User operation track backtracking method and device, equipment and storage medium

Abstract

The invention discloses a user operation track backtracking method and device, equipment and a storage medium. Comprising the steps that user operation data of a service system are obtained, and the user operation data comprise front-end browser data and rear-end application link data; performing data cleaning on the user operation data to generate standard data, and performing data series connection on the standard data to generate series data; and obtaining a query request, and generating a user operation track according to the query request and the serial data. The collected user operation data cover front-end browser data and rear-end application link data, operation information of the user in the whole service process can be comprehensively collected, and a rich and complete data source is provided for subsequent analysis and backtracking. The front-end browser data and the rear-end application link data are connected in series, so that a coherent operation process record can be formed, an operation track of a user can be understood more clearly, full-process business operation response reproduction can be performed, and the fault positioning efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, equipment and storage medium for tracing back user operation traces. Background Art

[0002] In today's digital and information age, various application systems and platforms widely serve people's work, life and entertainment. When users interact with these systems, a large amount of operation behavior and data will be generated. With the increasing complexity of business and the increasing requirements for system security, stability and user experience, it is crucial to understand the user's operation trajectory in the system.

[0003] The existing technology for fault location is to remotely restore the fault by checking with the salesperson, or to go to the site to collect relevant information of the user terminal and then reproduce it. This method is time-consuming and lacks basic information. The processing process is very passive and cannot fully restore the user's operation trajectory, which leads to poor fault location effect. Summary of the invention

[0004] The present invention provides a user operation track backtracing method, device, equipment and storage medium to connect front-end browser data and back-end application link data in series, so as to facilitate business operation track backtracing according to query requests and facilitate data analysis by operation and maintenance personnel.

[0005] According to one aspect of the present invention, a method for tracing back user operation traces is provided, the method comprising:

[0006] Obtaining user operation data of the business system, wherein the user operation data includes front-end browser data and back-end application link data;

[0007] Perform data cleansing on user operation data to generate standard data, and perform data concatenation on the standard data to generate concatenation data;

[0008] Get the query request and generate the user operation track based on the query request and concatenated data.

[0009] Optionally, obtaining user operation data of the business system includes: collecting back-end application link data of the business system through a collection probe; obtaining original browser data of the business system through a load gateway, and sending mirror data of the original browser data to the soft load; intercepting and capturing the mirror data to generate front-end browser data; and using the front-end browser data and back-end application link data as user operation data.

[0010] Optionally, data cleaning is performed on the user operation data to generate standard data, including: determining the data to be cleaned in the user operation data, wherein the data to be cleaned includes non-plaintext data and unstructured data; and converting the data to be cleaned into a specified format to generate standard data, wherein the standard data includes standard front-end data and standard back-end data.

[0011] Optionally, performing data concatenation on standard data to generate concatenation data, including: performing business information concatenation on standard front-end data according to a first designated field to generate first concatenation data, wherein the first concatenation data includes various core fields; associating the first concatenation data and standard back-end data through a second designated field to generate second concatenation data; performing node association on the standard back-end data in the second concatenation data through a third designated field to generate data links, and generating concatenation data according to each data link, wherein the concatenation data includes each data link and its corresponding core fields.

[0012] Optionally, business information of the standard front-end data is concatenated according to the first designated field to generate first concatenated data, including: determining request data and page data in the standard front-end data according to the first designated field; associating the request data and the page data to generate associated data; determining core fields of the associated data through a data printing tool, and aggregating the core fields to generate the first concatenated data.

[0013] Optionally, a user operation trajectory is generated based on the query request and the concatenated data, including: matching each core field in the concatenated data through the query request to determine the target core field corresponding to the query request; using the data link corresponding to the target core field as the target data link; and generating the user operation trajectory based on the target data link.

[0014] Optionally, after generating a user operation trace according to the query request and the concatenated data, the method further includes: performing performance monitoring on the standard data based on a preset cycle and specified monitoring items and determining monitoring results; and generating a performance report according to the monitoring results and the user operation trace.

