Business abnormality troubleshooting method, device, equipment, storage medium and program product

Abstract

The present application relates to a method, device, equipment, storage medium and program product for troubleshooting business anomalies. The method comprises: first, obtaining a baseline of application parameters and a baseline of network parameters of a target application corresponding to the current time period, then obtaining real-time parameters of the target application including real-time application parameters and real-time network parameters, and finally, determining whether there is an anomaly in the wide area network based on whether the real-time parameters are within the range corresponding to the baseline. Among them, the application parameters are used to characterize the operating status of the target application, the network parameters are used to characterize the interaction status between the target application and the wide area network, and the baseline is predicted based on the historical application parameters and historical network parameters of the target application in the previous time period of the current time period. This method can automatically check whether there is an anomaly in the wide area network.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a method, device, equipment, storage medium and program product for troubleshooting business anomalies. Background Art

[0002] In the field of Internet finance, there are many reasons that lead to a decrease in the success rate of business transactions, such as network problems, application problems, database problems, and server problems. Therefore, when the success rate of business transactions decreases, professional technicians are required to investigate the reasons one by one to locate the specific reasons that lead to the decrease in the success rate of business transactions. However, this manual investigation method is relatively inefficient. Summary of the invention

[0003] Based on this, it is necessary to provide a business anomaly troubleshooting method, device, equipment, storage medium and program product for automatically checking whether there are wide area network problems in response to the above technical problems.

[0004] In the first aspect, the present application provides a method for troubleshooting business anomalies. The method includes: obtaining a baseline of a target application corresponding to the current period, the baseline includes a baseline of application parameters and a baseline of network parameters, the application parameters are used to characterize the operating status of the target application, the network parameters are used to characterize the interaction status of the target application and the wide area network, and the baseline is predicted based on the application parameters and network parameters of the target application history in the previous period of the current period; obtaining real-time parameters of the target application, the real-time parameters include real-time application parameters and real-time network parameters; determining whether there is an anomaly in the wide area network based on whether the real-time parameters are within the range corresponding to the baseline.

[0005] In one of the embodiments, the application parameters include application response time parameters, application success rate parameters and application traffic parameters, and the network parameters include network link packet loss parameters.

[0006] In one of the embodiments, determining whether there is an abnormality in the wide area network is based on whether the real-time parameters are within the range corresponding to the baseline, including: determining whether the real-time application parameters are within the range corresponding to the baseline of the application parameters; if so, determining that there is no abnormality in the wide area network; if not, determining whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters.

[0007] In one of the embodiments, determining whether there is an abnormality in the wide area network is based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters, including: judging whether the real-time network parameters are within the range corresponding to the baseline of the network parameters; if so, determining that there is no abnormality in the wide area network; if not, determining that there is an abnormality in the wide area network.

[0008] In one of the embodiments, determining whether the real-time application parameter is within the range corresponding to the baseline of the application parameter includes: determining whether the real-time application response time parameter, the real-time application success rate parameter, and the real-time application traffic parameter are all within the range corresponding to the baseline of the application parameter; if so, determining that the real-time application parameter is within the range corresponding to the baseline of the application parameter; if not, determining that the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

[0009] In one of the embodiments, before obtaining the baseline of the target application corresponding to the current time period, the method further includes: inputting the historical application parameters and historical network parameters of the target application in the previous time period of the current time period into the prophet model to obtain the corresponding application parameter baseline and network parameter baseline.

[0010] In one of the embodiments, determining whether a real-time network link packet loss parameter is within a range corresponding to a baseline of the network parameter includes: obtaining a time when the real-time application parameter is not within a range corresponding to the baseline of the application parameter; and determining whether the real-time network link packet loss parameter within a preset time range before and after the time is within a range corresponding to the baseline of the network parameter.

[0011] In a second aspect, the present application also provides a service anomaly troubleshooting device. The device includes:

[0012] A first acquisition module is used to acquire a baseline of a target application corresponding to a current period, the baseline including a baseline of application parameters and a baseline of network parameters, the application parameters are used to characterize the operation status of the target application, the network parameters are used to characterize the interaction status between the target application and the wide area network, and the baseline is predicted based on the application parameters and network parameters of the target application history in the previous period of the current period;

[0013] A second acquisition module is used to acquire real-time parameters of a target application, where the real-time parameters include real-time application parameters and real-time network parameters;

[0014] The determination module is used to determine whether there is an abnormality in the wide area network according to whether the real-time parameters are within the range corresponding to the baseline.

[0015] In one of the embodiments, the application parameters include application response time parameters, application success rate parameters and application traffic parameters, and the network parameters include network link packet loss parameters.

