CN118051403A - Critical link analysis method, device, electronic equipment and storage medium - Google Patents

Abstract

The application relates to a method, a device, electronic equipment and a storage medium for analyzing a key link, wherein the method comprises the following steps: determining at least one key link involved in the operation process of a service page in a service scene according to the service scene aimed at by front-end service, wherein the service scene is a scene facing a set user or a set terminal, the service page is a page interacted with the user, and the key link is a link formed by key nodes in all nodes involved in the operation process of the service page; acquiring key link data in the key link through a software development kit based on the service scene and a preset service requirement, wherein the key link data is acquired in a set field mode; and after analyzing and processing the key link data according to a preset analysis strategy, displaying an analysis result on a display panel. The application meets the personalized monitoring requirement.

Description

Critical link analysis method, device, electronic equipment and storage medium

Technical Field

The present application relates to the field of big data, and in particular, to a method and apparatus for analyzing a critical link, an electronic device, and a storage medium.

Background

Monitoring is a complex distributed system that helps analyze performance problems by collecting system behavior data across different applications, different servers, and by sampling the collected system data.

The current data monitoring is basically full-link monitoring, is mostly a general monitoring scheme, is difficult to carry out customized monitoring aiming at specific service scenes and service requirements, and cannot meet personalized monitoring requirements.

Disclosure of Invention

The application provides an analysis method, an analysis device, electronic equipment and a storage medium of a key link, which are used for solving the problem that personalized monitoring cannot be achieved.

The application provides a method for analyzing a key link, which comprises the following steps: determining at least one key link involved in the operation process of a service page in a service scene according to the service scene aimed at by front-end service, wherein the service scene is a scene facing a set user or a set terminal, the service page is a page interacted with the user, and the key link is a link formed by key nodes in all nodes involved in the operation process of the service page; acquiring key link data in the key link through a software development kit based on the service scene and a preset service requirement, wherein the key link data is acquired in a set field mode; and after analyzing and processing the key link data according to a preset analysis strategy, displaying an analysis result on a display panel.

The application provides an analysis device of a key link, which comprises: the system comprises a determining module, a processing module and a processing module, wherein the determining module is used for determining at least one key link involved in the operation process of a business page in a business scene according to the business scene aimed at by front-end business, wherein the business scene is a scene facing a set user or a set terminal, the business page is a page interacted with the user, and the key link is a link formed by key nodes in all nodes involved in the operation process of the business page; the acquisition module is used for acquiring key link data in the key link through a software development kit based on the service scene and the preset service requirement, wherein the key link data is acquired in a set field mode; and the display module is used for displaying the analysis result on the display panel after analyzing and processing the key link data according to a preset analysis strategy.

The application provides an electronic device, comprising: at least one communication interface; at least one bus connected to the at least one communication interface; at least one processor coupled to the at least one bus; at least one memory coupled to the at least one bus.

The present application also provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions are read from the computer-readable storage medium by a processor of a computer device, and executed by the processor, cause the computer device to perform the methods provided in various alternative implementations of the analytical aspects of the critical links described above.

Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages: according to a service page in a service scene, determining a key link involved in the service page in the operation process, then acquiring key link data in the key link based on a preset service requirement, and finally carrying out data analysis on the key link data to obtain an analysis result. The application collects and analyzes the key link data based on the service scene and the service requirement, realizes the customized monitoring of the key link, and meets the personalized monitoring requirement.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.

In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.

One or more embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements, and in which the figures of the drawings are not to be taken in a limiting sense, unless otherwise indicated.

FIG. 1 is a flow chart of a method for analyzing a critical link according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a system architecture for critical link analysis according to an embodiment of the present application;

FIG. 3 is a schematic diagram of a technical gist of a software development kit according to an embodiment of the present application;

FIG. 4 is a schematic diagram of statistics type selection according to an embodiment of the present application;

FIG. 5-1 is a diagram of a total number of site loads and a total number of errors according to an embodiment of the present application;

FIG. 5-2 is a schematic diagram of average load per minute provided by an embodiment of the present application;

FIGS. 5-3 are schematic diagrams of average JS errors per minute provided by embodiments of the present application;