[0015] According to another aspect of the present invention, a user operation trajectory backtracking device is provided, the device comprising:

[0016] A user operation data acquisition module is used to acquire user operation data of the business system, wherein the user operation data includes front-end browser data and back-end application link data;

[0017] The data cleaning and serial connection module is used to clean the user operation data to generate standard data, and to serialize the standard data to generate serial connection data;

[0018] The user operation track acquisition module is used to obtain the query request and generate the user operation track according to the query request and the concatenated data.

[0019] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0020] at least one processor;

[0021] and a memory communicatively coupled to the at least one processor;

[0022] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute a user operation trajectory backtracking method described in any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a user operation trajectory backtracking method described in any embodiment of the present invention when executed.

[0024] The technical solution of the embodiment of the present invention can comprehensively collect the user's operation information in the entire business process by acquiring the front-end browser data and the back-end application link data, and provide a rich and complete data source for subsequent analysis and backtracking. By performing data cleaning on the user operation data to generate standard data, the noise, errors and inconsistencies in the data are eliminated, the quality and accuracy of the data are improved, and the subsequent processing and analysis are more reliable. By performing data concatenation on the standard data to generate concatenated data, a coherent operation process record can be formed, which helps to more clearly understand the user's operation trajectory, and can reproduce the business operation response of the entire process, thereby improving the efficiency and accuracy of fault location.

[0025] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 is a flowchart of a method for tracing back user operation traces provided according to the first embodiment of the present invention;

[0028] Figure 2 is a flowchart of another method for tracing back user operation traces provided according to the second embodiment of the present invention;

[0029] Figure 3 is a structural schematic diagram of a user operation trajectory backtracking device provided according to Embodiment 3 of the present invention;

[0030] Figure 4 It is a structural schematic diagram of an electronic device for implementing a user operation trajectory backtracking method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] Embodiment 1

[0034] Figure 1 A flowchart of a user operation trace back method is provided for the first embodiment of the present invention. This embodiment is applicable to the case of monitoring and tracing user operation data of a business system. The method can be executed by a user operation trace back device. The user operation trace back device can be implemented in the form of hardware and / or software. The user operation trace back device can be configured in a computer controller. Figure 1 As shown, the method includes:

[0035] S110. Obtain user operation data of the business system, wherein the user operation data includes front-end browser data and back-end application link data.

[0036] Among them, business system refers to a software system designed and developed to meet specific business needs. The business system includes multiple modules and functions for processing business processes, managing data and providing services. User operation data refers to various data generated by users in the process of using business systems. User operation data reflects user behavior and operation habits and can be used to analyze user needs, optimize system performance and improve user experience. Front-end browser data refers to data generated by the browser when the user uses the browser to access the business system. Front-end browser data includes but is not limited to page browsing records, interactive operation records and form filling data. For example, the URL of the page visited by the user, the button clicked, the text entered, etc. Back-end application link data refers to data generated by the application on the back-end server of the business system. Back-end application link data includes but is not limited to request response data, database operation records and business logic processing data. For example, the request parameters received by the server, the response status code returned, the database addition, deletion, modification and query operation records, etc.

[0037] Optionally, obtaining user operation data of the business system includes: collecting back-end application link data of the business system through a collection probe; obtaining original browser data of the business system through a load gateway, and sending mirror data of the original browser data to the soft load; intercepting and capturing the mirror data to generate front-end browser data; and using the front-end browser data and back-end application link data as user operation data.

[0038] Among them, the collection probe can obtain the back-end application link data of the business system by monitoring the server's network interface, application program interface (API) or database connection. The load gateway is deployed at the front end of the business system to distribute client requests to the back-end server and manage the server's load balancing. When the client accesses the business system through a browser, the request first passes through the load gateway. The load gateway can record the original browser data such as the source IP address, target URL, and request time of the request. The load gateway can use network traffic mirroring technology to send the original browser data to the soft load. Network traffic mirroring refers to copying the traffic on one network interface to another network interface without affecting the transmission of the original traffic. Soft load is a software load balancer that can receive mirrored data from the load gateway and process and analyze the data.

[0039] Specifically, the interception and capture of mirror data can be achieved by using network packet analysis tools or proxy servers. The front-end browser data and the back-end application link data respectively reflect the user's operation behavior in different aspects of the business system. By integrating these two types of data, we can have a more comprehensive understanding of the user's operation trajectory and the operation of the business system.

