Service exception analysis method and device, equipment and storage medium

Abstract

The application relates to the technical field of Internet, and discloses a service exception analysis method, device, equipment and storage medium. The method comprises the following steps: obtaining first access information generated by a test user based on an official version for interface access; obtaining second access information generated by the test user based on a gray version for interface access; identifying a service exception category of the first access information and the second access information, judging whether the second access information is added with a service exception category relative to the first access information; if yes, determining a test user corresponding to the added service exception category as a first target user, and obtaining third access information generated by the first target user based on the official version for interface access; and comparing and analyzing the third access information with the first access information and the second access information respectively to obtain a service exception analysis result. Through the above method, the accuracy and efficiency of the exception analysis can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a service anomaly analysis method, device, equipment and storage medium. Background Art

[0002] Most of the existing service anomaly analysis is based on computer analysis of exception logs, or exception reporting by the user side. For systems used by a large number of users, if service anomalies occur in large quantities and cannot be discovered in time, reporting by the user side will result in poor real-time problem solving and affect user experience. Therefore, most systems will set up a grayscale strategy to solve the problem of version release. Before the regular version update is released to the official environment, a grayscale pilot will be carried out to observe the abnormal situation of grayscale users using the system. However, the exception log analysis of a single operating environment cannot effectively analyze whether the anomaly is caused by the version release. Summary of the Invention

[0003] The present invention provides a service anomaly analysis method, device, equipment and storage medium, which can effectively improve the accuracy and efficiency of anomaly analysis.

[0004] To solve the above technical problems, the present invention adopts a technical solution: providing a service anomaly analysis method, comprising:

[0005] After the official version of the software is released, the test user is switched to the official version, and first access information generated by the test user accessing an interface based on the official version is obtained;

[0006] After the grayscale version of the software is released, switching the test user to the grayscale version, and obtaining second access information generated by the test user accessing an interface based on the grayscale version;

[0007] identifying service exception categories of the first access information and the second access information, and determining whether the second access information has a new service exception category compared to the first access information;

[0008] If yes, determine the test user corresponding to the newly added service exception category as the first target user, switch the first target user back to the official version, and obtain third access information generated by the first target user accessing the interface based on the official version;

[0009] The third access information is compared and analyzed with the first access information and the second access information respectively to obtain a service anomaly analysis result.

[0010] According to an embodiment of the present invention, comparing and analyzing the third access information with the first access information and the second access information to obtain a service anomaly analysis result further includes:

[0011] identifying a service exception category of the third access information;

[0012] comparing the service exception category of the third access information with the service exception category of the first access information to determine whether the service exception category of the third access information is the same as the service exception category of the first access information;

[0013] If so, the cause of the service anomaly is determined to be a release issue.

[0014] According to an embodiment of the present invention, comparing and analyzing the third access information with the first access information and the second access information to obtain a service anomaly analysis result further includes:

[0015] comparing the service exception category of the third access information with the service exception category of the second access information to determine whether the service exception category of the third access information is the same as the service exception category of the second access information;

[0016] If so, the cause of the service anomaly is determined to be a non-release issue.

[0017] According to an embodiment of the present invention, after determining whether the second access information has a new service exception category compared to the first access information, the method further includes:

[0018] If not, calculating a first service anomaly ratio according to the service anomaly category of the first access information, and calculating a second service anomaly ratio according to the service anomaly category of the second access information;

[0019] Determine a second target user based on the second service anomaly ratio and the first service anomaly ratio, switch the second target user back to the official version, and obtain fourth access information generated by the second target user accessing an interface based on the official version;

[0020] Identifying a service anomaly category of the fourth access information and calculating a third service anomaly ratio based on the identification result;

[0021] The third service anomaly ratio is compared and analyzed with the first service anomaly ratio and the second service anomaly ratio respectively to obtain a service anomaly analysis result.

[0022] According to an embodiment of the present invention, determining the second target user according to the second service anomaly ratio and the first service anomaly ratio includes:

[0023] Calculating a first difference between the second service anomaly ratio and the first service anomaly ratio;

[0024] Comparing the first difference with a first preset threshold to determine whether the first difference is greater than the first preset threshold;

[0025] If so, the test user corresponding to the service exception category in the second access information is determined as the second target user.

