System operation and maintenance method and device, electronic equipment and storage medium

Abstract

The invention discloses a system operation and maintenance method and device, electronic equipment and a storage medium. According to the specific scheme, the method comprises the steps of obtaining to-be-processed data of a target system under at least two evaluation dimensions; for the at least two evaluation dimensions, determining operation performance attributes of the target system according to the to-be-processed data under each evaluation dimension and the evaluation function corresponding to each evaluation dimension; when the operation performance attribute meets a preset condition, performing fault detection on the target system based on a preset fault detection tool to obtain a fault detection result; and determining a target emergency processing mode corresponding to the fault detection result, and performing fault repair processing on the target system based on the target emergency processing mode. According to the invention, the overall evaluation of the operation condition of the target system is realized, and the accuracy, rationality and comprehensiveness of the operation and maintenance of the target system are ensured.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a system operation and maintenance method, device, electronic equipment and storage medium. Background Art

[0002] After the application system is developed, in order to ensure the smooth operation of the application system, system operation and maintenance work such as system status monitoring, system anomaly detection, system problem analysis and processing, and verification processing after system problem processing will be carried out.

[0003] At present, the operation and maintenance of application systems is mainly handled by monitoring the data of the application system during operation, and judging each operation data through manual experience to determine whether there is an abnormality. Then, corresponding feedback is given according to the abnormal information. However, the existing technology mainly monitors each data separately, which makes it difficult to evaluate the overall operation of the application system and cannot guarantee the comprehensiveness of system operation and maintenance. In addition, determining whether there is an abnormality in the application system through manual experience is subjective to a certain extent, and the accuracy and rationality of system operation and maintenance cannot be guaranteed. Summary of the invention

[0004] The present invention provides a system operation and maintenance method, device, electronic equipment and storage medium, which realize an overall evaluation of the operation status of a target system and ensure the accuracy, rationality and comprehensiveness of the operation and maintenance of the target system.

[0005] According to one aspect of the present invention, a system operation and maintenance method is provided, the method comprising:

[0006] Obtaining data to be processed of the target system under at least two evaluation dimensions, wherein the at least two evaluation dimensions include at least two of a business processing volume dimension, a response time dimension, a business failure rate dimension, a central processing unit usage dimension, and a memory usage dimension;

[0007] For at least two evaluation dimensions, determining an operating performance attribute of the target system according to the to-be-processed data under each evaluation dimension and an evaluation function corresponding to each evaluation dimension;

[0008] When the operating performance attribute meets the preset conditions, a fault detection is performed on the target system based on a preset fault detection tool to obtain a fault detection result;

[0009] A target emergency processing method corresponding to the fault detection result is determined to perform fault repair processing on the target system based on the target emergency processing method.

[0010] According to another aspect of the present invention, a system operation and maintenance device is provided, the device comprising:

[0011] A data acquisition module, used to acquire the data to be processed of the target system under at least two evaluation dimensions, wherein the at least two evaluation dimensions include at least two of a business processing volume dimension, a response time dimension, a business failure rate dimension, a central processing unit usage dimension, and a memory usage dimension;

[0012] A performance attribute determination module, for determining, for at least two evaluation dimensions, an operating performance attribute of a target system according to the to-be-processed data under each evaluation dimension and an evaluation function corresponding to each evaluation dimension;

[0013] A system fault detection module is used to perform fault detection on the target system based on a preset fault detection tool to obtain a fault detection result when the operating performance attribute meets the preset conditions;

[0014] The emergency processing method determination module is used to determine a target emergency processing method corresponding to the fault detection result, so as to perform fault repair processing on the target system based on the target emergency processing method.

[0015] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by at least one processor. The computer program is executed by at least one processor so that the at least one processor can execute the system operation and maintenance method of any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the system operation and maintenance method of any embodiment of the present invention when executed.

[0020] According to another aspect of the present invention, there is provided a computer program product, including a computer program, characterized in that when the computer program is executed by a processor, the computer program implements the system operation and maintenance method as described in any embodiment of the present invention.

[0021] The technical solution of the embodiment of the present invention provides data support for the subsequent overall evaluation of the operating performance of the target system by obtaining the data to be processed under at least two evaluation dimensions of the target system. For at least two evaluation dimensions, the operating performance attributes of the target system are determined according to the data to be processed under each evaluation dimension and the evaluation function corresponding to each evaluation dimension. Based on this, it can be determined whether the target system has an operating anomaly through the operating performance attributes of the target system. When the operating performance attributes meet the preset conditions, it means that the target system has an operating anomaly. The target system is fault-detected based on a preset fault detection tool to obtain a fault detection result. Based on this, it can be determined whether the target system has an operating anomaly caused by a fault. The target emergency processing method corresponding to the fault detection result is determined to perform fault repair processing on the target system through the target emergency processing method. The present invention solves the problem that the system operation and maintenance in the prior art is subjective and cannot guarantee the accuracy, rationality and comprehensiveness of the system operation and maintenance. By obtaining the data to be processed, determining the operating performance attributes, detecting system faults and repairing system faults, the full life cycle management of system operation and maintenance is realized, and the automated processing of system operation and maintenance is realized, which ensures the accuracy, rationality and comprehensiveness of the target system operation and maintenance.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 is a flow chart of a system operation and maintenance method provided by an embodiment of the present invention;

[0025] Figure 2 is a flow chart of a system operation and maintenance method provided by an embodiment of the present invention;

[0026] Figure 3 is an example diagram of evaluation dimensions and weight coefficients provided by an embodiment of the present invention;

[0027] Figure 4 It is a structural schematic diagram of a system operation and maintenance device provided by an embodiment of the present invention;

[0028] Figure 5 It is a structural schematic diagram of an electronic device for implementing the system operation and maintenance method of an embodiment of the present invention. DETAILED DESCRIPTION

[0029] 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.

