Data processing system with machine learning engine to provide enterprise monitoring functions

• US 10,313,441 B2
• Filed: 02/13/2017
• Issued: 06/04/2019
• Est. Priority Date: 02/13/2017
• Status: Active Grant

• Current Assignee: Bank of America Corp.
• Original Assignee: Bank of America Corp.
• Inventors: Moiyallah, Jr., Samuel Massa, Castinado, Joseph Benjamin
• Primary Examiner(s): Duong, Oanh
• Application Number:
  US15/430,951
• Publication Number:
  US 20180234325A1
• Time in Patent Office: 841 Days
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04L 67/1097 for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]

Abstract

Aspects of the disclosure relate to implementing and using a data processing system with a machine learning engine to provide enterprise monitoring functions. A computing platform may receive environment mapping data from a distributed computing environment. Subsequently, the computing platform may generate a machine learning dataset based on the environment mapping data. Then, the computing platform may validate the machine learning dataset and may monitor the distributed computing environment. Based on monitoring the distributed computing environment, the computing platform may detect an environmental modification in the distributed computing environment. After detecting the environmental modification in the distributed computing environment, the computing platform may receive updated environment mapping data from the distributed computing environment. Subsequently, the computing platform may generate an updated machine learning dataset based on the updated environment mapping data received from the distributed computing environment.

Claims

1. A computing platform, comprising:

at least one processor;

a communication interface communicatively coupled to the at least one processor; and

memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to;

generate one or more environment scan commands directing one or more hardware elements included in a distributed computing environment to provide mapping data;

send, via the communication interface, to the distributed computing environment, the one or more environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide the mapping data;

receive, via the communication interface, environment mapping data from a-the distributed computing environment;

generate a machine learning dataset based on the environment mapping data received from the distributed computing environment;

validate the machine learning dataset generated based on the environment mapping data received from the distributed computing environment;

monitor the distributed computing environment;

based on monitoring the distributed computing environment, detect an environmental modification in the distributed computing environment;

in response to detecting the environmental modification in the distributed computing environment, generate one or more updated environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide updated mapping data;

send, via the communication interface, to the distributed computing environment, the one or more updated environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide the updated mapping data;

after detecting the environmental modification in the distributed computing environment, receive, via the communication interface, updated environment mapping data from the distributed computing environment; and

generate an updated machine learning dataset based on the updated environment mapping data received from the distributed computing environment.

2. The computing platform of claim 1, wherein receiving the environment mapping data from the distributed computing environment comprises receiving a first portion of the environment mapping data from one or more enterprise servers located in at least one data center associated with the distributed computing environment and receiving a second portion of the environment mapping data from one or more cloud servers associated with the distributed computing environment.

3. The computing platform of claim 1, wherein generating the machine learning dataset based on the environment mapping data received from the distributed computing environment comprises identifying one or more servers, switches, and other hardware elements included in the distributed computing environment and identifying one or more applications, libraries, and other software elements included in the distributed computing environment.

4. The computing platform of claim 3, wherein identifying the one or more servers, switches, and other hardware elements included in the distributed computing environment comprises tracking at least one hardware-software transaction flow using one or more trace identifiers.

5. The computing platform of claim 1, wherein detecting the environmental modification in the distributed computing environment comprises detecting one or more new hardware elements in the distributed computing environment.

6. The computing platform of claim 1, wherein detecting the environmental modification in the distributed computing environment comprises detecting one or more new software elements in the distributed computing environment.

7. The computing platform of claim 1, wherein validating the machine learning dataset generated based on the environment mapping data received from the distributed computing environment comprises validating the machine learning dataset based on input received from one or more user computing devices.

8. The computing platform of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

validate the updated machine learning dataset generated based on the updated environment mapping data received from the distributed computing environment.

9. The computing platform of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

monitor one or more activities in the distributed computing environment;

based on monitoring the one or more activities in the distributed computing environment, generate at least one activity issue notification; and

send, via the communication interface, to at least one user device, the at least one activity issue notification generated based on monitoring the one or more activities in the distributed computing environment.

10. The computing platform of claim 9, wherein the at least one activity issue notification generated based on monitoring the one or more activities in the distributed computing environment comprises an indication that a workload level of at least one hardware element included in the distributed computing environment exceeds a predetermined threshold.

