Multi-application recommendation engine for a remote network management platform

Patent metadata

Field	Value
Publication number	US-11706243-B2
Application number	US-202117446019-A
Country	US
Kind code	B2
Filing date	Aug 26, 2021
Priority date	Jul 8, 2019
Publication date	Jul 18, 2023
Grant date	Jul 18, 2023

Abstract

A remote network management platform may include persistent storage containing: (i) data related to a managed network, and (ii) a persona of a user. The remote network management platform may also include a platform application associated with a web-based user interface and using a portion of the data. The remote network management platform may also include a recommendation engine with access to a set of rules or a machine learning (ML) model corresponding to the platform application. The recommendation engine may be configured to: (i) read, from the persistent storage, the portion of the data and the persona; (ii) apply, to the portion of the data and the persona, the set of rules or the ML model to generate one or more recommendations; and (iii) transmit, by way of the web-based user interface and to the user, representations of the one or more recommendations.

First claim

What is claimed is:

1. A remote network management platform, comprising:
a processor; and
a memory, accessible by the processor, the memory storing instructions, that when executed by the processor, cause the processor to perform operations comprising:
receiving a first set of data associated with a platform application configured to be executed by the remote network management platform with respect to a managed network and a second set of data associated with a persona, wherein the persona defines a role of a user associated with the managed network;
generating, via a machine learning (ML) model, one or more recommendations associated with the platform application and the persona based on the first set of data and the second set of data; and
transmitting, to a display device within the managed network, one or more representations indicative of the one or more recommendations.

2. The remote network management platform of claim 1 , wherein the one or more recommendations comprise reconfiguring one or more computing devices within the managed network.

3. The remote network management platform of claim 1 , wherein the one or more recommendations comprise resolving a resource deficiency associated with one or more computing devices within the managed network.

4. The remote network management platform of claim 1 , wherein the one or more recommendations comprise updating or upgrading a software application configured to be executed by one or more computing devices within the managed network.

5. The remote network management platform of claim 1 , wherein the operations comprise:
receiving a third set of data associated with a second persona, wherein the second persona defines a second role of a second user associated with the managed network, wherein the second persona is different from the persona; and
generating, via the ML model, one or more second recommendations associated with the platform application and the second persona based on the first set of data and the third set of data, wherein the one or more recommendations are different from than the one or more second recommendations.

6. The remote network management platform of claim 1 , wherein the operations comprise:
receiving, from the display device, user input indicative of an action configured to change one or more operations of the managed network; and
executing the action based on the user input.

7. The remote network management platform of claim 6 , wherein the operations comprise:
receiving, from the display device, user feedback based on execution of the action; and
re-training the ML model based on the user feedback.

8. A method, comprising:
generating, by one or more processors associated with a remote network management platform via a machine learning (ML) model, one or more recommendations associated with a platform application configured to be executed by the remote network management platform to support one or more operations of a managed network, wherein the one or more recommendations are automatically generated based on a first set of data associated with the platform application and a second set of data associated with a persona configured to define a user role associated with the managed network;
transmitting, by the one or more processors to a display device within the managed network, one or more representations indicative of the one or more recommendations;
receiving, by the one or more processors from the display device, user input indicative of an action configured to change the one or more operations of the managed network; and
executing, by the one or more processors, the action based on the user input.

9. The method of claim 8 , wherein the one or more recommendations comprise reconfiguring one or more computing devices within the managed network.

10. The method of claim 8 , wherein the one or more recommendations comprise resolving a resource deficiency associated with one or more computing devices within the managed network.

11. The method of claim 8 , wherein the one or more recommendations comprise updating or upgrading a software application configured to be executed by one or more computing devices within the managed network.

12. The method of claim 8 , comprising:
receiving a third set of data associated with a second persona, wherein the second persona defines a second role of a second user associated with the managed network, wherein the second persona is different from the persona; and
generating, via the ML model, one or more second recommendations associated with the platform application and the second persona based on the first set of data and the third set of data, wherein the one or more recommendations are different from than the one or more second recommendations.

13. The method of claim 8 , comprising:
receiving, from the display device, user feedback based on execution of the action; and
re-training the ML model based on the user feedback.

14. The method of claim 8 , comprising training the ML model with one or more mappings between historical values within data associated with the managed network and one or more types of personae associated with the managed network.

15. A non-transitory, computer-readable medium, comprising instructions that when executed by one or more processors, cause the one or more processors to perform operations comprising:
receiving a first set of data associated with a platform application configured to be executed by a remote network management platform with respect to a managed network and a second set of data associated with a persona, wherein the persona defines a role of a user associated with the managed network;
automatically generating, via a machine learning (ML) model, one or more recommendations associated with the platform application and the persona based on the first set of data and the second set of data;
transmitting, to a display device within the managed network, one or more representations indicative of the one or more recommendations;
receiving, from the display device, user input indicative of an action configured to change one or more operations of the managed network; and
executing the action based on the user input.

16. The non-transitory, computer-readable medium of claim 15 , wherein the one or more recommendations comprise reconfiguring one or more computing devices within the managed network.

17. The non-transitory, computer-readable medium of claim 15 , wherein the one or more recommendations comprise resolving a resource deficiency associated with one or more computing devices within the managed network.

18. The non-transitory, computer-readable medium of claim 15 , wherein the operations comprise:
receiving a third set of data associated with a second persona, wherein the second persona defines a second role of a second user associated with the managed network, wherein the second persona is different from the persona; and
generating, via the ML model, one or more second recommendations associated with the platform application and the second persona based on the first set of data and the third set of data, wherein the one or more recommendations are different from than the one or more second recommendations.

19. The non-transitory, computer-readable medium of claim 15 , wherein the operations comprise:
receiving, from the display device, user feedback based on execution of the action; and
re-training the ML model based on the user feedback.

20. The non-transitory, computer-readable medium of claim 15 , wherein the operations

Assignees

• Servicenow Inc

Inventors

• Singh Manjeet

Classifications

• H04L41/147

  for predicting network behaviour · CPC title

• H04L41/149

  for prediction of maintenance · CPC title

• H04L41/40

  using virtualisation of network functions or resources, e.g. SDN or NFV entities · CPC title

• H04L67/02

  based on web technology, e.g. hypertext transfer protocol [HTTP] · CPC title

• H04L63/1433 Primary

  Vulnerability analysis · CPC title