A performance testing method and system for large amounts of industrial software data

Abstract

The present invention discloses a performance testing method and system for large amounts of industrial software big data. Among them, the performance testing method includes deploying an API request capture tool; simulating user access to the system under test, collecting API request information to generate a performance testing script; deploying a script management center tool for importing test cases, parsing the imported test cases, storing the parsed content in a use case maintenance table, and connecting to the database through a data testing script; deploying a test management center tool, including a message management center module for sending message tasks to the script management center, sending tasks for performance testing of large amounts of data; the performance testing script calls the data testing script, and the data testing script inserts test data into the database based on the status flag of the use case maintenance table, and the generated test data is used for performance testing of large amounts of data; for different business scenarios of industrial software, quickly create test data with large amounts of data.

Description

Technical Field

[0001] The present invention relates to the technical application field of industrial software performance testing, and specifically relates to a performance testing method and system for large amounts of industrial software data. Background Art

[0002] In traditional performance testing, the business scenarios are single, and the performance test results can only be obtained after the end of a single performance test, resulting in message lag and low utilization of time and resources. The invention patent CN201010613464.1 proposed "A Performance Testing System and Method". This system can monitor the performance data of the server under test in real time. When the CPU usage rate of the server under test does not reach the set threshold, the number of concurrent users is increased; when the CPU usage rate of the server under test exceeds the set threshold, the performance test is stopped. This performance testing method achieves a certain degree of unattended operation, but there are still certain defects:

[0003] 1. This system still targets a single performance testing scenario. When the business system is large and there are many performance scenarios to be tested, testers still need to intervene to switch scenarios, and switching business scenarios requires creating a large amount of SQL data, and artificially creating data will take a lot of time.

[0004] 2. This system only monitors the resources of the server under test in real time, with a single judgment condition, and does not obtain and analyze other key performance results, which may cause subsequent performance tests to be invalid and waste the time and resources of subsequent performance tests.

[0005] 3. When the CPU usage rate of the server under test exceeds the set threshold, the current test is stopped, and users cannot be notified in time, and there is still a time difference in problem troubleshooting and subsequent tests. Summary of the Invention

[0006] In order to overcome the above deficiencies in technology, the present invention provides a performance testing method and system for large amounts of industrial software data, which can quickly create test data with large amounts of data for different business scenarios of industrial software, thereby improving the efficiency of manually creating SQL statements. At the same time, it monitors the test results and the hardware resources of the server under test in real time, and when the preset performance indicators and server resources are not met during the test process, it gives timely notification and warning to the testers.

[0007] The first aspect of the present invention proposes a performance testing method for large amounts of industrial software data, including: deploying an API request capture tool, where the API request capture tool is used to collect API request information;

[0008] Based on a preset performance test scenario and performance test requirements, simulate a number of users accessing the corresponding business functions through a browser, collect API request information generated by the access based on an API request capture tool, and thus generate a performance test script; deploy a script management center tool, the script management center tool at least includes a test case maintenance module for importing multiple test cases, a function module for importing the performance test script, and data test scripts corresponding to test cases of different test scenarios. The script management center analyzes the imported test cases through the test case module and stores the parsed content in the case maintenance table. Among them, the data test script at least includes the script required to connect to the database; deploy a test management center tool, the test management center at least includes a message management center module, and the message management center module is used to send a message task to the script management center to start a large-volume performance test; the performance test script calls the data test script, and the data test script inserts simulated data of a preset data volume into the database based on the status flag of the test case maintenance table corresponding to the test case. The generated simulated data is used for the large-volume performance test; the message management center module receives the execution result of the data test script and starts the large-volume performance test task; start collecting test results and analyze the test results.

[0009] Further, the performance test script calls the data test script, and the data test script inserts simulated data of a preset data volume into the database based on the status flag of the test case maintenance module, specifically including: after the script management center tool receives the large-volume performance test request from the message management center module, it starts to execute the test case, and calls the data test script through the performance test script. The data test script judges whether it is necessary to insert data of a preset data volume based on the status flag of the test case maintenance table. If the status flag indicates that there is already data for performance testing, there is no need to insert data again. If the status flag indicates that there is no data for performance testing, insert data of a preset data volume.

