A method for detecting an anomaly includes retrieving a log file that includes log entries, grouping the log entries into clusters of log entry types based on number of occurrences and average time interval, and discovering a sequence of the log entry types within each of the clusters. The sequence of the log entry types is based on a shortest path from a first one of the log entry types to a last one of the log entry types.

Techniques described herein relate to a method for performing testing operations for information handling systems. The method includes obtaining a test case from an information handling system; in response to obtaining the test case: obtaining log information associated with the test case from the information handling system; performing data preparation to generate processed subsequences using the log information; applying a plurality of prediction models to the processed subsequences and training data to generate anomalous subsequence predictions; generating ensemble anomaly scores and severity indexes associated with the processed subsequences using the anomalous subsequence predictions and the processed subsequences; making a determination that the ensemble anomaly scores and severity indexes associated with the processed subsequences result in detection of an anomalous subsequence; and in response to the determination: determining a next best test case associated with the anomalous subsequence; and initiating performance of the next best test case.

Disclosed herein are a method for generating Gaussian error data using flash memory and an apparatus using the method. The method includes receiving a request to generate Gaussian error data and delivering an operation command to flash memory; generating Gaussian error noise based on a threshold voltage that is generated when the flash memory performs the operation command; and generating Gaussian error data so as to correspond to the Gaussian error noise and providing the same.

A method for targeted repair of a hardware component in a computing device that is part of a cloud computing system includes monitoring a plurality of hardware components in the computing device. At some point, a defective sub-component within the hardware component of the computing device is identified. In addition to the defective sub-component, the hardware component also includes at least one sub-component that is functioning properly and a spare component that can be used in place of the defective sub-component. The method also includes initiating a targeted repair action while the computing device is connected to the cloud computing system. The targeted repair action prevents the defective sub-component from being used by the computing device without preventing sub-components that are functioning properly from being used by the computing device. The targeted repair action causes the spare component to be used in place of the defective sub-component.

A method for generating a backup schedule, that includes receiving, by a scheduling agent, an event entry specifying an event associated with a container, determining that the event entry specifies an alert event, adding the event entry to a plurality of historical event entries in a historical event repository, determining that the plurality of historical event entries indicates a repeating error state of the container, determining that an error frequency of the repeating error state is greater than an existing backup frequency of a container backup schedule, and generating a backup schedule warning indicating a recommended backup frequency.

A non-volatile memory device, a method of operating the non-volatile memory device, and a memory system including the non-volatile memory device are provided. A non-volatile memory device includes a memory cell array including a plurality of memory cells configured to be each programmed to one state of a plurality of states, a page buffer circuit including a plurality of page buffers configured to each store received data as state data indicating a target state of a corresponding one of the plurality of memory cells, the page buffer circuit being configured to perform a state data reordering operation of changing a first state data order into a second state data order during performance of a program operation on selected memory cells of the plurality of memory cells, and a reordering control circuit configured to control the page buffer circuit to perform the state data reordering operation simultaneously with the program operation.

Systems and methods for managing the degradation of IHS performance due to software installations are described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: identify a workload; in response to the identification, configure a performance measurement; calculate a level of performance degradation of the IHS based, at least in part, upon the performance measurement; and in response to the level of performance degradation meeting a threshold value, provide an indication to a user or Information Technology (IT) administrator.

Non-limiting examples of systems, methods, and devices for automatic triaging of diagnostic failures for heterogeneous groups of tenants of a Software-as-a-Service, multi-tenant environment are disclosed herein. In an implementation, telemetry data for the heterogeneous groups of tenants is analyzed to classify individual tenant failures and detect the health status of the individual tenant. Tenant failures and/or tenant health statuses are filtered according to a threshold level. Anomalies having metrics that meet or exceed the threshold level are further analyzed to determine their priority (e.g., to a specific tenant). If the anomalies are known, then an existing entry for the anomaly is tagged and its priority may be changed. If the anomalies are unknown, then an entry is generated for the anomaly and prioritized. Tenants may be notified of a detected anomaly and may provide feedback. The feedback may be used to update triaging models.

A distributed system includes an edge device which is at least one of an automatically operable moving body and equipment, and a diagnostic data computer, in which the edge device converts state data representing a state of a component that is a constituent of a replaceable unit forming the edge device, into diagnostic data according to a predetermined diagnostic algorithm, and the diagnostic data computer acquires the diagnostic data from a first edge device, and specifies a second edge device that employs a component related to the component employed in he first edge device.

A cloud scraping system using pre-scraped big data includes an information providing server which, when receiving a scraping request from a user terminal, provides the user terminal with response information to the received scraping request, and a big data storage which stores pre-scraped information, wherein when the scraping request is about static information, the information providing server acquires the response information using the pre-scraped information. According to the above cloud scraping system using pre-scraped big data, there is an advantage that it is possible to quickly respond to a scraping request from the user terminal afterwards by pre-scraping and storing static information in the big data storage. Additionally, it is possible to improve the scraping server operation efficiency by making a proper use of a single or multi-processing scraping server based on policy information of a scraping target external institution.