Techniques for automated query retry in a database platform include assigning by at least one hardware processor a first execution of a query directed to database data to a first execution node of a plurality of execution nodes of an execution platform. The first execution node uses a first set of configurations during the first execution. The techniques further include determining that the first execution of the query by the first execution node results in a failed execution. The query is transferred to a second execution node of the plurality of execution nodes. A second execution of the query at the second execution node is caused. The second execution node uses a second set of configurations during the second execution. A cause of the failed execution at the first execution node is determined based on a result of the second execution of the query at the second execution node.

The invention relates to an embedded system on board an aircraft for detection and response to incidents with log recording, the aircraft comprising a calculator comprising applications using and generating data and being configured to detect events based on these data and predefined information specifying these events. The system comprises, for the calculator, an agent and a collector. The agent is an application component dedicated to an identified application and is configured to apply an incident detection logic to the detected events in order to detect at least one incident and to send to the collector, through detection messages, each detected incident according to a configurable transmission logic. The collector is configured to receive the messages and to apply, to the messages, a configurable recording logic of the messages in one or several log(s).

Techniques regarding anomaly forecasting are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a forecast component that can determine a probability of a computer application executing an anomaly state based on a probabilistic graph that is incrementally updated while the computer application is running.

A processing system includes safety monitoring circuits configured to generate error signals by monitoring a microprocessor operations, a memory controller, and/or a resource. The system further includes fault collection sub-circuits, each including one or more error combination circuits, each including a first programmable register and being configured to receive a subset of the error signals, determine whether an error signal is asserted, and store to the first register error status data that identifies the asserted error signal. Each error combination circuit is configured to read enable data from the first register and generate a combined error signal based on the error status and enable data. The error management circuit includes a second programmable register and is configured to receive the combined error signals, read routing data from the second register, and generate for each microprocessor an error signal based on the combined error signals and routing data.

A method for handling an anomaly of data, in particular in a motor vehicle. At least one sensor obtains data for the anomaly detection. The sensor examines the obtained data for anomalies, and generates an event as a function of the associated data when an anomaly is detected. It is decided whether the event is further processed, in particular stored and/or further communicated, at least in part.

An information processing system that extracts a specified piece of log data or a specified field that constitutes the specified piece of log data, from a log file in which pieces of log data having different recording formats are mixed, the information processing system includes a format-information recording portion configured to store format information in which a determination condition to identify a recording format of the specified piece of log data is contained, an extraction-condition recording portion configured to store an extraction condition to extract the specified piece of log data or the specified field, and an extraction processing portion configured to extract the specified piece of log data or the specified field, from the log file by using the format information stored in the format-information recording portion and the extraction condition.

A monitoring system is configured to distinguish between two types of alert rules—namely, invariant alert rules and variant alert rules—and to apply a different method of alert rule evaluation to each, wherein each alert rule evaluation method deals with the issue of latent data ingestion in a different way. By tailoring the alert rule evaluation method to the type of alert rule being evaluated, the system can apply an optimized approach for each type of alert rule in terms of achieving a trade-off between alert latency, alert accuracy, and cost of goods sold. In an embodiment, the system utilizes a machine learning model to classify a query associated with an alert rule as either increasing or non-increasing. Then, based on the query classification and a condition associated with the alert rule, the system determines if the alert rule is invariant or variant.

The present disclosure discloses a method and apparatus of monitoring an interface performance of a distributed application, a device and a storage medium, which relates to a field of computer technology, in particular to a field of cloud platform. The method includes: in case of detecting a caller request for calling an interface of the distributed application, obtaining a performance data of the interface for responding the caller request; updating a performance data distribution characteristic of the interface according to the performance data of the interface for responding the caller request, so as to obtain an updated performance data distribution characteristic; and monitoring the interface performance of the distributed application, according to the updated performance data distribution characteristic of the interface.

A method of monitoring Emergency Alert System (EAS) devices includes providing a system, the system including processor(s) in communication with memory(ies) storing instructions for execution by the processor(s), the instructions enabling monitoring of EAS devices, monitoring by the system the EAS devices for all changes to configuration settings and updates to software and firmware for the EAS devices (“changes”), the system further including database(s) automatically storing data regarding the changes, wherein data regarding changes to configuration settings comprises a copy of the configuration settings, wherein the copy is stored chronologically, and the monitoring includes avoiding use of a threshold. The system creates secondary instance(s) of the database(s), monitors for failures of the database(s) and automatically fail(s) over to the secondary instance(s) when fail(s) occur, notifying by the system designated receiver(s) of the changes, and assisting with filtering and/or sorting of selected data from the database.

A quality score for a computer application release is determined using a first number of unique users who have launched the computer application release on user devices and a second number of unique users who have encountered at least once an abnormal termination with the computer application release on user devices. Additionally or optionally, an application quality score can be computed for a computer application based on quality scores of computer application releases that represent different versions of the computer application. Additionally or optionally, a weighted application quality score can be computed for a computer application by further taking into consideration the average application quality score and popularity of a plurality of computer applications.