[0010] Further, the inserting of data of a preset data volume specifically includes: in the data test script, initialize the database connection through the set database information and table name, and call the database insert statement; obtain a cursor object for the executable SQL statement, write the inserted data in the form of a random variable and insert it in large batches through a loop. After the execution based on the preset data volume is completed, send a message to the message management center indicating that the insertion is completed, and return the result set in the form of a tuple.

[0011] Further, it also includes adding the identifier of the interface sending the API request and the identifier of the test step to the performance test sample and saving it.

[0012] Furthermore, start collecting test results and analyzing the test results, specifically including saving the stress test result data of each user server and the resource usage data of the server where the industrial software to be tested is deployed to a time series database according to the time series. Each piece of data includes at least a timestamp, and the data is sent regularly. Based on the Web page visual view, dynamically display the stress test result data and the resource usage data of the server.

[0013] Furthermore, it also includes: if the test result data is incorrect or the resource usage data of the server exceeds the preset threshold, notify the recipients set in the test parameter configuration through the message middleware, and view the stress test result data and the resource usage data of the server through the Web page access of the test management center tool.

[0014] Furthermore, the performance test method for the large amount of industrial software data also includes collecting, storing, and filtering the logs based on the preset log level, and displaying the logs based on graphical programming to quickly locate problems.

[0015] Furthermore, the test management center tool also includes a system configuration module, a resource file module, a task scheduling module, a monitoring module, a data analysis module, and a data display module; the system configuration module is used to configure the running parameters of the tested server and the test execution machine and the test environment; the resource file module is used to configure the test script; the task scheduling module is used to configure the task name, select the test script to be executed, the execution time and frequency, and start the performance test and execute the test script after the task is built and executed. The monitoring module is used to monitor the running conditions of the tested server and the test execution machine pool, and collect the running data of the tested server and the test execution machine pool; the data analysis module is used to analyze and summarize the performance test result indicators and the server resource usage through Python programming; the data display module is used to perform real-time dynamic display of various performance test result indicators and server resource usage set by the user through the visual view; the message management center module is also used to configure relevant notification personnel, notification methods, and notification frequencies, and notify the relevant person in charge in time through the message middleware; the log management module is used to collect the log files during the execution process of the test execution machine pool.

[0016] Furthermore, the data test script is a Python script, and the performance test script is a Jmeter script.

[0017] The second aspect of the present invention also proposes a performance testing system for running the above performance testing method, which at least includes a script management center, a real-time monitoring center, and a message management center. The script management center is used to adapt to different business scenarios to run corresponding scripts and create test data. The real-time monitoring system is used to obtain the performance test results and server resource information after running the script in real time and send them to the message management center. The message management center feedbacks the test results based on preset thresholds, performance test results, and server resource information.

[0018] The beneficial effects of the present invention are as follows:

[0019] 1. For the pain points of complex business scenarios, large data volume, and high timeliness in the performance testing of industrial software, different scripts are called to quickly generate a large amount of database data.

[0020] 2. During the performance testing process, the performance test results and server resources are monitored in real time, and messages are actively sent to users in a timely manner so that users can make quick adjustments. It is a performance testing method with good adaptability, strong pertinence, and high speed and efficiency in the field of industrial software.

[0021] 3. At the same time, by configuring scheduled tasks, the test results can be sent to the analysis device in real time. The analysis device can analyze the results and send the analysis results to the user through the mail configuration server, truly realizing an unattended performance testing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a schematic flow chart of the performance testing method for industrial software with a large amount of data in an embodiment of the present invention;

[0023] Figure 2 It is a schematic flow chart of generating performance test samples in an embodiment of the present invention;

[0024] Figure 3 It is an example diagram of the working process of the script management center tool in an embodiment of the present invention;

[0025] Figure 4 It is a schematic diagram of test case maintenance in an embodiment of the present invention

[0026] Figure 5 It is a schematic flow chart of the test results exceeding the preset threshold during the test execution in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] API: Application Programming Interface, also known as application programming interface, is an agreement for connecting different components of a software system.

[0028] Test case: A specific set of input data, operations or various environment settings, and expected results provided to the system under test for the purpose of testing;

[0029] Test script: A script written for automated testing. The writing of the test script must correspond to the corresponding test case;

[0030] Fiddler: An Internet debugging proxy tool that can not only capture various HTTP communications between computers and even mobile phones and the Internet, but also view them for analysis.