11. The computing platform of claim 9, wherein the at least one activity issue notification generated based on monitoring the one or more activities in the distributed computing environment comprises an indication that a technical issue encountered by at least one hardware element included in the distributed computing environment results from at least one root cause determined by the computing platform based on the updated machine learning dataset.

12. The computing platform of claim 1, wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

receive, via the communication interface, from at least one user device, information identifying one or more proposed changes to one or more hardware elements included in the distributed computing environment or one or more software elements included in the distributed computing environment;

in response to receiving the information identifying the one or more proposed changes to the one or more hardware elements included in the distributed computing environment or the one or more software elements included in the distributed computing environment, generate, based on the updated machine learning dataset, a listing of one or more predicted issues arising from the one or more proposed changes to the one or more hardware elements included in the distributed computing environment or the one or more software elements included in the distributed computing environment;

generate a notification for the at least one user device, the notification comprising the listing of the one or more predicted issues arising from the one or more proposed changes to the one or more hardware elements included in the distributed computing environment or the one or more software elements included in the distributed computing environment; and

send, via the communication interface, to the at least one user device, the notification generated for the at least one user device.

13. A method, comprising:

at a computing platform comprising at least one processor, memory, and a communication interface;

generating, by the at least one processor, one or more environment scan commands directing one or more hardware elements included in a distributed computing environment to provide mapping data;

sending, by the at least one processor, via the communication interface, to the distributed computing environment, the one or more environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide the mapping data;

receiving, by the at least one processor, via the communication interface, environment mapping data from the distributed computing environment;

generating, by the at least one processor, a machine learning dataset based on the environment mapping data received from the distributed computing environment;

validating, by the at least one processor, the machine learning dataset generated based on the environment mapping data received from the distributed computing environment;

monitoring, by the at least one processor, the distributed computing environment;

based on monitoring the distributed computing environment, detecting, by the at least one processor, an environmental modification in the distributed computing environment;

in response to detecting the environmental modification in the distributed computing environment, generating, by the at least one processor, one or more updated environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide updated mapping data;

sending, by the at least one processor, via the communication interface, to the distributed computing environment, the one or more updated environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide the updated mapping data;

after detecting the environmental modification in the distributed computing environment, receiving, by the at least one processor, via the communication interface, updated environment mapping data from the distributed computing environment; and

generating, by the at least one processor, an updated machine learning dataset based on the updated environment mapping data received from the distributed computing environment.

14. The method of claim 13, wherein receiving the environment mapping data from the distributed computing environment comprises receiving a first portion of the environment mapping data from one or more enterprise servers located in at least one data center associated with the distributed computing environment and receiving a second portion of the environment mapping data from one or more cloud servers associated with the distributed computing environment.

15. The method of claim 13, wherein generating the machine learning dataset based on the environment mapping data received from the distributed computing environment comprises identifying one or more servers, switches, and other hardware elements included in the distributed computing environment and identifying one or more applications, libraries, and other software elements included in the distributed computing environment.

16. The method of claim 15, wherein identifying the one or more servers, switches, and other hardware elements included in the distributed computing environment comprises tracking at least one hardware-software transaction flow using one or more trace identifiers.

17. The method of claim 13, wherein detecting the environmental modification in the distributed computing environment comprises detecting one or more new hardware elements in the distributed computing environment.

18. One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, memory, and a communication interface, cause the computing platform to:

generate one or more environment scan commands directing one or more hardware elements included in a distributed computing environment to provide mapping data;

send, via the communication interface, to the distributed computing environment, the one or more environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide the mapping data;

receive, via the communication interface, environment mapping data from the distributed computing environment;

generate a machine learning dataset based on the environment mapping data received from the distributed computing environment;

validate the machine learning dataset generated based on the environment mapping data received from the distributed computing environment;

monitor the distributed computing environment;

based on monitoring the distributed computing environment, detect an environmental modification in the distributed computing environment;

in response to detecting the environmental modification in the distributed computing environment, generate one or more updated environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide updated mapping data;

send, via the communication interface, to the distributed computing environment, the one or more updated environment scan commands directing the one or more hardware elements included in the distributed computing environment to provide the updated mapping data;

after detecting the environmental modification in the distributed computing environment, receive, via the communication interface, updated environment mapping data from the distributed computing environment; and

generate an updated machine learning dataset based on the updated environment mapping data received from the distributed computing environment.