Process automation action repository and assembler

• US 10,606,687 B2
• Filed: 12/04/2017
• Issued: 03/31/2020
• Est. Priority Date: 12/04/2017
• Status: Active Grant

• Current Assignee: Bank of America Corp.
• Original Assignee: Bank of America Corp.
• Inventors: Purushothaman, Sasidhar
• Primary Examiner(s): McCarthy, Christopher S
• Application Number:
  US15/830,206
• Publication Number:
  US 20190171513A1
• Time in Patent Office: 848 Days
• CPC Class Codes: B25J 9/1605 Simulation of manipulator lay-out, design, modelling of manipulator
• CPC Class Codes: G06F 11/0709 in a distributed system consisting of a plurality of standalone computer nodes, e.g. clusters, client-server systems
• CPC Class Codes: G06F 11/0736 in functional embedded systems, i.e. in a data processing system designed as a combination of hardware and software dedicated to performing a certain function testing or monitoring of automated control systems G05B23/02
• CPC Class Codes: G06F 11/0748 in a remote unit communicating with a single-box computer node experiencing an error/fault remote testing G06F11/2294
• CPC Class Codes: G06F 11/0751 Error or fault detection not based on redundancy power supply failures G06F1/30; network fault management H04L41/06
• CPC Class Codes: G06F 11/0787 Storage of error reports, e.g. persistent data storage, storage using memory protection
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 11/0793 Remedial or corrective actions recovery from an exception in an instruction pipeline G06F9/3861; by retry G06F11/1402; for recovering from a failure of a protocol instance or entity H04L69/40
• CPC Class Codes: G06F 8/30 Creation or generation of source code
• CPC Class Codes: G06F 8/60 Software deployment
• CPC Class Codes: G06F 9/455 Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04L 41/0654 using network fault recovery ring fault isolation or reconfiguration in loop networks without recovery actions by a network management system H04L12/437
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence

Abstract

A system for remediating computing-related events by taking into account the past performance of remediation processes and the current run-time environment in which the remedy will be deployed. Robotic Process Automation is implemented to identify computing-related events requiring automation and to record actions that are taken to remediate the events. Robotic scripts (bots) are created based on the recorded actions and are implemented in a learning-mode, in which run-time conditions and level of performance are recorded, such that, run-time conditions and performance are determinative of which bot or combination of bots are implemented for subsequent occurrence of computing-related events. Additionally, remedial process associated with the bot(s) may be executed in a simulated environment prior to the production run-time computing environment to validate the bot and insure the likelihood of effective performance of the remedial process in the run-time production environment.

Claims

1. A system for remediating computing-related events, the system comprising:

a computing platform including a memory and at least one processor in communication with the first memory;

a first robotic process automation (RPA) module stored in the memory, executable by the at least one processor and configured to monitor a computing environment to detect occurrences of a computing-related event, wherein the computing-related event is a behavior occurring within the computing environment that deviates from a normal state;

a second RPA module stored in the memory, executable by the at least one processor and configured to, in response to receiving notification, from the first RPA module, of each occurrence of the computing-related event;

record actions performed to remediate the computing-related event, and

create a robotic script (bot) that defines a remediation process for remediating the computing-related event based on the recorded actions and records (i) parameters of a run-time production computing environment in which the remediation process is deployed, and (ii) a level of performance of the remediation process in the computing environment.

2. The system of claim 1, further comprising:

a bot determining module stored in the memory, executable by the at least one processor and configured to, in response to creating a plurality of bots and receiving notification, from the first RPA module, of an occurrence of the computing-related event, determine which of the plurality of bots to deploy as a remediation process for the computing-related event.

3. The system of claim 2, wherein the bot determining module is further configured in response to determining to creating a plurality of bots and receiving notification, from the first RPA module, determine a combination of two or more the plurality of bots to deploy as the remediation process for the computing-related event.

4. The system of claim 3, wherein the second RPA module is further configured to create a robotic script (bot) for the combination of the two or more of the plurality of bots that defines a remediation process for remediating the computing-related event.

5. The system of claim 2, further comprising:

a bot simulation module stored in the memory, executable by the at least processor and configured to, prior to deploying one or more bots as remediation for a computing-related event, execute the one or more bots in a simulated environment having substantially same parameters as the run-time production computing environment, and

wherein the bot determining module is further configured to determine which of the one or more previously created bots to deploy as the remediation process, based on executing the one or more bots previously created bots in the simulated environment.

6. The system of claim 1, wherein the bot determining module is further configured to determine which of the plurality of bots to deploy as the remediation process for the computing-related event based at least one or more of (a) the computing-related event, (b) parameters of a run-time production computing environment in which the computing-related event occurred or a remediation process is to be deployed, (c) parameters of a run-time production computing environment in which the plurality of bots were previously deployed, and (d) performance of previous remediation processes in which the plurality of bots were previously deployed.

