Server fault detection method and device, processor and storage medium

Abstract

The invention discloses a server fault detection method and device, a processor and a storage medium. The method comprises the following steps: acquiring operation data of a server; the operation data are input into an extraction model for analysis, the operation state of the server is obtained, and the extraction model is obtained through training of historical operation data and historical operation states of the server; in response to the fact that the operation state is a fault state, a data detection model is used for positioning the fault position of a fault occurring in the server, the fault type of the fault is determined, and the data detection model is obtained by training an operation data sample of the server and a fault position sample of the server; based on the fault position and the fault type, fault information of the server is output, and the fault information is used for prompting that the server is in a fault state. According to the invention, the technical problem of low server fault detection efficiency is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of server management, and in particular to a method, device, processor and storage medium for detecting a server fault. Background Art

[0002] At present, in the wave of digital transformation, edge computing, as an extension and supplement to cloud computing, is gradually becoming an important development direction in the field of information technology. As the infrastructure of edge computing, the management efficiency and stability of edge servers are crucial to ensuring the performance and reliability of the entire edge computing system. With the rapid development of cloud computing and Internet of Things technologies, edge servers play an increasingly important role in data processing and storage. However, the remote management and maintenance of edge servers still face many challenges, such as incompatible management interfaces, inaccurate fault detection, and untimely alarm management. Among them, server fault detection is the top priority to ensure the normal operation of the server.

[0003] In related technologies, fault detection is usually based on rules and thresholds, which means they may not be able to adapt to complex and changing environments. Secondly, remote management and maintenance require administrators to have certain technical capabilities and experience, otherwise it may lead to operational errors or improper configuration, which will affect the normal operation of edge servers. In addition, remote management and maintenance also have security risks. If unencrypted communication or unauthenticated remote management is performed, it may be hacked or sensitive data may be stolen. Therefore, there is a technical problem of low efficiency in server fault detection.

[0004] Currently, no effective solution has been proposed to the above-mentioned technical problem of low efficiency in server fault detection. Summary of the invention

[0005] The embodiments of the present invention provide a method, device, processor and storage medium for detecting a server fault, so as to at least solve the technical problem of low efficiency of detecting a server fault.

[0006] According to one aspect of an embodiment of the present invention, a method for detecting a fault of a server is provided. The method may include: obtaining the operation data of the server; inputting the operation data into an extraction model for analysis to obtain the operation status of the server, wherein the extraction model is trained using the historical operation data and the historical operation status of the server; in response to the operation status being a fault state, locating the fault location of the fault occurring in the server using a data detection model, and determining the fault type of the fault, wherein the data detection model is trained using the operation data sample of the server and the fault location sample of the server; based on the fault location and the fault type, outputting the fault information of the server, wherein the fault information is used to indicate that the server is in a fault state.

[0007] Optionally, in response to the operating state being a fault state, a data detection model is used to locate a fault location of a fault occurring in the server, and a fault type of the fault is determined, including: in response to the operating state being a fault state, feature data is extracted from the operating data, wherein the feature data is used to indicate hardware operating data of the server; based on the feature data and the data detection model, the fault location of the fault occurring in the server is located, and the fault type of the server is determined.

[0008] Optionally, based on the characteristic data and the data detection model, locating the fault position of the fault occurring in the server includes: inputting the characteristic data into the data detection model to determine the fault position of the fault occurring in the server.

[0009] Optionally, based on the characteristic data, determining the fault type of the server includes: determining a data format corresponding to the characteristic data, wherein the data format is used to indicate a format type corresponding to the operating data; and comparing the data format with a storage format to determine the fault type of the server.

[0010] Optionally, the server fault detection method further includes: in response to the running state being a fault state, switching the server to a mirror server, wherein the mirror server is a pre-set backup server.

[0011] According to another aspect of an embodiment of the present invention, a server management system is also provided. The system may include: a core management module, which is used to manage and obtain the operation data in the server; a monitoring and alarm module, which is used to extract the operation status of the server using an extraction model based on the operation data obtained by the core management module, wherein the extraction model is obtained by training using the historical operation data and historical operation status of the server; in response to the operation status being a fault state, the fault location of the fault occurring in the server is located using a data detection model, and the fault type of the fault is determined, wherein the data detection model is obtained by training using the operation data sample of the server and the fault location sample of the server, and based on the fault location and fault type, the fault information of the server is output; a remote maintenance module, which is used to remotely process the fault information of the server based on the fault information determined by the monitoring and alarm module, and remotely manage the server at the same time; a user interaction module, which is used to interact with the management object of the server; and an extended function module, which is used to perform image backup and asset management on the server.