[0030] 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, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 This is a flow chart of a system operation and maintenance method provided in the first embodiment of the present invention. This embodiment is applicable to the case of performing system operation and maintenance on the target system. The method can be executed by a system operation and maintenance device. The system operation and maintenance device can be implemented in the form of hardware and / or software. The system operation and maintenance device can be configured in electronic devices such as mobile phones, computers or servers. Figure 1 As shown, the method includes:

[0033] S110: Obtain data to be processed of the target system under at least two evaluation dimensions.

[0034] Among them, at least two evaluation dimensions include at least two of the business processing volume dimension, the response time dimension, the business failure rate dimension, the CPU usage dimension, and the memory usage dimension. The business processing volume dimension can be used to characterize the number of businesses processed by the target system. The response time dimension can be used to characterize the response time of the target system processing the business. The business failure rate dimension can be used to characterize the failure of the target system when processing the business. The CPU usage dimension can be used to characterize the usage of the CPU when the target system processes the business. The memory usage dimension can be used to characterize the memory occupancy when the target system processes the business.

[0035] The target system can be understood as the application system that currently needs to be operated and maintained. The data to be processed can be the operating data corresponding to the target system when processing business. For example, the data to be processed can include the number of businesses processed by the target system, the response time of business processing, the failure rate of business processing, the memory occupied when processing business, and the utilization rate of the central processing unit when processing business, etc. This is just an example and does not impose specific restrictions on the data to be processed.

[0036] Specifically, according to the pre-set data collection method, data collection components and data collection frequency, the data to be processed in at least two evaluation dimensions when the target system processes the business is obtained, so as to make an overall evaluation of the operation status of the target system based on the data to be processed in at least two evaluation dimensions.

[0037] In an embodiment of the present invention, a method for obtaining the data to be processed of the target system may be: based on the data collection configuration information corresponding to the target system, collecting the original data of the target system under at least two evaluation dimensions, wherein the data collection configuration information at least includes data collection frequency, data collection method and data collection component; normalizing the original data under at least two evaluation dimensions to obtain the data to be processed.

[0038] Among them, the data collection configuration information may include data collection frequency, data collection method and data collection component. The data collection frequency is used to determine the frequency of collecting raw data. The data collection method can determine the method in which the raw data is collected. The data collection component can be understood as a tool for collecting raw data. The raw data can be the operating data when the system processes business. Normalization processing can be a process of mapping raw data under different evaluation dimensions to a preset interval. Optionally, the raw data under different evaluation dimensions can be uniformly mapped to the interval [0,1] so that the data under different evaluation dimensions can be further processed. For example, the raw data under the response time dimension can be the actual response time of the target system. Set the system preset peak value under the response time dimension to the preset maximum response time. Normalization processing of the raw data under the response time dimension can be: determining the ratio of the actual response time to the preset maximum response time, and using the ratio as the data to be processed under the response time dimension.

[0039] Specifically, according to the system number and system name of the target system, data collection configuration information adapted to the target system is determined from at least one pre-configured data collection configuration information. According to the data collection frequency, data collection method and data collection component in the data collection configuration information, raw data of the target system under at least two evaluation dimensions is collected.

[0040] In order to facilitate the subsequent determination of the overall operation of the target system based on the data of different evaluation dimensions, the original data under different evaluation dimensions can be normalized, that is, the original data under different evaluation dimensions are mapped to a preset interval to obtain the data to be processed.

[0041] Exemplarily, data collection configuration information corresponding to at least one system is initialized. The data collection configuration information may include data collection mode, data collection components, and data collection frequency. According to the system number and system name of the target system, the data collection configuration information matching the target system is determined. According to the data collection configuration information, data collection processing is performed on the target system to obtain raw data under at least two evaluation dimensions. The raw data under different evaluation dimensions are uniformly mapped to the interval of [0, 1] to obtain the data to be processed, so as to determine the overall operation status of the target system through the data to be processed.

[0042] S120: For at least two evaluation dimensions, determine the operating performance attributes of the target system according to the data to be processed under each evaluation dimension and the evaluation function corresponding to each evaluation dimension.

[0043] The evaluation function can be used to evaluate the operating performance of the target system under the current evaluation dimension, and the operating performance attribute can be used to evaluate the overall operating performance of the target system.

[0044] Specifically, for at least two evaluation dimensions, the evaluation attributes to be integrated corresponding to each evaluation dimension are determined according to the data to be processed under each evaluation dimension and the evaluation function corresponding to each evaluation dimension. The evaluation attributes to be integrated of the at least two evaluation dimensions are summed to obtain the operating performance attributes of the target system.