FIGS. 5-4 are schematic diagrams illustrating time-consuming page loading according to embodiments of the present application;

FIGS. 5-5 are schematic diagrams illustrating total time-consuming distribution of page loading according to embodiments of the present application;

FIGS. 5-6 are thermal diagrams illustrating total time-consuming page loading provided by embodiments of the present application;

FIGS. 5-7 are schematic diagrams illustrating time-consuming completion of DOM loading according to embodiments of the present application;

FIGS. 5-8 are schematic diagrams illustrating time-consuming distribution of DOM loading completion according to embodiments of the present application;

FIGS. 5-9 are schematic diagrams of time-consuming thermodynamic distributions for DOM loading completion provided by embodiments of the present application;

fig. 6 is a schematic diagram of an analysis result for a front-end service according to an embodiment of the present application;

FIG. 7 is a screening schematic diagram of a log query platform according to an embodiment of the present application;

FIG. 8 is a flow chart of an analysis of a critical link according to an embodiment of the present application;

FIG. 9 is a schematic diagram showing a comparison of performance indexes of a workbench according to an embodiment of the application;

Fig. 10 is a schematic structural diagram of an analysis device for a critical link according to an embodiment of the present application;

fig. 11 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The following disclosure provides many different embodiments, or examples, for implementing different structures of the application. In order to simplify the present disclosure, components and arrangements of specific examples are described below. They are, of course, merely examples and are not intended to limit the application. Furthermore, the present application may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.

The application provides a key link analysis method, which is applied to a server and used for personalized custom monitoring, as shown in fig. 1, and comprises the following steps:

step 101: and determining at least one key link involved in the operation process of the business page in the business scene according to the business scene aimed at by the front-end business.

The service scene is a scene facing to a set user or a set terminal, the service page is a page interacted with the user, and the key links are links formed by key nodes in all nodes involved in the operation process of the service page.

The application is applied to web scenes, each front-end service corresponds to a plurality of service scenes, the front-end service refers to a specific service name, such as the name of a configuration scheme book or a certain applet, the service scene refers to a scene facing a set user or a set terminal, such as a b-end service system, an h5 page, a toolbar page of a certain app, a workbench page of the certain app facing the user, or a workbench page of the certain app facing a background person. Each business scenario corresponds to a business page that directly interacts with the user.

The whole operation process from page loading, page opening to page operation of the service page can involve a plurality of service nodes, and the server takes a link formed by key nodes in all the service nodes as a key link, that is, the key link is a part of links in the whole link. The field definition of the critical link includes at least the following.

Business Type: a service type; bussiness Name: a service name; scene: scene which scene components are under the service type; stack: error stack error information.

The key nodes include, but are not limited to, page loads, interface requests, key action executions, and user interactions.

Step 102: and acquiring key link data in the key link through a software development kit based on the service scene and the preset service requirement.

Wherein, the key link data is collected in the form of a set field.

The server acquires preset service requirements, the preset service requirements are used for determining which data analysis results are required to be finally obtained, a software development kit is embedded in the key link by the server, and key link data in the key link are acquired based on the software development kit. The key link data comprises basic data, link data, performance data, abnormal data and user behavior data. The key link data is collected in the form of a set field, so that the data uploading form is simpler and more definite.

Step 103: and after analyzing and processing the key link data according to a preset analysis strategy, displaying an analysis result on a display panel.

The server analyzes and processes the key link data according to a preset analysis strategy to obtain an analysis result, wherein the analysis result comprises a statistical result of site data, a statistical result of page data, a statistical result of performance data and abnormal data, and finally the analysis result is displayed on a display panel for a user to check. The application combines the alarm and display panel to grasp the running condition of the project in real time, and grasp the page browsing quantity change, the line reporting error, the abnormal condition, the user preference and the like of the key link.

According to the method, key links involved in the operation process of the business page are determined according to the business page in the business scene, key link data in the key links are collected based on preset business requirements, and finally data analysis is carried out on the key link data to obtain an analysis result. The application collects and analyzes the key link data based on the service scene and the service requirement, realizes the customized monitoring of the key link, and meets the personalized monitoring requirement.