[0031] Jmeter: Software used to test client / server architectures (e.g. web applications). It can be used to test the performance of both static and dynamic resources.

[0032] In order to facilitate those skilled in the art to better understand the present invention, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. The following is only exemplary and does not limit the scope of protection of the present invention.

[0033] The present invention discloses a performance testing method for industrial software with large data volumes, such as Figure 1 The figure shows a flow chart of the performance testing method for industrial software with large amounts of data, which specifically includes: deploying an API request crawler tool, which is used to collect API request information; based on preset performance test scenarios and performance test requirements, simulating several users accessing corresponding business functions through browsers, and collecting the API request information generated by the access based on the API request crawler tool, thereby generating a performance test script; deploying a script management center tool, which includes at least a test case maintenance module for importing multiple test cases, a function module for importing performance test scripts, and data test scripts for test cases corresponding to different test scenarios. The script management center parses the imported test cases through the test case module and stores the parsed content in the use case maintenance table. Among them, the data testing script includes at least the script required to connect to the database; the test management center tool is deployed, and the test management center includes at least a message management center module, and the message management center module is used to send message tasks to the script management center to start performance testing of large amounts of data; based on the script management center tool, the performance testing script is imported, the message management center receives the message, and sends the scheduling task to the script management center; the performance testing script calls the data testing script, and the data testing script inserts a preset amount of simulated data into the database based on the status flag of the test case maintenance table of the corresponding test case, and the generated simulated data is used for performance testing of large amounts of data; the message management center module receives the execution result of the data testing script and starts the performance testing task of large amounts of data; start collecting and analyzing the test results.

[0034] Taking the performance test of a large number of industrial software applied in the pharmaceutical industry as an example, each step will be described below.

[0035] S1. Deploy an API request capture tool, which is used to collect API request information.

[0036] In an embodiment of the present invention, Fiddler is used as the API request capture tool. Download and install Fiddler. When users are testing, start Fiddler to implement the API request capture tool.

[0037] S2. Based on a preset performance test scenario and performance test requirements, simulate a number of users to access the corresponding business functions through a browser, and collect the API request information generated by the access based on the API request capture tool, so as to generate a performance test script.

[0038] According to the application scenario of the industrial software to be tested and the requirements of the corresponding performance test, simulate users to access the tested system, that is, the industrial software to be tested, through a browser. Simulate users to send API requests to the tested system through a browser.

[0039] For example, when multiple users request a certain business function at the same time, install and start Fiddlerr in the tested system, simulate users to access the tested system through a browser, and the process is shown as Figure 2 shown. Fiddlerr intercepts the API requests sent by simulated users, collects all API request information generated during the operation of the Web product, and saves it to form a script in Jmeter format.

[0040] In some embodiments, it further includes adding the identifier of the interface sending the API request and the identifier of the test step to the performance test sample. In addition, a unique ID is generated according to the timestamp of the request sent, and the request path is intercepted to generate a value, and a request identifier is added according to the form of the ID and the value.

[0041] S3. Deploy a script management center tool. The script management center tool at least includes a test case maintenance module for importing multiple test cases, an import performance test script function module for importing performance test scripts, and data test scripts for test cases corresponding to different test scenarios. The script management center analyzes the imported test cases through the test case module and stores the analyzed content in the case maintenance table. Among them, the data test script connects to the database.

[0042] The script management center is implemented by python. After writing a python script file, it is imported into the script management center. The script management center analyzes the imported test cases and manages the test cases. The working schematic diagram of the script management center tool is as Figure 3As shown. The script management center imports the performance test script. When the message management center module receives a message, it sends a task to the script management center. Then the script management center starts the task, executes the performance test script, and judges the status flag of the test case. If the status flag of the test status case is False, it calls the data test script to generate a large amount of test data. After the execution is completed, the data test script sends a message to the message management center module to start the performance test with a large amount of data.