[0026] According to one embodiment of the present invention, comparing and analyzing the third service anomaly ratio with the first service anomaly ratio and the second service anomaly ratio to obtain a service anomaly analysis result includes:

[0027] Calculating a second difference between the third service anomaly ratio and the second service anomaly ratio;

[0028] Comparing the second difference with a second preset threshold to determine whether the second difference is less than the second preset threshold;

[0029] If so, the cause of the service anomaly is determined to be a non-release issue.

[0030] According to one embodiment of the present invention, after comparing the second difference with a second preset threshold and determining whether the second difference is less than the second preset threshold, the method further includes:

[0031] If not, calculating a third difference between the third service anomaly ratio and the first service anomaly ratio;

[0032] Comparing the third difference with a third preset threshold to determine whether the third difference is less than the third preset threshold;

[0033] If so, the cause of the service anomaly is determined to be a release issue.

[0034] To solve the above technical problems, another technical solution adopted by the present invention is to provide a service anomaly analysis device, comprising:

[0035] A first acquisition module is configured to, after the official version of the software is released, switch the test user to the official version and obtain first access information generated by the test user accessing an interface based on the official version;

[0036] A second acquisition module is configured to, after the grayscale version of the software is released, switch the test user to the grayscale version and obtain second access information generated by the test user accessing an interface based on the grayscale version;

[0037] an identification and judgment module, configured to identify the service anomaly categories of the first access information and the second access information, and to judge whether the second access information has a new service anomaly category compared to the first access information;

[0038] a third acquisition module, configured to, if yes, determine the test user corresponding to the newly added service exception category as the first target user, switch the first target user back to the official version, and obtain third access information generated by the first target user accessing the interface based on the official version;

[0039] The comparison and analysis module is used to compare and analyze the third access information with the first access information and the second access information respectively to obtain a service anomaly analysis result.

[0040] To solve the above technical problems, another technical solution adopted by the present invention is: providing a computer device, including: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the service anomaly analysis method when executing the computer program.

[0041] In order to solve the above technical problems, another technical solution adopted by the present invention is: providing a computer storage medium on which a computer program is stored, and the computer program implements the above service anomaly analysis method when executed by a processor.

[0042] The beneficial effects of the present invention are as follows: by obtaining the first access information of the official version and the second access information of the grayscale version, and analyzing the abnormal data based on the first access information and the second access information, the test user who generated the abnormal data is switched back to the official version for access and obtains the third access information, and the service abnormality analysis is performed according to the third access information, the second access information and the first access information. The service abnormalities generated by the same group of test users in different operating environments can be analyzed, and at the same time, the abnormalities that occur before and after the same service in the same operating environment can be analyzed. Compared with the abnormal log analysis of a single environment or the abnormality analysis reported by the user, the accuracy and efficiency of the abnormality analysis are effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 1 is a flow chart of a service anomaly analysis method according to a first embodiment of the present invention;

[0044] Figure 2 2 is a flow chart of a service anomaly analysis method according to a second embodiment of the present invention;

[0045] Figure 3 Schematic diagram of the structure of a service anomaly analysis device according to an embodiment of the present invention;

[0046] Figure 4is a schematic structural diagram of a computer device according to an embodiment of the present invention;

[0047] Figure 5 It is a schematic diagram of the structure of a computer storage medium according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0049] The terms "first", "second" and "third" in the present invention are used only for descriptive purposes and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first", "second" and "third" may explicitly or implicitly include at least one of such features. In the description of the present invention, "multiple" means at least two, for example, two, three, etc., unless otherwise clearly and specifically defined. All directional indications in the embodiments of the present invention (such as up, down, left, right, front, back...) are only used to explain the relative positional relationship, movement, etc. between the components under a specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0050] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0051] Figure 1 It is a flow chart of the service anomaly analysis method of the first embodiment of the present invention. It should be noted that if there is substantially the same result, the method of the present invention is not based on Figure 1 The process sequence shown is limited. Figure 1 As shown, the method includes the steps of:

[0052] Step S101: After the official version of the software is released, the test user is switched to the official version, and first access information generated by the test user accessing the interface based on the official version is obtained.

