Operation and maintenance data analysis method used in localized environment

Abstract

The invention discloses an operation and maintenance data analysis method used in a localized environment. The method comprises the following steps: carrying out availability detection on services running in the localized environment based on a preset period; if the service does not have the fault, acquiring a performance index in the period, and judging whether the service has a potential fault according to the acquired performance index; if the reference index corresponding to the acquired performance index exists in the performance index database, acquiring a potential fault type and a standard solution corresponding to the reference index, and sending the standard solution to the client; if the reference index corresponding to the acquired performance index does not exist in the performance index database, sending the performance index to an operation and maintenance personnel terminal, receiving fault solving information sent by the operation and maintenance personnel terminal, and updating the fault solving information to the performance index database; according to the method, the situation that operation and maintenance personnel check the service process in real time is avoided, the operation and maintenance personnel can perform other important operation and maintenance work, and the working efficiency of the operation and maintenance personnel is improved.

Description

Technical Field

[0001] The present invention relates to the field of operation and maintenance data analysis, and in particular to an operation and maintenance data analysis method for a localized environment. Background Art

[0002] In the field of localization, as more and more localized environments are deployed, some operation and maintenance problems also arise, such as: service anomalies caused by database problems, middleware and operating system problems, etc. When operation and maintenance data problems occur, if traditional data collection and analysis methods are used, the collected operation and maintenance data needs to be processed again and analyzed and processed manually. This will put forward two requirements for operation and maintenance personnel. First, they must have a certain technical foundation and understand both front-end business and back-end technology. Second, they must have a lot of experience and can distinguish which data is important and which data is irrelevant, so as to quickly diagnose and solve problems. However, operation and maintenance personnel who meet the above two requirements are generally hired by other companies at high prices, resulting in the current lack of corresponding technical talents in enterprises.

[0003] In response to this situation, some practitioners have proposed a method for analyzing localized operation and maintenance data based on big data technology. Through big data technology, based on unified operation and maintenance data collection services, real-time operation and maintenance data are collected and an operation and maintenance big data platform is established to meet the full range of data collection, summary reporting, log analysis, real-time monitoring, unified alarm, and data display management functions in multiple environments of localized government affairs at a low cost. However, as far as this method is concerned, although the amount of data collected is large, it cannot effectively analyze the collected data. In other words, even if the user collects the corresponding operation and maintenance data through the established big data platform, if the operation and maintenance personnel do not have the relevant technical foundation and experience, they still cannot quickly analyze the operation and maintenance data. Even if some faults can be solved, it will take a lot of time and energy. Isn't this contrary to the original intention of saving costs and quickly solving operation and maintenance problems? Therefore, this method only achieves a large aggregation of operation and maintenance data, but does not achieve effective analysis of operation and maintenance data. In addition, for some non-fault abnormal problems such as system function degradation, service process abnormality, and performance index deterioration, this method cannot quickly perceive and output problem diagnosis information, let alone output reference opinions for solving problems; Therefore, how to develop a technical solution that can analyze operation and maintenance data based on the collection of domestic environment operation and maintenance data, so as to assist non-professional technicians to quickly discover and solve operation and maintenance problems, has become a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0004] In view of the problems in the prior art, the present invention provides an operation and maintenance data analysis method for a localized environment, so as to improve the effectiveness and accuracy of fault analysis in a localized environment, thereby helping to resolve potential faults that may exist and laying a foundation for the development of operation and maintenance activities.

[0005] In order to solve the above problems, the technical solution adopted by the invention is: A method for analyzing operation and maintenance data in a localized environment, the method comprising: S1, performs availability testing on services running in the localized environment based on a preset cycle; S2, if the service has no fault, obtaining a performance indicator within the period, and determining whether the service has a potential fault according to the obtained performance indicator; S3, if yes, querying a performance indicator database according to the obtained performance indicator to determine whether there is a benchmark indicator corresponding to the obtained performance indicator in the performance indicator database; S4. If the benchmark indicator corresponding to the acquired performance indicator exists in the performance indicator database, the potential fault type and standard solution corresponding to the benchmark indicator are obtained, and the standard solution is sent to the client; if the benchmark indicator corresponding to the acquired performance indicator does not exist in the performance indicator database, the performance indicator is sent to the operation and maintenance personnel terminal, and the fault solution information sent by the operation and maintenance personnel terminal is received, and the fault solution information is updated to the performance indicator database.