[0043] In some embodiments, the script management center has an import button to import the performance test script, that is, to import the test case. The test cases are maintained and stored in the oracle data table in the script management center. The table creation statement is as follows:

[0044] CREATE TABLE "TEST_CASES" ("ID" NUMBER(20,0) NOT NULL ENABLE, "CASE_NAME" VARCHAR2(256) NOT NULL ENABLE, "PYCASENAME" VARCHAR2(20,0) NOT NULL ENABLE, "OPERATE" VARCHAR2(256) NOT NULL ENABLE, "STATUS" NUMBER(1,0) DEFAULT 0, "CREATOR" VARCHAR2(64), "MODIFY_TIME" TIMESTAMP(6) DEFAULT NULL, PRIMARY KEY("ID"));

[0045] ID: Represents the unique identifier of our script case table

[0046] CASE_NAME: Represents the case name, the custom name of the test case, such as Test Case 1, Test Case 2

[0047] PYCASENAME: Represents the corresponding python script file of the case

[0048] STATUS: Status, the effective case is identified by True, and the invalid case is identified by False

[0049] OPERATE: Operations are stored in the database with 0, 1, 2. 0 represents edit, 1 represents execute, and 2 represents delete

[0050] CREATOR: Represents who created the case

[0051] MODIFY_TIME: Modification time, represents the modification time of the case

[0052] When we execute a test case, the corresponding Python script file will be run. By entering the starting value and the ending value in the interface, data can be generated. Therefore, as long as multiple Python scripts are written to implement different business scenarios, the test cases can cover different business scenarios. To write a Python script file, first, a case maintenance directory needs to be created, such as: D:\datatest\case\test_process_type.py. The schematic diagram of the case maintenance table in this implementation example is as Figure 4 shown.

[0053] S4. Deploy the test management center tool. The test management center at least includes a message management center module, which is used to send message tasks to the script management center to start the performance test with a large amount of data.

[0054] In some embodiments, the test management center tool includes the following modules: System configuration module: mainly used to configure the operating parameters of the server under test, the test execution machine, and the test environment. Resource file module: mainly used to configure test scripts. Task scheduling module: mainly used to configure the task name, select the test script to be executed, the execution time, and frequency. After the task is constructed and executed, the performance test is started and the test script is executed. Monitoring module: mainly used to monitor the running status of the server under test and the test execution machine pool, and collect the running data of the server under test and the test execution machine pool; Data analysis module: used to analyze and summarize the performance test result indicators and the server resource usage through Python programming. Data display module: used to perform real-time dynamic display of various performance test result indicators and server resource usage settings by the user in a visual manner. Message management center module: mainly used to configure relevant notification personnel, notification methods, and notification frequencies, and timely notify relevant responsible persons and the script management center to start tasks through a message middleware. Log management module: mainly used to collect log files during the execution process of the test execution machine pool.

[0055] The test management center tool can be accessed through a Web page.

[0056] Import multiple test cases in the case maintenance module of the script management center. One test case corresponds to one performance test script. Users can directly access the Web interface to import performance test scripts in the resource file, set and modify the number of virtual users, user think time, test result saving path, etc. in the test parameters of the system settings of the system to be tested. In the threshold management, CPU, memory, IO, network card usage thresholds, test error rate thresholds, log levels, various index display situations of test results, server resource usage situations, etc. of the stress test server resources can be newly added. At the same time, configure scheduled tasks in the task scheduling, build triggers to execute scheduled tasks, and configure post-build operations, configure test report templates and email recipient information, where the test report templates support default templates and user-defined settings; achieve unattended operation.

[0057] Among them, for the configuration of the scheduled task, it can trigger the interface to send tasks, that is, the test results can be sent to the information collection device at a fixed time for the collection of test results.

[0058] S5, the performance test script calls the data test script. The data test script inserts simulated data with a preset data volume into the database based on the status flag of the test case maintenance table corresponding to the test case. The generated simulated data is used for performance testing with a large amount of data.

[0059] Different test cases can be clicked according to the business scenario. When we execute a certain test case, that is, after starting the performance test with a large amount of data, the corresponding python script file will be run, initiating the insertion of data into the database. The data is written in the form of random variables and inserted through a loop to effectively achieve batch test data. During the data insertion process, we will also judge whether to insert according to the status field of the test case maintenance table. If the data already exists, it is not necessary to insert again. If it does not exist, the data insertion preparation will start.