In addition, the prior art generally uses full link acquisition, and full link monitoring of the service can collect a large amount of monitoring data, which needs to be effectively processed and analyzed to provide valuable problem investigation results. However, due to the large data volume and scattered data sources, the efficiency of data acquisition and processing is low, and a long time is required for processing a large amount of data, so that the monitoring effect and efficiency are affected.

The application collects key link data, can realize less and more important data collection compared with the collection of all link data, can quickly feed back the core problems of the system by monitoring the performance and error conditions of the core functions, has relatively smaller monitoring data volume, can reduce the workload of data processing and analysis, improves the efficiency of data collection and processing, and also improves the efficiency of problem investigation.

Fig. 2 is a schematic diagram of a system architecture of a critical link analysis in the present application, and it can be seen that the system includes three parts, namely an application layer, critical link monitoring and basic monitoring.

The application layer is a layer for establishing a direct relation between a key link and a user, and can be a B-end business system, an h5 page, an enterprise WeChat workbench or a WeChat customer service workbench by way of example. Core content critical link monitoring and basic monitoring.

The critical link analysis includes the following.

Core scene definition: key link scenarios, such as enterprise micro toolbar pages, enterprise micro workbench pages, H5 pages, etc., are defined and identified that establish relationships directly with users.

Key link node definition: important nodes in the critical links are determined, such as page loads, interface requests, critical action execution, user interactions, and the like.

Critical link monitoring SDK: and embedding a monitoring SDK for the key link, and collecting and reporting performance indexes and abnormal data related to the key node.

Key link tracking: and tracking the execution condition and performance data of each node in the key link to know the operation condition of the whole link.

Log cleansing policy and alarm policy: defining and configuring log cleaning strategy and alarm rule of key link to filter irrelevant information and find potential problem in time, and setting alarm frequency and group alarm mode.

The basic monitoring includes the following.

Reporting data: data related to users, environments, pages, performance, anomalies, requests, etc. are collected and reported for comprehensive analysis and monitoring.

And (3) data acquisition: and collecting page performance data, javaScript error data, interface performance data, static resource data and the like, and analyzing and optimizing the performance of the application program.

Log and alarm: and cleaning and processing the collected logs, configuring alarm rules and frequencies and a group alarm mode, and timely finding and solving potential problems.

Data presentation: the Grafana panel and other data display tools are used for visually displaying the monitoring data, including site data, page data, P90 data (90% quantile of performance) and abnormal data, so that the running condition and performance condition of the application program can be better known.

The application layer, the key link monitoring and the basic monitoring together form a complete key link analysis system based on service, the performance, the stability and the user experience of the application program can be comprehensively known through monitoring the key link and the basic monitoring data, potential problems can be timely found and solved, the quality and the user satisfaction of the application program are improved, and real-time performance monitoring, fault detection and system optimization are provided.

As an alternative embodiment, based on the service scenario and the preset service requirement, collecting the critical link data in the critical link through the software development kit includes: determining a service embedded point model according to a service scene and preset service requirements, wherein the service embedded point model adopts a 5w mode to acquire data; and acquiring key link data in the key link through a software development tool package and a service embedded point model by a set field.

The server determines a service embedded point model according to a service scene and preset service requirements, and adopts the service embedded point model to acquire and upload data according to a 5w mode, wherein the 5w mode is that what people do at what time and place based on what motivation, and the page operation of the application is that what id does what operation at what time and what node do based on what data feedback, so that the acquisition form of key link data is a set field, and the set field comprises an acquired execution main body, time, place, motivation and content. By adopting a 5w model, only the event type, the element acted by the event and the event related parameters are required to be paid attention to in development, so that simpler, direct and clear data reporting is realized.

As an alternative embodiment, the critical link data includes basic data, link data, performance data, anomaly data, and user behavior data, and the collecting the link data includes: acquiring key node data of key nodes in a key link through a software development kit; and tracking the key node data of each key node in the same key link to obtain the link data in the key link.

The application adopts different acquisition means aiming at different types of data, including technical means such as LCP event monitoring, send Beacon reporting, request Idle Callback callback and the like, so that the targeted acquisition means can improve the monitoring precision, reduce the situations of false reporting and missing reporting, can not influence the monitoring result by irrelevant factors, and can adapt to various different system architectures and service scenes.