[0045] S130: When the operating performance attribute meets the preset condition, a fault detection is performed on the target system based on a preset fault detection tool to obtain a fault detection result.

[0046] The preset condition may be a pre-set condition that is satisfied when the target system may have an abnormality. Optionally, the preset condition may be that the operating performance attribute reaches a preset attribute threshold. The preset attribute threshold may be a pre-set standard value for the target system to have an abnormality. The preset fault detection tool may be a pre-set tool for verifying whether the target system has a fault. The fault detection result may include information such as the fault type, fault level, and fault probability.

[0047] Specifically, when the operating performance attribute reaches a preset attribute threshold, it is determined that the target system has an abnormality. In order to determine whether the abnormality is a fault of the target system, a preset fault detection tool can be used to perform fault detection on the target system, and when it is determined to be a fault, a corresponding fault detection result is obtained.

[0048] Optionally, the method further includes: feeding back the fault detection results, operating performance attributes and corresponding data to be processed to the target terminal to update the fault list corresponding to the target system.

[0049] Optionally, when the operating performance attributes meet preset conditions, the method also includes: generating early warning prompt information based on preset early warning configuration information corresponding to the target system, the target system's pending data and operating performance attributes, so as to call a preset fault detection tool to perform fault detection on the target system based on the early warning prompt information.

[0050] The preset warning configuration information at least includes a warning information generation rule and a warning frequency. The warning information generation rule may be a pre-set rule for generating warning information. The warning frequency may be understood as the frequency of sending warning prompt information. The warning prompt information may be information used to prompt that the target system currently has an abnormality.

[0051] Specifically, according to the system number and system name of the target system, the preset warning configuration information corresponding to the target system is determined from at least one initialized preset warning configuration information. When the operating performance attribute of the target system reaches the preset attribute threshold, it is determined that the target system is abnormal. At this time, according to the warning information generation rules in the preset warning configuration information of the target system, as well as the pending data and operating performance attributes of the target system, the warning prompt information is generated, and the warning processing is performed according to the warning frequency. Based on this, it is convenient to call the preset fault detection tool to perform fault detection on the target system according to the warning prompt information.

[0052] Optionally, according to the preset alarm threshold corresponding to each data to be processed, an early warning process is performed on each data to be processed. It can be understood that when the data to be processed reaches the preset alarm threshold, an early warning prompt information is generated according to the preset early warning configuration information and the data to be processed, so as to perform early warning process based on the early warning prompt information. Among them, for the case of early warning for each data to be processed, the preset early warning configuration information includes the early warning information generation rules and early warning frequencies of the evaluation dimensions corresponding to each data to be processed. That is, the early warning information generation rules and early warning frequencies corresponding to different evaluation dimensions are different.

[0053] Exemplarily, when the data to be processed of the current evaluation dimension reaches a preset alarm threshold, warning prompt information is generated according to the preset warning configuration information corresponding to the current evaluation dimension and the data to be processed, so as to perform warning processing on the data to be processed of the current evaluation dimension based on the warning prompt information.

[0054] In an embodiment of the present invention, the method for determining the fault detection result may be: when the operating performance attribute is greater than a preset attribute threshold, a preset fault detection tool is used to detect the operating state of the target system when processing a preset business, and a state detection result is obtained; when the state detection result does not meet the preset state threshold, based on the state detection result, the fault level, fault type and fault probability of the target system are determined, wherein the fault probability is obtained by adjusting the preset fault probability based on the state detection result; the fault level, fault type and fault probability are used as the fault detection result of the target system.

[0055] The preset attribute threshold value can be understood as a pre-set standard value used to determine whether the target system has an abnormality. The preset business can be a key business processed by the target system, such as identity authentication and resource transfer business. The state detection result can be used to characterize the operating state of the target system when processing the preset business. The preset state threshold value can be a pre-set standard value for the target system to have a fault.

[0056] The fault level can be understood as the level to which the current fault belongs. Optionally, the fault level can be determined based on the state detection result and at least one preset state range. That is, the fault level corresponding to the state detection result is determined based on the preset state range to which the state detection result belongs and the fault level corresponding to each preset state range.

[0057] The fault type may be the type corresponding to the current fault. The fault type may be divided according to different standards. For example, the fault type may be two types: a fault corresponding to a critical business and a fault corresponding to a non-critical business. The fault probability may be understood as the probability of a fault of the current fault type. Optionally, the fault probability may be obtained by adjusting the preset fault probability according to the state detection result. The preset fault probability may be understood as a pre-set probability value of the possibility that the current fault type may fail. It may be understood that different fault types have corresponding preset fault probabilities. If the state detection result does not meet the preset state threshold, it means that a fault currently exists. After determining that it is a fault of the corresponding fault type, the preset fault probability corresponding to the current fault type may be adaptively increased to obtain the fault probability corresponding to the current fault type.

[0058] Specifically, when the operating performance attribute is greater than the preset attribute threshold, it indicates that there is an abnormality in the target system. Then, the preset fault detection tool can be called to detect the operating status of the target system when processing the preset business, and obtain the status detection result. When the status detection result does not meet the preset status threshold, it indicates that there is a fault in the target system. According to the status detection result and the preset fault arbitration information, the fault level, fault type and fault probability of the target system are determined. Among them, the fault arbitration information includes at least one fault level corresponding to a preset state range, at least two fault types corresponding to the target system, and a preset fault probability corresponding to each fault type. Among them, the preset state range can be understood as a state value range corresponding to different fault levels that is pre-set according to actual needs.