[0006] The beneficial effects of this program are: Beneficial effects: Based on the preset cycle, the availability test and performance indicator test of the services running in the domestic environment are carried out. If the service is found to have unexpected behavior and its performance meets the preset fault indicators, it will be marked as a fault. At the same time, the potential processing methods will be automatically obtained from the fault database based on its corresponding performance indicators within the cycle. Through the above process, the full life cycle automatic closed loop of service operation and maintenance can be quickly realized, and the full cycle of service operation can be covered, which greatly reduces the subsequent workload of operation and maintenance personnel. Operation and maintenance analysis can be completed by manually solving unresolved problems.

[0007] Furthermore, the S1 performs availability detection on the services running in the localized environment based on a preset period, including: Collecting monitoring data corresponding to the service based on a preset first detection frequency; Determining whether a first preset character string appears in the acquired monitoring data; If the first preset character string appears in the acquired monitoring data, calling a preset vulnerability library to search whether there is a target vulnerability containing the first preset character string; If yes, the service is marked as faulty and the number of failures of the service is recorded; If the number of failures is greater than or equal to a first value, the service is marked as a failed service and the availability check of the service is terminated, wherein the first number of times is a preset upper limit of a failure threshold.

[0008] Furthermore, after performing availability detection on the services running in the localized environment based on a preset period in S1, the method further includes: Obtaining identification information of all services running in the nationalized environment; Identify the type of the identification information and determine whether the type of the identification information is a public cloud type; If the type of the identification information is a public cloud type, calling a preset vulnerability library to compare the identification information to determine whether there is a target vulnerability corresponding to the identification information in the vulnerability library; If the target vulnerability corresponding to the identification information does not exist in the vulnerability database, a vulnerability not found prompt message is generated and sent to the terminal of the controller; If the target vulnerability corresponding to the identification information exists in the vulnerability library, the service address corresponding to the identification information and the target vulnerability are sent to the control personnel terminal.

[0009] Further, in S2, if the service does not fail, obtaining a performance indicator within the period, and judging whether the service has a potential failure according to the obtained performance indicator, includes: If the service does not fail, then obtaining performance indicators within the period, the performance indicators including: CPU indicators and memory indicators; Determine whether the CPU indicator meets the first standard condition; If the CPU indicator does not meet the first standard condition, marking the service corresponding to the CPU indicator as a first type of failure; Determine whether the memory indicator meets a second standard condition, and if the memory indicator does not meet the second standard condition, mark the service corresponding to the memory indicator as a second type of fault.

[0010] Further, if yes, in S3, querying a performance indicator database according to the acquired performance indicator to determine whether there is a benchmark indicator corresponding to the acquired performance indicator in the performance indicator database, including: Querying a performance indicator database according to the performance indicator corresponding to the first type of fault, and determining whether a first standard benchmark indicator exists in the performance indicator database; If the first standard benchmark indicator exists in the performance indicator database, query the performance indicator database according to the service corresponding to the first type of fault to determine the standard solution and the first potential fault type corresponding to the first standard benchmark indicator; If the first standard benchmark indicator does not exist in the performance indicator database, calling a service process corresponding to the performance indicator corresponding to the first type of fault, and generating a first monitoring request; monitoring whether a second preset character string appears at a preset first monitoring time based on the first monitoring request; If the second preset character string appears within the preset first monitoring time, a preset website server is queried based on a preset first query method to determine whether there is a corresponding patch package for the second preset character string.