[0016] In one of the embodiments, the determination module is specifically used to determine whether the real-time application parameters are within the range corresponding to the baseline of the application parameters; if so, it is determined that there is no abnormality in the wide area network; if not, it is determined whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters.

[0017] In one of the embodiments, the determination module is specifically used to determine whether the real-time network parameter is within the range corresponding to the baseline of the network parameter; if so, it is determined that there is no abnormality in the wide area network; if not, it is determined that there is an abnormality in the wide area network.

[0018] In one of the embodiments, the determination module is specifically used to determine whether the real-time application response time parameter, the real-time application success rate parameter and the real-time application traffic parameter are all within the range corresponding to the baseline of the application parameter; if so, it is determined that the real-time application parameter is within the range corresponding to the baseline of the application parameter; if not, it is determined that the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

[0019] In one of the embodiments, the device further includes a prediction module for inputting historical application parameters and historical network parameters of the target application in the previous period of the current period into a prophet model to obtain a corresponding baseline of the application parameters and a baseline of the network parameters.

[0020] In one of the embodiments, the determination module is specifically used to obtain the time when the real-time application parameters are not within the range corresponding to the baseline of the application parameters; and determine whether the real-time network link packet loss parameters within a preset time range before and after the time are within the range corresponding to the baseline of the network parameters.

[0021] In a third aspect, the present application further provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method for troubleshooting service anomalies as described in any one of the first aspects above is implemented.

[0022] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the service anomaly troubleshooting method as described in any one of the first aspects above.

[0023] In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the method for troubleshooting service anomalies as described in any one of the first aspects above is implemented.

[0024] The above-mentioned method, device, equipment, storage medium and program product for troubleshooting business anomalies first obtain the baseline of the application parameters and the baseline of the network parameters of the target application corresponding to the current time period, then obtain the real-time parameters of the target application including the real-time application parameters and the real-time network parameters, and finally determine whether the wide area network has an anomaly based on whether the real-time parameters are within the range corresponding to the baseline. Among them, the application parameters are used to characterize the operating status of the target application, and the network parameters are used to characterize the interaction status between the target application and the wide area network. The baseline is predicted based on the historical application parameters and the historical network parameters of the target application in the previous time period of the current time period. In this way, the baseline of the application parameters and the baseline of the network parameters are determined based on the historical parameters. When an abnormality occurs in the business, the real-time application parameters and real-time network parameters of the business are obtained, and the real-time application parameters and real-time network parameters are compared with the baseline of the application parameters and the baseline of the network parameters to determine whether the wide area network has an anomaly, thereby realizing automatic troubleshooting of wide area network problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is one of the flowcharts of a method for troubleshooting business anomalies in one embodiment;

[0026] Figure 2 This is a second flow chart of a method for troubleshooting business anomalies in another embodiment;

[0027] Figure 3 This is a third flow chart of a method for troubleshooting business anomalies in another embodiment;

[0028] Figure 4 This is a fourth flow chart of a method for troubleshooting business anomalies in another embodiment;

[0029] Figure 5 This is a fifth flow chart of a method for troubleshooting business anomalies in another embodiment;

[0030] Figure 6 This is a sixth flow chart of a method for troubleshooting business anomalies in another embodiment;

[0031] Figure 7 A flowchart of a method for troubleshooting business anomalies in another embodiment;

[0032] Figure 8 It is a structural block diagram of a device for troubleshooting business anomalies in one embodiment;

[0033] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0035] In the field of Internet finance, there are many reasons for the reduction of the success rate of business transactions, such as network problems, application problems, database problems, and server problems. Therefore, when the success rate of business transactions is reduced, professional technicians are required to check the reasons one by one to determine whether there are problems with the WAN network, the application, the database, and the server, and then locate the specific reasons for the reduction in the success rate of business transactions. However, this manual troubleshooting method is inefficient.

[0036] In view of this, the present application proposes a method for troubleshooting business anomalies. When a business anomaly occurs, real-time parameters are obtained to determine whether the wide area network has an anomaly. If the wide area network has an anomaly, it is determined that the business anomaly may be caused by the wide area network anomaly. If the wide area network has no anomaly at this time, it is determined that the business anomaly is not caused by the wide area network, thereby realizing automatic troubleshooting of wide area network problems.

[0037] In one embodiment, Figure 1 As shown, a method for troubleshooting business anomalies is provided, and the method is described by taking the method applied to a terminal as an example. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. The method includes the following steps:

[0038] Step 101: The terminal obtains a baseline of a target application corresponding to a current period.

[0039] The baseline includes the baseline of application parameters and the baseline of network parameters. The application parameters are used to characterize the operating status of the target application, and the network parameters are used to characterize the interaction status between the target application and the wide area network. The baseline is predicted based on the historical application parameters and historical network parameters of the target application in the previous period of the current period.

