Abstract: Methods and systems for managing operation of a data pipeline are disclosed. To manage the operation, a system may include one or more data sources, a data manager, and one or more downstream consumers. Requests for data from the downstream consumers may have unexpected characteristics that may cause misalignment of application programming interfaces used by the data pipeline. To remediate the misalignment and reduce occurrences of future misalignments, an error message may be obtained indicating a type of error associated with the request. The error message may be used to obtain an error classification for the request and an action set may be performed based on the error classification. In addition, data provided to the downstream consumers may cause misalignment of an application programming interface used by the downstream consumers. Similarly, an error message may be obtained and used to identify an appropriate action set to remediate the misalignment.

Abstract: Systems, methods, and computer-readable media for intelligent webhook are described herein. The intelligent webhook can insert code into one or containers associated with an application being deployed by an orchestration service. The code enables the intelligent webhook to monitor operations, including startup, of a container mutated to include the code. The intelligent webhook has knowledge of whether a mutated container failed to startup in a prior instance, and if it fails, the intelligent webhook can insert a modified version of the code and/or adjust resource limit constraints to facilitate mutation of a container scheduled to be deployed with an application.

Abstract: A monitoring-data processing method is executable by at least one processor included in a monitoring-data processing system that includes a control apparatus that retrieves monitoring data indicative of a surrounding of a vehicle. The monitoring-data processing method includes performing processing of the monitoring data retrieved by the control apparatus, and determining whether there is a malfunction in the monitoring-data processing system. The monitoring-data processing method additionally includes performing, in response to a malfunction determination that there is a malfunction in the monitoring-data processing system, a task of (i) switching the control apparatus to be in a reset state and thereafter (ii) restarting the control apparatus while holding data indicative of the malfunction in an internal storage of the control apparatus.

Abstract: A self-correcting secure computer system is provided. The computer system includes a read-only memory (ROM) device, a random access memory (RAM) device, and at least one processor in communication with the ROM device and the RAM device. The at least one processor is programmed to receive an activation signal; retrieve, from the ROM device, data to execute an operating system; execute, on the RAM device, the operating system based on the data from the ROM device; receive a clear RAM signal; end execution of the operating system on the RAM device; and depower the RAM device such that all data on the RAM device is deleted.

Abstract: Provided is a failover automation system and method comprising: obtaining, by a processor, a process inventory for a failover of an application from a first datacenter to a second data center; generating, by the processor, a data model for the failover based on the process inventor; generating, by the processor, a workflow for the failover based on the data model; assembling, by the processor, a set of one or more virtual engineers to perform the failover for the application based on the workflow; and performing, by the processor, the failover for the application with the set of one or more virtual engineers based on the workflow.

Abstract: Systems and methods are disclosed including a memory device and a processing device operatively coupled to the memory device. The processing device can perform operations including detecting a read error with respect to data residing in a first block of the memory device, wherein the first block is associated with a voltage offset bin; determining a most recently performed error-handling operation performed on a second block associated with the voltage offset bin; and performing the error-handling to recover the data.

Abstract: A storage platform (100) improves data flow when modifying mirrored volumes. A backup storage component (120 A) that receives a service request keeps a copy of change data when redirecting the service request to a primary storage component (120B) that owns the volume that the service request targets. The primary storage (120B) component does not need to return the change data to the backup storage component (120A) when the primary storage component (120B) instructs the backup storage component (120 A) to apply the modification request to the backup copy of the volume.

Abstract: A command to read specific data stored at a memory die is received. A read operation is performed while operating both a memory controller and the memory die simultaneously at a first frequency. A processor determines whether a first error rate associated with the memory die satisfies a first error threshold criterion (e.g., UECC). Responsive to determining that the first error rate satisfies the first error threshold criterion, the read operation is repeated while operating at least one of the memory controller or the memory die at a second frequency that is different from the first frequency. The processor determines whether a second error rate associated with the memory die satisfies a second error threshold criterion. Responsive to determining that the second error rate satisfies the second error threshold criterion (e.g. UECC persists), determining that the read operation has failed.

Abstract: An apparatus is disclosed for making circuitry with passive fundamental components more robust. In example implementations, an apparatus includes at least one passive fundamental component and at least one redundant passive fundamental component. The apparatus also includes fault tolerant circuitry coupled to the at least one passive fundamental component and the at least one redundant passive fundamental component. The fault tolerant circuitry includes fault detection circuitry configured to detect a fault of the at least one passive fundamental component. The fault tolerant circuitry also includes component repair circuitry configured to disconnect the at least one passive fundamental component based on the fault.

Abstract: A method, computer program product, and computer system for proactive microservice migration prior to server failure. A directed acyclic graph representing a microservice-based application and including nodes representing microservices is received. Multiple execution paths passing through the nodes are identified. Multiple unique servers configured to provide the microservices are identified. A Continuous Time Markov Chain model generated for each unique server is characterized by a failure rate and a repair rate of each unique server. A weight is computed for each unique server. A failure probability of each execution path is computed in dependence on the weight, and both failure and repair rate, of the unique servers. One or more vulnerable paths are selected from the multiple execution paths, wherein the failure probability of each selected vulnerable path exceeds a specified failure probability threshold. All microservices on at least one vulnerable path are migrated to one or more other servers.

