code;

generating a graphical representation of the code for display on a user interface based at least in part on the parsing, wherein the two or more selected APIs are used to generate the graphical representation of the code, and wherein the graphical representation of the code illustrates one or more connections and one or more data transfers between at least two elements caused by execution of the code;

identifying one or more anticipated failures associated with one or more of the plurality of components identified in the one or more issues; and

facilitating reprocessing of transactions associated with the anticipated failures.

19. The article of manufacture of claim 18 , wherein the program code causes said at least one processing device to further perform the steps of:

receiving the respective statuses of the one or more components; and

generating one or more visualizations depicting one or more of the respective statuses.

20. The article of manufacture of claim 18 wherein the at least two elements comprise a source system and a target system.