Embodiments of the present disclosure provide for predicted operational support data object selection and provision functionality. Predicted operational support data object(s) may be selected and provided to address particular malfunction classification(s) affecting networked device(s) on a dynamic home communications network. Some embodiments include identifying, in real-time, a device identification data set associated with a networked device set communicable with the dynamic home communications network; retrieving a device activity data set associated with the networked device set; applying a malfunction classification data model to the device activity data set to select the predicted operational support data object from the device operational support management repository; and outputting the predicted operational support data object to a client device in communication with the dynamic home communications network. The malfunction classification data model is trained based on training data, external aggregated activity data, and malfunction device history data.

Methods, systems, and computer-readable media are disclosed herein that monitor and improve network performance and reliability of a plurality of devices and nodes. In aspects, alert types are categorized based on the role, model, and operating system of a device or node within the network for which the alert was generated. A command set that is responsive to the alert and that is specially configured for the role, model, and operating system of the device or node is automatically selected to address the alert. The command set can be executed against the device or node (or neighboring device/node) in order to investigate the cause or source of the alert. Based on the results returned by the command set's execution, remediation actions can be selected and implemented to improve the technological performance (e.g., memory, CPU, connectivity) of the device or node in the network.

Systems and methods are provided for analyzing one or more root causes of service degradation events in a network or other environment. A method, according to one implementation, includes a step of monitoring a plurality of overlying services offered in an underlying infrastructure having a plurality of resources arranged with a specific topology. In response to detecting a negative impact on the overlying services during a predetermined time window and based on an understanding of the specific topology, the method further includes the step of identifying suspect components from the plurality of resources in the underlying infrastructure. The method also includes the step of obtaining status information with respect to the suspect components to determine a root cause of the negative impact on the overlying services.

Techniques for enabling secure access to data using data blocks is described. Computing device(s) can provide instruction(s) to a component associated with an entity, wherein the instruction(s) are associated with an identifier corresponding to a data block of a plurality of data blocks. The computing device(s) can receive, from the component, data associated with the component, wherein the data is associated with the identifier and is indicative of a state of the component. The computing device(s) can store the data in the data block and monitor, using rule(s), changes to the state of the component based at least partly on the data in the data block. As a result, techniques described herein enable near real-time—and in some examples, automatic—reporting and/or remediation for correcting changes to the state of the component using data that is securely accessed by use of data blocks.

A warning monitoring system includes: a warning information generation unit configured to receive a warning and a ripple warning generated due to the warning, each including a device name and sent by a device configuring a network, determine respective types of the warning and the ripple warning based on messages included in the warning and the ripple warning, and generate warning information in which the warning and the ripple warning are associated with the types; a network configuration database in which configuration information about the network is accumulated; and an interrelation analysis unit including a prior rule that indicates a generation manner of the ripple warning different depending on the type, and configured to acquire specific connection destination information by searching the network configuration database by using target information defined by the prior rule and the device name as keys, and relate the warning and the ripple warning.

An apparatus comprises a processing device configured to identify a given one of one or more assets in an information technology infrastructure associated with a support indicator associated with a priority level, and to obtain information characterizing state transitions of the one or more assets. The processing device is also configured to determine, based at least in part on a current state of the given asset identified utilizing the obtained information, a probability of the given asset transitioning to each of a plurality of states and to select, based at least in part on the determined probabilities, one of the plurality of states as a predicted future state of the given asset utilizing conformal prediction. The processing device is further configured to modify the priority level of the support indicator associated with the given asset based at least in part on the predicted future state of the given asset.

Techniques are described for an IT and security operations application to automatically generate aggregate (or “bulk,” “group,” or “composite”) notable events by identifying notable events sharing common characteristics and aggregating the related notable events into a single aggregate notable event entity that can be displayed and operated upon. The IT and security operations application identifies related notable events based on notable events generated by a common correlation search, notable events having common event attributes, based on user-specified relatedness criteria, or other such criteria. Once identified, in some embodiments, the IT and security operations application displays, in notable event lists and other interfaces, a singular aggregate notable event to users representing each of the identified related notable events.

Embodiments of the present invention provide a system for processing real-time event logs related to monitored events on a network. The system is configured for identifying one or more entity resources associated with an entity, continuously monitoring the one or more entity resources, identifying one or more events associated with the one or more entity resources, pre-processing the one or more events, via an artificial intelligence engine, identifying at least one event of the one or more events is abnormal based on pre-processing the one or more events, filtering the at least one event that is abnormal, segmenting the at least one event from the one or more events, and in response to segmenting the at least one event, storing the at least one event in a first log that is different from a second log that stores the one or more events excluding the at least one event.

A warning monitoring system includes: a warning information generation unit 10 configured to receive a warning and a ripple warning generated due to the warning, each including a device name and sent by a device configuring a network, determine respective types of the warning and the ripple warning based on messages included in the warning and the ripple warning, and generate warning information in which the warning and the ripple warning are associated with the types; a network configuration database 30 in which configuration information about the network is accumulated; and an interrelation analysis unit 20 including a prior rule that indicates a generation manner of the ripple warning different depending on the type, and configured to acquire specific connection destination information by searching the network configuration database 30 by using target information defined by the prior rule and the device name as keys, and relate the warning and the ripple warning.

A computer implemented method of monitoring operation of a communication network for the purpose of controlling the communication network. The method includes monitoring data relating to failures in the communication network; identifying a first set of failures comprising a statistically significant number of substantially similar failures; detecting that statistically significant number of failures of said first set of failures is associated with at least one common component, and responsively, outputting an alert related to the common component.