[0012] According to another aspect of an embodiment of the present invention, a server fault detection device is also provided. The device may include: an acquisition unit, used to acquire the operation data of the server; an analysis unit, used to input the operation data into an extraction model for analysis to obtain the operation status of the server, wherein the extraction model is trained using the historical operation data and historical operation status of the server; a positioning unit, used to locate the fault location of the fault occurring in the server using a data detection model in response to the operation status being a fault state, and determine the fault type of the fault, wherein the data detection model is trained using the operation data sample of the server and the fault location sample of the server; an output unit, used to output the fault information of the server based on the fault location and the fault type, wherein the fault information is used to prompt that the server is in a fault state.

[0013] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the server fault detection method in an embodiment of the present invention.

[0014] According to another aspect of an embodiment of the present invention, a processor is further provided, wherein the processor is used to run a program, wherein the server fault detection method in the embodiment of the present invention is executed when the program is run.

[0015] According to another aspect of the embodiment of the present invention, a computer program product is provided, which includes computer instructions, and when the computer instructions are executed by a processor, the server fault detection method in the embodiment of the present invention is implemented.

[0016] In an embodiment of the present invention, the operation data of the server is obtained; the operation data is input into an extraction model for analysis to obtain the operation status of the server, wherein the extraction model is obtained by training using the historical operation data and historical operation status of the server; in response to the operation status being a fault state, the fault location of the fault occurring in the server is located using a data detection model, and the fault type of the fault is determined, wherein the data detection model is obtained by training using the operation data samples of the server and the fault location samples of the server; based on the fault location and the fault type, the fault information of the server is output, wherein the fault information is used to prompt that the server is in a fault state. That is to say, the present invention determines the operation status of the server through the operation data of the server, thereby using the data detection model to detect the fault location and fault type of the server according to the operation status, thereby solving the technical problem of low efficiency of server fault detection and achieving the technical effect of improving the efficiency of server fault detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 is a flow chart of a method for detecting a server failure according to an embodiment of the present invention;

[0019] Figure 2 is a schematic diagram of a management system of a server according to an embodiment of the present invention;

[0020] Figure 3 is a schematic diagram of an intelligent management system architecture of an edge server according to an embodiment of the present invention;

[0021] Figure 4 It is a schematic diagram of a server fault detection device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, functional component or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, functional components or devices.

[0024] According to an embodiment of the present invention, an embodiment of a server fault detection method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0025] Figure 1 is a flow chart of a method for detecting a server failure according to an embodiment of the present invention. Figure 1 As shown, the method may include the following steps:

[0026] Step S101, obtaining the operation data of the server.

[0027] In the technical solution provided in the above step S101 of the present invention, the operation data may at least include but is not limited to the hardware status data of the server.

[0028] In this embodiment, the operation data of the server is obtained, for example, by using a monitoring tool, a third-party monitoring tool, viewing a log file, a remote monitoring tool, and other methods. This is only an illustrative example and does not limit the specific method of obtaining the operation data of the server.

[0029] Step S102: input the operation data into the extraction model for analysis to obtain the operation status of the server.

[0030] In the technical solution provided in the above step S102 of the present invention, the extraction model is obtained by training using the historical operation data and historical operation status of the server. The extraction model can also be established based on the extraction algorithm.

[0031] In this embodiment, after the operation data of the server is acquired in step S101, the operation data is input into the extraction model for analysis to obtain the operation status of the server, wherein the operation status may at least include the operation status of key components such as CPU, memory, disk, network, etc.

[0032] For example, through the extraction algorithm built into the server's management system, the hardware status of the server can be determined through operating data, providing strong support for rapid troubleshooting.

[0033] Step S103, in response to the running state being a fault state, using the data detection model to locate the fault location of the fault occurring in the server, and determining the fault type of the fault.

[0034] In the technical solution provided in the above step S103 of the present invention, the data detection model is trained by using the operation data samples of the server and the fault location samples of the server.

[0035] In this embodiment, after the running state of the server is obtained in step S102, when the running state is a fault state, the data detection model is used to locate the fault position of the fault occurring in the server and determine the fault type of the fault.

[0036] Optionally, when the operation status is a fault state, it means that the server cannot run at this time and the fault needs to be located. Based on this, feature data is extracted from the operation data, wherein the feature data is used to indicate the hardware operation data of the server.

[0037] Optionally, after extracting characteristic data from the operation data, the fault location and fault type of the server are located according to the characteristic data.

[0038] Optionally, in order to locate the fault position, the feature data is input into a data detection model, and the feature data is analyzed using the data detection model to obtain the fault position where the server fault occurs.