7. The system of claim 1, further comprising:

a bot determining module stored in the memory, executable by the at least one processor and configured to, in response to receiving notification, from the first RPA module, of an occurrence of the computing-related event;

determine to (i) implement the second RPA module to create a bot for remediating the computing-related event, or (ii) implement one or more of a plurality bots to remediate the computing-related event.

8. The system of claim 7, wherein the bot determining modules is further configured to determine to (i) or (ii) is based on at least one of (a) the computing-related event, (b) parameters of a run-time production computing environment in which the computing-related event occurred or a remediation process is to be deployed, (c) parameters of a run-time production computing environment in which the plurality of bots were previously deployed, and (d) performance of previous remediation processes in which the plurality of bots were previously deployed.

9. The system of claim 7, wherein the bot determining module is further configured in response to determining to implement one or more previously created bots to remediate the computing-related event, determine which of the plurality of bots to deploy as the remediation process.

10. The system of claim 7, wherein the bot determining module is further configured in response to determining to implement one or more previously created bots to remediate the computing-related event, determine a combination of two or more the plurality of bots to deploy as the remediation process.

11. The system of claim 10, wherein the second RPA module is further configured to create a robotic script (bot) for the combination of the two or more of the plurality of bots that defines a remediation process for remediating the computing-related event.

12. The system of claim 7, further comprising;

a bot simulation module stored in the memory, executable by the at least processor and configured to, prior to deploying one or more bots as remediation for a computing-related event, execute the one or more bots in a simulated environment having substantially same parameters as the run-time production computing environment, and

wherein the bot determining module is further configured to determine which of the one or more previously created bots to deploy as the remediation process, based on executing the one or more bots previously created bots in the simulated environment.

13. The system of claim 1, further comprising:

a bot simulation module stored in the memory, executable by the at least processor and configured to, prior to deploying the bot as remediation for a computing-related event;

execute the bot in a simulated environment having substantially same parameters as the run-time production computing environment,

determine a likely acceptable level of performance for the bot in the run-time production computing environment based on a performance of the bot in the simulated environment, and

in response to determining the likely acceptable level of performance, authorize the bot for remediating the computing-related event.

14. The system of claim 1, further comprising:

a remediation performance evaluating module stored in the memory, executable by the at least one processor and configured to, in response to deploying the bot as a remediation process for a computing-related event, determine performance of the remediation process in a run-time production computing environment.

15. A computer processor-implemented method for remediating computing-related events, the method comprising

monitoring, by a robotic process automation (RPA) computing module, a computing environment to detect occurrences of a computing-related event, wherein the computing-related event is a behavior occurring within the computing environment that deviates from a normal state;

in response to receiving notification of each occurrence of the computing-related event, recording, by a RPA computing module, actions performed to remediate the computing-related event; and

creating, by a RPA computing module, a robotic script (bot) that defines a remediation process for remediating the computing-related event based on the recorded actions and records (i) parameters of a run-time production computing environment in which the remediation process is deployed, and (ii) a level of performance of the remediation process in the computing environment.

16. The method of claim 15, further comprising in response to creating a plurality of bots and receiving notification of an occurrence of a computing-related event, determining, by a computing device processor, which of the plurality of bots to deploy as the remediation process.

17. The method of claim 16, wherein determining which of the plurality of bots to deploy as the remediation process, further comprises determining a combination of two or more the plurality of bots to deploy as the remediation process for the computing-related event and creating a bot comprising the two or more bots.

18. The method of claim 16, wherein determining which of the plurality of bots to deploy as the remediation process is based on at least one of (a) the computing-related event, (b) parameters of a run-time production computing environment in which the computing-related event occurred or a remediation process is to be deployed, (c) parameters of a run-time production computing environment in which the plurality of bots were previously deployed, and (d) performance of previous remediation processes in which the plurality of bots were previously deployed.

19. A computer program product, comprising:

a non-transitory computer-readable medium comprising codes for causing a computing device processor to;

monitor, by robotic process automation (RPA), a computing environment to detect occurrences of a computing-related event, wherein the computing-related event is a behavior occurring within the computing environment that deviates from a normal state;

in response to receiving notification of each occurrence of the computing-related event, record, by RPA, actions performed to remediate the computing-related event; and

create, by RPA, a robotic script (bot) that defines a remediation process for remediating the computing-related event based on the recorded actions and records (i) parameters of a run-time production computing environment in which the remediation process is deployed, and (ii) a level of performance of the remediation process in the computing environment.

20. The computer program product of claim 19, wherein the computer-readable medium further comprises codes for causing a computing device processor to, in response to creating a plurality of bots and receiving notification of an occurrence of a computing-related event, determine which of the plurality of bots to deploy as the remediation process.