[0011] Further, in S3, if yes, querying a performance indicator database according to the obtained performance indicator to determine whether there is a benchmark indicator corresponding to the obtained performance indicator in the performance indicator database, the method further includes: If the first standard benchmark indicator exists in the performance indicator data, sending the first potential fault type and the first standard solution to the client; If the first standard benchmark indicator does not exist in the performance indicator database, the first monitoring request is modified based on a preset modification rule to obtain a modification request, and the performance indicator is modified based on the modification request.

[0012] Furthermore, after S3, the method further includes: If the second preset character string does not appear within the preset first monitoring time, stop monitoring all contents within the preset first monitoring time based on the first monitoring request; Re-acquire a second monitoring request corresponding to the performance indicator based on a preset sampling rule, sample and filter the acquired second monitoring request, and obtain second monitoring content through the sampled data; filtering the second monitoring content to obtain content to be inspected; Acquire a target text corresponding to the content to be inspected from a preset fault text library; Determine whether there is a matching text corresponding to the target text in the fault text library; If the matching text corresponding to the target text exists in the fault text library, a modification prompt message is generated and sent to the control personnel terminal; If the matching text corresponding to the target text does not exist in the fault text library, a second potential fault type is sent to the control personnel, and a solution sent by the control personnel is received to store the solution in the performance indicator database.

[0013] Furthermore, after S3, the method further includes: If the second standard benchmark indicator exists in the performance indicator database, the second potential fault type is sent to the control personnel terminal; usually, a performance trend chart can be displayed to give the operation and maintenance personnel a preliminary intuitive understanding; If the second standard benchmark indicator does not exist in the performance indicator database, a service process corresponding to the second potential fault type is received, and a preset exception file is extracted from the service process, the exception file is formatted, and the formatted exception file is saved in the performance indicator database.

[0014] Further, in S4, if the benchmark indicator corresponding to the acquired performance indicator exists in the performance indicator database, the potential fault type and standard solution corresponding to the benchmark indicator are acquired, and the standard solution is sent to the client; if the benchmark indicator corresponding to the acquired performance indicator does not exist in the performance indicator database, the performance indicator is sent to the operation and maintenance personnel terminal, and the fault solution information sent by the operation and maintenance personnel terminal is received. After the fault solution information is updated to the performance indicator database, the method further includes: Obtaining a performance value corresponding to the service in a second period; A performance trend graph of the service and corresponding trend prediction information are generated according to the performance value, and the performance prediction information is sent to the control personnel terminal.

[0015] Further, in S4, if the benchmark indicator corresponding to the acquired performance indicator exists in the performance indicator database, the potential fault type and standard solution corresponding to the benchmark indicator are acquired, and the standard solution is sent to the client; if the benchmark indicator corresponding to the acquired performance indicator does not exist in the performance indicator database, the performance indicator is sent to the operation and maintenance personnel terminal, and the fault solution information sent by the operation and maintenance personnel terminal is received. After the fault solution information is updated to the performance indicator database, the method further includes: Obtaining a performance trend graph corresponding to each service from the performance indicator database; Displaying all services in the performance trend graph and receiving screening conditions input by the operation and maintenance personnel terminal; Filter all services according to the screening conditions to obtain target services that meet the preset screening conditions; The screening rules and standard solutions corresponding to the preset screening conditions are combined and stored in the performance indicator database. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of the system of the present invention; DETAILED DESCRIPTION The following is further described in detail through specific implementation methods: Example 1 like Figure 1 As shown, a method for analyzing operation and maintenance data in a localized environment includes: S1, performs availability checks on services running in the localized environment based on a preset cycle.

[0017] S2: If the service does not fail, the performance indicators within the period are obtained, and it is determined whether the service has a potential failure based on the obtained performance indicators.

[0018] S3: If yes, query the performance indicator database according to the obtained performance indicator to determine whether there is a benchmark indicator corresponding to the obtained performance indicator in the performance indicator database.