[0039] For example, the data detection model is used to locate the fault location to a specific field replaceable unit (FRU).

[0040] Optionally, to determine the type of fault, the data format corresponding to the characteristic data can be determined, wherein the data format is used to indicate the format type corresponding to the operating data, and the data format may at least include but is not limited to: Simple Network Management Protocol Trap (SNMP Trap), Simple Mail Transfer Protocol (SMTP), system log (syslog), etc.; the data format is compared with the storage format to determine the fault type of the server.

[0041] Step S104: outputting the fault information of the server based on the fault location and the fault type.

[0042] In the technical solution provided in the above step S104 of the present invention, the fault information is used to prompt that the server is in a fault state.

[0043] In this embodiment, after locating the fault location of the fault occurring in the server and determining the fault type of the fault in step S103, the fault location and fault type are compared with the fault location and fault type stored in the server. When the comparison result is a match, the fault information of the current server can be determined and the fault information of the server can be output.

[0044] For example, when a fault or abnormal situation is detected, an alarm is triggered immediately. It supports multiple formats of alarm information reporting, such as SNMP Trap, SMTP, and syslog, to ensure that administrators can receive alarm information in a timely manner and take appropriate measures.

[0045] It should be noted that the above embodiments can be executed by an edge server intelligent management system.

[0046] In the above steps S101 to S104 of the present invention, the operation data of the server is obtained; the operation data is input into the extraction model for analysis to obtain the operation status of the server, wherein the extraction model is obtained by training using the historical operation data and historical operation status of the server; in response to the operation status being a fault state, the fault location of the fault occurring in the server is located using the data detection model, and the fault type of the fault is determined, wherein the data detection model is obtained by training using the operation data samples of the server and the fault location samples of the server; based on the fault location and the fault type, the fault information of the server is output, wherein the fault information is used to prompt that the server is in a fault state. That is to say, the present invention determines the operation status of the server through the operation data of the server, thereby using the data detection model to detect the fault location and fault type of the server according to the operation status, thereby solving the technical problem of low efficiency of server fault detection and achieving the technical effect of improving the efficiency of server fault detection.

[0047] The above method of this embodiment is further introduced below.

[0048] As an optional implementation method, in response to the operating state being a fault state, a data detection model is used to locate the fault location of the fault occurring in the server, and the fault type of the fault is determined, including: in response to the operating state being a fault state, feature data is extracted from the operating data, wherein the feature data is used to indicate the hardware operating data of the server; based on the feature data and the data detection model, the fault location of the fault occurring in the server is located, and the fault type of the server is determined.

[0049] In this embodiment, when the operating state is a fault state, feature data is extracted from the operating data, for example, basic statistical features, time series features, frequency domain features, etc. are extracted from the operating data, wherein statistical features are used to represent the distribution and central tendency of the operating data, time series features are used to describe the pattern of changes in the operating data over time, and frequency domain features are used to describe the characteristics of the operating data in the frequency domain. This is only for illustrative purposes and does not limit the specific method for extracting feature data.

[0050] Optionally, after the feature data is extracted, the fault location of the server fault is located according to the feature data and the data detection model, and the fault type of the server is determined.

[0051] Optionally, by determining the fault location and fault type of the fault, strong support is provided for rapid troubleshooting, which not only reduces the troubleshooting time but also improves the accuracy of fault handling.

[0052] As an optional implementation manner, based on the characteristic data and the data detection model, the fault position of the fault occurring in the server is located, including: inputting the characteristic data into the data detection model to determine the fault position of the fault occurring in the server.

[0053] In this embodiment, the characteristic data is input into the data detection model, and the characteristic data is analyzed using the data detection model to determine the fault location of the server fault.

[0054] Optionally, by inputting feature data into a data detection model, the fault location of the server can be identified more accurately to avoid misjudgment or missed judgment.

[0055] As an optional implementation method, determining the fault type of the server based on the characteristic data includes: determining the data format corresponding to the characteristic data, wherein the data format is used to indicate the format type corresponding to the running data; comparing the data format with the storage format to determine the fault type of the server.

[0056] In this embodiment, the data format corresponding to the characteristic data is determined, and the data format is compared with the storage format to determine the fault type of the server. For example, the data format is: SNMP Trap, SMTP, syslog, etc.

[0057] Optionally, by determining different data types, different alarm information reporting methods can be selected subsequently to ensure that the administrator can receive the alarm information in a timely manner and take corresponding processing measures.

[0058] As an optional implementation manner, the server fault detection method further includes: in response to the running state being a fault state, switching the server to a mirror server, wherein the mirror server is a pre-set backup server.