The software development kit is composed of the following modules: the system comprises a data acquisition module, an error monitoring module, a performance monitoring module, a user behavior monitoring module and a data reporting module.

1. And a data acquisition module: for collecting various monitoring data in the front-end application. The data acquisition module can collect data in modes of burying points, monitoring events, capturing anomalies and the like, and sends the data to the server for processing and storage.

Wherein the base data comprises: page load event: listening to page load events using a window.onloaddocument.add eventListener ('DOMContentLoaded') or the like, calculating page load time using a window.performance.timing object, calculating time triggered by events from the beginning of a page to DOMContentLoaded using DOMContentLoaded time, and acquiring first rendering time using a performance.getEntriesBtype ('paint') method.

Ajax or network request event: monitoring events of Ajax requests or other network requests, and collecting information such as time consumption of interface requests, success request Idle Callback or failure state of requests, request messages, response data, error, timeout, abort exception and the like.

Error event: capture error events window. Error, unhandled rejection event, control. Error overwrite, etc.

User behavior events: and monitoring behavior events of the user, and collecting behaviors such as clicking, inputting and scrolling of the user.

Page jump event: monitoring changes of page jump events window, onbefore unloading, window, location and the like, and collecting page jump time and paths of a user in front-end application.

Wherein the link data includes: the starting point of the critical link, the ending point of the critical link, localstroy stored report queue data, a request function wrapper, the critical link execution time, a function of the critical link data, and the like.

The link data is obtained from the key node data group of the key nodes in the key link by tracking the key node data of each key node in the same key link.

2. And an error monitoring module: monitoring JavaScript errors, resource loading errors, network request errors and the like, wherein the JavaScript errors comprise: error overwriting, unhandedrejection event listening, error event listening, vue exception capture. The error monitoring module is responsible for collecting stack information of errors, error types, time of occurrence of the errors and the like, reporting the stack information, the error types, the time of occurrence of the errors and the like, and recording and analyzing data.

3. And a performance monitoring module: the method comprises the steps of measuring page loading time, resource loading time, interface request time and rendering performance, wherein the first screen loading time, the white screen time, loaded (data loading), DNS (Domain NAME SYSTEM )), TCP (Transmission Control Protocol, transmission control protocol) time are measured, and related reports and charts are generated so as to know the performance of the application.

4. User behavior monitoring module: collecting and recording clicking, inputting, scrolling and other behaviors of a user, wherein the monitoring behaviors are performed under the condition of user authorization or are processed for the acquired user ids, and a single user cannot be positioned; and comprehensively analyzing the operation behavior data of all users to optimize operation paths and the like, and further optimizing user experience.

5. And a data reporting module: and compressing, encrypting and the like the acquired key link data to ensure the safety and the integrity of the data.

Fig. 3 is a schematic view of technical points of a software development kit, where the technical points mainly include: performance metrics, management request objects, network library extensions, list Error, framework, and filter Error types.

As an optional implementation manner, after the analysis processing is performed on the key link data according to the preset analysis policy, displaying the analysis result on the display panel includes: cleaning the logs in the key link data according to a preset cleaning rule; aiming at the cleaned log, determining an analysis result of key link data according to a statistical type selected by a user on a display panel, wherein the analysis result comprises site data, page data, performance data and abnormal data, and the site data comprises the total number of sites, the successful number of sites, the error number of site report, the success rate of sites and the failure rate of sites; and visually displaying the analysis result on a display panel.

The server cleans the log in the key link data according to a preset cleaning rule, wherein the preset cleaning rule can be an alarm rule, and the server sends an alarm in cooperation with the alarm rule. For example, the linearity of data is to count data every 15 seconds and judge the success rate every 15 seconds, but the overall success rate is calculated according to 15 minutes, so that a certain period is less than 95% and no alarm is given, because the alarm rule is set to be continuously less than 95% within 15 minutes.

The preset cleaning rule can also be that obvious error data, missing data and the like are removed, and then the analysis result is visually displayed on the display panel according to the cleaned log, wherein the analysis result comprises various contents such as site data, page data, performance data, abnormal data and the like. The analysis result can be all analysis results, and can also be a statistical result of a certain link obtained according to the statistical type selected by the user on the display panel.