[0059] Based on the above, the fault level corresponding to the target system is determined according to the preset state range to which the state detection result belongs. The fault type corresponding to the target system is determined according to the state detection result, and the fault probability of the target system is determined according to the preset fault probability corresponding to the fault type of the target system. The fault level, fault type and fault probability are used as the fault detection result of the target system.

[0060] Exemplarily, the preset business is a critical business as an example for explanation. When the operating performance attribute is greater than the preset attribute threshold, it means that the target system is abnormal. According to the preset fault detection tool, the operating state of the target system when processing the critical business is detected to obtain the state detection result. If the state detection result meets the preset state threshold, it means that there is no fault in the target system. Correspondingly, if the state detection result does not meet the preset state threshold, it means that there is a fault in the target system. At this time, the fault detection result of the target system can be determined according to the preset fault arbitration information and the state detection result. It can be understood that if the current fault is a fault that occurs when processing the critical business, the fault type of the target system can be a fault corresponding to the critical business. According to the preset state range to which the state detection result belongs, the fault level corresponding to the state detection result is determined. According to the fault type corresponding to the state detection result, the preset fault probability corresponding to the current fault type is determined. When there is a fault in the target system, the preset fault probability is increased to obtain the fault probability corresponding to the target system. The above fault type, fault level and fault probability are used as the fault detection result of the target system.

[0061] S140: Determine a target emergency processing method corresponding to the fault detection result, and perform fault repair processing on the target system based on the target emergency processing method.

[0062] The target emergency processing method may be determined according to the fault detection result, and is used to perform a series of recovery actions when a fault occurs in the target system, so as to restore the target system to a normal state.

[0063] Specifically, the corresponding target emergency processing method is determined according to the fault type, fault level and fault probability in the fault detection result, so as to perform fault repair processing on the target system by executing a series of recovery actions in the target emergency processing method.

[0064] It should be noted that if there are multiple emergency processing methods corresponding to the fault detection result, the emergency processing method with higher effectiveness can be used as the target emergency processing method according to the effectiveness of the emergency processing methods.

[0065] Optionally, after performing fault repair processing on the target system based on the target emergency processing method, the method also includes: evaluating the data to be processed, the preset fault detection tool and the target emergency processing method corresponding to the target system to obtain a target evaluation result, and optimizing the data acquisition configuration information, the preset fault detection tool and the target emergency processing method corresponding to the data to be processed based on the target evaluation result.

[0066] The target evaluation result may be the result obtained after evaluating the effectiveness of various operation and maintenance operations of the target system. The operation and maintenance processing operation may include the operation of obtaining data to be processed, the operation of fault detection on the target system, and the operation of fault repair on the target system. The data collection configuration information may include the data collection frequency, data collection method, and data collection components for collecting the data to be processed.

[0067] Specifically, in order to improve the effectiveness of system operation and maintenance, effectiveness evaluation can be performed on various operation and maintenance operations to obtain target evaluation results, so as to update and optimize various operation and maintenance operations according to the target evaluation results. That is, effectiveness evaluation is performed on the acquired data to be processed, the preset fault detection tools, and the target emergency treatment methods to obtain the target evaluation results. According to the target evaluation results, the data collection configuration information, the preset fault detection tools, and the target emergency treatment methods are optimized and updated to improve the effectiveness and automation of system operation and maintenance processing.

[0068] The technical solution of this embodiment provides data support for the subsequent overall evaluation of the operating performance of the target system by obtaining the data to be processed under at least two evaluation dimensions of the target system. For at least two evaluation dimensions, the operating performance attributes of the target system are determined according to the data to be processed under each evaluation dimension and the evaluation function corresponding to each evaluation dimension. Based on this, it can be determined whether the target system has an operating anomaly through the operating performance attributes of the target system. When the operating performance attributes meet the preset conditions, it means that the target system has an operating anomaly. The target system is fault-detected based on a preset fault detection tool to obtain a fault detection result. Based on this, it can be determined whether the target system has an operating anomaly caused by a fault. The target emergency processing method corresponding to the fault detection result is determined to perform fault repair processing on the target system through the target emergency processing method. The present invention solves the problem that the system operation and maintenance in the prior art is subjective and cannot guarantee the accuracy, rationality and comprehensiveness of the system operation and maintenance. By obtaining the data to be processed, determining the operating performance attributes, detecting system faults and repairing system faults, the full life cycle management of system operation and maintenance is realized, and the automated processing of system operation and maintenance is realized, which ensures the accuracy, rationality and comprehensiveness of the target system operation and maintenance.

[0069] Embodiment 2

[0070] Figure 2 1 is a flowchart of a system operation and maintenance method provided by Embodiment 2 of the present invention. This embodiment is a preferred embodiment of the above embodiment. For its specific implementation, please refer to the technical solution of this embodiment. Among them, the technical terms that are the same or corresponding to the above embodiment are not repeated here. Figure 2 As shown, the method includes:

[0071] S210: Obtain data to be processed of the target system under at least two evaluation dimensions.