[0040] In a specific implementation, users access the front-end web through the F5 (hard load) gateway, so the browser data is mirrored from the F5 (hard load) and a copy is given to nginx (soft load). The browser data can be intercepted and captured from this data. After the data is captured, it is reported to the colletor, and then the data is stored and sent out.

[0041] S120, performing data cleansing on the user operation data to generate standard data, and performing data concatenation on the standard data to generate concatenation data.

[0042] Data cleaning refers to processing raw data to remove noise, errors and inconsistencies, so that user operation data meets the standards. The data cleaning process can include steps such as data deduplication, format standardization, outlier processing and data filling. Data cleaning can include json parsing, unix timestamp parsing, regular parsing, data encryption and decryption, data mapping and other processes. Data concatenation refers to connecting multiple related data records according to certain rules to form a continuous data sequence. Data concatenation can be used to analyze the relationship and trend between data, as well as to generate user operation trajectories.

[0043] Optionally, data cleaning is performed on the user operation data to generate standard data, including: determining the data to be cleaned in the user operation data, wherein the data to be cleaned includes non-plaintext data and unstructured data; and converting the data to be cleaned into a specified format to generate standard data, wherein the standard data includes standard front-end data and standard back-end data.

[0044] Among them, in the user operation data, non-plaintext data may be encrypted data or data stored in a special encoding format. Determine whether it is non-plaintext data by analyzing the characteristics and format of the data. If the data presents garbled characters or special character combinations, it may be encrypted or encoded non-plaintext data. At the same time, the controller can refer to the documents and data storage specifications of the business system to understand which data may be encrypted or encoded. Unstructured data refers to data without a fixed format or structure, such as text descriptions, free text content in log files, etc. The controller can identify the form and content of the data. If the data does not have an obvious table structure, field delimiters or a fixed format, it is judged as unstructured data.

[0045] Specifically, encrypted non-plaintext data needs to be decrypted. Decryption requires the use of corresponding encryption algorithms and keys. For encoded data, decoding operations are required to convert it into a readable plaintext format. For unstructured data in log files, regular expressions or specific data extraction algorithms can be used to extract key information such as timestamps, event types, error codes, etc., and convert them into structured table data. Standard front-end data and standard back-end data are data that meet specific standards and specifications after cleaning and format conversion.

[0046] S130: Obtain a query request, and generate a user operation trajectory according to the query request and the concatenated data.

[0047] Among them, the query request refers to the request made by the user to the business system for querying data, and the query request may include information such as query conditions, query scope, and output format of query results. The user operation track refers to the operation path and behavior record of the user in the process of using the business system.

[0048] Optionally, a user operation trajectory is generated based on the query request and the concatenated data, including: matching each core field in the concatenated data through the query request to determine the target core field corresponding to the query request; using the data link corresponding to the target core field as the target data link; and generating the user operation trajectory based on the target data link.

[0049] Among them, the query request is initiated by the user to obtain the analysis needs of specific information. The query request can be in the form of an SQL query statement, an API request parameter, or a specific query interface input. The core fields in the concatenated data are key information fields determined during the data concatenation process. When a query request is received, the controller will match the conditions or parameters in the query request with the core fields in the concatenated data. The matching can be based on string matching, numerical comparison, time range filtering, etc. For example, if the query request is to find the operation track of a certain user, the system will match the user ID in the query request with the user ID core field in the concatenated data.

[0050] Specifically, by matching the query request with the core fields in the serial data, the controller can determine the target core field corresponding to the query request. The target core field may include user ID, operation type, operation time, etc. The controller can then search for data link nodes with the same associated field value in the serial data based on the target core field, and then determine the corresponding data link. For example, if the target core field contains a request ID, the system can search for all data link nodes with the same request ID in the serial data, and use the data link composed of these nodes as the target data link. The target data link reflects the specific process and processing steps of user operations that meet the query request conditions in the business system.