[0060] Taking the connection to the oracle database in the data test script as an example, to create one million data in the oracle database, we can define a table object class class A, initialize the database connection cx - Oracle, obtain a cursor object that can execute SQL statements, and the result set returned after execution is displayed in tuple form by default.

[0061] In some embodiments, for example, for the creation time field, by setting a string in a time format and writing a for loop, the time field dt inserted in each loop will automatically decrease by one day, i.e., dt=(dt+datetime.timedelta(days=-1)). If modifying the time field may require fixing data within a certain time period, the time can be converted to the corresponding timestamp modify_time=time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(1585497600-random.randrange(1,1000000))). Then, data can be inserted in batches through the executemany method, i.e., insert into table name (fields) values (placeholder).

[0062] Another business scenario is for different fields such as the ID field. In the loop, the ID is located as str(i), and for the input_key field, we set input_key='LIMS: ammonia nitrogen content'+shift_date.

[0063] S6, the message management center module receives the execution result of the data test script and starts a performance test task with a large amount of data;

[0064] S7, start collecting test results and analyzing the test results.

[0065] When starting the performance test task, the result collection device and the server monitoring device are started. Among them, the server monitoring device monitors the hardware resources of the server under test, and the result collection device collects performance test receipts. In an embodiment of the present invention, through the configuration of a scheduled task, an interface is triggered to send a task, and the test results are sent to the result collection device at regular intervals. The stress test results of each server and the server resource usage conditions are collected and saved in a time series database. In a database stored based on time, each piece of data has a timestamp; the collected test results are integrated and sent to the analysis device. The analysis device conducts data summarization and analysis based on the collected test result data and server resource usage data, and performs real-time dynamic display of various performance test result indicators and server resource usage conditions set by the user in a visual manner. When the test result error rate or the server resource usage rate exceeds the set threshold, the flowchart is as Figure 5 shown. Through the message middleware, relevant responsible persons are notified in a timely manner. The relevant responsible persons can access and view the historical test index data and server resource monitoring data through the Web page for troubleshooting and analysis.

[0066] Users can learn the real-time performance test results in a timely manner and perform manual intervention in a timely manner, avoiding the waste of time and resources during the period from the occurrence of errors in the performance test to the end of the performance test, and ensuring the efficiency of the performance test.

[0067] S8, collect, store and filter logs based on a preset log level, and display the logs through Python graphical programming, so as to quickly locate problems.

[0068] In some embodiments, the log management module based on the script management center is used to collect the log information generated by the test execution machine pool. The optional log levels are as follows: DEBUG < INFO < WARNING < ERROR < Fatal. Date files corresponding to the dates are generated and saved on the hard disk. The log analysis will parse the log files of the dates and search according to the keywords input by the user, enabling quick location.

[0069] S9. Configure the mail service center to send the test report results to different users

[0070] In some embodiments, it also includes configuring the mail service center to send the test report results to different users.

[0071] Another aspect of the present invention provides an industrial software large - data - volume performance testing system, which at least includes a script management center, a real - time monitoring center, and a message management center. The script management center is used to adapt to different business scenarios to run corresponding scripts and create test data; the real - time monitoring system is used to obtain the performance test results and server resource information after running the scripts in real time and send them to the message management center; the message management center feeds back the test results based on preset thresholds, performance test results, and server resource information.

[0072] It should be noted that: in other embodiments, the steps of the corresponding methods are not necessarily executed in the order shown and described in this specification. In some other embodiments, the steps included in the method may be more or less than those described in this specification. In addition, a single step described in this specification may be decomposed into multiple steps for description in other embodiments; and multiple steps described in this specification may also be combined into a single step for description in other embodiments.