[0040] Among them, the target application is the application with business anomalies, and it is necessary to analyze the cause of the business anomaly to see if it is affected by wide area network problems. The baseline of the application parameter is the range corresponding to the parameter value of the application parameter under normal circumstances, including the upper limit and the lower limit, and the baseline of the network parameter is the range corresponding to the parameter value of the network parameter under normal circumstances, including the upper limit and the lower limit. The application parameters reflect the various real-time states of the application during operation, which may include response time, success rate, etc. The network parameters reflect the state of the wide area network on which the target application runs, which may include the packet loss rate of the network link, etc. Optionally, only one application is run on a more important network link. The baseline of the application parameter and the baseline of the network parameter are predicted by the model based on the historical application parameters and historical network parameters of the target application in the previous period of the current period. For example: record 0:00 of each day as T, input the time series data of application parameters and network parameters in the time period from T-7 to T into the model for prediction to obtain the baseline of application parameters and the baseline of network parameters in the time period from T to T+7. That is, the baseline of the current period is predicted based on the historical parameter data, and the baseline of the next time period is obtained by iterating different time periods in sequence. The accuracy of the baseline is higher.

[0041] Step 102: The terminal obtains real-time parameters of the target application.

[0042] Among them, real-time parameters include real-time application parameters and real-time network parameters. Real-time parameters refer to application parameters and network parameters of the current period. Application parameters and network parameters are both time series data. When the service of the target application is abnormal and needs to be judged for the cause, the real-time parameters of the target application in the current period are obtained for judgment.

[0043] Step 103: The terminal determines whether there is an abnormality in the wide area network according to whether the real-time parameter is within a range corresponding to the baseline.

[0044] The terminal determines whether the acquired real-time application parameters are within the range corresponding to the baseline of the application parameters, that is, whether the time series data of the application parameters within a period of time are all between the upper and lower limits of the time corresponding to the baseline of the application parameters. It determines whether the real-time network parameters are within the range corresponding to the baseline of the network parameters, that is, whether the time series time of the network parameters within a period of time are all between the upper and lower limits of the time corresponding to the baseline of the network parameters. The above judgment determines whether there is an abnormality in the wide area network where the target application is running.

[0045] In the above-mentioned service troubleshooting method, first, the baseline of the application parameters and the baseline of the network parameters of the target application corresponding to the current period are obtained, then the real-time parameters of the target application including the real-time application parameters and the real-time network parameters are obtained, and finally, whether the wide area network has an abnormality is determined based on whether the real-time parameters are within the range corresponding to the baseline. Among them, the application parameters are used to characterize the operating status of the target application, and the network parameters are used to characterize the interaction status between the target application and the wide area network. The baseline is predicted based on the historical application parameters and the historical network parameters of the target application in the previous period of the current period. In this way, the baseline of the application parameters and the baseline of the network parameters are determined based on the historical parameters. When an abnormality occurs in the service, the real-time application parameters and real-time network parameters of the service are obtained, and the real-time application parameters and real-time network parameters are compared with the baseline of the application parameters and the baseline of the network parameters to determine whether the wide area network has an abnormality, thereby realizing automatic troubleshooting of wide area network problems.

[0046] Optionally, the application parameters include application response time parameters, application success rate parameters, and application traffic parameters, and the network parameters include network link packet loss parameters. Among them, the application response time parameter is used to characterize the response time of the application, the application success rate parameter is used to characterize the success rate of application execution, and the application traffic parameter is used to characterize the traffic during the application operation. The network link packet loss parameter is used to characterize the packet loss of the wide area network link where the application is located. The application response time parameter, application success rate parameter, application traffic parameter, and network link packet loss parameter are all time series data.

[0047] In one embodiment, whether the wide area network is abnormal can be determined based on whether the acquired real-time parameters are within the range corresponding to the baseline, such as Figure 2 As shown, the steps include:

[0048] Step 201: The terminal determines whether the real-time application parameter is within a range corresponding to the baseline of the application parameter.

[0049] The baseline of the application parameter includes an upper limit and a lower limit of the application parameter, and determines whether the real-time application parameter is within the range corresponding to the baseline of the application parameter, that is, whether the real-time application parameter is within the upper limit and the lower limit of the application parameter at the corresponding time.

[0050] Step 202: If yes, it is determined that there is no abnormality in the wide area network.

[0051] Specifically, if the real-time application parameters are all within the upper and lower limits of the application parameters at the corresponding time, it is determined that there is no abnormality in the wide area network, the service abnormality is not affected by the wide area network, and there is no need to pay attention to this cause.

[0052] Step 203: If not, the terminal determines whether there is an abnormality in the wide area network according to whether the real-time network parameters are within the range corresponding to the baseline of the network parameters.

