Reactive semi-analytical orchestration for reproducing failures in container-based data protection systems

1 . A method for managing a data protection system, the method comprising:

obtaining, by an interaction manager, a failure notification for a data protection workload executing on the data protection system,

wherein the data protection system comprises a plurality of services, and

wherein the data protection workload is executed by the plurality of services communicating with each other using application programming interface (API) calls;

based on the failure notification, identifying a portion of the plurality of services used for the data protection workload;

performing a recreation of the data protection workload to identify a failure point associated with the failure notification; and

performing a remediation action of the data protection workload based on the recreation.

2 . The method of claim 1 , wherein the recreation is performed by simulating the portion of the plurality of services to obtain a simulated environment and simulating the API calls in the simulated environment to identify which of the API calls indicates the failure point.

3 . The method of claim 1 , wherein the remediation action comprises one of: restarting the data protection workload in the data protection system, replacing at least one service of the portion of the plurality of services based on the failure point, issuing a notification to an administrator of the failure point, and modifying a sequence of the API calls.

4 . The method of claim 1 , wherein performing the remediation action comprises applying the failure point to a failure prediction engine, and wherein the failure prediction engine determines the remediation action based on the failure point.

5 . The method of claim 4 , further comprising:

updating the failure prediction engine based on the remediation action by updating an action-reward associated with the remediation action and applying a reinforcement learning on the failure prediction engine based on the action-reward.

6 . The method of claim 1 , wherein the plurality of services comprises: an asset backup service, a pillar service, an asset restoration service, a scheduler, and a user interface communicating with a client device.

7 . The method of claim 1 , wherein the failure point is based on one of a list consisting of: one of the API calls being out of order, an overloading of one of the plurality of services, and a detected latency issue.

8 . 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 a data protection system, the method comprising:

obtaining, by an interaction manager, a failure notification for a data protection workload executing on the data protection system,

wherein the data protection system comprises a plurality of services, and

wherein the data protection workload is executed by the plurality of services communicating with each other using application programming interface (API) calls;

based on the failure notification, identifying a portion of the plurality of services used for the data protection workload;

performing a recreation of the data protection workload to identify a failure point associated with the failure notification; and

performing a remediation action of the data protection workload based on the recreation.

9 . The non-transitory computer readable medium of claim 8 , wherein the recreation is performed by simulating the portion of the plurality of services to obtain a simulated environment and simulating the API calls in the simulated environment to identify which of the API calls indicates the failure point.

10 . The non-transitory computer readable medium of claim 8 , wherein the remediation action comprises one of: restarting the data protection workload in the data protection system, replacing at least one service of the portion of the plurality of services based on the failure point, issuing a notification to an administrator of the failure point, and modifying a sequence of the API calls.

11 . The non-transitory computer readable medium of claim 8 , wherein performing the remediation action comprises applying the failure point to a failure prediction engine, and wherein the failure prediction engine determines the remediation action based on the failure point.

12 . The non-transitory computer readable medium of claim 11 , further comprising:

updating the failure prediction engine based on the remediation action by updating an action-reward associated with the remediation action and applying a reinforcement learning on the failure prediction engine based on the action-reward.

13 . The non-transitory computer readable medium of claim 8 , wherein the plurality of services comprises: an asset backup service, a pillar service, an asset restoration service, a scheduler, and a user interface communicating with a client device.

14 . The non-transitory computer readable medium of claim 8 , wherein the failure point is based on one of a list consisting of: one of the API calls being out of order, an overloading of one of the plurality of services, and a detected latency issue.

15 . A system comprising:

an interaction manager, operating on a processor; and

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

obtaining a failure notification for a data protection workload executing on a data protection system,

wherein the data protection system comprises a plurality of services, and

wherein the data protection workload is executed by the plurality of services communicating with each other using application programming interface (API) calls;

based on the failure notification, identifying a portion of the plurality of services used for the data protection workload;

performing a recreation of the data protection workload to identify a failure point associated with the failure notification,

wherein the recreation is performed by simulating the portion of the plurality of services to obtain a simulated environment and simulating the API calls in the simulated environment to identify which of the API calls indicates the failure point; and

performing a remediation action of the data protection workload based on the recreation.

16 . The system of claim 15 , wherein the remediation action comprises one of: restarting the data protection workload in the data protection system, replacing at least one service of the portion of the plurality of services based on the failure point, issuing a notification to an administrator of the failure point, and modifying a sequence of the API calls.

17 . The system of claim 15 , wherein performing the remediation action comprises applying the failure point to a failure prediction engine, and wherein the failure prediction engine determines the remediation action based on the failure point.

18 . The system of claim 17 , further comprising:

updating the failure prediction engine based on the remediation action by updating an action-reward associated with the remediation action and applying a reinforcement learning on the failure prediction engine based on the action-reward.

19 . The system of claim 15 , wherein the plurality of services comprises: an asset backup service, a pillar service, an asset restoration service, a scheduler, and a user interface communicating with a client device.

20 . The system of claim 15 , wherein the failure point is based on one of a list consisting of: one of the API calls being out of order, an overloading of one of the plurality of services, and a detected latency issue.