If the analysis result of the key link data is determined according to the statistical type selected by the user on the display panel, the specific method is as follows: determining a target system type selected by a user on a display panel, wherein the system type comprises a user-oriented system and a background system; determining a target system domain name selected by a user on a display panel, wherein each system type corresponds to a plurality of system domain names; determining target front-end services selected by a user on a display panel, wherein each system domain name corresponds to a plurality of front-end services; determining a target service scene selected by a user on a display panel, wherein each front-end service corresponds to a plurality of service scenes; determining a target key link selected by a user on a display panel, wherein each business scene corresponds to at least one key link; determining target key nodes selected by a user on a display panel, wherein each key link corresponds to at least one key node; and analyzing and processing the data in the target system type, the target system domain name, the target front-end service, the target service scene, the target key link or the target key node to obtain an analysis result.

The statistical types include a variety of contents: the statistics types are progressive layer by layer, and the statistics types comprise target system types, target system domain names, target front-end services, target service scenes, target key links or target key nodes.

The system types include a user-oriented system and a background system, each system type corresponds to a plurality of system domain names, each system domain name corresponds to a plurality of front-end services, fig. 4 is a schematic diagram of statistical type selection, each front-end service corresponds to a plurality of service scenarios, for example, each service system of the B-end, an h5 page, an enterprise WeChat workbench or a WeChat customer service workbench. Each business scenario corresponds to at least one key link, and each key link corresponds to at least one key node.

After the user selects the statistic types layer by layer, data analysis processing can be performed according to the statistic types selected by the user, so that data analysis of a large statistic level, such as data analysis of a system type, can be obtained, and data analysis of a small statistic level, such as data analysis of a certain key node, can be obtained. Only the level of front-end traffic is counted in fig. 4.

The analysis results for a system domain name include monitoring of the latest time period (including total site loading and error number in fig. 5-1; average number of loads per minute in fig. 5-2; average number of JS errors per minute in fig. 5-3), front-end page loading monitoring (page loading time in fig. 5-4, total page loading time distribution in fig. 5-5, total page loading time thermodynamic diagram in fig. 5-6), DOM (document object model) loading (DOM loading completion time in fig. 5-7, DOM loading completion time distribution in fig. 5-8, DOM loading completion time thermodynamic distribution in fig. 5-9), wherein fig. 5-1 to 5-8 may be displayed simultaneously on a statistics panel.

Fig. 6 is a schematic diagram of an analysis result for a front-end service, where it can be seen that the analysis result includes a total number of stations, a success number, a failure number, and a success rate distribution diagram.

As an alternative embodiment, after the analysis result is visually displayed on the display panel, the method further includes: if a click command aiming at the analysis result on the display panel is monitored, linking to a log query platform; and displaying the log corresponding to the analysis result in the log query platform.

The display panel is connected with the log query platform, if a user clicks a certain analysis result on the display panel, the log query platform can be jumped from a presentation page of the current analysis result in the display panel, and the log corresponding to the clicked analysis result is displayed in the log query platform. For example, the statistics panel is used for counting and outputting the data such as the success rate, the failure rate, the total calling number and the like of the key links, so that a user can check the failure reason on the statistics panel, can directly click the failure number, is linked to a log query platform, checks a specific error log, conveniently tracks and locates, and accurately locates the code problem.

Different screening conditions are also arranged on the log query platform, so that a user can query the error log in a refined manner according to the different screening conditions, and the quick positioning is convenient. The log query platform supports searching by using various screening conditions, and the searching efficiency is improved. Fig. 7 is a screening schematic of a log query platform.

As an optional implementation manner, the user behavior data is operation behavior data of a user in a page running process, the operation behavior data of each key node carries a user identifier, and after the analysis result is visually displayed on the display panel, the method further includes: aiming at the abnormal result, the key nodes with the operation behavior data of the user identifier are connected in series through the link log to obtain a user operation link; and carrying out anomaly analysis on the data in the user operation link.

