Fault handling method, apparatus, device, medium, and program product

Abstract

The disclosure provides a fault handling method, which can be applied to the field of artificial intelligence technology. The fault handling method comprises the following steps: obtaining a plurality of processing schemes of a fault to be handled; calculating an effectiveness score S1, a capacity score S2 and a handling complexity score S3 of each processing scheme, wherein the effectiveness score S1 represents a probability of success of the processing scheme, the capacity score S2 represents a feasible capacity of minimum granularity of the processing scheme, and the handling complexity score S2 represents a handling time t and a maximum tolerance time T of the processing scheme; calculating a handling score S of each processing scheme by using the effectiveness score S1, the capacity score S2 and the handling complexity score S3 of each processing scheme; and selecting a processing scheme that satisfies a preset condition in the handling score S to handle the fault to be handled. The disclosure also provides a fault handling device, equipment, a storage medium and a program product.

Description

Technical Field

[0001] This disclosure relates to the field of artificial intelligence, specifically to a method, apparatus, device, medium, and program product for handling faults. Background Technology

[0002] With the rapid development and application of technologies such as artificial intelligence, cloud computing, and virtualization, the demand for hardware and software infrastructure by major enterprises has increased exponentially. Consequently, the maintenance costs of computer-related equipment are also rising. As alarms occur frequently, staff mainly rely on their work experience to determine the root cause of alarms and handle pending faults. The root cause of an alarm is the pending fault. However, alarms are multifaceted, redundant, and coupled, which can cause widespread alarms when faults occur at certain core levels. If staff lack experience, they may be unable to handle or quickly resolve such faults.

[0003] In the process of realizing the concept of this invention, the inventors discovered that the related technologies have at least the following problems: the root cause of the alarm needs to be investigated and handled manually, which is inefficient and unstable, and there are risks in handling the fault. Summary of the Invention

[0004] In view of the above problems, this disclosure provides fault handling methods, apparatus, equipment, media and program products that improve the efficiency of fault handling.

[0005] According to a first aspect of this disclosure, a method for handling faults is provided, comprising:

[0006] Obtain multiple solutions for the pending fault;

[0007] Calculate the effectiveness score S1, capacity score S2, and disposal complexity score S3 for each processing scheme. The effectiveness score S1 represents the probability of successful processing of the scheme, the capacity score S2 represents the feasible capacity of the scheme at the smallest granularity, and the disposal complexity score S3 represents the processing time t and the maximum tolerance time T of the scheme.

[0008] The disposal score S of each disposal scheme is calculated by using the effectiveness score S1, capacity score S2, and disposal complexity score S3 of each disposal scheme.

[0009] Select a processing scheme that meets the preset conditions and handles the fault to be processed.

[0010] According to embodiments of this disclosure, calculating the capacity score for each processing scheme includes:

[0011] In the case of pending faults, obtain the number of devices n that can be restarted without affecting the operation of the service, the total number m of devices with pending faults and devices with the same function as the devices with pending faults, the average CPU utilization c of devices without pending faults, and the maximum CPU utilization C that the devices can tolerate.

[0012] The restart score Sc is calculated based on the number of devices n that can be restarted without affecting business operation and the total number of devices m among the devices connected to the business.

[0013] The isolation score Sg is obtained based on the ratio of average CPU utilization c to maximum CPU utilization C.

[0014] Add the restart score Sc and the isolation score Sg to obtain the capacity score S2.

[0015] According to embodiments of this disclosure, the restart score Sc is calculated using the following formula:

[0016] .

[0017] According to embodiments of this disclosure, the isolation fraction Sg is calculated using the following formula:

[0018] .

[0019] According to embodiments of this disclosure, the processing complexity score S3 is calculated using the following formula:

[0020] .

[0021] According to embodiments of this disclosure, the disposal score S of the processing scheme is calculated using the following formula:

[0022] ;

[0023] Where k1, k2 and k3 are the weighting coefficients of S1, S2 and S3, respectively.