[0053] In step S101, the selection of test users can cover as many types of roles as possible and the business volume does not fluctuate much, and the selected test users are marked in the configuration of the gateway. After the official version of the software is released, the test user is switched to the official version, the interface access request of the test user is received and the interface access request is executed in the official version, and the first access information is generated and stored in the database. In a feasible implementation, if the interface called by the interface access request is an operation-type interface, such as add, delete, and modify operations, and there is no response result, the first access information includes but is not limited to the interface URL, interface parameters, time consumption, and status code. In other implementations, if the interface called by the interface access request is a query-type interface and there is a response result, the first access information may also include the response result. In this embodiment, when the interface access request is forwarded to the corresponding service component at the gateway, the first access information is recorded in the database.

[0054] Step S102: After the grayscale version of the software is released, the test user is switched to the grayscale version, and second access information generated by the test user accessing the interface based on the grayscale version is obtained.

[0055] In step S102, after the grayscale version of the software is released, the grayscale switch is turned on at the gateway, the test user's traffic is switched to the grayscale version, the test user's interface access request is received and the interface access request is executed in the grayscale version, and the second access information is generated and stored in the database. In a feasible implementation, if the interface called by the interface access request is an operation-type interface, such as add, delete, or modify operations, and there is no response result, the second access information includes but is not limited to the interface URL, interface parameters, time consumption, and status code. In other implementations, if the interface called by the interface access request is a query-type interface and there is a response result, the second access information may also include the response result. In this embodiment, when the interface access request is forwarded to the corresponding service component at the gateway, the second access information is recorded in the database.

[0056] Step S103: Identify the service anomaly categories of the first access information and the second access information, and determine whether the second access information has a new service anomaly category compared to the first access information.

[0057] In step S103, this embodiment identifies the service exception category of the interface access in the official version based on the status code in the first access information, and identifies the service exception category of the interface access in the grayscale version based on the status code in the second access information. The status codes are, for example, 500, 400, 404, and 200, where 500, 400, and 404 indicate service exceptions, that is, the interface access request cannot be processed normally, and 200 indicates normal service, that is, the interface access request is processed normally and returned.

[0058] This embodiment can set up a scheduled job to periodically read access information from the database and perform a comparative analysis of service anomaly categories and anomaly data for the same service component in both the official and phased versions. Generally, for the same group of test users with minimal fluctuations in traffic volume, the service anomaly categories and total number of anomalies will not fluctuate significantly to a certain extent.

[0059] Assume that the status codes in the second access information are 500, 400, and 404, and the status codes in the first access information are 400 and 404. Then, the second access information has a new service exception category: 500. Furthermore, assume that the status codes in the second access information are 400 and 404, and the status codes in the first access information are 500, 400, and 404. Then, the second access information does not have a new service exception category compared to the first access information.

[0060] Step S104: If yes, the test user corresponding to the newly added service exception category is determined as the first target user, the first target user is switched back to the official version, and third access information generated by the first target user accessing the interface based on the official version is obtained.

[0061] In step S104, the third access information is generated when the first target user switches to the official version at time T and accesses the interface based on the official version. The first access information is generated when the test user switches to the official version at time T-1 and accesses the interface based on the official version. The third access information contains similar content to the first and second access information. The first target user is part of the test user group, and time T-1 is after time T.

[0062] Step S105: Compare and analyze the third access information with the first access information and the second access information respectively to obtain a service anomaly analysis result.

[0063] In step S105, this embodiment can set up a scheduled job task to periodically read access information from the database and calculate the service anomaly categories and anomaly data for the same service component in the official version and the phased version. Generally, for the same batch of test users with minimal fluctuation in business volume, the service anomaly categories and total number of anomalies will not change significantly to a certain extent.

[0064] In a feasible implementation, the service exception category of the third access information is identified; the service exception category of the third access information is compared with the service exception category of the first access information to determine whether the service exception category of the third access information is the same as the service exception category of the first access information; if so, the cause of the service exception is determined to be a version issue. The version issue may be that there is a problem with the gray version, while the official version is normal. After determining that the cause of the service exception is a version issue, the service exception category, the service exception cause, and the corresponding service component can be encapsulated into a message body and asynchronously pushed to the message queue for exception reporting. This embodiment analyzes the exceptions that occur before and after the same service in the same operating environment, and can determine whether the service exception is caused by a version issue, effectively improving the accuracy and efficiency of exception analysis.