In the page running process, any operation behavior of a user on the page has corresponding operation behavior data, the operation behavior data also carries a user identifier, and when a series of operation behaviors of the user are finished, if an abnormal result is generated, whether the abnormal result is generated by improper operation of the user is inquired in the following way: and determining key nodes where the operation behavior data are located through the operation behavior data with the user identifier, forming a user operation link according to the key nodes, and finally carrying out anomaly analysis on the data in the user operation link.

The online user operation behaviors are complex and changeable, and some problems can be hidden after the user operates for many times, so that data analysis can be performed according to the behaviors of the user in a targeted manner, and whether an abnormal result is generated by the improper behaviors of the user or not is judged.

The display panel performs fine analysis on each error reporting type, supports error reporting log query positioning, accurately analyzes the logs through monitoring and embedding errors of the reporting line environment and some custom anomalies, accurately positions code problems, and can see the error reporting number and error reporting reasons at the same time, and then analyzes the operation where the user has problems.

As an alternative embodiment, before the acquiring, by the software development kit, the critical link data in the critical link, the method further includes: acquiring user behavior data in a full link according to the full link involved in the operation process of the service page; establishing a user portrait according to the user behavior data; a critical link is determined based on the user representation.

The determination of the critical link may also be based on user profile determination, which is performed by: and analyzing the reported user behavior by combining the full links involved in the operation process of the service page, establishing a user portrait, and generating a key link service flow. Establishing a user representation refers to optimizing product design and experience by collecting, sorting and analyzing relevant data of users to form comprehensive description and understanding of the users, and knowing user requirements in depth. Specifically, the user portrayal includes 1. User attributes: account attributes, base attributes, business attributes, base attributes such as regional attributes, demographic attributes, economic attributes, life stages, family information, health care, preference interests, social attributes; 2. behavior attributes such as access behavior, application behavior, business behavior, operation behavior; 3. marketing attributes 4. Risk attributes, including insurance policy, marketing fraud risk, money laundering risk, etc.

The product identifies key links of the user when using the product or service, which are typically the core processes or key functions of the user using the product, based on the user's needs and behaviors according to the data analysis tools and techniques.

For example, the business process of configuring a scheme book to a user to purchase and create a policy includes the following: 01_get home security scheme, 02_save home information, 03_get new product get recommended products list, 04_get one-key pay DSL (DomainSpecificLanguage, a computer programming language with limited expressive power for a domain), 05_get scheme quote, 06_wind check, 07_save customer scheme, 08_generate scheme book, 09_user view scheme book, 10_immediate application, 11_create policy.

Based on the same technical conception, the application also provides an analysis flow chart of the key link, as shown in fig. 8, taking front-end service as an example of cloud outbound, firstly judging whether the cloud outbound is successful, if so, reporting success information by the embedded point at the end b, uploading the success information to a server, cleaning data by the server, outputting a visual scheme, and also giving an alarm.

According to the application, customized monitoring is carried out according to different service scenes and requirements, a service flow key link is defined, and the service data and the performance data are associated by combining front-end buried points, data acquisition, data processing and visual display, so that the performance and abnormal conditions of the key link are accurately monitored, and the problems are timely found and solved.

The application can quickly find problems and bottlenecks in a system by collecting and analyzing the data in the key links, timely take measures to solve the problems, improve the reliability and stability of the system, and timely find performance problems and errors of front-end pages, and improve user experience and satisfaction, thereby increasing user viscosity and loyalty, quickly positioning the problems, reducing troubleshooting time and lowering operation and maintenance costs and labor costs. The display panel can analyze the bottleneck and short plates of the business process, optimize the business process, improve the business efficiency and benefit, collect user behaviors and demands based on user identification, optimize product design, and improve product quality and market competitiveness. FIG. 9 is a graphical representation of a comparison of table performance metrics. It can be seen that the performance of the table of the present application is greatly improved over the performance of the prior art.

Based on the same technical concept, the application also provides an analysis device of the key link, as shown in fig. 10, which is characterized in that the device comprises:

The determining module 1001 is configured to determine, according to a service scenario targeted by a front-end service, at least one key link involved in an operation process of a service page in the service scenario, where the service scenario is a scenario facing a set user or a set terminal, the service page is a page that interacts with the user, and the key link is a link formed by key nodes in all nodes involved in the operation process of the service page;

the acquisition module 1002 is configured to acquire, based on a service scenario and a preset service requirement, key link data in a key link through a software development kit, where the key link data is acquired in a form of a set field;

and the display module 1003 is used for displaying the analysis result on the display panel after analyzing and processing the key link data according to a preset analysis strategy.

