A method for execution by a storage network begins by issuing a decode threshold number of read requests for a set of encoded data slices to a plurality of storage units of a set of storage units and continues by determining whether less than a decode threshold number of read requests has been received in a time window. The method continues by identifying one or more encoded data slices encoded data slices associated with read requests of the decode threshold number of read requests that have not been received and for an encoded data slice of the one or more encoded data slices, issuing a priority read request to a storage unit storing a copy of the encoded data slice. The method then continues by receiving a response from the storage unit storing the copy of the encoded data, where the storage unit storing the copy of the encoded data slice is adapted to delay one or more maintenance tasks in response to the priority read request.

Various embodiments support or provide for interactive electronic documentation (or an electronic document) for operational activities associated with a system or service, such as one monitored or maintained by a system administrator or engineer. In particular, some embodiments provide for an interactive electronic document associated with a runbook, which can comprise a set of actions (e.g., list of operations, procedures, steps, and the like) to be performed with respect to a system or service in connection with an operational event, such as a system/service incident, scheduled maintenance, or a support operation.

Systems, methods and/or computer program products dynamically managing log levels of microservices in a service mesh based on predicted error rates of calls made to the service mesh. A first AI module predicts health, status and/or failures of microservices individually or as part of microservice chains with a particular confidence level. Using health status mapped to the microservices and historical information inputted into a knowledge base (including error rates), the first AI module predicts error rates of the API call for each user profile or generally by the service mesh. A second AI module analyzes the predictions provided by the first AI module and determines whether the predictions meet threshold levels of confidence. To improve the confidence of predictions that are below threshold levels, the second AI module dynamically adjusts application logs of the microservices and/or proxies thereof to an appropriate level to capture more detailed information within the logs.

Apparatus and method for scalable error reporting. For example, one embodiment of an apparatus comprises error detection circuitry to detect an error in a component of a first tile within a tile-based hierarchy of a processing device; error classification circuitry to classify the error and record first error data based on the classification; a first tile interface to combine the first error data with second error data received from one or more other components associated with the first tile to generate first accumulated error data; and a master tile interface to combine the first accumulated error data with second accumulated error data received from at least one other tile interface to generate second accumulated error data and to provide the second accumulated error data to a host executing an application to process the second accumulated error data.

A computer system is provided. The computer system includes a memory, a network interface, and at least one processor configured to monitor a user interface comprising a plurality of user interface elements; detect at least one changed element within the plurality of user interface elements; classify, in response to detecting the at least one changed element, the at least one changed element as either indicating or not indicating an error; generate, in response to classifying the at least one changed element as indicating an error, an error signature that identifies the at least one changed element; identify, using the error signature, a remediation for the error; and provide the remediation in association with the at least one changed element.

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.

Aspects of the disclosure describe methods and systems for cross-referencing forensic snapshots over time. In one exemplary aspect, a method may comprise receiving a first snapshot of a computing device at a first time and a second snapshot of the computing device at a second time and applying a pre-defined filter to the first snapshot and the second snapshot, wherein the pre-defined filter includes a list of files that are to be extracted from each snapshot. The method may comprise subsequent to applying the pre-defined filter, identifying differences in the list of files extracted from the first snapshot and the second snapshot. The method may comprise creating a change map for the computing device that comprises the differences in the list of files over a period of time, wherein the period of time comprises the first time and the second time, and outputting the change map in a user interface.

In an embodiment, an electronic circuit includes: a plurality of signal channels; a signal collection circuit configured to determine an action of the electronic circuit based on channel signals from the plurality of signal channels; and a first signal management circuit coupled between the plurality of signal channels and the signal collection circuit, the first signal management circuit including: a set of internal registers, a set of user registers, and a decoder configured to program the set of internal registers based on a content of the set of user registers, where the first signal management circuit is configured to receive the channel signals via the plurality of signal channels, generate first aggregated signals based on the received channel signals and a content of the set of internal registers, and transmitting the first aggregated signals to the signal collection circuit.

A processing device in a memory system determines to send system state information associated with the memory device to a host system and identifies a subset of a plurality of event entries from a staging buffer based on one or more filtering factors, the plurality of event entries corresponding to events associated with the memory device. The processing device further sends the subset of the plurality of event entries as the system state information to the host system over a communication pipe having limited bandwidth.

An error documentation system including tools to collect and analyze application error data for individual development teams and tools to share documented defects and solutions across development teams during any stage of development cycle. The system may receive and analyze event logs for error events triggered by applications on end-user devices. The system may automatically generate defect tickets and/or ticket entries for defects identified in event logs. The system may train one or more machine learning (ML) models to correlate input with identified defects from a defects database. In response to identifying correlated identified defects, the system may generate ticket entries indicating the correlated identified defects and associated solutions for the defects. The system may provide an interface for users to query the data stored in the database.