[0065] In another feasible implementation, the service exception category of the third access information is identified; the service exception category of the third access information is compared with the service exception category of the second access information to determine whether the service exception category of the third access information is the same as the service exception category of the second access information; if so, the cause of the service exception is determined to be a non-release problem. The non-release problem may be a problem with an associated party. After determining that the cause of the service exception is a non-release problem, the service exception category, the service exception cause, and the corresponding service component can be encapsulated into a message body and asynchronously pushed to the message queue for exception reporting. This embodiment analyzes the service exceptions generated by the same batch of test users in different operating environments, and can determine whether the service exception is caused by a release problem, effectively improving the accuracy and efficiency of the exception analysis.

[0066] The service anomaly analysis method of the first embodiment of the present invention obtains the first access information of the official version and the second access information of the grayscale version, analyzes the abnormal data based on the first access information and the second access information, switches the test user who generated the abnormal data back to the official version for access and obtains the third access information, and performs service anomaly analysis based on the third access information, the second access information and the first access information. It can analyze the service anomalies generated by the same group of test users in different operating environments, and can also analyze the anomalies of the same service that occur before and after in the same operating environment. Compared with the abnormal log analysis of a single environment or the user-reported anomaly analysis, it effectively improves the accuracy and efficiency of the anomaly analysis.

[0067] Figure 2 It is a flow chart of the service anomaly analysis method of the second embodiment of the present invention. It should be noted that if there is substantially the same result, the method of the present invention does not Figure 2 The process sequence shown is limited. Figure 2 As shown, the method includes the steps of:

[0068] Step S201: After the official version of the software is released, the test user is switched to the official version, and first access information generated by the test user accessing the interface based on the official version is obtained.

[0069] In this embodiment, Figure 2 Step S201 and Figure 1 The process is similar to step S101 in , and for the sake of simplicity, it will not be repeated here.

[0070] Step S202: After the grayscale version of the software is released, the test user is switched to the grayscale version, and second access information generated by the test user accessing the interface based on the grayscale version is obtained.

[0071] In this embodiment, Figure 2 Step S202 and Figure 1 The process is similar to step S102 in , and for the sake of simplicity, it will not be repeated here.

[0072] Step S203: Identify the service anomaly categories of the first access information and the second access information, and determine whether the second access information has a new service anomaly category compared to the first access information.

[0073] In this embodiment, Figure 2 Step S203 and Figure 1 In step S203, if yes, then execute steps S204-S205; if no, then execute steps S206-S209.

[0074] Step S204: If yes, the test user corresponding to the newly added service exception category is determined as the first target user, the first target user is switched back to the official version, and third access information generated by the first target user accessing the interface based on the official version is obtained.

[0075] In this embodiment, Figure 2 Step S204 and Figure 1 The process is similar to step S104 in the embodiment and will not be described again for the sake of brevity.

[0076] Step S205: Compare and analyze the third access information with the first access information and the second access information respectively to obtain a service anomaly analysis result.

[0077] In this embodiment, Figure 2 Step S205 and Figure 1 The process is similar to step S105 in , and for the sake of brevity, it will not be repeated here.

[0078] Step S206: If not, calculate a first service anomaly ratio according to the service anomaly category of the first access information, and calculate a second service anomaly ratio according to the service anomaly category of the second access information.

[0079] In step S206, after step S203, if the second access information does not include any new service anomaly categories compared to the first access information, the first service anomaly ratio and the second service anomaly ratio are calculated. The first service anomaly ratio is the ratio of the number of abnormal status codes in the first access information to the total number of status codes, and the second service anomaly ratio is the ratio of the number of abnormal status codes in the second access information to the total number of status codes.

[0080] Step S207: Determine the second target user based on the second service anomaly ratio and the first service anomaly ratio, switch the second target user back to the official version, and obtain fourth access information generated by the second target user accessing the interface based on the official version.

[0081] In step S207, a first difference between the second service anomaly ratio and the first service anomaly ratio is calculated; the first difference is compared with a first preset threshold to determine whether the first difference is greater than the first preset threshold; if so, the test user corresponding to the service anomaly category in the second access information is determined as the second target user. In this embodiment, if the first difference is greater than the first preset threshold, it indicates that the abnormal data fluctuates significantly.