[0019] S4: If there is a benchmark indicator corresponding to the obtained performance indicator in the performance indicator database, the potential fault type and standard solution corresponding to the benchmark indicator are obtained, and the standard solution is sent to the client; if there is no benchmark indicator corresponding to the obtained performance indicator in the performance indicator database, the performance indicator is sent to the operation and maintenance personnel terminal, and the fault solution information sent by the operation and maintenance personnel terminal is received, and the fault solution information is updated to the performance indicator database.

[0020] The present invention is mainly to solve the problem of being able to effectively handle the abnormal status of services running in a localized environment. To this end, in a localized environment, by continuously detecting the availability and performance of services running in the environment, a corresponding method is obtained and a system log is generated to the computer of the operation and maintenance personnel, so that the corresponding abnormal situation is located and quickly processed, and performance analysis is performed on various services in the localized environment on the cloud to timely discover potential risks and solve problems.

[0021] The preset performance indicator database stores benchmark indicators, which correspond to standard solutions and potential fault types. When you need to check the information in the benchmark indicator database, you only need to compare the content to be queried with the indicators in the benchmark indicator database to obtain the corresponding information.

[0022] In order to solve the above-mentioned technical problems, the operation and maintenance data analysis method for a domestic environment provided by the present invention mainly includes three aspects. On the one hand, by establishing an analysis mechanism specifically for the operation and maintenance data in the domestic environment, the characteristics of the operation and maintenance data are analyzed, so as to timely and effectively discover the potential failure problems of services running in the domestic environment; on the other hand, a relevant performance indicator database is provided for the work of operation and maintenance personnel in the domestic environment, and the indicator parameters required by the operation and maintenance personnel in the work process are provided to improve the work efficiency of the operation and maintenance personnel; finally, through a large amount of data, the laws of running services in the domestic environment are analyzed to optimize the work process of the operation and maintenance personnel.

[0023] The establishment of the performance indicator library of the present invention is mainly to monitor the availability of the service in each cycle when the service is running in the domestic environment. If a fault is found, the corresponding indicator data is stored in the performance indicator database. If no fault is found, the running service is fault detected according to the obtained performance indicators, information is added according to the detection results, and an update mechanism is implemented to update the performance indicator library.

[0024] Therefore, the establishment of the performance index database first requires the calculation of the system availability from multiple aspects, wherein the calculation of the availability is performed by collecting the monitoring data of the service or index, and the difference in the monitoring data causes some changes in the calculation method of the availability. Therefore, in order to obtain the availability calculation of the system in the present invention, the monitoring data must first be collected from the data source, then the calculation method of the availability is determined, and finally the availability index of the specific service is calculated.

[0025] The data information is collected mainly through a certain monitoring mechanism to collect monitoring data at different time points. After the required data is collected, the data can be stored, and the availability of the monitoring data can be obtained by performing specific calculations on the monitoring data storage. In order to better obtain the availability index, the service needs to be classified in a variety of ways, because the analysis target may be different services, so the service must be classified first, including the classification of public clouds and private clouds. When classifying, the service is first classified by data center, and the operation and maintenance data of the same data center is stored in the same table, and then the type of data is determined. According to the classification of the data, the availability is calculated to obtain the corresponding index, in which different indicator data are calculated from the system level and resource level, and judged by various forms of indicators.

[0026] In the above classification process, the data in the data center is classified differently, and the availability indicators obtained according to the data classification need to be calculated separately to determine whether there are abnormalities. During the calculation process, the availability needs to be calculated from the monitoring dimension, such as indicator availability, including time availability and performance availability.

[0027] Among them, the time availability calculation method is to collect monitoring data corresponding to the service based on a preset first detection frequency, specifically including availability and fault number information; then determine whether the service identifier has a vulnerability based on a preset vulnerability library; if the service has a vulnerability, obtain the performance status corresponding to the service identifier to determine whether the vulnerability is caused by the corresponding vulnerability; if the vulnerability exists, determine whether the performance indicator of the service in the preset period meets the first standard condition based on the service identifier; if it does not meet the first standard condition, obtain the availability indicator of the service.