[0051] Furthermore, when generating the user operation trajectory, the nodes in the data link can be arranged in chronological order and business logic based on the analysis and integration of the data link to form a continuous operation process. Specifically, the controller can first determine the starting point and end point of the target data link. The starting point refers to the user's first operation request, and the end point can be the last operation response of the user to complete a specific task or a specific state in the system. Then, the nodes in the target data link are sorted and connected according to the chronological order and business logic. During the connection process, some additional information, such as operation time, operation type, operation result, etc., can also be added to enrich the content of the user operation trajectory. The controller will eventually output the connected node sequence as the user operation trajectory. It should be noted that the user operation trajectory can be displayed in the form of charts, lists, etc., so that the user can intuitively understand his operation process and the response of the system.

[0052] Optionally, after generating a user operation trace according to the query request and the concatenated data, the method further includes: performing performance monitoring on the standard data based on a preset cycle and specified monitoring items and determining monitoring results; and generating a performance report according to the monitoring results and the user operation trace.

[0053] Specifically, the preset cycle is a time interval set for regular performance monitoring of standard data. Specified monitoring items are indicators used to measure the performance of standard data determined based on business needs and performance concerns. Performance monitoring can be achieved by using performance monitoring tools or writing custom monitoring scripts. Performance monitoring tools can usually automatically collect and analyze data for specified monitoring items and provide a visual display of monitoring results. Customized monitoring scripts can be written based on specific business needs and monitoring items, and are highly flexible. The monitoring results are conclusions drawn from the analysis and evaluation of the data collected during the performance monitoring process. When generating a performance report, the performance indicator data in the monitoring results can be associated with the operation steps and timestamps in the user operation trajectory to analyze the impact of performance issues on user operations.

[0054] In a specific implementation, when performing performance monitoring, the front-end data can be aggregated and counted according to the work number dimension and the business dimension, and minute-level monitoring can be performed. For monitoring of the business dimension, problems at the front-end level can be discovered in a timely manner, including static resource loading, etc. For example, monitoring items for front-end browser data may include: success rate: threshold monitoring, 99%<, request volume: dynamic threshold, fluctuation range controlled within the 3-sigma interval, average response time: dynamic threshold, fluctuation range controlled within the 3-sigma interval, first screen time: >2 times the overall average, white screen time: >2 times the overall average, resource loading time: >2 times the overall average. For monitoring of the work number dimension, problems with the salesperson's terminal can be discovered, and it can also be discovered whether the salesperson's office network is slow. Exemplarily, the monitoring items for the work number dimension are as follows: success rate: threshold <99%, average time consumption: >2 times the overall average, low version browser monitoring: an alarm is generated when a Google Chrome browser lower than 127.0.2533.100 appears, abnormal terminal monitoring: an alarm is generated when an IE explore browser that is clearly not supported by the system appears.

[0055] In a specific implementation, when performing performance monitoring, the backend service dimensions can also be aggregated and statistically analyzed, and minute-level monitoring can be performed. For the monitoring of backend services, it is possible to quickly discover services with slow backend responses and abnormal responses, and use it in conjunction with front-end monitoring to quickly distinguish between front-end and back-end problems. The monitoring of the back-end service dimensions is designed as follows: Success rate: threshold <99%, call volume: dynamic threshold, the fluctuation range is controlled within the 3-sigma range, and the average response time: dynamic threshold, the fluctuation range is controlled within the 3-sigma range.

[0056] The technical solution of the embodiment of the present invention can comprehensively collect the user's operation information in the entire business process by acquiring the front-end browser data and the back-end application link data, and provide a rich and complete data source for subsequent analysis and backtracking. By performing data cleaning on the user operation data to generate standard data, the noise, errors and inconsistencies in the data are eliminated, the quality and accuracy of the data are improved, and the subsequent processing and analysis are more reliable. By performing data concatenation on the standard data to generate concatenated data, a coherent operation process record can be formed, which helps to more clearly understand the user's operation trajectory, and can reproduce the business operation response of the entire process, thereby improving the efficiency and accuracy of fault location.

[0057] Embodiment 2

[0058] Figure 2This is a flowchart of a method for tracing back user operation traces provided in the second embodiment of the present invention. This embodiment adds a specific process of performing data concatenation on standard data to generate concatenated data on the basis of the first embodiment. The specific contents of steps S210 and S260 are roughly the same as steps S110 and S130 in the first embodiment, so they will not be described in detail in this embodiment. Figure 2 As shown, the method includes:

[0059] S210. Obtain user operation data of the business system, wherein the user operation data includes front-end browser data and back-end application link data.