[0024] According to embodiments of this disclosure, before obtaining multiple processing solutions for the fault to be processed, the method further includes:

[0025] Obtain historical faults and multiple corresponding handling solutions;

[0026] Establish a mapping list of historical faults and their corresponding multiple handling solutions.

[0027] According to embodiments of this disclosure, multiple processing solutions for obtaining a fault to be processed include:

[0028] Obtain alarm data;

[0029] Determine the diagnostic decision tree corresponding to the alarm data based on the alarm data;

[0030] The root cause of the alarm is found by using a decision diagnostic tree. The root cause of the alarm is an unresolved fault.

[0031] Based on the mapping list, find multiple processing solutions corresponding to the fault to be processed.

[0032] A second aspect of this disclosure provides a fault handling apparatus, comprising:

[0033] The acquisition module is used to acquire multiple processing solutions for the fault to be processed;

[0034] The first calculation module is used to calculate the effectiveness score S1, capacity score S2 and disposal complexity score S3 for each processing scheme. The effectiveness score S1 represents the probability of successful processing of the processing scheme, the capacity score S2 represents the feasible capacity of the processing scheme at the smallest granularity, and the disposal complexity score S3 represents the processing time t and the maximum tolerance time T of the processing scheme.

[0035] The second calculation module is used to calculate the disposal score S of each processing scheme based on the effectiveness score S1, capacity score S2 and disposal complexity score S3 of each processing scheme.

[0036] The handling module is used to select a handling scheme that meets the preset conditions to handle the fault to be handled.

[0037] A third aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the aforementioned fault handling method.

[0038] A fourth aspect of this disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform a method for handling the aforementioned fault.

[0039] The fifth aspect of this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements a method for handling the aforementioned fault.

[0040] The methods, apparatus, electronic devices, storage media, and computer program products provided by the embodiments of this disclosure can quickly output the optimal processing solution to handle the fault by calculating the effectiveness score S1, capacity score S2, and handling complexity score S3 of each processing solution, resulting in high efficiency and high stability. Attached Figure Description

[0041] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0042] Figure 1 The illustration schematically depicts application scenarios of fault handling methods, apparatus, devices, media, and program products according to embodiments of the present disclosure;

[0043] Figure 2 A flowchart illustrating a fault handling method according to an embodiment of the present disclosure is shown schematically;

[0044] Figure 3 A flowchart illustrating a fault handling method according to another embodiment of the present disclosure is shown schematically;

[0045] Figure 4 A schematic diagram illustrating a fault handling apparatus according to an embodiment of the present disclosure is shown; and

[0046] Figure 5 A block diagram of an electronic device suitable for implementing a fault handling method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0047] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0048] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0049] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0050] When using expressions such as "at least one of A, B, and C," the expression should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.). When using expressions such as "at least one of A, B, or C," the expression should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, or C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0051] In the technical solution disclosed herein, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and there is no violation of public order and good morals.

[0052] In existing technologies, when an alarm occurs, staff need to find the root cause of the alarm and handle the pending fault. However, manual troubleshooting is time-consuming and prone to errors. After finding the fault, it needs to be handled based on individual work experience. Since everyone's experience is different, their ability to handle faults varies. Many complex faults require finding experienced staff to handle them again, resulting in low efficiency and a high error rate.

[0053] The embodiments of this disclosure provide a fault handling method, apparatus, electronic device, storage medium, and program product, which mainly belong to the field of artificial intelligence.

[0054] Figure 1 The illustrations depict application scenarios of fault handling methods, apparatus, electronic devices, storage media, and program products according to embodiments of the present disclosure.

[0055] It is important to note that Figure 1 The examples shown are merely examples of application scenarios that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0056] like Figure 1 As shown, application scenario 100 according to this embodiment may include terminal devices 101, 102, and 103, a network 104, and a server 105. Network 104 serves as a medium for providing a communication link between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0057] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0058] Terminal devices 101, 102, and 103 can be various electronic devices with displays and web browsing capabilities, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0059] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using terminal devices 101, 102, and 103 (for example only). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0060] It should be noted that the fault handling method provided in this embodiment can generally be executed by server 105. Correspondingly, the fault handling device provided in this embodiment can generally be located in server 105. The fault handling method provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105. Correspondingly, the fault handling device provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105.