[0053] If not all real-time application parameters are within the upper and lower limits of the application parameters at the corresponding time, that is, some application parameters exceed the upper or lower limit corresponding to the baseline of the application parameters at the corresponding time, then continue to determine whether the real-time network parameters are within the range corresponding to the baseline of the network parameters, and determine whether there is an abnormality in the wide area network based on the determination result of the real-time network parameters.

[0054] In the above embodiment, it is first determined whether the application parameters of the target application exceed the baseline of the application parameters. If the application response time, application success rate and application traffic are all within the corresponding baseline, it means that the wide area network is normal and there is no need to determine the network parameters, thereby saving troubleshooting time and improving efficiency.

[0055] In one embodiment, when the above application parameter judgment is abnormal, the step of determining whether there is an abnormality in the wide area network is as follows: Figure 3 As shown, including:

[0056] Step 301: The terminal determines whether the real-time network parameter is within a range corresponding to the baseline of the network parameter.

[0057] The baseline of the network parameters includes an upper limit and a lower limit, and it is determined whether the real-time network parameters are within the range corresponding to the baseline of the network parameters, that is, whether the real-time network parameters are all within the upper limit and the lower limit of the network parameters at the corresponding time.

[0058] Step 302: If yes, determine that there is no abnormality in the wide area network.

[0059] Specifically, if the real-time network parameters are all within the upper and lower limits of the network parameters at the corresponding time, it is determined that there is no abnormality in the wide area network, the service abnormality is not affected by the wide area network, and there is no need to pay attention to this cause.

[0060] Step 303: If not, it is determined that there is an abnormality in the wide area network.

[0061] If the real-time network parameters are not all within the upper and lower limits of the network parameters at the corresponding time, that is, some network parameters exceed the upper or lower limits of the baseline of the network parameters at the corresponding time, it is determined that the WAN is abnormal. This can provide a reference for operation and maintenance personnel, and the business abnormality at this time may be caused by the WAN abnormality.

[0062] Optionally, determine whether the real-time application parameter is within the range corresponding to the baseline of the application parameter, such as Figure 4 As shown, the specific steps include:

[0063] Step 401 : The terminal determines whether a real-time application response time parameter, a real-time application success rate parameter, and a real-time application flow parameter are all within a range corresponding to a baseline of the application parameter.

[0064] Optionally, the baseline of the application parameter includes a baseline of the application response time, a baseline of the application success rate, and a baseline of the application flow. The terminal determines whether the real-time application response time parameter is within the range corresponding to the baseline of the application response time, whether the real-time application success rate parameter is within the range corresponding to the baseline of the application success rate, and whether the real-time application flow parameter is within the range corresponding to the baseline of the application flow.

[0065] Step 402: If yes, determine that the real-time application parameter is within the range corresponding to the baseline of the application parameter.

[0066] If the real-time application response time parameter, the real-time application success rate parameter, and the real-time application traffic parameter are all within the ranges corresponding to their respective baselines, it is determined that the real-time application parameter is within the range corresponding to the baseline of the application parameter.

[0067] Step 403: If not, it is determined that the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

[0068] If any one of the real-time application response time parameter, the real-time application success rate parameter and the real-time application traffic parameter exceeds the range of the corresponding baseline, it is determined that the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

[0069] In an embodiment of the present application, the baseline of the target application corresponding to the current time is obtained through the historical parameters of the target application. The specific steps also include: inputting the historical application parameters and historical network parameters of the target application in the previous time period of the current time period into the prophet model to obtain the corresponding application parameter baseline and network parameter baseline.

[0070] Among them, the prophet model is a time series prediction model. By inputting a known time series, including the timestamp and corresponding value of the time series, and inputting the length of the time series to be predicted; then the prophet model can output the trend of the future time series. At the same time, the output result can provide necessary statistical indicators, including fitting curves, the upper limit of the time series and the lower limit of the time series. Therefore, if you want to get the baseline of the target application corresponding to the current period, input the historical application parameters and historical network parameters of the target application in the previous period of the current period into the prophet model respectively, and get the corresponding application parameter baseline and network parameter baseline. The optional application parameter baseline also includes the application response time baseline, the application success rate baseline and the application traffic baseline, and the network parameter baseline includes the network link baseline.

[0071] In the above embodiment, the prediction baseline for the next time period is obtained through the model using the historical data of the previous time period. The baseline prediction process is obtained by continuously iterating based on the historical data of the previous time period of the current time period. The baseline obtained in this way is more accurate, thereby improving the accuracy of the judgment result.