[0072] Among them, at least two evaluation dimensions include at least two of the business processing volume dimension, the response time dimension, the business failure rate dimension, the central processing unit usage dimension and the memory usage dimension.

[0073] S220. For at least two evaluation dimensions, determine the evaluation attribute to be integrated corresponding to the current evaluation dimension according to the data to be processed corresponding to each sub-evaluation dimension under the current evaluation dimension, the first weight coefficient corresponding to each sub-evaluation dimension, and the second weight coefficient corresponding to the current evaluation dimension.

[0074] Among them, each evaluation dimension includes at least one sub-evaluation dimension. For example, in the business processing volume dimension, the sub-evaluation dimension may include a query business processing sub-dimension and a maintenance business processing sub-dimension. The first weight coefficient may be a pre-set weight coefficient corresponding to the sub-evaluation dimension. The second weight coefficient may be a pre-set weight coefficient corresponding to the evaluation dimension. Optionally, the setting of the first weight coefficient and the second weight coefficient may be determined according to the target system's requirements for the evaluation dimension. For example, if the target system is an internal management system, which is characterized by being more sensitive to business failure rate and having a high tolerance for response time, the first weight coefficient and the second weight coefficient corresponding to the business failure rate dimension may be adaptively increased, and the first weight system and the second weight coefficient corresponding to the response time dimension may be adaptively decreased. The evaluation attributes to be fused can be used to characterize the operating performance of the target system under the current evaluation dimension.

[0075] Specifically, for at least two evaluation dimensions, the sub-evaluation attribute to be fused corresponding to each sub-evaluation dimension is determined according to the to-be-processed data of each sub-evaluation dimension under the current evaluation dimension and the first weight coefficient. The evaluation attribute to be fused corresponding to the current evaluation dimension is determined according to the sub-evaluation attribute to be fused corresponding to at least one sub-evaluation dimension under the current evaluation dimension and the second weight coefficient.

[0076] S230: Determine the operating performance attributes of the target system according to the evaluation attributes to be integrated corresponding to at least two evaluation dimensions.

[0077] Specifically, the evaluation attributes to be integrated corresponding to at least two evaluation dimensions are summed up to obtain the operation performance attributes corresponding to the target system.

[0078] Optionally, the operating performance of the target system can be determined by the following evaluation function:

[0079]

[0080] Where I represents the running performance attribute, w i represents the second weight coefficient of the i-th evaluation dimension, m represents the total number of evaluation dimensions, and I ij represents the data to be processed under the jth sub-evaluation dimension under the i-th evaluation dimension, w ij It represents the first weight coefficient corresponding to the jth sub-evaluation dimension under the i-th evaluation dimension, and n represents the number of sub-evaluation dimensions of the i-th evaluation dimension.

[0081] Exemplarily, taking the target system as an internal management system, at least two evaluation dimensions are five evaluation dimensions, namely, business processing volume dimension, response time dimension, business failure rate dimension, central processing unit usage dimension, and memory usage dimension. Among them, the business processing volume dimension includes the query business processing sub-dimension and the maintenance business processing sub-dimension. The response time dimension includes the query response time sub-dimension and the maintenance response time sub-dimension. The business failure rate dimension includes the query business failure rate sub-dimension and the maintenance business failure rate sub-dimension. The central processing unit (CPU) usage dimension includes the central processing unit maximum usage rate sub-dimension and the central processing unit average usage rate sub-dimension. The memory usage dimension includes the memory maximum usage rate sub-dimension and the memory average usage rate sub-dimension.

[0082] See also Figure 3 , the system preset peak values ​​corresponding to different sub-evaluation dimensions can be set respectively, so as to normalize the original data according to the system preset peak values ​​and obtain the data to be processed. For example, the system preset peak value corresponding to the sub-dimension of query business processing is 100tps, and the original data is 80tps, then the data to be processed is 80 / 100=0.8. Based on the above, the corresponding data to be processed under different sub-evaluation dimensions are obtained.

[0083] According to the above evaluation function, the operating performance attributes corresponding to the internal management system are determined as: I = 0.2*(0.3*0.8+0.7*0.6)+0.1*(0.3*0.5+0.7*0.33)+0.3*(0.3*0.5+0.7*0)+0.2*(0.7*0.78+0.3*1)+0.2*(0.7*0.78+0.3*0.2) = 0.505.

[0084] S240: When the operating performance attribute meets the preset condition, a fault detection is performed on the target system based on a preset fault detection tool to obtain a fault detection result.

[0085] S250. For at least one preset emergency processing method, determine an emergency processing method to be adjusted corresponding to the fault detection result.

[0086] The preset emergency processing method can be understood as at least one processing method for processing target system failures that is preset and corresponds to the target system. The emergency processing method to be adjusted can be an emergency processing method determined from at least one preset emergency processing method.

[0087] Specifically, for at least one preset emergency processing method corresponding to the target system, the emergency processing method to be adjusted corresponding to the fault detection result is determined according to the fault detection result corresponding to the current target system.

[0088] S260: Verify the emergency processing method to be adjusted based on at least one preset business processing instance of the target system to obtain at least one verification result.