[0061] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0062] The following will be based on Figure 1 The described scene, through Figures 2-3 The fault handling method of the disclosed embodiments will be described in detail.

[0063] Figure 2 A flowchart illustrating a fault handling method according to an embodiment of the present disclosure is shown schematically.

[0064] like Figure 2 As shown, the fault handling method of this embodiment includes operations S210 to S240.

[0065] During operation S210, multiple processing options for the fault to be processed are obtained;

[0066] The faults to be processed here are all historical faults that have occurred in the past. Some of these historical faults have been handled through various processing schemes. By operating S210, the foundation for the calculation of various fractions below is laid.

[0067] In operation S220, calculate the effectiveness score S1, capacity score S2, and disposal complexity score S3 for each processing scheme;

[0068] Because the recorded historical faults are abstract fault information, omitting some on-site information such as fault time and capacity information, it is necessary to combine the current on-site information and characteristics to re-screen and sort the initially obtained multiple processing solutions. The effectiveness, capacity, and processing complexity of each processing solution are used to determine whether it can handle the fault and to find the most suitable solution. First, the effectiveness score S1, capacity score S2, and processing complexity score S3 of each processing solution are calculated. The effectiveness score S1 represents the probability of successful processing, the capacity score S2 represents the feasible capacity at the smallest granularity, and the processing complexity score S3 represents the processing time t and the maximum tolerance time T.

[0069] The effectiveness score S1 is the probability value of the successful handling of the treatment plan. The probability value of the successful handling of the treatment plan is a probability value based on the statistics of historical handling results.

[0070] The capacity score S2 for each processing scheme can only be calculated if the calculation conditions are met. If the calculation conditions are not met, the capacity score S2 is 0. The calculation conditions include the transaction volume of the device's backend server and the CPU utilization of each device meeting the preset threshold. The transaction volume refers to the number of transactions that occur on the backend server of the current device. For example, if there are 5 transfer transactions, the transaction volume is 5. To calculate the capacity score S2 for each processing scheme, it is necessary to first obtain the following: the number of devices n that can be restarted without affecting the operation of the business when there is a pending fault; the total number m of devices with pending faults and devices with the same function as the devices with pending faults; the average CPU utilization c of devices without pending faults; and the maximum CPU utilization C that each device can tolerate. The maximum CPU utilization C that each device can tolerate is the same.

[0071] Regarding the number of devices (n) that can be restarted without affecting business operations, and the total number (m) of devices with pending faults and devices with the same function as those with pending faults, let's explain in detail below. For example, if a housing provident fund website's backend server is connected to 10 devices, and a pending fault occurs, restarting 6 devices allows users to still access the website normally, but restarting 7 devices significantly slows down website access. Therefore, the number of devices that can be restarted without affecting business operations is considered to be 6, and n is 6. If a business consists of multiple functions, and each function is connected to multiple devices, for example, if one device for the transfer function experiences a pending fault, and this transfer function is connected to 9 other devices without pending faults, then the total number of devices is 10, and m is 10.

[0072] The restart score Sc is calculated based on the number of devices (n) that can be restarted without affecting service operation and the total number of devices (m) within the service connection; based on n and 0.5 The relative magnitude of m determines how Sc is calculated. The specific calculation of the fraction Sc is performed using the following formula:

[0073] .

[0074] The isolation score Sg is obtained based on the ratio of average CPU utilization c to maximum CPU utilization C. If all devices corresponding to a function fail, the isolation score Sg is recorded as 0. If some devices corresponding to a function fail, the isolation score Sg is calculated using the following formula:

[0075] .

[0076] Add the restart score Sc and the isolation score Sg to obtain the capacity score S2.

[0077] The formula for calculating the disposal complexity score S3 is determined based on the disposal time t and the maximum tolerance time T of the disposal plan. Specifically, it is calculated using the following formula:

[0078] .