[0028] Among them, the total number of failures is the sum of the number of failures of each monitored object, and the availability is expressed as (available time / preset duration)*100%. The available time is the normal time of the actual operation of the monitored object. The available time statistical process is as follows: a. Initialize the available time TotalTime to 0 to represent the total available time, and CurrentTime to 0 to represent the total monitoring time; b. Determine whether there is an abnormal record of indicators. If there is no abnormal record, go to c; if the indicator is abnormal, record the specific abnormal time and abnormal type; c. Update the start time of the monitoring cycle and the abnormal record; d. Determine the abnormal type. If it is a hardware failure, go to a; e. If the difference between the current time and the time of the abnormal record is >2 hours; then Go to f; otherwise go to a; f. Determine whether there is an abnormal record. If not, go to e; g. Determine the indicator type. If it is a CPU consumption abnormality, go to h; h. Determine whether the indicator CPU usage is less than the threshold. If so, go to i, otherwise go to a; i. Update the indicator end time. If the indicator takes <10 seconds, include the time taken for this indicator in the available time CurrentTime and the total indicator duration TotalTime; j. Determine whether the time interval between CurrentTime and the start time is <2 hours. i. Determine whether the indicator is abnormal. If so, go to a; Return whether a downtime warning is required; k. Return the service identifier; By determining the availability, you can determine whether an indicator warning is required.

[0029] Next, the performance status of different indicators of the same service needs to be calculated, where the performance status includes the service resource status and the data type of the monitored object, etc. The monitored object is the server. Among them, the availability of the server of the monitored object is determined by collecting the values ​​used by the server according to the preset second detection frequency (for example, 5 minutes), and combining the preset second vulnerability library to determine whether the values ​​are related to the vulnerability of the server. If included, it is determined whether the server has a fault. By judging whether the indicators in the acquired resources meet the first data standard, for example, judging whether the memory indicator and processor indicator of the resource are within the normal threshold. The second data standard is the resource indicator obtained from reading the fault information, such as the memory consumption value, the available central processing unit, and the percentage of available central processing units. The performance status can be calculated by whether the service resource status of the two types of indicators meets the second standard conditions.

[0030] Through the above method, it is possible to better distinguish between monitoring indicators and fault information at different times. By using the data of monitoring indicators, the performance of the target service over a period of time can be analyzed, and then the similarity between the fault times in the fault information can be used to determine whether there is a second vulnerability. If the faults appear regularly within a period of time, it is determined that the target service data is related to the second vulnerability.

[0031] Through the above-mentioned method, in cloud computing, the computing time of cloud computing can be reduced, the computing efficiency can be improved, and the availability of the processing system in the localized environment can be improved. Therefore, this patent application analyzes the operation and maintenance data to obtain the corresponding performance, reducing the time and space requirements for operation and maintenance analysis in the localized environment.

[0032] In order to overcome the above technical problems, two parameters are introduced into the same indicator type in the invention, wherein the two parameters introduced include CPU state parameters and operating frequency parameters, so that data processing is performed for different parameters. For example, the corresponding CPU state parameters and the corresponding state frequency can be extracted from the monitoring, and the processing result of the CPU parameters can be obtained according to the CPU state and the corresponding indicator threshold in the prior art, and the extracted processor frequency is filtered to obtain the filtered parameter data for calculation, and the corresponding indicator is obtained through the corresponding parameter calculation, wherein the processing value can be optimized according to the change rate of the CPU state and the corresponding filtering value.

[0033] For example, monitor the CPU clock frequency and the corresponding CPU failure time rate. Through the CPU clock frequency, CPU usage and CPU clock frequency failure time rate, monitor the total failure time. The monitored object is the specified business service.

[0034] It should be noted that the above embodiments are product embodiments corresponding to the previous method embodiments. For the description of the optional implementation methods in the product embodiments, reference can be made to the corresponding description in the above method embodiments, which will not be repeated here.