[0059] In this embodiment, when the operation state is a fault state, it means that the server cannot operate, based on which, the server can be switched to a mirror server, wherein the mirror server can also be called a backup mirror, and the server can also be called a primary mirror.

[0060] For example, when the primary image fails, the system can automatically switch to the backup image to run, ensuring high reliability and stability of the system. This dual-image backup mechanism not only improves the system's fault tolerance, but also ensures business continuity.

[0061] It should be noted that the above embodiments can be executed by an edge server intelligent management system.

[0062] According to an embodiment of the present invention, a server management system is also provided. It should be noted that the server management system can be used to execute the server fault detection method in the method embodiment.

[0063] Figure 2 FIG. 1 is a schematic diagram of a server management system according to an embodiment of the present invention. Figure 2 As shown, the management system 200 of the server may include: a core management module 201 , a monitoring and alarm module 202 , a remote maintenance module 203 , a user interaction module 204 and an extended function module 205 .

[0064] The core management module 201 is used to manage and obtain the operation data in the server.

[0065] The monitoring and alarm module 202 is used to extract the operating status of the server based on the operating data obtained by the core management module 201 by using an extraction model, wherein the extraction model is trained using the historical operating data and historical operating status of the server; in response to the operating status being a fault state, the data detection model is used to locate the fault location of the fault occurring in the server and determine the fault type of the fault, wherein the data detection model is trained using the operating data samples of the server and the fault location samples of the server, and based on the fault location and fault type, the server fault information is output.

[0066] The remote maintenance module 203 is used to remotely process the fault information of the server based on the fault information determined by the monitoring and alarm module 202, and remotely manage the server.

[0067] The user interaction module 204 is used to interact with the management objects of the server.

[0068] The extended function module 205 is used to perform image backup and asset management on the server.

[0069] In this embodiment, the core management module 201 serves as the core of the system. The module integrates multiple management interfaces such as IPMIV2.0, CLI, HTTPS, SNMP V3, etc., to ensure that the system can be flexibly and seamlessly connected with various standard management systems to meet diverse system integration requirements.

[0070] Optionally, the monitoring and alarm module 202 includes a fault detection submodule and an alarm management submodule. Among them, the fault detection submodule: through the built-in advanced algorithm, this module can monitor the hardware status of the server in real time, and quickly locate the specific FRU when an abnormality is found, providing strong support for rapid troubleshooting.

[0071] Optionally, once the alarm management submodule detects a fault or abnormal situation, the module will immediately trigger an alarm and report the alarm information to the administrator through SNMP Trap, SMTP, syslog and other formats to ensure the high reliability operation of the equipment 24 hours a day, 7 days a week.

[0072] Optionally, the remote maintenance module 203 includes a virtual kernel (Kernel-based Virtual Machine, referred to as KVM) submodule and a virtual media submodule. Among them, the virtual KVM submodule provides a powerful remote maintenance function, supports a screen display with a maximum resolution of 1920*1200, and enables the administrator to perform remote operation and maintenance of the system without having to be on site.

[0073] Optionally, the administrator of the virtual media submodule can virtualize local media devices or images and folders as media devices of remote servers, thereby simplifying the installation and configuration process of the operating system and improving maintenance efficiency. The transmission speed of the virtual optical drive can reach 8MB / s, further accelerating the data transmission speed.

[0074] Optionally, the user interaction module 204 includes a Web user interface submodule and a screenshot and video recording module. The Web user interface submodule provides an intuitive and easy-to-use Web user interface, and the administrator can complete the system settings and query tasks by simply clicking, greatly reducing the difficulty of management.

[0075] Optionally, the screenshot and video submodule allows administrators to view screenshots without logging into the system, making it easier to conduct scheduled inspections and troubleshoot problems. At the same time, the module also supports screen video recording, providing strong support for fault analysis and system optimization.

[0076] Optionally, the extended function module 205 includes a DNS / directory service submodule, a software dual-image backup submodule, an intelligent asset management submodule, and an IPv6 support module. Among them, the DNS / directory service submodule system can support domain management and directory services, thereby simplifying the complexity of server management network and configuration and improving management efficiency.

[0077] Optionally, the software dual-image backup submodule implements a dual-image backup mechanism for the software. When a primary image fails, the system can automatically switch to the backup image for operation, thereby ensuring high reliability and stability of the system.

[0078] Optionally, the intelligent asset management submodule can perform intelligent management of server assets, realize automatic inventory and tracking of assets, and improve the accuracy and efficiency of asset management.