[0079] By operating S220, the effectiveness score S1, capacity score S2, and disposal complexity score S3 of each processing scheme can be accurately calculated. Based on this, the final disposal score S of each processing scheme can be calculated.

[0080] In operation S230, the disposal score S of each processing scheme is calculated using the effectiveness score S1, capacity score S2, and disposal complexity score S3 of each processing scheme.

[0081] The treatment score S of the treatment plan is calculated using the following formula:

[0082] ;

[0083] Where k1, k2, and k3 are the weighting coefficients of S1, S2, and S3, respectively, and the size of k1, k2, and k3 is determined according to the actual situation.

[0084] By operating S230, the treatment score S for each treatment plan can be accurately calculated, and each treatment plan can be presented in numerical form, which facilitates the comparison between treatment plans and the selection of the final treatment plan.

[0085] In operation S230, a processing scheme that meets the preset conditions for processing score S is selected to process the fault to be processed.

[0086] Based on the handling score S of each handling solution, the activity process engine recommends and sorts multiple handling solutions for the fault to be handled, outputs the optimal solution, and presets a handling threshold. If the handling score S of the optimal solution is lower than the handling threshold, the system initially believes that the handling solution cannot handle the fault to be handled and needs to make a comprehensive judgment in combination with other factors; if the handling score S of the optimal solution is higher than the handling threshold, the system uses the optimal solution to handle the fault to be handled.

[0087] By operating the S240, the optimal solution can be output. The system uses the optimal solution to automatically handle the fault to be processed. The whole process does not require manual intervention, and it has a high degree of intelligence, high efficiency and low error rate.

[0088] According to embodiments of this disclosure, based on the scores of multiple factors for each processing scheme, an optimal processing scheme can be quickly output through an efficient algorithm, intelligently handling the fault to be processed without relying on manual labor, with high processing efficiency and high success rate, which can reduce losses caused by equipment failure.

[0089] In existing technologies, for example, when a WebLogic alarm is generated, staff need to first determine the device type to which the alarm belongs, then identify which device within that device type has malfunctioned, and then compare the various indicators of the malfunctioning device with those of other devices that are not malfunctioning to find out which indicator is abnormal, thus finding the root cause of the alarm. This process is complex and prone to errors.

[0090] Figure 3 A flowchart illustrating a fault handling method according to another embodiment of this disclosure is shown schematically. Except for the following, all other contents of this embodiment are the same as those described above. Figure 2 The content is the same.

[0091] like Figure 3As shown, before obtaining multiple processing solutions for the fault to be processed, operations S310 to S340 are also included.

[0092] Operate S310 to obtain alarm data;

[0093] Alarms refer to information pushed out when certain software or hardware problems occur. In this embodiment, alarm data is uniformly obtained through an alarm entry point for unified processing and storage. The alarm entry point includes tools such as Kafka and APIs for retrieving alarm data. To facilitate subsequent investigation of the root cause of alarms and feedback data to the fault handling platform, the obtained alarm data needs to be classified and normalized. Different alarm data correspond to different types of IT devices, such as physical machines, routers, operating systems, and middleware. Therefore, we can classify alarms into different IT device types.

[0094] When operating S320, a diagnostic decision tree corresponding to the alarm data is determined based on the alarm data;

[0095] Operations and maintenance personnel can graphically organize and design the diagnostic process and troubleshooting sequence to obtain a diagnostic decision tree. Historical faults also have corresponding diagnostic decision trees. After each handling process is completed, the remaining faults and their multiple corresponding handling solutions are fed back to the fault handling platform to continuously update the diagnostic decision tree.

[0096] When operating the S330, the root cause of the alarm is found through the diagnostic decision tree. The root cause of the alarm is an unresolved fault.

[0097] When operating S340, multiple processing solutions corresponding to the fault to be processed are found based on the mapping relationship list.

