IP Library Granted Patent US 11,329,896
Granted Patent B1
US 11,329,896 · App. 17/173,250 · Granted May 10, 2022

Cognitive data protection and disaster recovery policy management

Inventors: Anil Kumar Narigapalli (Hyderabad, IN); Laxmikantha Sai Nanduru (R K Puram Post, IN); Venkateswarlu Basyam (Hyderabad, IN); Srilakshmi Surapaneni (Hyderabad, IN); Bernhard Julius Klingenberg (Grover Beach, CA)
Assignee: Kyndryl, Inc.
H04L41/5019H04L41/508H04L41/5054H04L41/5058H04L47/2425
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Quick Facts
Patent No.
US 11,329,896
App. No.
17/173,250
Granted
May 10, 2022
Kind
B1
Abstract

An embodiment for cognitively aligning data protection (DP) and disaster recovery (DR) policies is provided. The embodiment may include ingesting a variety of data associated with one or more applications into a repository. The embodiment may also include executing differential analysis on the data and changes to the data to identify differences between the data and the changes to the data. The changes to the data may be obtained by periodically polling internal and external data sources. The embodiment may also include translating the differences between the data and the changes to the data into an updated SLA. The embodiment may further include in response to determining that the differences between the data and the changes to the data warrant a change in the current DP and DR policies, generating one or more recommendations to modify the current DP and DR policies and/or create new DP and DR policies.

Claims (39)

1. A computer-based method of cognitively aligning data protection (DP) and disaster recovery (DR) policies, the method comprising:

ingesting a variety of data associated with one or more applications into a repository, the data including a current priority of the one or more applications, current DP and DR policies contained in a service-level agreement (SLA), existing industry, sector, and government regulatory requirements, and new industry, sector, and government regulatory requirements;

executing differential analysis on the data and changes to the data, wherein the changes to the data are obtained by periodically polling internal and external data sources;

identifying differences between the data and the changes to the data based on the differential analysis;

translating the differences between the data and the changes to the data into an updated SLA;

determining whether the differences between the data and the changes to the data warrant a change in the current DP and DR policies and/or creation of new DP and DR policies; and

in response to determining that the differences between the data and the changes to the data warrant the change in the current DP and DR policies and/or the creation of the new DP and DR policies, generating one or more recommendations to modify the current DP and DR policies and/or create the new DP and DR policies.

2. The method of claim 1 , wherein pre-configured, customizable rules are utilized in executing the differential analysis.

3. The method of claim 1 , wherein the one or more applications are mapped to one or more hosts.

4. The method of claim 1 , wherein the one or more generated recommendations are presented to a business stakeholder.

5. The method of claim 1 , wherein one or more orchestration engines are utilized to automatically modify the current DP and DR policies and/or create the new DP and DR policies based on the one or more generated recommendations.

6. The method of claim 1 , wherein the one or more generated recommendations are based on a detected difference between the current priority of the one or more applications and a past priority of the one or more applications.

7. The method of claim 1 , wherein the data is selected from a group consisting of performance metrics data of products and services in an organization, business climate data, one or more geographic spans of the one or more applications, data retention requirements in the SLA, and internal details on policies and objectives of an organization.

8. A computer system, the computer system comprising:

one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage media, and program instructions stored on at least one of the one or more tangible storage media for execution by at least one of the one or more processors via at least one of the one or more memories, each storage medium of the one or more storage media not being a transitory propagating signal, the computer system configured to perform a method, the method comprising:

ingesting a variety of data associated with one or more applications into a repository, the data including a current priority of the one or more applications, current data protection (DP) and disaster recovery (DR) policies contained in a service-level agreement (SLA), existing industry, sector, and government regulatory requirements, and new industry, sector, and government regulatory requirements;

executing differential analysis on the data and changes to the data, wherein the changes to the data are obtained by periodically polling internal and external data sources;

identifying differences between the data and the changes to the data based on the differential analysis;

translating the differences between the data and the changes to the data into an updated SLA;

determining whether the differences between the data and the changes to the data warrant a change in the current DP and DR policies and/or creation of new DP and DR policies; and

in response to determining that the differences between the data and the changes to the data warrant the change in the current DP and DR policies and/or the creation of the new DP and DR policies, generating one or more recommendations to modify the current DP and DR policies and/or create the new DP and DR policies.

9. The computer system of claim 8 , wherein pre-configured, customizable rules are utilized in executing the differential analysis.

10. The computer system of claim 8 , wherein the one or more applications are mapped to one or more hosts.

11. The computer system of claim 8 , wherein the one or more generated recommendations are presented to a business stakeholder.

12. The computer system of claim 8 , wherein one or more orchestration engines are utilized to automatically modify the current DP and DR policies and/or create the new DP and DR policies based on the one or more generated recommendations.

13. The computer system of claim 8 , wherein the one or more generated recommendations are based on a detected difference between the current priority of the one or more applications and a past priority of the one or more applications.

14. The computer system of claim 8 , wherein the data is selected from a group consisting of performance metrics data of products and services in an organization, business climate data, one or more geographic spans of the one or more applications, data retention requirements in the SLA, and internal details on policies and objectives of an organization.

15. A computer program product, the computer program product comprising: one or more computer-readable tangible storage media and program instructions stored on at least one of the one or more tangible storage media, each storage medium of the one or more storage media not being a transitory propagating signal, the program instructions executable by a processor capable of performing a method, the method comprising:

ingesting a variety of data associated with one or more applications into a repository, the data including a current priority of the one or more applications, current data protection (DP) and disaster recovery (DR) policies contained in a service-level agreement (SLA), existing industry, sector, and government regulatory requirements, and new industry, sector, and government regulatory requirements;

executing differential analysis on the data and changes to the data, wherein the changes to the data are obtained by periodically polling internal and external data sources;

identifying differences between the data and the changes to the data based on the differential analysis;

translating the differences between the data and the changes to the data into an updated SLA;

determining whether the differences between the data and the changes to the data warrant a change in the current DP and DR policies and/or creation of new DP and DR policies; and

in response to determining that the differences between the data and the changes to the data warrant the change in the current DP and DR policies and/or the creation of the new DP and DR policies, generating one or more recommendations to modify the current DP and DR policies and/or create the new DP and DR policies.

16. The computer program product of claim 15 , wherein pre-configured, customizable rules are utilized in executing the differential analysis.

17. The computer program product of claim 15 , wherein the one or more applications are mapped to one or more hosts.

18. The computer program product of claim 15 , wherein the one or more generated recommendations are presented to a business stakeholder.

19. The computer program product of claim 15 , wherein one or more orchestration engines are utilized to automatically modify the current DP and DR policies and/or create the new DP and DR policies based on the one or more generated recommendations.

20. The computer program product of claim 15 , wherein the one or more generated recommendations are based on a detected difference between the current priority of the one or more applications and a past priority of the one or more applications.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 18, 2021
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: KYNDRYL, INC.
Reel/Frame 058213/0912 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 11, 2021
From: NARIGAPALLI, ANIL KUMAR; NANDURU, LAXMIKANTHA SAI; BASYAM, VENKATESWARLU; SURAPANENI, SRILAKSHMI; KLINGENBERG, BERNHARD JULIUS
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 055224/0159 →
Cited By (1)
US 12,277,039