[0079] Optionally, the IPv6 support submodule enables the system to support IPv6 functions, facilitate the construction of a full IPv6 environment, solve the problem of IP address exhaustion, and adapt to the development trend of future networks.

[0080] In this embodiment, the operation data of the server is obtained; the operation data is input into the extraction model for analysis to obtain the operation status of the server, wherein the extraction model is obtained by training using the historical operation data and historical operation status of the server; in response to the operation status being a fault state, the fault location of the fault occurring in the server is located using the data detection model, and the fault type of the fault is determined, wherein the data detection model is obtained by training using the operation data samples of the server and the fault location samples of the server; based on the fault location and the fault type, the fault information of the server is output, wherein the fault information is used to prompt that the server is in a fault state. That is to say, the present invention determines the operation status of the server through the operation data of the server, thereby using the data detection model to determine the fault location and fault type of the server according to the operation status, thereby solving the technical problem of low efficiency of server fault detection and achieving the technical effect of improving the efficiency of server fault detection.

[0081] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0082] At present, in the wave of digital transformation, edge computing, as an extension and supplement to cloud computing, is gradually becoming an important development direction in the field of information technology. As the infrastructure of edge computing, the management efficiency and stability of edge servers are crucial to ensuring the performance and reliability of the entire edge computing system. With the rapid development of cloud computing and Internet of Things technologies, edge servers play an increasingly important role in data processing and storage. However, the remote management and maintenance of edge servers still face many challenges, such as incompatible management interfaces, inaccurate fault detection, and untimely alarm management. Among them, server fault detection is the top priority to ensure the normal operation of the server.

[0083] In related technologies, fault detection is usually based on rules and thresholds, which means that they may not be able to adapt to complex and changing environments. Secondly, remote management and maintenance require administrators to have certain technical capabilities and experience, otherwise it may lead to operational errors or improper configuration, which will affect the normal operation of the edge server. In addition, remote management and maintenance also have security risks. If unencrypted communication or unauthenticated remote management is performed, it may be hacked or sensitive data may be stolen. Therefore, there is a technical problem of low efficiency in server fault detection. In view of the above-mentioned technical problem of low efficiency in server fault detection, no effective solution has been proposed.

[0084] However, the embodiment of the present invention proposes an intelligent management system for edge servers, which significantly improves the remote management efficiency of edge servers, the accuracy of fault detection, and the convenience of system maintenance by integrating a series of innovative management functions and technologies. The system not only has high compatibility and scalability, but also supports IPv6 functions, adapts to the development trend of future networks, solves the technical problem of low server fault detection efficiency, and achieves the technical effect of improving server fault detection efficiency.

[0085] The embodiments of the present invention are further described below.

[0086] Figure 3 is a schematic diagram of an intelligent management system architecture of an edge server according to an embodiment of the present invention, such as Figure 3 As shown, the intelligent management system (Intelligent Baseboard Management Controller, iBMC system for short) 300 of the edge server is logically divided into five levels: core management layer 301, monitoring and alarm layer 302, remote maintenance layer 303, user interaction layer 304 and extended function layer 305.

[0087] In this embodiment, the core management layer 301: The core management layer is the core part of the iBMC system, and mainly includes a management interface module 3011. This module integrates multiple management interfaces such as IPMI V2.0, CLI, HTTPS, and SNMP V3 to ensure that the system can be flexibly and seamlessly connected with various standard management systems. These interfaces not only meet the diverse system integration requirements, but also improve the compatibility and scalability of the system. Through the management interface module, administrators can easily remotely configure, monitor, and manage edge servers, greatly improving management efficiency.

[0088] Optionally, monitoring and alarm layer 302: The monitoring and alarm layer mainly includes a fault detection module 3021 and an alarm management module 3022. The fault detection module 3021 can monitor the hardware status of the server in real time, including the operation of key components such as CPU, memory, disk, network, etc., through built-in advanced algorithms. Once an abnormality is found, the module will quickly locate the specific FRU (Field Replaceable Unit) to provide strong support for rapid troubleshooting. This precise fault location capability not only reduces the time for troubleshooting, but also improves the accuracy of fault handling.

[0089] Optionally, the alarm management module 3022 is responsible for triggering an alarm immediately when a fault or abnormal situation is detected. The module supports multiple formats of alarm information reporting methods such as SNMP Trap, SMTP, and syslog, ensuring that the administrator can receive the alarm information in a timely manner and take corresponding processing measures. In addition, the alarm management module also supports alarm classification and alarm filtering functions, which can perform different processing according to the severity and urgency of the alarm, avoiding unnecessary alarm interference.

