Abstract: 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.

Abstract: Methods, apparatus, and processor-readable storage media for automatically orchestrating deployments of software-defined storage stacks are provided herein. An example computer-implemented method includes obtaining a software-defined storage deployment request from at least one user; determining a request type associated with the software-defined storage deployment request by processing at least a portion of payload content of the software-defined storage deployment request; orchestrating one or more tasks required for carrying out the requested software-defined storage deployment based at least in part on the determined request type and the processed payload content; and performing at least one automated action based at least in part on the one or more orchestrated tasks.

Abstract: Methods, apparatus, and processor-readable storage media for automatically orchestrating deployments of software-defined storage stacks are provided herein. An example computer-implemented method includes obtaining a software-defined storage deployment request from at least one user; determining a request type associated with the software-defined storage deployment request by processing at least a portion of payload content of the software-defined storage deployment request; orchestrating one or more tasks required for carrying out the requested software-defined storage deployment based at least in part on the determined request type and the processed payload content; and performing at least one automated action based at least in part on the one or more orchestrated tasks.

Abstract: 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.

Abstract: A system is described for sending alert messages collected for cloud computing system to external systems. The alert messages may be sent according to determined protocols, such as the syslog protocol and/or SNMP trap, among other appropriate protocols. Partitioning and/or fragmenting of the alert message may be provided based on the use of various types of message identifications and/or other information in which, by virtue of the partitioning and fragmenting, an alert message, regardless of its length, may be sent and reconstructed at the external system. The system advantageously provides for transmission of alert messages using mechanisms other than the syslog protocol and with additional included alert attribute information.

Abstract: A system is described for sending alert messages collected for cloud computing system to external systems. The alert messages may be sent according to determined protocols, such as the syslog protocol and/or SNMP trap, among other appropriate protocols. Partitioning and/or fragmenting of the alert message may be provided based on the use of various types of message identifications and/or other information in which, by virtue of the partitioning and fragmenting, an alert message, regardless of its length, may be sent and reconstructed at the external system. The system advantageously provides for transmission of alert messages using mechanisms other than the syslog protocol and with additional included alert attribute information.

Abstract: A system is described for sending alert messages collected for cloud computing system to external systems. The alert messages may be sent according to determined protocols, such as the syslog protocol and/or SNMP trap, among other appropriate protocols. Partitioning and/or fragmenting of the alert message may be provided based on the use of various types of message identifications and/or other information in which, by virtue of the partitioning and fragmenting, an alert message, regardless of its length, may be sent and reconstructed at the external system. The system advantageously provides for transmission of alert messages using mechanisms other than the syslog protocol and with additional included alert attribute information.

Abstract: A system provides a controller user interface control and/or display of aspects of a storage area network (SAN) and components thereof, including performance characteristics and alert relationship analyses. The controller enables determinations of alert relationships “on-the-fly” for alerts affecting and affected by multiple causes, symptoms and impacts in the SAN, including on-the-fly determinations of root causes. The on-the-fly determinations of the controller provide that the alert relationships may be determined in response to a query or request by the user without requiring the maintaining of a large stored hierarchical relationship structure of alerts.