[0060] Optionally, obtaining user operation data of the business system includes: collecting back-end application link data of the business system through a collection probe; obtaining original browser data of the business system through a load gateway, and sending mirror data of the original browser data to the soft load; intercepting and capturing the mirror data to generate front-end browser data; and using the front-end browser data and back-end application link data as user operation data.

[0061] S220: Clean the user operation data to generate standard data.

[0062] Optionally, data cleaning is performed on the user operation data to generate standard data, including: determining the data to be cleaned in the user operation data, wherein the data to be cleaned includes non-plaintext data and unstructured data; and converting the data to be cleaned into a specified format to generate standard data, wherein the standard data includes standard front-end data and standard back-end data.

[0063] S230. Perform business information concatenation on the standard front-end data according to the first designated field to generate first concatenation data, wherein the first concatenation data includes various core fields.

[0064] Optionally, business information of the standard front-end data is concatenated according to the first designated field to generate first concatenated data, including: determining request data and page data in the standard front-end data according to the first designated field; associating the request data and the page data to generate associated data; determining core fields of the associated data through a data printing tool, and aggregating the core fields to generate the first concatenated data.

[0065] Among them, the first designated field is a field used to identify a specific business operation or user session, which can be a user ID, session ID, request ID, etc. Through the first designated field, the front-end data can be classified and associated according to specific business logic. For example, for an online shopping website, each shopping behavior of the user may have a unique session ID. Through this session ID, the controller can determine all request data and page data generated by the user during the shopping process. The request data includes the HTTP request information sent by the user, such as the requested URL, request method, and request header information. The page data may include the page content visited by the user, page element information, and page loading time. There is a close correlation between the request data and the page data. A request usually leads to the loading or updating of a page, and the change of the page will trigger a new request. By associating the request data and the page data, the specific operation of the user and the change of the page can be understood.

[0066] Specifically, when determining the core fields of the associated data, the controller can use a data printing tool to output the various fields of the associated data, and then determine the core fields based on business needs and the purpose of data analysis. Through the data printing tool, the controller can quickly determine the content and structure of the associated data, thereby determining which fields are most important for business analysis and user behavior tracking. For example, for an online shopping website, the core fields may include user ID, session ID, requested product page URL, purchased product information, etc. Finally, the controller aggregates the core fields to generate the first concatenated data.

[0067] S240. Associating the first series connection data with the standard backend data through a second designated field to generate second series connection data.

[0068] Specifically, the second designated field can establish an effective association between the front-end data and the back-end data. That is, the second designated field is a field commonly used by the front-end and back-end in the business process, such as user ID, order number, request ID, etc. The controller can search for records corresponding to the first serial data in the standard back-end data according to the second designated field. For example, the second designated field can be an order number. For each order in the first serial data, the controller can search for back-end operation records with the same order number in the standard back-end data. The controller will eventually merge the found back-end data with the corresponding front-end data to form the second serial data.

[0069] S250. Perform node association on the standard backend data in the second serial data through the third designated field to generate data links, and generate serial data according to each data link, wherein the serial data includes each data link and its corresponding core fields.

[0070] The third designated field is used to establish associations between different nodes in the backend data to build a data link. For example, the requested process number, transaction ID, etc. can be selected as the third designated field to identify the relationship between different operation steps in the backend system.

[0071] Specifically, the controller will group the standard backend data in the second serial data according to the third designated field. Backend operation records with the same third designated field are grouped together to represent a specific data link node. Then, the controller will sort and connect these nodes according to the time sequence and business logic to form a data link. For example, if multiple services in the backend system process requests in a certain order, the operation records of these services can be connected according to the time sequence of the service calls and the transaction ID to form a complete data link. Finally, the controller will associate each data link with the corresponding front-end operation information (i.e., the core field in the first serial data) to generate serial data containing each data link and its corresponding core field.

