Predicting Equipment Fail Mode from Process Trace

    公开(公告)号:US20240362106A1

    公开(公告)日:2024-10-31

    申请号:US18141389

    申请日:2023-04-29

    IPC分类号: G06F11/07

    摘要: A predictive model for equipment fail modes. An anomaly is detected in a collection of trace data, then key features are calculated. A search is conducted for the same or similar anomalies having the same key features in a database of past trace data. If the same anomaly occurred before and is in the database, then the type of anomaly, its root cause, and action steps to correct can be retrieved from the database.

    SERVER MANAGEMENT SYSTEM USING AI
    4.
    发明公开

    公开(公告)号:US20240362104A1

    公开(公告)日:2024-10-31

    申请号:US18644440

    申请日:2024-04-24

    申请人: GenlAI CO., LTD

    发明人: Se Kweon YOO

    IPC分类号: G06F11/07 G06F8/65 G06F11/00

    摘要: Provided is a server management system managing two or more management target servers, including: a database for storing data related to the management target servers; and a management server collecting hardware-related data and software-related data from the management target servers, identifying and managing a status of each management target server, and providing various server management information including management service statistical data and a management service report to an administrator terminal used by an administrator and a customer terminal requesting the management target server, wherein the management server analyzes the management target server by using AI technology, predicts an status and a fault of the management target through this analysis, and through the prediction, when an issue occurs, transfers an alarm message as a text message to the relevant administrator terminal and customer terminal. There is an effect capable of preventing faults being likely to occur in the servers in advance.

    Data Center Monitoring and Management Operation for Predicting Memory Failures Within a Data Center

    公开(公告)号:US20240362102A1

    公开(公告)日:2024-10-31

    申请号:US18140921

    申请日:2023-04-28

    IPC分类号: G06F11/07

    CPC分类号: G06F11/0772 G06F11/0793

    摘要: A system, method, and computer-readable medium for performing a data center monitoring and management operation, The data center monitoring and management operation includes receiving data center data for a data center, the data center data comprising data center memory associated data; receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset memory associated data; providing the data center memory associated data and the data center asset memory associated data to a memory failure prediction model; and, training the memory failure prediction model using the data center memory associated data and the data center asset memory associated data.

    METHOD AND SYSTEM FOR REAL-TIME IDENTIFICATION OF BLAST RADIUS OF A FAULT IN A GLOBALLY DISTRIBUTED VIRTUAL DESKTOP FABRIC

    公开(公告)号:US20240362098A1

    公开(公告)日:2024-10-31

    申请号:US18766373

    申请日:2024-07-08

    申请人: Workspot, Inc.

    IPC分类号: G06F11/07 G06F9/451

    摘要: A system and method for determining a blast radius of a major incident occurring in a virtual desktop system is disclosed. The virtual desktop system has interconnected service components and provides access to virtual desktops by client devices. An event collection module collects events from the service components. An aggregation module merges the collected events in a time-ordered stream, provides context to the events in the time-ordered stream through relationships between the collected events, and generates a correlated event stream. An analysis module determines a stream of problem reports from the correlated event stream. The analysis module determines a spike in the stream of problem reports and determines the attributes of the problem reports in the spike to define the major incident. The analysis module determines a scope of the major incident and a corresponding attribute, to determine a blast radius associated with the major incident in the desktop system.

    Operating quantum devices using a temporal metric

    公开(公告)号:US12130694B2

    公开(公告)日:2024-10-29

    申请号:US17941365

    申请日:2022-09-09

    申请人: Google LLC

    摘要: Systems and methods for operating one or more qubits in a quantum computing system are provided. In some examples, a method can include obtaining past time data associated with a temporal metric of an operating parameter of a qubit in a quantum device. The method can include selecting an operating parameter value based at least in part on the past time data associated with the temporal metric of the operating parameter to reduce likelihood of occurrence of a time dependent defect. The time dependent defect can exhibit a time dependent behavior. The method can include operating the qubit in the quantum device at the operating parameter value.

    TECHNOLOGY SYSTEM AUTO-RECOVERY AND OPTIMALITY ENGINE AND TECHNIQUES

    公开(公告)号:US20240354188A1

    公开(公告)日:2024-10-24

    申请号:US18761425

    申请日:2024-07-02

    IPC分类号: G06F11/07

    摘要: Disclosed are hardware and techniques for correcting computer process faults by identifying risk associated with correcting a computer process fault and computer processes that may depend on the corrected computer process. The interdependent computer processes in a network may be determined by evaluating a stream of process break flags from a monitoring component coupled to the network. Each computer process break flag in the stream of computer process break flags indicates a process fault detected by the monitoring component and is correlated to a corrective response. The break flag and the corrective response are assigned a risk. A risk matrix accounts for interdependencies between computer processes and identified corrective actions. A final response strategy that corrects the computer process faults is determined using the assigned risk and computer system interdependence. A runbook stores the final response strategy, which may be updated based on changing computer process interdependencies and assigned risk.