[0082] The first preset threshold can be set by the user or automatically by the computer. The fourth access information is generated when the second target user switches to the official version at time T and accesses the interface based on the official version. The first access information is generated when the test user switches to the official version at time T-1 and accesses the interface based on the official version. The content included in the fourth access information is similar to the first access information, the second access information, and the third access information. The second target user is part of the test user, and time T is after time T-1.

[0083] Step S208: Identify the service anomaly category of the fourth access information and calculate the third service anomaly ratio according to the identification result.

[0084] In step S208, this embodiment can set a JOB scheduled task to regularly read the access information in the database and calculate the service anomaly categories and anomaly data for the same service component in the official version and the gray version for comparative analysis. Generally speaking, for the same batch of test users with little fluctuation in business volume, the service anomaly classification and total number of anomalies will not change significantly to a certain extent. The third service anomaly ratio is the ratio between the number of abnormal status codes in the fourth access information and the total number of status codes.

[0085] Step S209: Compare and analyze the third service anomaly ratio with the first service anomaly ratio and the second service anomaly ratio to obtain a service anomaly analysis result.

[0086] In step S209, the second difference between the third service anomaly ratio and the second service anomaly ratio is calculated; the second difference is compared with the second preset threshold to determine whether the second difference is less than the second preset threshold; if so, the cause of the service anomaly is determined to be a non-release issue. If not, the third difference between the third service anomaly ratio and the first service anomaly ratio is calculated; the third difference is compared with the third preset threshold to determine whether the third difference is less than the third preset threshold; if so, the cause of the service anomaly is determined to be a release issue. The second preset threshold and the third preset threshold of this embodiment may be the same or different. After determining the cause of the service anomaly, the service anomaly category, the cause of the service anomaly, and the corresponding service component may be encapsulated into a message body and asynchronously pushed to the message queue for anomaly reporting.

[0087] The service anomaly analysis method of the second embodiment of the present invention is based on the first embodiment and determines the cause of the service anomaly by the fluctuation of abnormal data, thereby further improving the accuracy and efficiency of the anomaly analysis.

[0088] Figure 3 FIG is a schematic diagram of the structure of the service anomaly analysis device according to an embodiment of the present invention. Figure 3 As shown, the device 30 includes a first acquisition module 31 , a second acquisition module 32 , an identification and judgment module 33 , a third acquisition module 34 and a comparison and analysis module 35 .

[0089] The first acquisition module 31 is used to switch the test user to the official version after the official version of the software is released, and obtain the first access information generated by the test user accessing the interface based on the official version;

[0090] The second acquisition module 32 is used to switch the test user to the grayscale version after the grayscale version of the software is released, and obtain the second access information generated by the test user accessing the interface based on the grayscale version;

[0091] The identification and judgment module 33 is used to identify the service anomaly categories of the first access information and the second access information, and to judge whether the second access information has a new service anomaly category compared with the first access information;

[0092] The third acquisition module 34 is configured to, if yes, determine the test user corresponding to the newly added service exception category as the first target user, switch the first target user back to the official version, and obtain third access information generated by the first target user accessing the interface based on the official version;

[0093] The comparison and analysis module 35 is used to compare and analyze the third access information with the first access information and the second access information respectively to obtain a service anomaly analysis result.

[0094] See also Figure 4 , Figure 4 FIG. 1 is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Figure 4 As shown, the computer device 40 includes a processor 41 and a memory 42 coupled to the processor 41 .

[0095] The memory 42 stores program instructions for implementing the service anomaly analysis method described in any one of the above embodiments.

[0096] The processor 41 is configured to execute program instructions stored in the memory 42 to analyze the cause of the service abnormality.

[0097] The processor 41 may also be referred to as a CPU (Central Processing Unit). The processor 41 may be an integrated circuit chip having signal processing capabilities. The processor 41 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. The general-purpose processor may be a microprocessor or any conventional processor.