[0072] Optionally, in order to ensure the accuracy of the real-time network link packet loss parameter judgment, the step of judging whether the network link packet loss parameter is within the range corresponding to the baseline of the network parameter is as follows: Figure 5 As shown, including:

[0073] Step 501: The terminal obtains the time when the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

[0074] If any one of the real-time application response time parameter, the real-time application success rate parameter and the real-time application traffic parameter exceeds the range of the corresponding baseline, the time when any one of the real-time application parameters exceeds the range corresponding to the baseline of the application parameter is obtained.

[0075] Step 502: The terminal determines whether the real-time network link packet loss parameter within a preset time range before and after the time is within the range corresponding to the baseline of the network parameter.

[0076] When judging whether the real-time network link packet loss parameter is within the range corresponding to the baseline of the network parameter, the time series data of the real-time network link packet loss parameter within the preset time range before and after the above-mentioned time point is obtained according to the above-mentioned acquired time point, and optionally, the time when the above-mentioned real-time application parameter exceeds the range corresponding to the baseline of the application parameter is recorded as T2, and the preset time can be 5 minutes, that is, judging whether the time series data of the network link packet loss parameter within the time period of T2-5 to T2+5 is within the range corresponding to the baseline of the network parameter at the corresponding time. Among them, the preset time can be set.

[0077] In the above embodiment, by obtaining the time period when the application parameters are abnormal, and then judging whether the time series data of the network parameters before and after the abnormal time period are within the range corresponding to the baseline, the judgment result is more accurate because the abnormal time is clearer.

[0078] In the examples of this application, please refer to Figure 6 , which shows a flow chart of a method for troubleshooting a service anomaly provided in an embodiment of the present application, the method for troubleshooting a service anomaly includes the following steps:

[0079] Step 601: The terminal inputs the historical application parameters and historical network parameters of the target application in the previous period of the current period into a prophet model to obtain the corresponding application parameter baseline and network parameter baseline.

[0080] Step 602: The terminal obtains a baseline of the target application corresponding to the current time period.

[0081] Step 603: The terminal determines whether the real-time application response time parameter, the real-time application success rate parameter, and the real-time application flow parameter are all within the range corresponding to the baseline of the application parameter.

[0082] Step 604: If yes, it is determined that there is no abnormality in the wide area network.

[0083] Step 605: If not, the terminal obtains the time when the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

[0084] Step 606: The terminal determines whether the real-time network link packet loss parameter within a preset time range before and after the time is within the range corresponding to the baseline of the network parameter.

[0085] Step 607: If yes, it is determined that there is no abnormality in the wide area network.

[0086] Step 608: If not, it is determined that there is an abnormality in the wide area network.

[0087] In order to facilitate readers to understand the technical solution provided by the embodiment of the present application, the overall process of the service anomaly troubleshooting method of the present application is illustrated below. Figure 7 .

[0088] First, obtain the historical network link packet loss data, application response time, application success rate, and application traffic time series data, input the prophet model for prediction, and obtain the network link packet loss baseline, application response time baseline, application success rate baseline, and application traffic baseline for the current period. For example, if the data is iteratively predicted with a cycle of one week, at 0:00 on June 27, the data from June 20 0:00 to June 27 0:00 is input into the prophet model. Prophet is trained based on the data of this week and predicts the baseline of the next cycle, that is, the baseline of the next cycle from June 27 0:00 to July 40:00, which is the upper and lower limits calculated by the prophet model.

[0089] Then obtain the real-time network link packet loss data, application response time, application success rate and application traffic time series data of the current time period, such as 6.30 15:09-6.30 16:09, and determine whether the real-time application response time is within the range corresponding to the baseline of the application response time of the above-predicted time period. If yes, continue to determine whether the real-time application success rate is within the range corresponding to the application success rate baseline of the above-predicted time period. If no, determine whether the real-time network link packet loss data is within the range corresponding to the network link packet loss baseline of the above-predicted time period. Determine whether the real-time application success rate is within the range corresponding to the application success rate baseline. If yes, determine whether the real-time application traffic is within the range corresponding to the application traffic baseline. If no, determine whether the real-time network link packet loss data is within the range corresponding to the network link packet loss baseline. Determine whether the real-time application traffic is within the range corresponding to the application traffic baseline. If yes, it means that the wide area network has no abnormality at this time and no attention is needed, that is, the business abnormality is not affected by the wide area network abnormality. If no, determine whether the real-time network link packet loss data is within the range corresponding to the network link packet loss baseline. Determine whether the real-time network link packet loss data is within the range corresponding to the network link packet loss baseline. If yes, it means that the WAN is not abnormal at this time and no attention is needed, that is, the business abnormality is not affected by the WAN abnormality. If no, it means that the WAN is abnormal at this time and the business abnormality may be affected by the WAN abnormality.

[0090] Optionally, at 0:00 on June 28, use the data from 0:00 on June 21 to 0:00 on June 28 to make a prediction, and repeat the process in sequence.