[0089] The preset business processing instance may be a pre-set instance that simulates a real business operation. The preset business processing instance may be used to verify whether the operating state of the target system adjusted based on the emergency processing method to be adjusted is normal. The verified result is used as the verification result. Each preset business processing instance corresponds to a verification result.

[0090] Specifically, the target system is adjusted according to the emergency processing method to be adjusted, and the adjusted target system is verified according to at least one preset business processing instance corresponding to the target system to obtain a verification result corresponding to each preset business processing instance, so as to determine whether the emergency processing method to be adjusted is suitable for handling the failure of the current target system through the verification result.

[0091] S270: Based on a preset time decay function and at least one verification result, an effectiveness evaluation is performed on the emergency handling method to be adjusted to obtain an evaluation result.

[0092] The preset time decay function can be preset and used to evaluate whether the emergency treatment method to be adjusted is effective. The preset time decay function can be expressed as follows:

[0093]

[0094] Among them, E0 is the initial parameter set according to business needs. To ensure the convergence of the above function, the value of E0 is a positive number less than e / (e-1). e is a natural constant. α is the evaluation value. α is determined by the verification result corresponding to each preset business processing instance. The value of α is between [-1,1]. n represents the number of times the preset business processing instance is executed. t is the number of intervals from the last execution of the preset business processing instance. t=0,1,2... E represents the evaluation result of effectiveness. The evaluation result can be used to characterize whether the emergency processing method to be adjusted is suitable for handling the failure of the current target system.

[0095] Specifically, the verification result corresponding to at least one preset business processing instance is processed through a preset time decay function to determine the effectiveness of the emergency processing method to be adjusted and obtain an evaluation result.

[0096] S280. According to the evaluation result, the emergency processing method to be adjusted is adjusted to obtain a target emergency processing method, so as to perform fault repair processing on the target system based on the target emergency processing method.

[0097] The target emergency processing method may be an emergency processing method that is suitable for processing faults of the current target system after the emergency processing method to be adjusted is adjusted.

[0098] Specifically, if the evaluation result does not meet the preset threshold, the emergency treatment method to be adjusted is adjusted. If the target system has at least two preset emergency treatment methods, the target emergency treatment method is determined from the preset emergency treatment methods other than the emergency treatment method to be adjusted; if the target system has only one preset emergency treatment method, a new preset emergency treatment method is determined based on the target system's data to be processed, operating performance attributes, and fault detection results, and the preset emergency treatment method is used as the target emergency treatment method corresponding to the target system, so as to perform fault repair processing on the target system based on the target emergency treatment method.

[0099] Optionally, the method further includes: updating the new preset emergency handling method to a corresponding emergency handling method list, wherein the emergency handling method list includes all preset emergency handling methods corresponding to the target system.

[0100] The technical solution of this embodiment provides data support for the subsequent overall evaluation of the operating performance of the target system by obtaining the data to be processed under at least two evaluation dimensions of the target system. For at least two evaluation dimensions, the evaluation attribute to be fused corresponding to the current evaluation dimension is determined according to the data to be processed corresponding to each sub-evaluation dimension under the current evaluation dimension, the first weight coefficient corresponding to each sub-evaluation dimension, and the second weight coefficient corresponding to the current evaluation dimension. According to the evaluation attributes to be fused corresponding to at least two evaluation dimensions, the operating performance attribute of the target system is determined, so as to determine whether the target system has an operating anomaly through the operating performance attribute, and realize the rapid perception of the abnormality of the target system. When the operating performance attribute meets the preset conditions, the target system is fault-detected based on the preset fault detection tool to obtain the fault detection result, and the fault determination of the abnormal target system is realized. For at least one preset emergency processing method, the emergency processing method to be adjusted corresponding to the fault detection result is determined. The emergency processing method to be adjusted is verified based on at least one preset business processing instance of the target system to obtain at least one verification result. According to the preset time decay function and at least one verification result, the effectiveness of the emergency processing method to be adjusted is evaluated to obtain an evaluation result. According to the evaluation results, the emergency treatment method to be adjusted is adjusted to obtain the target emergency treatment method, so as to perform fault repair on the target system based on the target emergency treatment method. Based on this, the emergency treatment and effectiveness evaluation of the target system are realized, the full life cycle management of the target system operation and maintenance is realized, the automation of system operation and maintenance is realized, and the accuracy, rationality and comprehensiveness of the target system operation and maintenance are guaranteed.

[0101] Embodiment 3

[0102] Figure 4 Schematic diagram of the structure of a system operation and maintenance device provided by Embodiment 3 of the present invention. Figure 4 As shown, the device includes: a data acquisition module 310, a performance attribute determination module 320, a system fault detection module 330 and an emergency processing method determination module 340.

[0103] The data acquisition module 310 is used to obtain the data to be processed of the target system under at least two evaluation dimensions, wherein the at least two evaluation dimensions include at least two of the business processing volume dimension, the response time dimension, the business failure rate dimension, the CPU usage dimension, and the memory usage dimension; the performance attribute determination module 320 is used to determine the operating performance attributes of the target system for at least two evaluation dimensions according to the data to be processed under each evaluation dimension and the evaluation function corresponding to each evaluation dimension; the system fault detection module 330 is used to perform fault detection on the target system based on a preset fault detection tool to obtain a fault detection result when the operating performance attribute meets the preset conditions; the emergency processing method determination module 340 is used to determine the target emergency processing method corresponding to the fault detection result, so as to perform fault repair processing on the target system based on the target emergency processing method.