[0090] Optionally, the remote maintenance layer 303 mainly includes a virtual KVM module 3031 and a virtual media module 3032. The virtual KVM module 3031 provides a powerful remote maintenance function and supports a screen display with a maximum resolution of 1920x1200. Through this module, the administrator can remotely operate and maintain the edge server without going to the site, such as system installation, configuration update, troubleshooting, etc. This remote maintenance method not only improves maintenance efficiency, but also reduces maintenance costs.

[0091] Optionally, the virtual media module 3032 allows the administrator to virtualize a local media device or image or folder as a media device of a remote server. Through this module, the administrator can easily transfer the operating system installation image, driver, configuration file, etc. to the remote server, thereby simplifying the installation and configuration process of the operating system. The transmission speed of the virtual optical drive can reach 8MB / s, which further speeds up the data transmission speed and improves the maintenance efficiency.

[0092] Optionally, the user interaction layer 304 mainly includes a Web user interface module 3041 and a screenshot and video module 3042. The Web user interface module 3041 provides an intuitive and easy-to-use Web user interface, and the administrator can complete the system settings and query tasks by simply clicking. This graphical interface design greatly reduces the difficulty of management, making it easy for even non-professional administrators to get started.

[0093] Optionally, the screenshot and video module 3042 allows the administrator to view the screenshots without logging into the system. This function is particularly suitable for scheduled inspections and troubleshooting scenarios. The administrator can quickly understand the operating status and abnormal conditions of the server by viewing the screenshots. At the same time, the module also supports the screen recording function, which can record the operation process and fault phenomena of the server, providing strong support for fault analysis and system optimization.

[0094] Optionally, the extended function layer 305 mainly includes a DNS / directory service module 3051, a software dual-image backup module 3052, an intelligent asset management module 3053, and an IPv6 support module 3054. The DNS / directory service module 3051 enables the system to support domain management and directory services, thereby simplifying the complexity of server management network and configuration. Through this module, the administrator can conveniently manage the server's network configuration, user permissions, etc., thereby improving management efficiency.

[0095] Optionally, the software dual-image backup module 3052 implements a dual-image backup mechanism for the software. When the primary image fails, the system can automatically switch to the backup image for operation, ensuring the high reliability and stability of the system. This dual-image backup mechanism not only improves the fault tolerance of the system, but also ensures the continuity of business.

[0096] Optionally, the intelligent asset management module 3053 is responsible for intelligent management of server assets. Through this module, the system can automatically inventory and track the hardware and software assets of the server, including the model, serial number, configuration information, etc. of the equipment. This intelligent asset management method not only improves the accuracy and efficiency of asset management, but also facilitates the administrator to uniformly configure and manage the server.

[0097] Optionally, the IPv6 support module 3054 enables the system to support IPv6 functions. With the exhaustion of IPv4 addresses and the popularization of IPv6, supporting IPv6 functions is essential for building a full IPv6 environment and adapting to the development trend of future networks. Through this module, the iBMC system can easily communicate and integrate with other devices that support IPv6, improving the compatibility and scalability of the system.

[0098] The following is a further explanation of the intelligent management system of the edge server of the present invention by taking a large-scale Internet of Things project as an example.

[0099] In this embodiment, a large-scale Internet of Things project is taken as an example. The project covers multiple fields such as smart cities, intelligent transportation, and environmental monitoring, and deploys tens of thousands of edge servers, which are responsible for data processing, storage, and real-time analysis. Due to the large number of servers and their dispersed geographical locations, traditional manual management and monitoring methods are inadequate and cannot meet the urgent needs of the project for efficient and accurate management. In this context, the project team decided to introduce the intelligent management system (iBMC) of the present invention in order to achieve a dual improvement in management efficiency and server stability.

[0100] Optionally, integrate multiple management interfaces to improve management flexibility: After the introduction of the iBMC system, project administrators are no longer limited to a single management method. They can access the system through multiple interfaces such as IPMIV2.0, CLI, HTTPS, SNMP V3, etc., and choose the most appropriate management tool according to actual needs. For example, in daily maintenance, administrators may prefer to use the intuitive Web user interface for operation; while for in-depth configuration or troubleshooting, they may choose the more flexible CLI interface. This diversified management method not only improves management flexibility, but also greatly improves management efficiency.