[0091] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0092] Based on the same inventive concept, the embodiment of the present application also provides a service anomaly troubleshooting device for implementing the service anomaly troubleshooting method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more service anomaly troubleshooting device embodiments provided below can refer to the limitations of the service anomaly troubleshooting method above, and will not be repeated here.

[0093] In one embodiment, Figure 8 As shown, a service anomaly troubleshooting device 800 is provided, comprising: a first acquisition module 801, a second acquisition module 802 and a determination module 803, wherein:

[0094] The first acquisition module 801 is used to acquire the baseline of the target application corresponding to the current period, the baseline includes the baseline of the application parameters and the baseline of the network parameters, the application parameters are used to characterize the operation status of the target application, the network parameters are used to characterize the interaction status between the target application and the wide area network, and the baseline is predicted based on the application parameters and the historical network parameters of the target application in the previous period of the current period;

[0095] The second acquisition module 802 is used to acquire real-time parameters of the target application, where the real-time parameters include real-time application parameters and real-time network parameters;

[0096] The determination module 803 is used to determine whether there is an abnormality in the wide area network according to whether the real-time parameter is within the range corresponding to the baseline.

[0097] In one embodiment of the present application, the application parameters include application response time parameters, application success rate parameters and application traffic parameters, and the network parameters include network link packet loss parameters.

[0098] In one embodiment of the present application, the determination module 803 is specifically used to determine whether the real-time application parameters are within the range corresponding to the baseline of the application parameters; if so, it is determined that there is no abnormality in the wide area network; if not, it is determined whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters.

[0099] In one embodiment of the present application, the determination module 803 is specifically used to determine whether the real-time network parameters are within the range corresponding to the baseline of the network parameters; if so, it is determined that there is no abnormality in the wide area network; if not, it is determined that there is an abnormality in the wide area network.

[0100] In one embodiment of the present application, the determination module 803 is specifically used to determine whether the real-time application response time parameter, the real-time application success rate parameter and the real-time application traffic parameter are all within the range corresponding to the baseline of the application parameter; if so, it is determined that the real-time application parameter is within the range corresponding to the baseline of the application parameter; if not, it is determined that the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

[0101] In one embodiment of the present application, the device also includes a prediction module, which is used to input the historical application parameters and historical network parameters of the target application in the previous period of the current period into a prophet model to obtain the corresponding application parameter baseline and network parameter baseline.

[0102] In one embodiment of the present application, the determination module 803 is specifically used to obtain the time when the real-time application parameters are not within the range corresponding to the baseline of the application parameters; and determine whether the real-time network link packet loss parameters within a preset time range before and after the time are within the range corresponding to the baseline of the network parameters.

[0103] Each module in the above-mentioned business anomaly troubleshooting device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0104] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for troubleshooting business anomalies is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse, etc.

[0105] Those skilled in the art will understand that Fig. 9The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0106] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0107] Obtain the baseline of the target application corresponding to the current time period, the baseline includes the baseline of application parameters and the baseline of network parameters, the application parameters are used to characterize the running status of the target application, the network parameters are used to characterize the interaction status between the target application and the wide area network, the baseline is predicted based on the historical application parameters and historical network parameters of the target application in the previous time period of the current time period; obtain the real-time parameters of the target application, the real-time parameters include real-time application parameters and real-time network parameters; determine whether there is an abnormality in the wide area network based on whether the real-time parameters are within the range corresponding to the baseline.

[0108] In one embodiment, when the processor executes the computer program, the following steps are also implemented: the application parameters include application response time parameters, application success rate parameters and application traffic parameters, and the network parameters include network link packet loss parameters.

[0109] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining whether there is an abnormality in the wide area network based on whether the real-time parameters are within the range corresponding to the baseline, including: determining whether the real-time application parameters are within the range corresponding to the baseline of the application parameters; if so, determining that there is no abnormality in the wide area network; if not, determining whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters.

[0110] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters, including: judging whether the real-time network parameters are within the range corresponding to the baseline of the network parameters; if so, determining that there is no abnormality in the wide area network; if not, determining that there is an abnormality in the wide area network.

[0111] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining whether the real-time application parameters are within the range corresponding to the baseline of the application parameters, including: determining whether the real-time application response time parameter, the real-time application success rate parameter and the real-time application traffic parameter are all within the range corresponding to the baseline of the application parameters; if so, determining that the real-time application parameters are within the range corresponding to the baseline of the application parameters; if not, determining that the real-time application parameters are not within the range corresponding to the baseline of the application parameters.

[0112] In one embodiment, when the processor executes the computer program, the following steps are also implemented: before obtaining the baseline of the target application corresponding to the current time period, the method also includes: inputting the historical application parameters and historical network parameters of the target application in the previous time period of the current time period into the prophet model to obtain the corresponding application parameter baseline and network parameter baseline.