[0072] In a specific implementation, after designing the data concatenation process, the controller can use fornaxee (data factory) to stream the data. The specific steps are as follows: 1. Associate the front-end request data and page data through page_id, aggregate the core fields of the two data, and finally obtain a complete front-end data with business information, terminal information, operator information, front-end performance and status. 2. Associate the front-end complete data with core fields with the back-end call chain data through the trace_id field to form front-end and back-end concatenation data. At this point, a basic data structure has been formed, and this data can be used for basic troubleshooting. 3. Through the opentracing specification, use parent_span_id and span_id to associate the data of the parent node and child node of the back-end call chain to form a single piece of data with from and to information, which is convenient for front-end view construction. After the data is concatenated, each call chain data will contain multiple core fields. In these core fields, you can clearly see what business the salesperson is handling for the designated account, what terminal is used, what browser version, the success status of the front-end and each page, the time taken for the request, the response status of the back-end, the time taken, and the abnormal error situation.

[0073] S260: Obtain a query request, and generate a user operation track according to the query request and the concatenated data.

[0074] Optionally, a user operation trajectory is generated based on the query request and the concatenated data, including: matching each core field in the concatenated data through the query request to determine the target core field corresponding to the query request; using the data link corresponding to the target core field as the target data link; and generating the user operation trajectory based on the target data link.

[0075] Optionally, after generating a user operation trace according to the query request and the concatenated data, the method further includes: performing performance monitoring on the standard data based on a preset cycle and specified monitoring items and determining monitoring results; and generating a performance report according to the monitoring results and the user operation trace.

[0076] The technical solution of the embodiment of the present invention can comprehensively collect the user's operation information in the entire business process by acquiring the front-end browser data and the back-end application link data, and provide a rich and complete data source for subsequent analysis and backtracking. By performing data cleaning on the user operation data to generate standard data, the noise, errors and inconsistencies in the data are eliminated, the quality and accuracy of the data are improved, and the subsequent processing and analysis are more reliable. By performing data concatenation on the standard data to generate concatenated data, a coherent operation process record can be formed, which helps to more clearly understand the user's operation trajectory, and can reproduce the business operation response of the entire process, thereby improving the efficiency and accuracy of fault location.

[0077] Embodiment 3

[0078] Figure 3 This is a schematic diagram of the structure of a user operation trajectory backtracking device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a user operation data acquisition module 310, which is used to acquire user operation data of the business system, wherein the user operation data includes front-end browser data and back-end application link data;

[0079] The data cleaning and serial connection module 320 is used to clean the user operation data to generate standard data, and to serially connect the standard data to generate serial connection data;

[0080] The user operation trace acquisition module 330 is used to acquire a query request and generate a user operation trace according to the query request and the concatenated data.

[0081] Optionally, the user operation data acquisition module 310 is specifically used to: collect the back-end application link data of the business system through the collection probe; obtain the original browser data of the business system through the load gateway, and send the mirror data of the original browser data to the soft load; intercept and capture the mirror data to generate the front-end browser data; use the front-end browser data and the back-end application link data as user operation data.

[0082] Optionally, the data cleaning and serial connection module 320 specifically includes: a data cleaning unit, used to: determine the data to be cleaned in the user operation data, wherein the data to be cleaned includes non-plaintext data and unstructured data; convert the data to be cleaned into a specified format to generate standard data, wherein the standard data includes standard front-end data and standard back-end data.

[0083] Optionally, the data cleaning and concatenation module 320 specifically includes: a data concatenation unit, used to: perform business information concatenation on the standard front-end data according to the first designated field to generate first concatenation data, wherein the first concatenation data includes each core field; associate the first concatenation data and the standard back-end data through the second designated field to generate second concatenation data; perform node association on the standard back-end data in the second concatenation data through the third designated field to generate a data link, and generate concatenation data according to each data link, wherein the concatenation data includes each data link and its corresponding core fields.

[0084] Optionally, the data concatenation unit specifically includes: a business information concatenation sub-unit, used to: determine the request data and page data in the standard front-end data according to the first specified field; associate the request data and the page data to generate associated data; determine the core fields of the associated data through a data printing tool, and aggregate the core fields to generate the first concatenation data.

[0085] Optionally, the user operation trace acquisition module 330 is specifically used to: match each core field in the serial data through a query request to determine the target core field corresponding to the query request; use the data link corresponding to the target core field as the target data link; and generate the user operation trace according to the target data link.