[0098] Obtain historical faults and their corresponding multiple handling solutions; establish a mapping list of historical faults and their corresponding multiple handling solutions; based on the mapping list, find multiple handling solutions corresponding to the fault to be handled, so as to calculate the handling score for each handling solution in the future.

[0099] According to embodiments of this disclosure, by setting up a diagnostic decision tree, the root cause of the alarm can be quickly found based on the alarm and the diagnostic decision tree. Multiple processing solutions for the fault to be processed can be obtained through the mapping relationship list. Through the feedback of the fault to be processed and the corresponding multiple processing solutions, the diagnostic decision tree can be continuously updated, automatically improving the accuracy of diagnosis. It has a high degree of automation, high work efficiency, and high accuracy.

[0100] Based on the above-mentioned fault handling method, this disclosure also provides a fault handling device. The following will be combined with... Figure 4 The device is described in detail.

[0101] Figure 4 A schematic block diagram of a fault handling apparatus according to an embodiment of the present disclosure is shown.

[0102] like Figure 4 As shown, the fault handling device 400 of this embodiment includes an acquisition module 410, a first calculation module 420, a second calculation module 430, and a handling module 440.

[0103] The acquisition module 410 is used to acquire multiple processing solutions for the fault to be processed. In one embodiment, the acquisition module 410 can be used to perform the operation S210 described above, which will not be repeated here.

[0104] The first calculation module 420 is used to calculate the effectiveness score S1, capacity score S2, and disposal complexity score S3 for each processing scheme. The effectiveness score S1 represents the probability of successful processing of the scheme, the capacity score S2 represents the feasible capacity at the smallest granularity of the processing scheme, and the disposal complexity score S3 represents the processing time t and the maximum tolerance time T of the processing scheme. In one embodiment, the first calculation module 420 can be used to perform the operation S220 described above, which will not be repeated here.

[0105] The second calculation module 430 is used to calculate the disposal score S of each processing scheme using the effectiveness score S1, capacity score S2, and disposal complexity score S3 of each processing scheme. In one embodiment, the second calculation module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0106] The handling module 440 is used to select a handling scheme that meets preset conditions to handle the fault to be handled. In one embodiment, the handling module 440 can be used to perform the operation S240 described above, which will not be repeated here.

[0107] According to embodiments of this disclosure, any plurality of modules among the acquisition module 410, the first calculation module 420, the second calculation module 430, and the processing module 440 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the acquisition module 410, the first calculation module 420, the second calculation module 430, and the processing module 440 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any one of the three implementation methods or a suitable combination of any of them. Alternatively, at least one of the acquisition module 410, the first calculation module 420, the second calculation module 430, and the processing module 440 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0108] Figure 5 A block diagram of an electronic device suitable for implementing a fault handling method according to an embodiment of the present disclosure is shown schematically.

[0109] like Figure 5 As shown, an electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0110] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 502 and / or RAM 503. It should be noted that programs may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in one or more memories.

[0111] According to embodiments of this disclosure, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0112] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0113] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 502 and / or RAM 503 and / or one or more memories other than ROM 502 and RAM 503 described above.

[0114] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the item recommendation method provided in the embodiments of this disclosure.

