Granted Patent B1

US 11,398,960 · App. 17/226,532 · Granted Jul 26, 2022

Inventors: Shelesh Chopra (Bangalore, IN); Anannya Roy Chowdhury (Jamshedpur, IN); Parminder Singh Sethi (Ludhiana, IN)

Assignee: EMC IP Holding Company LLC

H04L41/5025H04L41/507H04L41/5048H04L41/5096

Abstract

Claims (97)

1. A method for managing an application in a production host environment, the method comprising:

obtaining a set of upgrade issue reports associated with the application;

populating a self-healing training database using a set of features for each of the set of upgrade issue reports;

after populating the self-healing training database, generating a self-healing classification model based on the self-healing training database,

wherein generating the self-healing classification model comprises:

applying a z-score to each upgrade issue report of the upgrade issue reports based on similarities on the set of features and further based on a determination about whether the upgrade issue report specifies a self-healable issue,

processing the z-score of each upgrade issue report to generate the self-healing classification model;

after populating the self-healing database:

obtaining, by an application upgrade management system, an upgrade issue report for the application;

applying the self-healing classification model to the upgrade issue report to obtain a state of the upgrade issue report;

making a determination that the state indicates a self-healable state;

based on the determination, performing a self-healing process on the application based on the upgrade issue report; and

storing a resolution report based on results of the self-healing process.

2. The method of claim 1 , further comprising:

after the storing, performing a retraining on the self-healing classification model using the resolution report to obtain an updated self-healing classification model;

obtaining a second upgrade issue report for the application;

applying the updated self-healing classification model to the second upgrade issue report to obtain a second state of the second upgrade issue report;

making a second determination that the second state does not indicate the self-healable state; and

based on the second determination:

providing the second upgrade issue report to an administrative system;

receiving a response from the administrative system; and

storing a second resolution report based on the response.

3. The method of claim 1 , further comprising:

prior to populating the self-healing training database:

identifying a portion of the set of upgrade issue reports of a first type;

performing a pre-processing pipeline on the portion of the set of upgrade issue reports to obtain processed upgrade issue reports; and

performing a feature extraction on the processed update issue reports to identify a first portion of the set of features.

4. The method of claim 3 , wherein a second portion of the set of upgrade issue reports comprises a second portion of the set of features.

5. The method of claim 3 ,

wherein identifying the portion of the set of upgrade issue reports with the first type comprises performing a content analysis to identify non-useful information, and

wherein performing the pre-processing pipeline comprises removing the non-useful information.

6. The method of claim 1 ,

wherein the upgrade issue report is generated based on at least a result of an attempt to upgrade the application.

7. A non-transitory computer readable medium comprising computer readable program code, which when executed by a computer processor enables the computer processor to perform a method for managing applications, the method comprising:

obtaining a set of upgrade issue reports associated with the application;

populating a self-healing training database using a set of features for each of the set of upgrade issue reports;

after populating the self-healing training database, generating a self-healing classification model based on the self-healing training database, wherein generating the self-healing classification model comprises:

applying a z-score to each upgrade issue report of the upgrade issue reports based on similarities on the set of features and further based on a determination about whether the upgrade issue report specifies a self-healable issue;

processing the z-score of each upgrade issue report to generate the self-healing classification model;

after populating the self-healing database:

obtaining, by an application upgrade management system, an upgrade issue report for the application;

applying the self-healing classification model to the upgrade issue report to obtain a state of the upgrade issue report;

making a determination that the state indicates a self-healable state;

based on the determination, performing a self-healing process on the application based on the upgrade issue report; and

storing a resolution report based on results of the self-healing process.

8. The non-transitory computer readable medium of claim 7 , the method further comprising:

after the storing, performing a retraining on the self-healing classification model using the resolution report to obtain an updated self-healing classification model;

obtaining a second upgrade issue report for the application;

applying the updated self-healing classification model to the second upgrade issue report to obtain a second state of the second upgrade issue report;

making a second determination that the second state does not indicate the self-healable state; and

based on the second determination:

providing the second upgrade issue report to an administrative system;

receiving a response from the administrative system; and

storing a second resolution report based on the response.

9. The non-transitory computer readable medium of claim 7 , the method further comprising:

prior to populating the self-healing training database:

identifying a portion of the set of upgrade issue reports of a first type;

performing a pre-processing pipeline on the portion of the set of upgrade issue reports to obtain processed upgrade issue reports; and

performing a feature extraction on the processed update issue reports to identify a first portion of the set of features.

10. The non-transitory computer readable medium of claim 9 , wherein a second portion of the set of upgrade issue reports comprises a second portion of the set of features.

11. The non-transitory computer readable medium of claim 9 ,

wherein identifying the portion of the set of upgrade issue reports of the first type comprises performing a content analysis to identify non-useful information, and

wherein performing the pre-processing pipeline comprises removing the non-useful information.

12. The non-transitory computer readable medium of claim 7 , wherein the upgrade issue report is generated based on at least a result of an attempt to upgrade the application.

13. A system comprising:

a processor; and

memory comprising instructions, which when executed by the processor, perform a method comprising:

obtaining a set of upgrade issue reports associated with the application;

populating a self-healing training database using a set of features for each of the set of upgrade issue reports;

after populating the self-healing training database, generating a self-healing classification model based on the self-healing training database,

wherein generating the self-healing classification model comprises:

applying a z-score to each upgrade issue report of the upgrade issue reports based on similarities on the set of features and further based on a determination about whether the upgrade issue report specifies a self-healable issue;

processing the z-score of each upgrade issue report to generate the self-healing classification model;

after populating the self-healing database:

obtaining, by an application upgrade management system, an upgrade issue report for the application;

applying the self-healing classification model to the upgrade issue report to obtain a state of the upgrade issue report;

making a determination that the state indicates a self-healable state;

based on the determination, performing a self-healing process on the application based on the upgrade issue report; and

storing a resolution report based on results of the self-healing process.

14. The system of claim 13 , further comprising:

after the storing, performing a retraining on the self-healing classification model using the resolution report to obtain an updated self-healing classification model;

obtaining a second upgrade issue report for the application;

applying the updated self-healing classification model to the second upgrade issue report to obtain a second state of the second upgrade issue report;

making a second determination that the second state does not indicate the self-healable state; and

based on the second determination:

providing the second upgrade issue report to an administrative system;

receiving a response from the administrative system; and

storing a second resolution report based on the response.

15. The system of claim 13 , further comprising:

prior to populating the self-healing training database:

identifying a portion of the set of upgrade issue reports of a first type;

performing a pre-processing pipeline on the portion of the set of upgrade issue reports to obtain processed upgrade issue reports; and

performing a feature extraction on the processed update issue reports to identify a first portion of the set of features.

16. The system of claim 15 , wherein a second portion of the set of upgrade issue reports comprises a second portion of the set of features.

17. The system of claim 15 ,

wherein identifying the portion of the set of upgrade issue reports of the first type comprises performing a content analysis to identify non-useful information, and

wherein performing the pre-processing pipeline comprises removing the non-useful information.

Assignments (10)