A component tracking system includes a plurality of devices that each include a device component monitoring subsystem that monitors for and records the addition and/or removal of device components to/from that device. A device component manager system that is coupled to each of the plurality of devices identifies, via a recording by a first device monitoring subsystem in a first device included in the plurality of devices, the removal of a first device component from the first device. The device component manager system then determines, via a recording by a second device component monitoring subsystem in a second device included in the plurality of devices, that the first device component has been added to the second device within a time period and, in response, the device component manager device prevents a removed first device component alarm.

A data processing board according to an embodiment of the present disclosure includes a data processing module including at least one data processing board for automatically assigning an identifier according to the voltage value measured in the internal circuit and a communication board for transmitting and receiving signal to/from the data processing board, and a data processing system including the data processing module and a monitor collecting device for selecting and parallel-processing the data received from the data processing module.

A system and method is disclosed for the automated identification of causal relationships between a selected set of trigger events and observed abnormal conditions in a monitored computer system. On the detection of a trigger event, a focused, recursive search for recorded abnormalities in reported measurement data, topological changes or transaction load is started to identify operating conditions that explain the trigger event. The system also receives topology data from deployed agents which is used to create and maintain a topological model of the monitored system. The topological model is used to restrict the search for causal explanations of the trigger event to elements of that have a connection or interact with the element on which the trigger event occurred. This assures that only monitoring data of elements is considered that are potentially involved in the causal chain of events that led to the trigger event.

A performance manager (400, 500) and a method (200) performed thereby are provided, for managing the performance of a logical server of a data center. The data center comprises at least one memory pool in which a memory block has been allocated to the logical server. The method (200) comprises determining (230) performance characteristics associated with a first portion of the memory block, comprised in a first memory unit of the at least one memory pool; and identifying (240) a second portion of the memory block, comprised in a second memory unit of the at least one memory pool, to which data of the first portion of the memory block may be migrated to apply performance characteristics associated with the second portion. The method (200) further comprises initiating migration (250) of the data to the second portion of the memory block.

A system and method is disclosed for identifying and evaluating the business relevant impact of observed operating anomalies of monitored components of computing environments like data centers or cloud computing environments. The disclosed technology uses end-to-end transaction trace, availability and resource utilization data in combination with topology data received from agents deployed to the monitored computing environment. An abnormal operating condition is localized within a topological model of the monitored environment and has a defined temporal extent. On detection of an anomaly, affected transaction traces are selected that used the topology entity on which the anomaly was observed while the anomaly existed. Those transactions are then traced backwards, until a topology entity is reached that represents an entry point of monitored system. The affected transactions are compared with unaffected transactions that entered via the entry point to determine the extent to which the entry service is affected by the abnormal behavior.

An agent device 1 of a monitoring system 5 includes: an acquisition unit 22 that sequentially acquires monitored values from a processing unit 21; a removal unit 23 that generates denoised monitored values by removing noise from the monitored values; and a transmission unit that transmits the denoised monitored values to a manager device 2. The manager device 2 includes a determination unit 62 that determines the monitoring interval, at which monitored values are acquired from the agent device 1, by referencing the denoised monitored values acquired from the agent device 1.

A supervisory control system provides power management in an electronic device by providing timeout periods for a hardware component to lower levels of the operating system such as a power management arbitrator and/or a hardware interface controller. The power management arbitrator and/or hardware interface controller transition at least a portion of a hardware component to a lower-power state based on monitored activity information of the hardware component. The supervisory control system may further provide wakeup periods to the power management arbitrator and/or a hardware interface controller to determine whether the hardware component should be transitioned to a higher-power state at the end of the wakeup period if the hardware component satisfies a transition condition.

Techniques for multi-domain systems integration and evaluation are disclosed, including: obtaining criteria associated with a strategic objective; determining that a first system, operating in a first operating domain, is only partially capable of satisfying a first criterion in the criteria; determining that a second system, operating in a second operating domain that is different from the first operating domain, is capable of augmenting the first system with respect to satisfying the first criterion; responsive to determining that the second system is capable of augmenting the first system with respect to satisfying the first criterion, modeling a multi-domain system including at least a first component from the first system and at least a second component from the second system; and generating a performance metric that objectively evaluates capabilities of the multi-domain system against the criteria associated with the strategic objective.

A method, performed by a computing device, includes (a) building a data structure that describes dependence relationships between components of a virtual appliance, the components comprising respective computational processes which may be invoked during booting, a dependence relationship indicating that one component must complete before a second component may be invoked, (b) identifying, with reference to the data structure and an essential set of components which were pre-defined to be essential to the virtual appliance, a set of components that must complete for booting to be considered finished, and, after identifying the required set of components, repeatedly (c) querying each required component for its respective completion status, (d) calculating an estimated completion percentage for booting the virtual appliance with reference to the respective completion statuses of each required component versus all required components, and (e) displaying an indication of the completion percentage to a user via a user interface.

A system on a chip (SoC) includes a first domain comprising a first processor configured to boot the SoC, and a first debug subsystem, a second domain comprising a second processor, the second domain configurable as either a safety domain or a general-purpose processing domain, and isolation circuitry between the first domain and the second domain. During boot-up of the SoC, the first processor provides code to the second domain which, when executed by the second processor, configures the second domain as either a safety domain or as a general-purpose processing domain.