[0115] When the computer program is executed by the processor 501, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0116] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0117] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0118] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on a user's computing device, partially on a user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0119] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0120] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0121] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A method for handling a fault, comprising: Obtain multiple solutions for the pending fault; Calculate the effectiveness score S1 and the processing complexity score S3 for each processing scheme, where the effectiveness score S1 represents the probability of the processing scheme being successfully processed; In the case of the pending fault, obtain the number of devices n that can be restarted without affecting the operation of the service, the total number m of devices m that have the pending fault and devices with the same function as the devices that have the pending fault, the average CPU utilization c of devices that have not had the pending fault, and the maximum CPU utilization C that the devices can tolerate. Based on the number of devices n that can be restarted without affecting the operation of the service among the devices connected to the service and the total number of devices m, the restart score Sc is obtained; The restart score Sc is calculated using the following formula: ； The isolation score Sg is obtained based on the ratio of the average CPU utilization c to the maximum CPU utilization C. If all devices corresponding to a function fail, the isolation score Sg is recorded as 0. If some devices corresponding to a function fail, the isolation score Sg is calculated using the following formula: ； Under the condition that the preset calculation conditions are met, the restart score Sc and the isolation score Sg are added together to obtain the capacity score S2 for each processing scheme; under the condition that the preset calculation conditions are not met, the capacity score S2 is recorded as 0; the preset calculation conditions include the transaction volume of the device's backend server and the CPU utilization of each device meeting the preset threshold, the transaction volume representing the number of transactions occurring on the current device's backend server; the capacity score S2 represents the feasible capacity of the processing scheme at the smallest granularity, and the processing complexity score S3 represents the processing time t and the maximum tolerance time T of the processing scheme; The processing complexity score S3 is calculated using the following formula: ； The disposal score S of each processing scheme is calculated using the effectiveness score S1, capacity score S2, and disposal complexity score S3 of each processing scheme. The processing scheme that satisfies the preset conditions is selected to process the fault to be processed.

2. The method according to claim 1, wherein, The disposal score S of the treatment scheme is calculated using the following formula: ; Where k1, k2 and k3 are the weighting coefficients of S1, S2 and S3, respectively.

3. The method according to claim 1, wherein, Before obtaining multiple processing solutions for the fault to be processed, the method further includes: Obtain historical faults and multiple corresponding processing solutions for the historical faults; Establish a mapping list between historical faults and the multiple processing solutions corresponding to those historical faults.

4. The method according to claim 3, wherein, The multiple processing solutions for obtaining the fault to be processed include: Obtain alarm data; A diagnostic decision tree corresponding to the alarm data is determined based on the alarm data; The root cause of the alarm is found through the diagnostic decision tree, and the root cause of the alarm is the fault to be processed. Based on the mapping list, find multiple processing solutions corresponding to the fault to be processed.

5. A fault handling device, comprising: The acquisition module is used to acquire multiple processing solutions for the fault to be processed; The first calculation module is used to calculate the effectiveness score S1 and the handling complexity score S3 for each of the processing schemes. The effectiveness score S1 represents the probability of the processing scheme being successfully handled. The module also obtains the number of devices n that can be restarted without affecting the operation of the service in the case of the pending fault, the total number m of devices with the pending fault and devices with the same function as the devices with the pending fault, the average CPU utilization c of devices without the pending fault, and the maximum CPU utilization C that the devices can tolerate. Based on the number of devices n that can be restarted without affecting the operation of the service among the devices connected to the service and the total number of devices m, the restart score Sc is obtained; The restart score Sc is calculated using the following formula: ； The isolation score Sg is obtained based on the ratio of the average CPU utilization c to the maximum CPU utilization C. If all devices corresponding to a function fail, the isolation score Sg is recorded as 0. If some devices corresponding to a function fail, the isolation score Sg is calculated using the following formula: ； Under the condition that the preset calculation conditions are met, the restart score Sc and the isolation score Sg are added together to obtain the capacity score S2 for each processing scheme; under the condition that the preset calculation conditions are not met, the capacity score S2 is recorded as 0; the preset calculation conditions include the transaction volume of the device's backend server and the CPU utilization of each device meeting the preset threshold, the transaction volume representing the number of transactions occurring on the current device's backend server; the capacity score S2 represents the feasible capacity of the processing scheme at the smallest granularity, and the processing complexity score S3 represents the processing time t and the maximum tolerance time T of the processing scheme; The processing complexity score S3 is calculated using the following formula: ； The second calculation module is used to calculate the disposal score S of each processing scheme using the effectiveness score S1, capacity score S2 and disposal complexity score S3 of each processing scheme. The processing module is used to select a processing scheme that meets the preset conditions to process the fault to be processed.

6. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors perform the fault handling method according to any one of claims 1 to 4.

7. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform a fault handling method according to any one of claims 1 to 4.

8. A computer program product comprising a computer program that, when executed by a processor, implements a fault handling method according to any one of claims 1 to 4.

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