Optionally, the acquisition module 1002 is configured to:

Determining a service embedded point model according to a service scene and preset service requirements, wherein the service embedded point model adopts a 5w mode to acquire data;

And acquiring key link data in the key link through a software development tool package and a service embedded point model by a set field.

Optionally, the critical link data includes basic data, link data, performance data, anomaly data, and user behavior data, and the acquisition module 1002 is configured to:

acquiring key node data of key nodes in a key link through a software development kit;

and tracking the key node data of each key node in the same key link to obtain the link data in the key link.

Optionally, the device is further configured to:

Cleaning the logs in the key link data according to a preset cleaning rule;

Aiming at the cleaned log, determining an analysis result of key link data according to a statistical type selected by a user on a display panel, wherein the analysis result comprises site data, page data, performance data and abnormal data, and the site data comprises the total number of sites, the successful number of sites, the error number of site report, the success rate of sites and the failure rate of sites;

And visually displaying the analysis result on a display panel.

Optionally, the device is further configured to:

Determining a target system type selected by a user on a display panel, wherein the system type comprises a user-oriented system and a background system;

determining a target system domain name selected by a user on a display panel, wherein each system type corresponds to a plurality of system domain names;

determining target front-end services selected by a user on a display panel, wherein each system domain name corresponds to a plurality of front-end services;

determining a target service scene selected by a user on a display panel, wherein each front-end service corresponds to a plurality of service scenes;

determining a target key link selected by a user on a display panel, wherein each business scene corresponds to at least one key link;

determining target key nodes selected by a user on a display panel, wherein each key link corresponds to at least one key node;

And analyzing and processing the data in the target system type, the target system domain name, the target front-end service, the target service scene, the target key link or the target key node to obtain an analysis result.

Optionally, the device is further configured to:

If a click command aiming at the analysis result on the display panel is monitored, linking to a log query platform;

and displaying the log corresponding to the analysis result in the log query platform.

Optionally, the user behavior data is operation behavior data of a user in a page running process, and the operation behavior data of each key node carries a user identifier, and the device is further used for:

Aiming at the abnormal result, the key nodes with the operation behavior data of the user identifier are connected in series through the link log to obtain a user operation link;

And carrying out anomaly analysis on the data in the user operation link.

Optionally, acquiring user behavior data in the full link according to the full link involved in the operation process of the service page;

establishing a user portrait according to the user behavior data;

a critical link is determined based on the user representation.

As shown in fig. 11, an embodiment of the present application provides an electronic device, which includes a processor 1101, a communication interface 1102, a memory 1103, and a communication bus 1104, where the processor 1101, the communication interface 1102, and the memory 1103 perform communication with each other through the communication bus 1104.

A memory 1103 for storing a computer program.

In one embodiment of the present application, the processor 1101 is configured to implement the method for analyzing a critical link provided in any of the foregoing method embodiments when executing a program stored in the memory 1103.

The present application also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method for analyzing a critical link as provided in any of the method embodiments described above.

The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

From the above description of embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus a general purpose hardware platform, or may be implemented by hardware. Based on such understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the related art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the method described in the respective embodiments or some parts of the embodiments.

It is to be understood that the terminology used herein is for the purpose of describing particular example embodiments only, and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises," "comprising," "includes," "including," and "having" are inclusive and therefore specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof. The method steps, processes, and operations described herein are not to be construed as necessarily requiring their performance in the particular order described or illustrated, unless an order of performance is explicitly stated. It should also be appreciated that additional or alternative steps may be used.

The foregoing is only a specific embodiment of the application to enable those skilled in the art to understand or practice the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (11)

1. A method of critical link analysis, the method comprising:

Determining at least one key link involved in the operation process of a service page in a service scene according to the service scene aimed at by front-end service, wherein the service scene is a scene facing a set user or a set terminal, the service page is a page interacted with the user, and the key link is a link formed by key nodes in all nodes involved in the operation process of the service page;

acquiring key link data in the key link through a software development kit based on the service scene and a preset service requirement, wherein the key link data is acquired in a set field mode;

And after analyzing and processing the key link data according to a preset analysis strategy, displaying an analysis result on a display panel.