[0113] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining whether the real-time network link packet loss parameter is within the range corresponding to the baseline of the network parameter, including: obtaining the time when the real-time application parameter is not within the range corresponding to the baseline of the application parameter; determining whether the real-time network link packet loss parameter within a preset time range before and after the time is within the range corresponding to the baseline of the network parameter.

[0114] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0115] Obtain the baseline of the target application corresponding to the current time period, the baseline includes the baseline of application parameters and the baseline of network parameters, the application parameters are used to characterize the running status of the target application, the network parameters are used to characterize the interaction status between the target application and the wide area network, the baseline is predicted based on the historical application parameters and historical network parameters of the target application in the previous time period of the current time period; obtain the real-time parameters of the target application, the real-time parameters include real-time application parameters and real-time network parameters; determine whether there is an abnormality in the wide area network based on whether the real-time parameters are within the range corresponding to the baseline.

[0116] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: the application parameters include application response time parameters, application success rate parameters and application traffic parameters, and the network parameters include network link packet loss parameters.

[0117] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining whether there is an abnormality in the wide area network based on whether the real-time parameters are within the range corresponding to the baseline, including: determining whether the real-time application parameters are within the range corresponding to the baseline of the application parameters; if so, determining that there is no abnormality in the wide area network; if not, determining whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters.

[0118] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters, including: judging whether the real-time network parameters are within the range corresponding to the baseline of the network parameters; if so, determining that there is no abnormality in the wide area network; if not, determining that there is an abnormality in the wide area network.

[0119] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining whether the real-time application parameters are within the range corresponding to the baseline of the application parameters, including: determining whether the real-time application response time parameter, the real-time application success rate parameter and the real-time application traffic parameter are all within the range corresponding to the baseline of the application parameters; if so, determining that the real-time application parameters are within the range corresponding to the baseline of the application parameters; if not, determining that the real-time application parameters are not within the range corresponding to the baseline of the application parameters.

[0120] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: before obtaining the baseline of the target application corresponding to the current time period, the method also includes: inputting the historical application parameters and historical network parameters of the target application in the previous time period of the current time period into the prophet model to obtain the corresponding application parameter baseline and network parameter baseline.

[0121] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining whether the real-time network link packet loss parameters are within the range corresponding to the baseline of the network parameters, including: obtaining the time when the real-time application parameters are not within the range corresponding to the baseline of the application parameters; determining whether the real-time network link packet loss parameters within a preset time range before and after the time are within the range corresponding to the baseline of the network parameters.

[0122] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0123] Obtain the baseline of the target application corresponding to the current time period, the baseline includes the baseline of application parameters and the baseline of network parameters, the application parameters are used to characterize the running status of the target application, the network parameters are used to characterize the interaction status between the target application and the wide area network, the baseline is predicted based on the historical application parameters and historical network parameters of the target application in the previous time period of the current time period; obtain the real-time parameters of the target application, the real-time parameters include real-time application parameters and real-time network parameters; determine whether there is an abnormality in the wide area network based on whether the real-time parameters are within the range corresponding to the baseline.

[0124] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: the application parameters include application response time parameters, application success rate parameters and application traffic parameters, and the network parameters include network link packet loss parameters.

[0125] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining whether there is an abnormality in the wide area network based on whether the real-time parameters are within the range corresponding to the baseline, including: determining whether the real-time application parameters are within the range corresponding to the baseline of the application parameters; if so, determining that there is no abnormality in the wide area network; if not, determining whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters.

[0126] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining whether there is an abnormality in the wide area network based on whether the real-time network parameters are within the range corresponding to the baseline of the network parameters, including: judging whether the real-time network parameters are within the range corresponding to the baseline of the network parameters; if so, determining that there is no abnormality in the wide area network; if not, determining that there is an abnormality in the wide area network.

[0127] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining whether the real-time application parameters are within the range corresponding to the baseline of the application parameters, including: determining whether the real-time application response time parameter, the real-time application success rate parameter and the real-time application traffic parameter are all within the range corresponding to the baseline of the application parameters; if so, determining that the real-time application parameters are within the range corresponding to the baseline of the application parameters; if not, determining that the real-time application parameters are not within the range corresponding to the baseline of the application parameters.

[0128] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: before obtaining the baseline of the target application corresponding to the current time period, the method also includes: inputting the historical application parameters and historical network parameters of the target application in the previous time period of the current time period into the prophet model to obtain the corresponding application parameter baseline and network parameter baseline.

[0129] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining whether the real-time network link packet loss parameters are within the range corresponding to the baseline of the network parameters, including: obtaining the time when the real-time application parameters are not within the range corresponding to the baseline of the application parameters; determining whether the real-time network link packet loss parameters within a preset time range before and after the time are within the range corresponding to the baseline of the network parameters.