[0035] The above is only an embodiment of the invention, and the common knowledge such as the known specific structure and characteristics in the scheme is not described in detail here. It should be pointed out that for those skilled in the art, several deformations and improvements can be made without departing from the structure of the invention, which should also be regarded as the scope of protection of the invention, and these will not affect the effect of the implementation of the invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A method for analyzing operation and maintenance data in a localized environment, characterized in that: The method comprises: S1, performs availability testing on services running in the localized environment based on a preset cycle; S2, if the service has no fault, obtaining a performance indicator within the period, and determining whether the service has a potential fault according to the obtained performance indicator; S3, if yes, querying a performance indicator database according to the obtained performance indicator to determine whether there is a benchmark indicator corresponding to the obtained performance indicator in the performance indicator database; S4. If the benchmark indicator corresponding to the acquired performance indicator exists in the performance indicator database, the potential fault type and standard solution corresponding to the benchmark indicator are obtained, and the standard solution is sent to the client; if the benchmark indicator corresponding to the acquired performance indicator does not exist in the performance indicator database, the performance indicator is sent to the operation and maintenance personnel terminal, and the fault solution information sent by the operation and maintenance personnel terminal is received, and the fault solution information is updated to the performance indicator database.

2. The operation and maintenance data analysis method for a localized environment according to claim 1, characterized in that: The S1 performs availability detection on the services running in the localization environment based on a preset period, including: collecting monitoring data corresponding to the service based on a preset first detection frequency; determining whether a first preset character string appears in the acquired monitoring data; if the first preset character string appears in the acquired monitoring data, calling a preset vulnerability library to search whether there is a target vulnerability containing the first preset character string; if so, marking the service as a fault and recording the number of faults of the service; if the number of faults is greater than or equal to the first value, marking the service as a faulty service and terminating the availability detection of the service, wherein the first number value is a preset upper limit of the fault threshold.

3. The operation and maintenance data analysis method for a localized environment according to claim 2 is characterized in that: In S1, after performing availability detection on the services running in the nationalized environment based on a preset period, the method further includes: obtaining identification information of all services running in the nationalized environment; identifying the type of the identification information to determine whether the type of the identification information is a public cloud type; if the type of the identification information is a public cloud type, calling a preset vulnerability library to compare the identification information to determine whether there is a target vulnerability corresponding to the identification information in the vulnerability library; if there is no target vulnerability corresponding to the identification information in the vulnerability library, generating a vulnerability not found prompt message and sending it to the control personnel terminal; if there is a target vulnerability corresponding to the identification information in the vulnerability library, sending the service address corresponding to the identification information and the target vulnerability to the control personnel terminal.

4. The operation and maintenance data analysis method for a localized environment according to claim 3 is characterized in that: S2, if the service has not failed, obtain performance indicators within the period, and determine whether the service has a potential failure based on the obtained performance indicators, including: if the service has not failed, obtain performance indicators within the period, the performance indicators including: CPU indicators and memory indicators; determine whether the CPU indicators meet the first standard conditions; if the CPU indicators do not meet the first standard conditions, mark the service corresponding to the CPU indicators as a first type of failure; determine whether the memory indicators meet the second standard conditions, if the memory indicators do not meet the second standard conditions, mark the service corresponding to the memory indicators as a second type of failure.

5. The operation and maintenance data analysis method for a localized environment according to claim 4 is characterized in that: If S3 is yes, then query the performance indicator database according to the obtained performance indicator to determine whether there is a benchmark indicator corresponding to the obtained performance indicator in the performance indicator database, including: query the performance indicator database according to the performance indicator corresponding to the first type of fault, and determine whether there is a first standard benchmark indicator in the performance indicator database; if the first standard benchmark indicator exists in the performance indicator database, query the performance indicator database according to the service corresponding to the first type of fault, and determine the standard solution and the first potential fault type corresponding to the first standard benchmark indicator; if the first standard benchmark indicator does not exist in the performance indicator database, call the service process corresponding to the performance indicator corresponding to the first type of fault, and generate a first monitoring request; based on the first monitoring request, monitor whether a second preset character string appears within the preset first monitoring time; if the second preset character string appears within the preset first monitoring time, query the preset website server based on the preset first query method to determine whether there is a corresponding patch package for the second preset character string.