[0098] See Figure 5 , Figure 5Schematic diagram of the structure of the computer storage medium of the embodiment of the present invention. The computer storage medium of the embodiment of the present invention stores a program file 51 that can implement all the above methods, wherein the program file 51 can be stored in the above computer storage medium in the form of a software product, including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned computer storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0099] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0100] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0101] The above are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A service anomaly analysis method, characterized in that: include: After the official version of the software is released, the test user is switched to the official version, and first access information generated by the test user accessing an interface based on the official version is obtained; After the grayscale version of the software is released, switching the test user to the grayscale version, and obtaining second access information generated by the test user accessing an interface based on the grayscale version; identifying service exception categories of the first access information and the second access information, and determining whether the second access information has a new service exception category compared to the first access information; If yes, determine the test user corresponding to the newly added service exception category as the first target user, switch the first target user back to the official version, and obtain third access information generated by the first target user accessing the interface based on the official version; Comparing and analyzing the third access information with the first access information and the second access information to obtain a service anomaly analysis result, further comprising: identifying a service exception category of the third access information; Comparing the service exception category of the third access information with the service exception category of the first access information to determine whether the service exception category of the third access information is the same as the service exception category of the first access information; if so, determining that the cause of the service exception is a release issue; Compare the service exception category of the third access information with the service exception category of the second access information to determine whether the service exception category of the third access information is the same as the service exception category of the second access information; if so, determine that the cause of the service exception is a non-release problem.

2. The service anomaly analysis method according to claim 1, characterized in that: After determining whether the second access information has a new service exception category compared to the first access information, the method further includes: If not, calculating a first service anomaly ratio according to the service anomaly category of the first access information, and calculating a second service anomaly ratio according to the service anomaly category of the second access information; Determine a second target user based on the second service anomaly ratio and the first service anomaly ratio, switch the second target user back to the official version, and obtain fourth access information generated by the second target user accessing an interface based on the official version; Identifying a service anomaly category of the fourth access information and calculating a third service anomaly ratio based on the identification result; The third service anomaly ratio is compared and analyzed with the first service anomaly ratio and the second service anomaly ratio respectively to obtain a service anomaly analysis result.

3. The service anomaly analysis method according to claim 2, characterized in that: The determining the second target user according to the second service anomaly ratio and the first service anomaly ratio includes: Calculating a first difference between the second service anomaly ratio and the first service anomaly ratio; Comparing the first difference with a first preset threshold to determine whether the first difference is greater than the first preset threshold; If so, the test user corresponding to the service exception category in the second access information is determined as the second target user.

4. The service anomaly analysis method according to claim 2, characterized in that: Comparing and analyzing the third service anomaly ratio with the first service anomaly ratio and the second service anomaly ratio to obtain a service anomaly analysis result includes: Calculating a second difference between the third service anomaly ratio and the second service anomaly ratio; Comparing the second difference with a second preset threshold to determine whether the second difference is less than the second preset threshold; If so, the cause of the service anomaly is determined to be a non-release issue.

5. The service anomaly analysis method according to claim 4, characterized in that: After comparing the second difference with a second preset threshold and determining whether the second difference is less than the second preset threshold, the method further includes: If not, calculating a third difference between the third service anomaly ratio and the first service anomaly ratio; Comparing the third difference with a third preset threshold to determine whether the third difference is less than the third preset threshold; If so, the cause of the service anomaly is determined to be a release issue.

6. A service anomaly analysis device, characterized in that: include: A first acquisition module is configured to, after the official version of the software is released, switch the test user to the official version and obtain first access information generated by the test user accessing an interface based on the official version; A second acquisition module is configured to, after the grayscale version of the software is released, switch the test user to the grayscale version and obtain second access information generated by the test user accessing an interface based on the grayscale version; an identification and judgment module, configured to identify the service anomaly categories of the first access information and the second access information, and to judge whether the second access information has a new service anomaly category compared to the first access information; a third acquisition module, configured to, if yes, determine the test user corresponding to the newly added service exception category as the first target user, switch the first target user back to the official version, and obtain third access information generated by the first target user accessing the interface based on the official version; a comparison and analysis module, configured to compare and analyze the third access information with the first access information and the second access information respectively to obtain a service anomaly analysis result, and further comprising: identifying a service anomaly category of the third access information; Compare the service exception category of the third access information with the service exception category of the first access information to determine whether the service exception category of the third access information is the same as the service exception category of the first access information; if so, determine that the cause of the service exception is a version issue; compare the service exception category of the third access information with the service exception category of the second access information to determine whether the service exception category of the third access information is the same as the service exception category of the second access information; if so, determine that the cause of the service exception is not a version issue.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the service anomaly analysis method according to any one of claims 1 to 5 when executing the computer program.

8. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the service anomaly analysis method according to any one of claims 1 to 5 is implemented.

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