System and method for ranking data storage devices for efficient production agent deployment
A method for processing backup policy generation requests includes receiving, by a production agent manager, a backup policy generation request, in response to receiving the backup policy generation request: identifying a backup to transfer to a backup storage, wherein the backup comprises a plurality of data blocks, performing a data storage device evaluation on a set of data storage devices to obtain a set of health scores, wherein each health score of the set of health scores corresponds to a data storage device of the set of data storage devices, assigning, based on the set of health scores, a production agent to a data storage device of the set of data storage devices to generate a backup policy, and initiating, based on the backup policy, a deployment of the production agent to the data storage device.
1. A method for processing backup policy generation requests, the method comprising:
receiving, by a production agent manager, a backup policy generation request;
in response to receiving the backup policy generation request:
identifying a backup to transfer to a backup storage,
wherein the backup comprises a plurality of data blocks;
performing, based on a shapely additive explanation (SHAP) model, a data storage device evaluation on a set of data storage devices to obtain a set of health scores,
wherein each health score of the set of health scores corresponds to a data storage device of the set of data storage devices;
assigning, based on the set of health scores, a production agent to a data storage device of the set of data storage devices to generate a backup policy; and
initiating, based on the backup policy, a deployment of the production agent to the data storage device.
2. The method of claim 1 , wherein performing, based on the SHAP model, the data storage device evaluation comprises:
identifying a first set of data storage device parameters for a first data storage device;
performing an interaction analysis on the first set of data storage device parameters to obtain interaction values for the first data storage device;
identifying a second set of data storage device parameters for a second data storage device;
performing a second interaction analysis on the second set of data storage device parameters to obtain second interaction values for the second data storage device;
generating a compound parameter data structure using the first interaction values and the second interaction values; and
generating the set of health scores based on the compound parameter data structure.
3. The method of claim 2 , wherein the first set of data storage device parameters comprises at least one of: a status of the data storage device, whether the data storage device is part of a cluster, a measurement of consumed processing power, a version of a virtual machine file system, a type of storage device, and a total storage capacity.
4. The method of claim 3 , wherein the first set of data storage device parameters further comprises a total number of virtual machines assigned to the data storage device.
5. The method of claim 3 , wherein the first set of data storage device parameters further comprises a total number of production agents assigned to the data storage device.
6. The method of claim 1 , wherein assigning the production agent to the data storage device comprises:
ranking each data storage device in the set of data storage devices based on the set of health scores;
making a determination that the data storage device is the highest ranked; and
based on the determination, assigning the production agent to the data storage device.
7. The method of claim 1 , wherein initiating the production agent deployment comprises enabling the production agent to utilize computing resources of the data storage device.
8. A system, comprising:
a processor; and
memory comprising instructions, which when executed by the processor, perform a method, the method comprising:
receiving a backup policy generation request;
in response to receiving the backup policy generation request:
identifying a backup to transfer to a backup storage, wherein the backup comprises a plurality of data blocks;
performing, based on a shapely additive explanation (SHAP) model, a data storage device evaluation on a set of data storage devices to obtain a set of health scores, wherein each health score of the set of health scores corresponds to a data storage device of the set of data storage devices;
assigning, based on the set of health scores, a production agent to a data storage device of the set of data storage devices to generate a backup policy; and
initiating, based on the backup policy, a deployment of the production agent to the data storage device.
9. The system of claim 8 , wherein performing, based on the SHAP model, the data storage device evaluation comprises:
identifying a first set of data storage device parameters for a first data storage device;
performing an interaction analysis on the first set of data storage device parameters to obtain interaction values for the first data storage device;
identifying a second set of data storage device parameters for a second data storage device;
performing a second interaction analysis on the second set of data storage device parameters to obtain second interaction values for the second data storage device;
generating a compound parameter data structure using the first interaction values and the second interaction values; and
generating the set of health scores based on the compound parameter data structure.
10. The system of claim 9 , wherein the first set of data storage device parameters comprises at least one of: a status of the data storage device, whether the data storage device is part of a cluster, a measurement of consumed processing power, a version of a virtual machine file system, a type of storage device, and a total storage capacity.
11. The system of claim 10 , wherein the first set of data storage device parameters further comprises a total number of virtual machines assigned to the data storage device.
12. The system of claim 10 , wherein the first set of data storage device parameters further comprises a total number of production agents assigned to the data storage device.
13. The system of claim 8 , wherein assigning the production agent to the data storage device comprises:
ranking each data storage device in the set of data storage devices based on the set of health scores;
making a determination that the data storage device is the highest ranked; and
based on the determination, assigning the production agent to the data storage device.
14. The system of claim 8 , wherein initiating the production agent deployment comprises enabling the production agent to utilize computing resources of the data storage device.
15. 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, the method comprising:
receiving, by a production agent manager, a backup policy generation request;
in response to receiving the backup policy generation request:
identifying a backup to transfer to a backup storage, wherein the backup comprises a plurality of data blocks;
performing, based on a shapely additive explanation (SHAP) model, a data storage device evaluation on a set of data storage devices to obtain a set of health scores, wherein each health score of the set of health scores corresponds to a data storage device of the set of data storage devices;
assigning, based on the set of health scores, a production agent to a data storage device of the set of data storage devices to generate a backup policy; and
initiating, based on the backup policy, a deployment of the production agent to the data storage device.
16. The non-transitory computer readable medium of claim 15 , wherein performing, based on the SHAP model, the data storage device evaluation comprises:
identifying a first set of data storage device parameters for a first data storage device;
performing an interaction analysis on the first set of data storage device parameters to obtain interaction values for the first data storage device;
identifying a second set of data storage device parameters for a second data storage device;
performing a second interaction analysis on the second set of data storage device parameters to obtain second interaction values for the second data storage device;
generating a compound parameter data structure using the first interaction values and the second interaction values; and
generating the set of health scores based on the compound parameter data structure.
17. The non-transitory computer readable medium of claim 16 , wherein the first set of data storage device parameters comprises at least one of: a status of the data storage device, whether the data storage device is part of a cluster, a measurement of consumed processing power, a version of a virtual machine file system, a type of storage device, and a total storage capacity.
18. The non-transitory computer readable medium of claim 17 , wherein the first set of data storage device parameters further comprises a total number of virtual machines assigned to the data storage device.
19. The non-transitory computer readable medium of claim 17 , wherein the first set of data storage device parameters further comprises a total number of production agents assigned to the data storage device.
20. The non-transitory computer readable medium of claim 15 , wherein assigning the production agent to the data storage device comprises:
ranking each data storage device in the set of data storage devices based on the set of health scores;
making a determination that the data storage device is the highest ranked; and
based on the determination, assigning the production agent to the data storage device.