[0101] Optionally, real-time monitoring and fault warning to ensure system stability: The fault detection module of the iBMC system provides a solid guarantee for the stable operation of the project. This module can monitor the hardware status of the server in real time, including key indicators such as CPU usage, memory usage, disk health, network traffic, etc. Once an abnormality is detected, the system will immediately trigger an alarm and push the alarm information to the administrator through SNMP Trap, SMTP, syslog and other methods. For example, during a regular inspection, the system successfully detected a bad sector on the hard disk of a server located in a remote area and triggered an alarm in time. After receiving the alarm, the administrator immediately carried out emergency processing on the server through the remote maintenance function, successfully avoiding data loss and system crash, and ensuring the continuous operation of the project.

[0102] Optionally, remote maintenance function simplifies system upgrade and configuration: The virtual KVM and virtual media functions of the iBMC system provide great convenience for remote maintenance. During a system upgrade, the project team faced a challenge: due to the large number of servers and their wide distribution, if they were upgraded one by one on site, it would not only be time-consuming and labor-intensive, but also might affect the normal operation of the project. However, through the virtual KVM function of the iBMC system, the administrator can remotely access the server console to upgrade and configure the system. At the same time, using the virtual media function, the administrator uploaded the local operating system image and upgrade package to the server, simplifying the installation and upgrade process of the operating system. In this way, the project team completed the upgrade of all servers in a short time, ensuring the smooth progress of the project.

[0103] Optional Web user interface and screenshots to help troubleshoot: The Web user interface and screenshot and recording functions of the iBMC system provide administrators with an intuitive and easy-to-use management interface. During a troubleshooting, the administrator viewed the server log information through the Web user interface and found abnormal login attempts and incorrect system configurations. In order to better understand the cause of the failure, the administrator used the screenshot function to capture the screen when the failure occurred. These screenshots provide strong support for fault analysis, helping administrators quickly locate the problem and take appropriate repair measures.

[0104] Optionally, expand the functional layer to improve management efficiency and accuracy: In addition to the core functions mentioned above, the iBMC system also provides extended functions such as DNS / directory services, software dual-image backup, intelligent asset management, and IPv6 support. Through DNS / directory services, the project team can easily manage the server's network configuration and user permissions, improving management efficiency. The software dual-image backup mechanism ensures the high reliability and stability of the system. Even if the main image fails, the system can automatically switch to the backup image for operation. The intelligent asset management function enables the project team to grasp the hardware and software assets of the server in real time, providing strong support for asset configuration and optimization. The IPv6 support function enables the system to adapt to the development trend of future networks and provides a guarantee for the long-term operation of the project.

[0105] In this embodiment, by integrating a series of innovative management functions and technologies, the remote management efficiency of the edge server, the accuracy of fault detection, and the convenience of system maintenance are significantly improved. The system is not only highly compatible and scalable, but also supports IPv6 functions, adapts to the development trend of future networks, solves the technical problem of low server fault detection efficiency, and achieves the technical effect of improving server fault detection efficiency.

[0106] According to an embodiment of the present invention, a server fault detection device is also provided. It should be noted that the server fault detection device can be used to execute the server fault detection method in the method embodiment.

[0107] Figure 4 FIG. 1 is a schematic diagram of a server fault detection device according to an embodiment of the present invention. Figure 4 As shown, the server fault detection device 400 may include: an acquisition unit 401 , an analysis unit 402 , a positioning unit 403 and an output unit 404 .

[0108] The acquisition unit 401 is used to acquire the operation data of the server.

[0109] The analysis unit 402 is used to input the operation data into the extraction model for analysis to obtain the operation status of the server, wherein the extraction model is trained using the historical operation data and historical operation status of the server.

[0110] The positioning unit 403 is used to locate the fault location of the fault occurring in the server using a data detection model in response to the operating state being a fault state, and to determine the fault type of the fault, wherein the data detection model is trained using the operating data samples of the server and the fault location samples of the server.

[0111] The output unit 404 is used to output the fault information of the server based on the fault location and the fault type, wherein the fault information is used to prompt that the server is in a fault state.

[0112] Optionally, the positioning unit 403 may include: an extraction module, used to extract feature data from the operating data in response to the operating state being a fault state, wherein the feature data is used to indicate the hardware operating data of the server; a positioning module, used to locate the fault location of the fault occurring in the server based on the feature data and a data detection model, and determine the fault type of the server.

[0113] Optionally, the positioning module may include: a determination submodule, which is used to input the characteristic data into the data detection model to determine the fault location of the fault occurring in the server.

[0114] Optionally, the determination submodule may also be used to determine a data format corresponding to the characteristic data, wherein the data format is used to indicate a format type corresponding to the operating data; and the data format is compared with the storage format to determine the fault type of the server.

[0115] Optionally, the server fault detection device 400 may further include: a switching unit, configured to switch the server to a mirror server in response to the running state being a fault state, wherein the mirror server is a pre-set backup server.