[0073] Each embodiment in this specification is described in a progressive manner. The same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiments. The systems and system embodiments described above are merely illustrative, and some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

Claims

1. A performance testing method for industrial software with large amounts of data, characterized in that: include: Deploy an API request crawler tool, wherein the API request crawler tool is used to collect API request information; Based on the preset performance test scenarios and performance test requirements, simulate several users accessing the corresponding business functions through browsers, collect the API request information generated by the access using API request crawling tools, and then generate performance test scripts; Deploy a script management center tool, which includes at least a test case maintenance module for importing multiple test cases, a function module for importing performance test scripts, and data test scripts for test cases corresponding to different test scenarios. The script management center parses the imported test cases through the test case module and stores the parsed content in a case maintenance table, wherein the data test scripts include at least the scripts required for connecting to the database; Deploy a test management center tool, which includes at least a message management center module. The message management center module is used to send message tasks to the script management center to start performance testing of large amounts of data; The performance test script calls the data test script. The data test script inserts a preset amount of simulated data into the database based on the status flag of the test case maintenance table of the corresponding test case. The generated simulated data is used for performance testing of large amounts of data. The message management center module receives the execution results of the data test script and starts the performance test task of large data volume; Start test result collection and analyze test results; The inserting of a preset amount of data includes: In the data test script, the database information and table name are set to initialize the database connection and call Database insert statement; Get the cursor object that can execute SQL statements, write the inserted data into the form of random variables and insert them in batches through a loop. After the execution is completed based on the preset data volume, send the message management center an insertion completion message and return the result set to display in tuples.

2. The performance testing method for industrial software with large amounts of data according to claim 1, characterized in that: The performance test script calls the data test script, and the data test script inserts a preset amount of simulated data into the database based on the status flag of the test case maintenance module, specifically including: After receiving the performance test request of large data volume from the message management center module, the script management center tool starts to execute the test case and calls the data test script through the performance test script. The data test script determines whether it is necessary to insert the preset data volume based on the status flag of the test case maintenance table. If the status flag indicates that data for performance testing already exists, there is no need to insert data. If the status flag indicates that there is no data for performance testing, a preset amount of data is inserted.

3. The performance testing method for industrial software with large data volumes according to claim 1, characterized in that: The method also includes adding the identifier of the interface for sending the API request and the identifier of the test step to the performance test sample and saving the result.

4. The performance testing method for industrial software with large amounts of data according to claim 1, characterized in that: Start collecting and analyzing test results, including: The stress test result data of each user server and the resource usage data of the server where the industrial software to be tested is deployed are saved in a time series database in time series. Each piece of data includes at least a timestamp and the data is sent regularly. The stress test result data and the resource usage data of the server are dynamically displayed based on a visual graph on a web page.

5. The performance testing method for industrial software with large data volumes according to claim 4, characterized in that: Also includes: If the test result data is incorrect or the server resource usage data exceeds the preset threshold, the recipients set in the test parameter configuration will be notified through the message middleware, and the stress test result data and server resource usage data can be viewed through the web page of the test management center tool.

6. The performance testing method for industrial software with large amounts of data according to claim 5, characterized in that: The performance testing method for industrial software with large amounts of data also includes collecting, storing, and filtering logs based on preset log levels, and displaying logs based on graphical programming to quickly locate problems.

7. The performance testing method for industrial software with large amounts of data according to claim 5, characterized in that: The test management center tool also includes a system configuration module, a resource file module, a task scheduling module, a monitoring module, a data analysis module and a data display module; The system configuration module is used to configure the tested server, test execution machine operating parameters and test environment; The resource file module is used to configure the test script; The task scheduling module is used to configure the task name, select the test script to be executed, the execution time and frequency, and, after the task is built and executed, start the performance test and execute the test script; The monitoring module is used to monitor the operation of the tested server and the test execution machine pool, and collect the operation data of the tested server and the test execution machine pool; The data analysis module is used to analyze and summarize the performance test result indicators and server resource usage through Python programming; The data display module is used to display various performance test result indicators and server resource usage set by the user in real time in a visual and dynamic manner; The message management center module is also used to configure relevant notification personnel, notification methods, and notification frequencies, and to promptly notify relevant persons in charge through the message middleware.

8. The performance testing method for industrial software with large data volumes according to any one of claims 1 to 7, characterized in that: The data test script is a Python script, and the performance test script is a Jmeter script.

9. A performance testing system for running the industrial software large data volume performance testing method according to any one of claims 1 to 8, characterized in that: At least including script management center, real-time monitoring center and message management center, The script management center is used to adapt to different business scenarios to run corresponding scripts and create test data; The real-time monitoring center is used to obtain the performance test results and server resource information after running the script in real time and send them to the message management center; The message management center feeds back test results based on preset thresholds, performance test results, and server resource information.

Images