2. The method of claim 1, wherein the collecting, by a software development kit, critical link data in the critical link based on the traffic scenario and a preset traffic requirement comprises:

Determining a service embedded point model according to the service scene and a preset service requirement, wherein the service embedded point model adopts a 5w mode for data acquisition;

and acquiring key link data in the key links through the software development tool package and the service embedded point model by setting fields, wherein the setting fields comprise an acquired execution subject, time, place, motivation and content.

3. The method of claim 1, wherein the critical link data comprises base data, link data, performance data, anomaly data, and user behavior data, and wherein collecting the link data comprises:

Acquiring key node data of key nodes in the key links through the software development tool package;

And tracking the key node data of each key node in the same key link to obtain the link data in the key link.

4. The method of claim 1, wherein displaying the analysis result on the display panel after the analyzing the critical link data according to the preset analysis policy comprises:

cleaning the log in the key link data according to a preset cleaning rule;

Aiming at the cleaned log, determining an analysis result of key link data according to a statistical type selected by a user on a display panel, wherein the analysis result comprises site data, page data, performance data and abnormal data, and the site data comprises the total number of sites, the successful number of sites, the error number of site report, the success rate of sites and the failure rate of sites;

and visually displaying the analysis result on a display panel.

5. The method of claim 4, wherein determining the analysis result of the critical link data based on the statistical type selected by the user on the display panel for the cleaned log comprises:

determining a target system type selected by a user on the display panel, wherein the system type comprises a user-oriented system and a background system;

Determining a target system domain name selected by a user on the display panel, wherein each system type corresponds to a plurality of system domain names;

Determining target front-end services selected by a user on the display panel, wherein each system domain name corresponds to a plurality of front-end services;

determining a target service scene selected by a user on the display panel, wherein each front-end service corresponds to a plurality of service scenes;

Determining a target key link selected by a user on the display panel, wherein each service scene corresponds to at least one key link;

determining target key nodes selected by a user on the display panel, wherein each key link corresponds to at least one key node;

and analyzing and processing the data in the target system type, the target system domain name, the target front-end service, the target service scene, the target key link or the target key node to obtain an analysis result.

6. The method of claim 4, wherein after visually displaying the analysis results on the display panel, the method further comprises:

If a click command aiming at the analysis result on the display panel is monitored, linking to a log query platform;

And displaying the log corresponding to the analysis result in the log query platform.

7. A method according to claim 3, wherein the user behavior data is operation behavior data of a user in the page running process, the operation behavior data of each key node carries a user identifier, and after the analysis result is visually displayed on the display panel, the method further comprises:

Aiming at the abnormal result, the key nodes with the operation behavior data of the user identifier are connected in series through the link log to obtain a user operation link;

And carrying out anomaly analysis on the data in the user operation link.

8. The method of claim 1, wherein prior to collecting critical link data in the critical link by a software development kit, the method further comprises:

acquiring user behavior data in a full link according to the full link involved in the operation process of the service page;

Establishing a user portrait according to the user behavior data;

and determining a key link according to the user portrait.

9. An apparatus for analyzing a critical link, the apparatus comprising:

The system comprises a determining module, a processing module and a processing module, wherein the determining module is used for determining at least one key link involved in the operation process of a business page in a business scene according to the business scene aimed at by front-end business, wherein the business scene is a scene facing a set user or a set terminal, the business page is a page interacted with the user, and the key link is a link formed by key nodes in all nodes involved in the operation process of the business page;

The acquisition module is used for acquiring key link data in the key link through a software development kit based on the service scene and the preset service requirement, wherein the key link data is acquired in a set field mode;

And the display module is used for displaying the analysis result on the display panel after analyzing and processing the key link data according to a preset analysis strategy.

10. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;

A memory for storing a computer program;

a processor for implementing the method of any of claims 1-8 when executing a program stored on a memory.

11. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program which, when executed by a processor, implements the method of any of claims 1-8.