[0086] Optionally, the device also includes: a performance monitoring module, which is used to: after generating a user operation trajectory according to the query request and the serial data, perform performance monitoring on the standard data based on a preset cycle and specified monitoring items and determine the monitoring results; generate a performance report according to the monitoring results and the user operation trajectory.

[0087] The technical solution of the embodiment of the present invention can comprehensively collect the user's operation information in the entire business process by acquiring the front-end browser data and the back-end application link data, and provide a rich and complete data source for subsequent analysis and backtracking. By performing data cleaning on the user operation data to generate standard data, the noise, errors and inconsistencies in the data are eliminated, the quality and accuracy of the data are improved, and the subsequent processing and analysis are more reliable. By performing data concatenation on the standard data to generate concatenated data, a coherent operation process record can be formed, which helps to more clearly understand the user's operation trajectory, and can reproduce the business operation response of the entire process, thereby improving the efficiency and accuracy of fault location.

[0088] A user operation track backtracking device provided by an embodiment of the present invention can execute a user operation track backtracking method provided by any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0089] Embodiment 4

[0090] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0091] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0092] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0093] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a user operation trajectory backtracking method.

[0094] In some embodiments, a method for tracing back a user operation trajectory may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for tracing back a user operation trajectory described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform a method for tracing back a user operation trajectory in any other appropriate manner (e.g., by means of firmware).

[0095] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0096] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0097] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0098] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0099] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0100] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0101] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0102] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for tracing back user operation traces, characterized in that: include: Acquire user operation data of the business system, wherein the user operation data includes front-end browser data and back-end application link data; Performing data cleaning on the user operation data to generate standard data, and performing data concatenation on the standard data to generate concatenation data; A query request is obtained, and a user operation trajectory is generated according to the query request and the concatenated data.

2. The method according to claim 1, characterized in that The obtaining of user operation data of the business system includes: Collect backend application link data of business systems through collection probes; Obtaining original browser data of the business system through the load gateway, and sending mirror data of the original browser data to the soft load; Intercepting and capturing the mirror data to generate the front-end browser data; The front-end browser data and the back-end application link data are used as the user operation data.

3. The method according to claim 1, characterized in that The step of performing data cleaning on the user operation data to generate standard data includes: Determining data to be cleaned in the user operation data, wherein the data to be cleaned includes non-plaintext data and unstructured data; The data to be cleaned is converted into a specified format to generate the standard data, wherein the standard data includes standard front-end data and standard back-end data.

4. The method according to claim 3, characterized in that The step of performing data concatenation on the standard data to generate concatenated data includes: Performing business information concatenation on the standard front-end data according to the first designated field to generate first concatenated data, wherein the first concatenated data includes various core fields; Associating the first concatenated data with the standard backend data through a second designated field to generate second concatenated data; The standard backend data in the second serial data is node-associated through the third designated field to generate a data link, and the serial data is generated according to each of the data links, wherein the serial data includes each data link and its corresponding core fields.

5. The method according to claim 4, characterized in that The step of performing business information concatenation on the standard front-end data according to the first designated field to generate first concatenated data includes: Determine the request data and page data in the standard front-end data according to the first designated field; Associating the request data with the page data to generate associated data; The core fields of the associated data are determined by a data printing tool, and the core fields are aggregated to generate the first series data.

6. The method according to claim 4, characterized in that The generating a user operation track according to the query request and the concatenated data includes: Matching each of the core fields in the concatenated data through the query request to determine a target core field corresponding to the query request; Using the data link corresponding to the target core field as the target data link; The user operation trajectory is generated according to the target data link.

7. The method according to claim 1, characterized in that After generating the user operation track according to the query request and the concatenated data, the method further includes: Performing performance monitoring on the standard data based on a preset cycle and specified monitoring items and determining monitoring results; A performance report is generated according to the monitoring results and the user operation trace.

8. A user operation track backtracking device, characterized in that: include: A user operation data acquisition module, used to acquire user operation data of the business system, wherein the user operation data includes front-end browser data and back-end application link data; A data cleaning and serial connection module, used for performing data cleaning on the user operation data to generate standard data, and performing data serial connection on the standard data to generate serial connection data; The user operation track acquisition module is used to acquire a query request and generate a user operation track according to the query request and the concatenated data.

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

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

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