Automatically remediating storage device issues using machine learning techniques
Methods, apparatus, and processor-readable storage media for automatically remediating storage device issues using machine learning techniques are provided herein. An example computer-implemented method includes obtaining performance-related information pertaining to one or more storage devices; automatically determining one or more workflows to be executed in connection with remediating at least one issue attributed to at least a portion of the one or more storage devices, wherein determining the one or more workflows comprises applying one or more machine learning techniques to the obtained performance-related information; and performing one or more automated actions based at least in part on the one or more workflows.
1. A computer-implemented method comprising:
obtaining performance-related information pertaining to one or more storage devices;
automatically determining one or more workflows to be executed in connection with remediating at least one issue attributed to at least a portion of the one or more storage devices, wherein determining the one or more workflows comprises applying one or more machine learning techniques to the obtained performance-related information and comparing at least a portion of the obtained performance-related information to at least one set of configuration information pertaining to multiple storage device remediation workflows; and
performing one or more automated actions based at least in part on the one or more workflows, wherein performing one or more automated actions comprises automatically initiating at least a portion of the one or more workflows related to adding one or more ports to at least one port group associated with the at least a portion of the one or more storage devices;
wherein the method is performed by at least one processing device comprising a processor coupled to a memory.
2. The computer-implemented method of claim 1 , wherein comparing the at least a portion of the obtained performance-related information to the at least one set of configuration information comprises utilizing at least one lookup table.
3. The computer-implemented method of claim 1 , wherein performing the one or more automated actions comprises automatically outputting an identification of the one or more workflows to at least one provisioning tool associated with the one or more storage devices.
4. The computer-implemented method of claim 1 , wherein performing the one or more automated actions comprises automatically outputting an identification of the one or more workflows to at least one user associated with the one or more storage devices for execution approval.
5. The computer-implemented method of claim 1 , wherein performing the one or more automated actions comprises automatically outputting an identification of the one or more workflows and an indication of user approval of the one or more workflows to at least one provisioning tool associated with the one or more storage devices.
6. The computer-implemented method of claim 1 , wherein the performance-related information identifies at least one performance-related event reported by a storage device monitoring tool.
7. The computer-implemented method of claim 6 , wherein determining one or more workflows to be executed in connection with remediating at least one issue comprises determining one or more workflows to be executed in connection with reactively remediating the at least one performance-related event reported by the storage device monitoring tool.
8. The computer-implemented method of claim 1 , wherein the performance-related information comprises a prediction of at least one performance-related issues generated by a storage device monitoring tool.
9. The computer-implemented method of claim 8 , wherein determining one or more workflows to be executed in connection with remediating at least one issue comprises determining one or more workflows to be executed in connection with proactively remediating the prediction of at least one performance-related issues generated by the storage device monitoring tool.
10. A non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device:
to obtain performance-related information pertaining to one or more storage devices;
to automatically determine one or more workflows to be executed in connection with remediating at least one issue attributed to at least a portion of the one or more storage devices, wherein determining the one or more workflows comprises applying one or more machine learning techniques to the obtained performance-related information and comparing at least a portion of the obtained performance-related information to at least one set of configuration information pertaining to multiple storage device remediation workflows; and
to perform one or more automated actions based at least in part on the one or more workflows, wherein performing one or more automated actions comprises automatically initiating at least a portion of the one or more workflows related to adding one or more ports to at least one port group associated with the at least a portion of the one or more storage devices.
11. The non-transitory processor-readable storage medium of claim 10 , wherein comparing the at least a portion of the obtained performance-related information to the at least one set of configuration information comprises utilizing at least one lookup table.
12. The non-transitory processor-readable storage medium of claim 10 , wherein performing the one or more automated actions comprises automatically outputting an identification of the one or more workflows to at least one provisioning tool associated with the one or more storage devices.
13. The non-transitory processor-readable storage medium of claim 10 , wherein performing the one or more automated actions comprises automatically outputting an identification of the one or more workflows to at least one user associated with the one or more storage devices for execution approval.
14. An apparatus comprising:
at least one processing device comprising a processor coupled to a memory;
the at least one processing device being configured:
to obtain performance-related information pertaining to one or more storage devices;
to automatically determine one or more workflows to be executed in connection with remediating at least one issue attributed to at least a portion of the one or more storage devices, wherein determining the one or more workflows comprises applying one or more machine learning techniques to the obtained performance-related information and comparing at least a portion of the obtained performance-related information to at least one set of configuration information pertaining to multiple storage device remediation workflows; and
to perform one or more automated actions based at least in part on the one or more workflows, wherein performing one or more automated actions comprises automatically initiating at least a portion of the one or more workflows related to adding one or more ports to at least one port group associated with the at least a portion of the one or more storage devices.
15. The apparatus of claim 14 , wherein comparing the at least a portion of the obtained performance-related information to the at least one set of configuration information comprises utilizing at least one lookup table.
16. The apparatus of claim 14 , wherein performing the one or more automated actions comprises automatically outputting an identification of the one or more workflows to at least one provisioning tool associated with the one or more storage devices.
17. The apparatus of claim 14 , wherein performing the one or more automated actions comprises automatically outputting an identification of the one or more workflows to at least one user associated with the one or more storage devices for execution approval.
18. The apparatus of claim 14 , wherein performing the one or more automated actions comprises automatically outputting an identification of the one or more workflows and an indication of user approval of the one or more workflows to at least one provisioning tool associated with the one or more storage devices.
19. The apparatus of claim 14 , wherein the performance-related information identifies at least one performance-related event reported by a storage device monitoring tool.
20. The apparatus of claim 14 , wherein the performance-related information comprises a prediction of at least one performance-related issues generated by a storage device monitoring tool.