[0130] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0131] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0132] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0133] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for troubleshooting business anomalies, characterized in that: The method comprises: Obtaining a baseline of a target application corresponding to a current period, the baseline including a baseline of application parameters and a baseline of network parameters, the application parameters being used to characterize the running status of the target application, the network parameters being used to characterize the interaction status between the target application and a wide area network, the baseline being predicted based on the historical application parameters and historical network parameters of the target application in a period before the current period; the application parameters including application response time parameters, application success rate parameters, and application traffic parameters, and the network parameters including network link packet loss parameters; Acquire real-time parameters of the target application, wherein the real-time parameters include real-time application parameters and real-time network parameters; Determining whether the wide area network is abnormal according to whether the real-time parameter is within a range corresponding to the baseline; The determining whether the wide area network is abnormal according to whether the real-time parameter is within the range corresponding to the baseline includes: determining whether the real-time application parameter is within a range corresponding to a baseline of the application parameter; If yes, it is determined that there is no abnormality in the wide area network; If not, determining whether the wide area network has an abnormality according to whether the real-time network parameter is within the range corresponding to the baseline of the network parameter; The determining whether the wide area network is abnormal according to whether the real-time network parameter is within a range corresponding to the baseline of the network parameter includes: Determining whether the real-time network parameter is within a range corresponding to a baseline of the network parameter; If yes, it is determined that there is no abnormality in the wide area network; If not, it is determined that there is an abnormality in the wide area network; Determining whether the real-time network parameter is within a range corresponding to the baseline of the network parameter includes: Acquire the time when the real-time application parameter is not within the range corresponding to the baseline of the application parameter; It is determined whether the real-time network link packet loss parameter within a preset time range before and after the time is within a range corresponding to the baseline of the network parameter.

2. The method according to claim 1, characterized in that The determining whether the real-time application parameter is within a range corresponding to the baseline of the application parameter includes: Determining whether a real-time application response time parameter, a real-time application success rate parameter, and a real-time application flow parameter are all within a range corresponding to a baseline of the application parameter; If so, determining that the real-time application parameter is within a range corresponding to the baseline of the application parameter; If not, it is determined that the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

3. The method according to any one of claims 1 to 2, characterized in that: Before obtaining the baseline of the target application corresponding to the current period, the method further includes: The historical application parameters and historical network parameters of the target application in the previous period of the current period are input into a prophet model to obtain the corresponding baselines of the application parameters and the network parameters.

4. A device for troubleshooting business anomalies, characterized in that: The device comprises: A first acquisition module is used to acquire a baseline of a target application corresponding to a current period, wherein the baseline includes a baseline of application parameters and a baseline of network parameters, wherein the application parameters are used to characterize the operation status of the target application, and the network parameters are used to characterize the interaction status between the target application and a wide area network, and wherein the baseline is predicted based on the application parameters and network parameters of the target application history in the previous period of the current period; the application parameters include application response time parameters, application success rate parameters, and application traffic parameters, and the network parameters include network link packet loss parameters; A second acquisition module, used to acquire real-time parameters of the target application, wherein the real-time parameters include real-time application parameters and real-time network parameters; A determination module, configured to determine whether the wide area network has an abnormality according to whether the real-time parameter is within a range corresponding to the baseline; The determination module is specifically used to determine whether the real-time application parameter is within the range corresponding to the baseline of the application parameter; if so, determine whether there is no abnormality in the wide area network; if not, determine whether there is an abnormality in the wide area network according to whether the real-time network parameter is within the range corresponding to the baseline of the network parameter; The determination module is specifically used to determine whether the real-time network parameter is within the range corresponding to the baseline of the network parameter; if so, determine that there is no abnormality in the wide area network; if not, determine that there is an abnormality in the wide area network; The determination module is specifically used to obtain the time when the real-time application parameter is not within the range corresponding to the baseline of the application parameter; and determine whether the real-time network link packet loss parameter within a preset time range before and after the time is within the range corresponding to the baseline of the network parameter.

5. The device according to claim 4, characterized in that The determination module is specifically used to determine whether the real-time application response time parameter, the real-time application success rate parameter and the real-time application traffic parameter are all within the range corresponding to the baseline of the application parameter; if so, it is determined that the real-time application parameter is within the range corresponding to the baseline of the application parameter; if not, it is determined that the real-time application parameter is not within the range corresponding to the baseline of the application parameter.

6. The device according to claim 4, characterized in that The device also includes: The prediction module is used to input the historical application parameters and historical network parameters of the target application in the previous period of the current period into the prophet model to obtain the corresponding baseline of the application parameters and the baseline of the network parameters.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 3 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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