According to an embodiment, an error log list and alarm service system comprises an execution terminal receiving an alarm including error information according to an operation error in a machine facility designated through an error log list and alarm service platform and a monitoring server collecting a result of monitoring an operation state and operation error in the machine facility, extracting the error information according to an information setting value set by the execution terminal, and providing the extracted error information through a web or app platform.

Techniques are disclosed relating to a method that includes accessing, by a failure management program, a failure log that includes a plurality of character strings corresponding to errors that are associated with execution of one or more batch processes. The failure management program may compare a particular character string of the plurality of character strings to a set of character strings that are associated with respective ones of a plurality of failure categories. This comparing may include determining whether particular keywords that are included in respective ones of the set of character strings are included in the particular character string. In response to the comparing, the failure management program may assign a particular error corresponding to the particular character string to a particular failure category, or may determine a new failure category if the particular character string does not match an existing failure category.

According to various embodiments, a method, medium, and system for exporting log messages related to a particular job running in a micro services system is described in this disclosure. The method uses a mapping table to narrow down the search scope for finding relevant log files. The mapping table maps a job attribute combination to one or more micro services, and thus will direct the search for relevant log messages only to those log files related to the one or more micro services. The search scope can be further narrowed down using a start time and end time of the job. Once the relevant log files are found, log messages containing an identifier of the job can be extracted from the relevant log files for display or for a user to download. The mapping table can be automatically generated by parsing through historical files in a system non-busy time.

A UART includes a transmission register, a receive register, a virtual remappable pin, a parity error check circuit to evaluate contents of the receive register for a parity error, and control logic to determine contents of the transmission register. The contents include underlying data and a parity bit based thereupon. The control logic is to route the contents through the first virtual remappable pin to the receive register. The control logic is to, before reception of the entire contents at the receive register, cause modified contents to be provided to the receive register. The modified contents are to cause a parity error. The modified contents are to include different underlying data or a different parity bit than the contents of the transmission register. The control logic is to determine whether the parity error check circuit detected the parity error.

Various embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured accurately and programmatically train a responder prediction machine learning model for generating response team predictions based on the systematic collection of one or more responder prediction training corpuses comprising one or more alert related datasets in a responder prediction server system. For example, the responder prediction server system may extract one or more alert attributes for each of the one or more alert related datasets for training one or more responder prediction machine learning models and/or one or more prioritization machine learning models. The responder prediction machine learning model and prioritization machine learning models may process one or more alerts, in real-time, to generate one or more response team prediction objects for rendering in a response team suggestion interface.

An apparatus comprises a processing device configured to identify, at a first microservice, a service call that is to be transmitted to a second microservice, and to modify the service call to include context information, the context information characterizing a current state of execution of one or more tasks by one of the first microservice and the second microservice. The processing device is further configured to provide, from the first microservice to the second microservice, the modified service call including the context information. The context information enables re-initiation of said one of the first microservice and the second microservice to continue execution of the one or more tasks from the current state.

The systems and methods described herein provide the ability to detect a clocking element fault within an IC device and switch to an alternate clock. In response to detection of a fault in a phase-lock-loop (PLL) clocking element, the device may switch to an alternate clock so that error reporting logic can make forward progress on generating error message. The error message may be generated within an Intellectual Property (IP) cores (e.g., IP blocks), and may send the error message from the IP core to a system-on-a-chip (SOC), such as through an SOC Functional Safety (FuSA) error reporting infrastructure. In various examples, the clocking error may also be output to a hardware SOC pin, such as to provide a redundant path for error indication.

A system and method for allowing an assignee to rapidly collect data about a bug/error that is associated with the execution of a software application on a computing device. The method includes including receiving, from a client device, a request to resolve an error associated with an execution of an application on a remote server. The request includes configuration information for connecting to the remote server and an identifier to a component of the application. The method includes determining one or more files associated with the component of the application. The method includes establishing a connection to the remote server using the configuration information. The method includes retrieving the one or more files from the remote server via the connection. The method includes granting, to an assignee device, access to the one or more files that were retrieved from the remote server.

A method for managing applications includes obtaining, by a client in a customer environment, an upgrade issue report for the application, making a first determination that a resynchronization of a client self-healing classification model with the production host environment (PHE) self-healing classification model is required, wherein the PHE self-healing classification model is stored in the PHE, performing the resynchronization with the PHE self-healing classification model to obtain a synchronized client self-healing classification model, applying the synchronized client self-healing classification model to the upgrade issue report to obtain a state of the upgrade issue report, making a second determination that the state indicates a self-healable state, based on the second determination, performing a self-healing process on the application based on the upgrade issue report, and storing a resolution report based on results of the self-healing process, wherein the PHE is operatively connected to the customer environment.

Aspects of the disclosure relate to data feed meta detail categorization for confidence. A computing platform may retrieve source data from a source system and identify a first set of patterns associated with the source data. The computing platform may retrieve, from a target system, transferred data associated with a data transfer from the source system to the target system and identify a second set of patterns associated with transferred data. The computing platform may evaluate integrity of the transferred data by comparing the first set of patterns with the second set of patterns. The computing platform may detect whether the first set of patterns falls within an expected deviation from the second set of patterns based on the comparison. The computing platform may send one or more notifications based on detecting that the first set of patterns falls outside the expected deviation from the second set of patterns.