Abstract: Exposing a memory cell value during trace replay prior to an execution time at which the memory cell value was recorded into a trace. A computer system identifies a first and a second trace fragment within a trace, each recording an uninterrupted consecutive execution of a plurality of executable instructions. The computer system determines that the first trace fragment is orderable prior to the second trace fragment and, based on an inter-fragment analysis, that a value of a memory cell recorded into the second trace fragment is compatible with the first trace fragment. The computer system generates output data indicating that the value of the memory cell can be exposed, during a replay of the trace, at a first execution time that is prior to a second execution time of an event that caused the value of the memory cell to be recorded into the second trace fragment.

Abstract: Methods, systems, and apparatuses for storing operational information related to operation of a non-volatile array are described. For example, the operational information may be stored in a in a subarray of a memory array for use in analyzing errors in the operation of memory array. In some examples, an array driver may be located between a command decoder and a memory array. The array driver may receive a signal pattern used to execute an access instruction for accessing non-volatile memory cells of a memory array and may access the first set of non-volatile memory cells according to the signal pattern. The array driver may also store the access instruction (e.g., the binary representation of the access instruction) at a non-volatile subarray of the memory array.

Abstract: An apparatus comprises a processing device configured to obtain a testing data set associated with a test scenario comprising a configuration phase and execution of test suites, the testing data set comprising a first portion generated from the configuration phase and additional portions generated from execution of the test suites. The processing device is also configured to generate a first data structure based on analyzing the first portion of the testing data set in a first namespace, and to insert at least a portion of the first data structure into additional namespaces each comprising a corresponding one of the additional portions of the testing data set generated from execution of one of the test suites. The processing device is further configured to generate additional data structures based on analyzing the additional portions of the testing data set and the inserted components of the first data structure in the additional namespaces.

Abstract: An automated system is provided for facilitating resolution of an incident on a digital processing system. The automated system has a data storage unit with information on previous incidents, a user interface and a resolution facilitation server. The server receives incident information from a monitoring system, including status information for at least one operating parameter of the digital processing system. The server is configured to apply a machine learning model to determine a first recommended action using the incident information and the previous incident information, present the first recommended action to the user, and receive a recommendation response. The server is also configured to establish a recommendation score based at least in part on the recommendation response and to update the machine learning model using the incident information, the first action recommendation, and/or the first recommendation score.

Abstract: A system includes a memory device and a processing device coupled to the memory device. The memory processing device can perform operations including receiving data indicative of occurrence of a plurality of events. The processing device can perform operations including determining an event log type for each of the plurality of events. The processing device can perform operations including storing an identifier associated with each of the determined event log types. The processing device can perform operations including updating a counter value associated with each identifier in response to occurrence of an event associated with the respective identifier.

Abstract: A software framework for implementation in the performance of automated robotic workflows imparts a hierarchical communications command structure, utilizing an actor-based model to run driver software isolated from scheduling software, by instantiating a message-based abstraction layer that acts as an intermediary between the scheduling software and the third-party driver software. The actor-based model is used within the message-based abstraction layer to isolate the third-party software controlling third party instruments from scheduling software, where such scheduling software and third-party instruments are operating on a common computing platform. This framework prevents scheduling applications from entering an error state, or crashing, where the third-party software component also crashes, and allows the scheduling software to restart the third-party software to continue with the processes controlled by the scheduling software, without interruption to the automated workflow environment.

Abstract: Systems and methods of reconstructing execution call flows to detect anomalies are provided. A device can establish call flows using information extracted from a log file. Each of the call flows can identify information from the log file of a call flowing through a plurality of modules. The device can identify a count of a number of occurrences of one or more keywords in information of each call flow. The device can generate a vector of numbers for each call flow based at least on the count for the one or more keywords for that call flow. The device can classify each call flow into one or more clusters that indicate whether an operation of the call flow is anomalous. The device can classify each call flow using the vector of numbers for each call flow.

Abstract: A system is provided for code base sharing during computing application failure using a distributed register network. In particular, the system may comprise a plurality of computing application systems that are associated with one another and stored on a distributed register. In this regard, the distributed register may share a code base as well as processing logs for each application. The system may use a deep learning based machine learning process for identifying the dependencies, input data sources for each application, and expected data outputs. Accordingly, if an application experiences a failure, the payload of the failed application may be read and/or processed by another application to maintain the workflow. Furthermore, the system may use AI/ML processes to analyze the code base and/or system logs associated with application failures and generate recommendations for remediating failures.

Abstract: Embodiments for an intelligent log analysis and retention for microservices applications. Such log analysis is helpful in troubleshooting failure conditions that may occur intermittently or repeatedly within a microservices environment. Executed operations by microservices, applications, or components generate logs, and these logs are classified based on certain parameters. A default log retention period defines how long the logs are stored in the system, and a log analytical engine determines and assigns weights constituting additional retention time to keep logs for failed operations. These logs can then be analyzed to determine causes of the failure, and build failure models to predict future failure conditions. Logs for successful operations can be timely deleted to save storage space.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: monitoring data center assets within a data center; identifying an issue within the data center, the issue being associated with an operational situation associated with a particular component of the data center; scheduling a remediation task via a data center monitoring and management application, the remediation task being designed to address the issue within the data center; and, performing a data center remediation operation based upon the remediation task.