6. The operation and maintenance data analysis method for a localized environment according to claim 5, characterized in that: In S3, if yes, then query the performance indicator database according to the obtained performance indicator to determine whether there is a benchmark indicator corresponding to the obtained performance indicator in the performance indicator database. The method also includes: if the first standard benchmark indicator exists in the performance indicator database, sending the first potential fault type and the first standard solution to the client; if the first standard benchmark indicator does not exist in the performance indicator database, correcting the first monitoring request based on a preset correction rule to obtain a correction request, and correcting the performance indicator based on the correction request.

7. The operation and maintenance data analysis method for a localized environment according to claim 6, characterized in that: After S3, the method also includes: if the second preset character string does not appear within the preset first monitoring time, stop monitoring all contents within the preset first monitoring time based on the first monitoring request; re-acquire the second monitoring request corresponding to the performance indicator based on the preset sampling rule, and sample and filter the acquired second monitoring request, and obtain the second monitoring content through the sampled data; filter the second monitoring content to obtain the content to be tested; obtain the target text corresponding to the content to be tested from the preset fault text library; determine whether there is a matching text corresponding to the target text in the fault text library; if there is a matching text corresponding to the target text in the fault text library, generate a modification prompt information, and send the modification prompt information to the control personnel terminal; if there is no matching text corresponding to the target text in the fault text library, send a second potential fault type to the control personnel, and receive the solution sent by the control personnel to store the solution in the performance indicator database.

8. The operation and maintenance data analysis method for a localized environment according to claim 7, characterized in that: After S3, the method also includes: if the second standard benchmark indicator exists in the performance indicator database, sending the second potential fault type to the control personnel terminal; if the second standard benchmark indicator does not exist in the performance indicator database, receiving the service process corresponding to the second potential fault type, and extracting a preset exception file in the service process, formatting the exception file, and saving the formatted exception file to the performance indicator database.

9. The operation and maintenance data analysis method for a localized environment according to claim 8, characterized in that: S4, if the benchmark indicator corresponding to the acquired performance indicator exists in the performance indicator database, then acquiring the potential fault type and standard solution corresponding to the benchmark indicator, and sending the standard solution to the client; If the benchmark indicator corresponding to the acquired performance indicator does not exist in the performance indicator database, the performance indicator is sent to the operation and maintenance personnel terminal, and the fault resolution information sent by the operation and maintenance personnel terminal is received. After the fault resolution information is updated to the performance indicator database, the method further includes: obtaining a performance value corresponding to the service in the second period; A performance trend graph of the service and corresponding trend prediction information are generated according to the performance value, and the performance prediction information is sent to the control personnel terminal.

10. The operation and maintenance data analysis method for a localized environment according to any one of claims 1 to 9, characterized in that: S4, if the benchmark indicator corresponding to the acquired performance indicator exists in the performance indicator database, then acquiring the potential fault type and standard solution corresponding to the benchmark indicator, and sending the standard solution to the client; If the benchmark indicator corresponding to the acquired performance indicator does not exist in the performance indicator database, the performance indicator is sent to the operation and maintenance personnel terminal, and the fault resolution information sent by the operation and maintenance personnel terminal is received. After the fault resolution information is updated to the performance indicator database, the method also includes: obtaining a performance trend chart corresponding to each service from the performance indicator database; displaying all services in the performance trend chart, and receiving filtering conditions input by the operation and maintenance personnel terminal; filtering all services according to the filtering conditions to obtain target services that meet the preset filtering conditions; and storing the filtering rules and standard solutions corresponding to the preset filtering conditions in the performance indicator database.

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