[0104] The technical solution of this embodiment provides data support for the subsequent overall evaluation of the operating performance of the target system by obtaining the data to be processed under at least two evaluation dimensions of the target system. For at least two evaluation dimensions, the operating performance attributes of the target system are determined according to the data to be processed under each evaluation dimension and the evaluation function corresponding to each evaluation dimension. Based on this, it can be determined whether the target system has an operating anomaly through the operating performance attributes of the target system. When the operating performance attributes meet the preset conditions, it means that the target system has an operating anomaly. The target system is fault-detected based on a preset fault detection tool to obtain a fault detection result. Based on this, it can be determined whether the target system has an operating anomaly caused by a fault. The target emergency processing method corresponding to the fault detection result is determined to perform fault repair processing on the target system through the target emergency processing method. The present invention solves the problem that the system operation and maintenance in the prior art is subjective and cannot guarantee the accuracy, rationality and comprehensiveness of the system operation and maintenance. By obtaining the data to be processed, determining the operating performance attributes, detecting system faults and repairing system faults, the full life cycle management of system operation and maintenance is realized, and the automated processing of system operation and maintenance is realized, which ensures the accuracy, rationality and comprehensiveness of the target system operation and maintenance.

[0105] On the basis of the above embodiment, optionally, the data acquisition module includes: a raw data acquisition unit, used to collect raw data of the target system under at least two evaluation dimensions based on data acquisition configuration information corresponding to the target system, wherein the data acquisition configuration information at least includes data acquisition frequency, data acquisition method and data acquisition component; a data normalization processing unit, used to normalize the raw data under at least two evaluation dimensions to obtain data to be processed.

[0106] Optionally, each evaluation dimension includes at least one sub-evaluation dimension, and the performance attribute determination module includes: an evaluation attribute determination unit to be integrated, used to determine the evaluation attribute to be integrated corresponding to the current evaluation dimension for at least two evaluation dimensions based on the unprocessed data corresponding to each sub-evaluation dimension under the current evaluation dimension, the first weight coefficient corresponding to each sub-evaluation dimension, and the second weight coefficient corresponding to the current evaluation dimension; an operating performance attribute determination unit, used to determine the operating performance attributes of the target system based on the evaluation attributes to be integrated corresponding to at least two evaluation dimensions.

[0107] Optionally, when the operating performance attributes meet preset conditions, the device also includes: an early warning processing module, which is used to generate early warning prompt information based on the preset early warning configuration information corresponding to the target system, the target system's pending data and the operating performance attributes, so as to call a preset fault detection tool to perform fault detection on the target system based on the early warning prompt information, wherein the preset early warning configuration information includes at least early warning information generation rules and early warning frequency.

[0108] Optionally, a system fault detection module is used to, when the operating performance attribute is greater than a preset attribute threshold, use a preset fault detection tool to detect the operating status of the target system when processing a preset business, and obtain a status detection result; when the status detection result does not meet the preset status threshold, determine the fault level, fault type and fault probability of the target system based on the status detection result, wherein the fault probability is obtained by adjusting the preset fault probability based on the status detection result; and use the fault level, fault type and fault probability as the fault detection result of the target system.

[0109] Optionally, the target system includes at least one preset emergency handling method and an emergency handling method determination module, which is used to determine the emergency handling method to be adjusted corresponding to the fault detection result for at least one preset emergency handling method; verify the emergency handling method to be adjusted based on at least one preset business processing instance of the target system to obtain at least one verification result; evaluate the effectiveness of the emergency handling method to be adjusted based on a preset time attenuation function and at least one verification result to obtain an evaluation result; adjust the emergency handling method to be adjusted based on the evaluation result to obtain the target emergency handling method.

[0110] Optionally, after performing fault repair processing on the target system based on the target emergency processing method, the device also includes: a system operation and maintenance optimization module, which is used to evaluate the data to be processed, the preset fault detection tool and the target emergency processing method corresponding to the target system, and obtain a target evaluation result, so as to optimize the data acquisition configuration information corresponding to the data to be processed, the preset fault detection tool and the target emergency processing method based on the target evaluation result.

[0111] The system operation and maintenance device provided in the embodiment of the present invention can execute the system operation and maintenance method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0112] Embodiment 4

[0113] Figure 5 1 is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0114] like Figure 5 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0115] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0116] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the system operation and maintenance method.

[0117] In some embodiments, the system operation and maintenance method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the system operation and maintenance method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the system operation and maintenance method in any other appropriate manner (e.g., by means of firmware).

[0118] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0119] The computer program for implementing the system operation and maintenance method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program can be executed completely on the machine, partially on the machine, partially on the machine as an independent software package and partially on a remote machine, or completely on a remote machine or server.

