Abstract: A device context of a device is identified based on device data including a current state of the device, and a user context of a user is identified based on user data including user interaction with a user interface for the device. A current task that the user is performing on the device in relation to the current state of the device is identified, and knowledge regarding how the user is performing the current task using the user interface is extracted, using an artificial intelligence technique with respect to the identified device context and the identified user context. The extracted knowledge for the identified current task is stored within a knowledge base, and can be used to adapt the user interface for another user performing the current task on the device in the current state.

Abstract: Tasks of a group are respectively assigned to devices for execution. For each task, a completion time for a task is determined based on an associated cluster of the device to which the task has been assigned for execution is determined. If the completion time of a task exceeds an execution window of the device to which the task has been assigned, the task is removed from the group. The tasks remaining in the group are executed on the devices to which the tasks have been assigned for execution.

Abstract: Presented is a method and system for automatically selecting agent-based or agentless monitoring using a configuration management database (CMDB). The method includes determining whether a system is business critical or business non-critical, selecting agent-based monitoring if the system is business critical and selecting agentless monitoring if the system is business non-critical.

Abstract: A device context of a device is identified based on device data including a current state of the device, and a user context of a user is identified based on user data including user interaction with a user interface for the device. A current task that the user is performing on the device in relation to the current state of the device is identified, and knowledge regarding how the user is performing the current task using the user interface is extracted, using an artificial intelligence technique with respect to the identified device context and the identified user context. The extracted knowledge for the identified current task is stored within a knowledge base, and can be used to adapt the user interface for another user performing the current task on the device in the current state.

Abstract: Tasks of a group are respectively assigned to devices for execution. For each task, a completion time for a task is determined based on an associated cluster of the device to which the task has been assigned for execution is determined. If the completion time of a task exceeds an execution window of the device to which the task has been assigned, the task is removed from the group. The tasks remaining in the group are executed on the devices to which the tasks have been assigned for execution.

Abstract: Provided is a method of automatically discovering topology of an information technology (IT) infrastructure. Topology relationships amongst configuration items (CI) present in a semi-structured data generated by an information technology component of the IT infrastructure are determined. Topology relationships amongst configuration items (CI) present in a structured data generated by the information technology component of the IT infrastructure are determined. The topology relationships amongst the configuration items (CI) present in the semi-structured data are reconciled with the topology relationships amongst the configuration items (CI) present in the structured data.

Abstract: Provided is a method of automatically discovering topology of an information technology (IT) infrastructure. Topology relationships amongst configuration items (CI) present in a semi-structured data generated by an information technology component of the IT infrastructure are determined. Topology relationships amongst configuration items (CI) present in a structured data generated by the information technology component of the IT infrastructure are determined. The topology relationships amongst the configuration items (CI) present in the semi-structured data are reconciled with the topology relationships amongst the configuration items (CI) present in the structured data.

Abstract: Based on an event classification for an event of a cross-domain computing environment, a metric of a configuration item is obtained and used to isolate a causation of the event, wherein the event is a symptom or occurrence of an operational problem of at least one computing device in the cross-domain computing environment.

Abstract: Based on an event classification for an event of a cross-domain computing environment, a metric of a configuration item is obtained and used to isolate a causation of the event.

Abstract: Presented is a method and system for automatically selecting agent-based or agentless monitoring using a configuration management database (CMDB). The method includes determining whether a system is business critical or business non-critical, selecting agent-based monitoring if the system is business critical and selecting agentless monitoring if the system is business non-critical.