[0116] In this embodiment, the operation data of the server is obtained; the operation data is input into the extraction model for analysis to obtain the operation status of the server, wherein the extraction model is obtained by training using the historical operation data and historical operation status of the server; in response to the operation status being a fault state, the fault location of the fault occurring in the server is located using the data detection model, and the fault type of the fault is determined, wherein the data detection model is obtained by training using the operation data samples of the server and the fault location samples of the server; based on the fault location and the fault type, the fault information of the server is output, wherein the fault information is used to prompt that the server is in a fault state. That is to say, the present invention determines the operation status of the server through the operation data of the server, thereby using the data detection model to determine the fault location and fault type of the server according to the operation status, thereby solving the technical problem of low efficiency of server fault detection and achieving the technical effect of improving the efficiency of server fault detection.

[0117] According to an embodiment of the present invention, a computer-readable storage medium is further provided. The storage medium includes a stored program, wherein the program executes the server fault detection method in the method embodiment.

[0118] According to an embodiment of the present invention, a processor is further provided. The processor is used to run a program, wherein the server fault detection method in the method embodiment is executed when the program is running.

[0119] According to an embodiment of the present invention, a computer program product is further provided. The computer program product includes computer instructions. When the computer instructions are executed by a processor, the server fault detection method in the method embodiment is implemented.

[0120] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0121] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0122] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0123] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0124] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0125] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent functional component, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software functional component, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc., which can store program codes.

[0126] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for detecting a server failure, characterized in that: include: Get the server's operating data; Inputting the operation data into an extraction model for analysis to obtain the operation status of the server, wherein the extraction model is trained using the historical operation data and historical operation status of the server; In response to the operating state being a fault state, locating a fault location of a fault occurring in the server by using a data detection model, and determining a fault type of the fault, wherein the data detection model is trained by using an operating data sample of the server and a fault location sample of the server; Based on the fault location and the fault type, fault information of the server is output, wherein the fault information is used to prompt that the server is in the fault state.

2. The method according to claim 1, characterized in that In response to the operating state being a fault state, locating a fault location of a fault occurring in the server by using a data detection model, and determining a fault type of the fault, including: In response to the operating state being the fault state, extracting feature data from the operating data, wherein the feature data is used to indicate hardware operating data of the server; Based on the characteristic data and the data detection model, the fault location of the fault occurring in the server is located, and the fault type of the server is determined.

3. The method according to claim 2, characterized in that Locating the fault position of the fault occurring in the server based on the feature data and the data detection model includes: The characteristic data is input into the data detection model to determine the fault location of the fault occurring in the server.

4. The method according to claim 3, characterized in that Determining the fault type of the server based on the characteristic data includes: Determining a data format corresponding to the characteristic data, wherein the data format is used to indicate a format type corresponding to the operation data; The data format is compared with the storage format to determine the fault type of the server.

5. The method according to claim 1, characterized in that The method further comprises: In response to the operating state being the fault state, the server is switched to a mirror server, wherein the mirror server is a pre-set backup server.

6. A server management system, characterized in that: include: A core management module, used to manage and obtain the operation data in the server; A monitoring and alarm module, configured to extract the operating status of the server using an extraction model based on the operating data acquired by the core management module, wherein the extraction model is trained using the historical operating data and historical operating status of the server; in response to the operating status being a fault state, locate the fault location of the fault occurring in the server using a data detection model, and determine the fault type of the fault, wherein the data detection model is trained using the operating data samples of the server and the fault location samples of the server, and output the fault information of the server based on the fault location and the fault type; A remote maintenance module, configured to remotely process the fault information of the server based on the fault information determined by the monitoring and alarm module, and remotely manage the server; A user interaction module, used to interact with the management object of the server; The extended function module is used for performing image backup and asset management on the server.

7. A server fault detection device, characterized in that: include: An acquisition unit, used for acquiring operation data of the server; An analysis unit, configured to input the operation data into an extraction model for analysis to obtain the operation status of the server, wherein the extraction model is trained using the historical operation data and historical operation status of the server; a positioning unit, configured to locate a fault position of the fault occurring in the server using a data detection model in response to the operating state being a fault state, and determine a fault type of the fault, wherein the data detection model is trained using an operating data sample of the server and a fault position sample of the server; An output unit is used to output the fault information of the server based on the fault location and the fault type, wherein the fault information is used to prompt that the server is in the fault state.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 6.

9. A processor, characterized in that: The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 6 when running.

10. A computer program product, characterized in that The computer program product comprises computer instructions, which implement the method according to any one of claims 1 to 6 when executed by a processor.

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