[0120] Embodiment 5

[0121] Embodiment 5 of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a processor to execute a system operation and maintenance method, the method comprising:

[0122] Obtain the data to be processed of the target system under at least two evaluation dimensions, wherein the at least two evaluation dimensions include at least two of a business processing volume dimension, a response time dimension, a business failure rate dimension, a central processing unit usage dimension, and a memory usage dimension; for the at least two evaluation dimensions, determine the operating performance attributes of the target system according to the data to be processed under each evaluation dimension and an evaluation function corresponding to each evaluation dimension; when the operating performance attributes meet preset conditions, perform fault detection on the target system based on a preset fault detection tool to obtain a fault detection result; determine a target emergency processing method corresponding to the fault detection result, and perform fault repair processing on the target system based on the target emergency processing method.

[0123] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0124] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0125] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0126] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0127] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0128] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A system operation and maintenance method, characterized in that: include: Obtaining data to be processed of the target system under at least two evaluation dimensions, wherein the at least two evaluation dimensions include at least two of a business processing volume dimension, a response time dimension, a business failure rate dimension, a central processing unit usage dimension, and a memory usage dimension; For the at least two evaluation dimensions, determining the operating performance attribute of the target system according to the to-be-processed data under each evaluation dimension and the evaluation function corresponding to each evaluation dimension; When the operating performance attribute meets a preset condition, performing fault detection on the target system based on a preset fault detection tool to obtain a fault detection result; A target emergency processing method corresponding to the fault detection result is determined, so as to perform fault repair processing on the target system based on the target emergency processing method.

2. The method according to claim 1, characterized in that The obtaining of the data to be processed of the target system under at least two evaluation dimensions includes: According to data collection configuration information corresponding to the target system, raw data of the target system under at least two evaluation dimensions are collected, wherein the data collection configuration information at least includes a data collection frequency, a data collection method, and a data collection component; The original data under the at least two evaluation dimensions are normalized to obtain data to be processed.

3. The method according to claim 1, characterized in that: Each of the evaluation dimensions includes at least one sub-evaluation dimension, and determining the operating performance attribute of the target system according to the to-be-processed data under each evaluation dimension and the evaluation function corresponding to each evaluation dimension includes: For the at least two evaluation dimensions, determine the evaluation attribute to be fused corresponding to the current evaluation dimension according to the to-be-processed data corresponding to each sub-evaluation dimension under the current evaluation dimension, the first weight coefficient corresponding to each sub-evaluation dimension, and the second weight coefficient corresponding to the current evaluation dimension; The operating performance attributes of the target system are determined according to the to-be-fused evaluation attributes corresponding to the at least two evaluation dimensions.

4. The method according to claim 1, characterized in that: When the operating performance attribute meets a preset condition, the method further includes: According to the preset warning configuration information corresponding to the target system, the data to be processed of the target system and the operating performance attributes, warning prompt information is generated to call a preset fault detection tool based on the warning prompt information to perform fault detection on the target system, wherein the preset warning configuration information includes at least warning information generation rules and warning frequency.

5. The method according to claim 1, characterized in that When the operating performance attribute meets the preset condition, performing fault detection on the target system based on a preset fault detection tool to obtain a fault detection result includes: In the case where the operating performance attribute is greater than a preset attribute threshold, using a preset fault detection tool to detect the operating state of the target system when processing a preset business, and obtaining a state detection result; In the case where the state detection result does not meet the preset state threshold, determining the fault level, fault type and fault probability of the target system based on the state detection result, wherein the fault probability is obtained by adjusting the preset fault probability according to the state detection result; The fault level, the fault type and the fault probability are used as the fault detection result of the target system.

6. The method according to claim 1, characterized in that The target system includes at least one preset emergency processing method, and the determining of the target emergency processing method corresponding to the fault detection result includes: For the at least one preset emergency processing method, determining an emergency processing method to be adjusted corresponding to the fault detection result; Verifying the emergency processing method to be adjusted based on at least one preset business processing instance of the target system to obtain at least one verification result; According to the preset time decay function and the at least one verification result, the effectiveness of the emergency handling method to be adjusted is evaluated to obtain an evaluation result; According to the evaluation result, the emergency handling method to be adjusted is adjusted to obtain a target emergency handling method.

7. The method according to claim 1, characterized in that After performing fault repair processing on the target system based on the target emergency processing mode, the method further includes: The data to be processed, the preset fault detection tool and the target emergency processing method corresponding to the target system are evaluated to obtain a target evaluation result, so as to optimize the data acquisition configuration information, the preset fault detection tool and the target emergency processing method corresponding to the data to be processed based on the target evaluation result.

8. A system operation and maintenance device, characterized in that: include: A data acquisition module, used to acquire the data to be processed of the target system under at least two evaluation dimensions, wherein the at least two evaluation dimensions include at least two of a business processing volume dimension, a response time dimension, a business failure rate dimension, a central processing unit usage dimension, and a memory usage dimension; a performance attribute determination module, configured to determine, for the at least two evaluation dimensions, an operating performance attribute of the target system according to the to-be-processed data under each evaluation dimension and an evaluation function corresponding to each evaluation dimension; A system fault detection module, used to perform fault detection on the target system based on a preset fault detection tool to obtain a fault detection result when the operating performance attribute meets a preset condition; The emergency processing method determination module is used to determine a target emergency processing method corresponding to the fault detection result, so as to perform fault repair processing on the target system based on the target emergency processing method.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the system operation and maintenance method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the system operation and maintenance method according to any one of claims 1 to 7 when executed.

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