Data processing method and device, equipment, medium and product

Abstract

The invention discloses a data processing method and device, equipment, a medium and a product, and is applied to the technical field of big data, the data processing method comprises the steps that a data link is acquired, the data link comprises at least two target micro-services and a data transmission relation between the at least two target micro-services, each target micro-service in the at least two target micro-services is provided with a data acquisition point; collecting log data of a target micro-service where the data collection point is located through the data collection point; performing data integration processing on the log data of the at least two target micro-services to obtain test general situation report data of the data link; and displaying a visual interface corresponding to the test general situation report data according to the test general situation report data. In the embodiment of the invention, the problem that the mode of manually inputting the test data is easily influenced by factors such as subjective judgment and skill level of testers, so that the test data is inaccurate can be effectively avoided.

Description

Technical Field

[0001] The present application belongs to the field of big data technology, and in particular relates to a data processing method, device, equipment, medium and product. Background Art

[0002] The microservice architecture splits the application into multiple independent microservices, each of which can be independently deployed, expanded, and maintained. Multiple microservices communicate with each other through interfaces, forming dependencies. Therefore, when testing microservices, you need to ensure that all dependent microservice interfaces are working properly in order to conduct effective testing.

[0003] In the related art, testers are usually required to manually input the test data such as request data and response data of each microservice that each tested microservice depends on. However, this method of manually inputting test data is easily affected by factors such as the tester's subjective judgment and skill level, resulting in inaccurate test data. Summary of the invention

[0004] The embodiments of the present application provide a data processing method, apparatus, device, medium and product, which can effectively avoid the problem of inaccurate test data caused by the manual entry of test data, which is easily affected by factors such as the subjective judgment and skill level of the tester.

[0005] In a first aspect, an embodiment of the present application provides a data processing method, the data processing method comprising:

[0006] Acquire a data link, where the data link includes at least two target microservices and a data transmission relationship between at least two target microservices, and each of the at least two target microservices is provided with a data collection point;

[0007] Collect log data of the target microservice where the data collection point is located through the data collection point;

[0008] Perform data integration processing on the log data of at least two target microservices to obtain test overview report data of the data link;

[0009] According to the test overview report data, a visualization interface corresponding to the test overview report data is displayed.

[0010] In some implementations of the embodiments of the present application, before executing the step of acquiring the data link, the data processing method further includes:

[0011] According to the test task requirements, determine at least two target microservices participating in the data link and the data transmission relationship between at least two target microservices;

[0012] According to at least two target microservices and the data transmission relationship between at least two target microservices, a data link corresponding to the test task requirements is constructed.

[0013] In some implementations of the embodiments of the present application, the test task requirement includes a first test task requirement and a second test task requirement; and determining, according to the test task requirement, at least two target microservices participating in the data link and a data transmission relationship between the at least two target microservices, including:

[0014] According to the requirements of the first test task, select at least two target microservices from multiple microservices;

[0015] According to the second test task requirement, a data transmission relationship between at least two target microservices is generated.

[0016] In some implementations of the embodiments of the present application, before executing the step of acquiring the data link, the data processing method further includes:

[0017] By means of plug-in tracking, a data collection point is set on each of the at least two target microservices. The data collection point is configured with a collection rule, and the collection rule is determined based on the test task requirements and the data transmission relationship between the at least two target microservices.

[0018] In some implementations of the embodiments of the present application, the log data of at least two target microservices includes first log data and second log data, the first log data is log data of each target microservice in the at least two target microservices within a first time period, and the second log data is log data of each target microservice in the at least two target microservices within a second time period, and the second time period is earlier than the first time period in time; the test overview report data includes first test overview report data and second test overview report data;

[0019] Perform data integration processing on the log data of at least two target microservices to obtain test overview report data of the data link, including:

[0020] Generate first total indicator data according to the first preset performance indicator and the first summary data, the first summary data including the first log data of each target microservice, the first total indicator data including the first indicator data corresponding to the first log data of each target microservice in at least two target microservices, the first indicator data being used to characterize the test result of the target microservice corresponding to the first preset performance indicator in the first time period;

[0021] Performing data integration processing on the first indicator data in the first total indicator data to generate first test overview report data of the data link;

[0022] Generate second total indicator data according to the second preset performance indicator and the second summary data, where the second summary data includes the second log data of each target microservice, and the second total indicator data includes the second indicator data corresponding to the second log data of each target microservice in at least two target microservices;

[0023] Data integration processing is performed on the second indicator data in the second total indicator data to generate second test overview report data of the data link.

[0024] In some implementations of the embodiments of the present application, the visual interface includes a first display area and a second display area;

[0025] According to the test profile report data, a visualization interface corresponding to the test profile report data is displayed, including:

[0026] Displaying visualization content corresponding to the first test overview report data in the first display area;

[0027] Visual content corresponding to the second test overview report data is displayed in the second display area.

[0028] In some implementations of the embodiments of the present application, the data processing method further includes:

[0029] In the case where new log data is collected through the data collection point of the i-th target microservice among the at least two target microservices, the log data of the at least two target microservices are updated based on the new log data, so as to perform data integration processing on the updated log data to obtain test overview report data of the data link, where i is a positive integer.

[0030] In some implementations of the embodiments of the present application, the visualization interface includes a plurality of data element options, and the data element options correspond to data in the test profile report data;

[0031] The data processing method also includes:

[0032] receiving a user input on a target data element option, where the target data element option is at least one of a plurality of data element options;

[0033] In response to the input, obtaining target data corresponding to the target data element option from the test profile report data;

[0034] Based on the target data, display at least one of the following:

[0035] A visualization interface corresponding to the target data, and target content corresponding to the target data.

[0036] In a second aspect, an embodiment of the present application provides a data processing device, the device comprising:

[0037] An acquisition module, used to acquire a data link, the data link includes at least two target microservices and a data transmission relationship between at least two target microservices, each of the at least two target microservices is provided with a data collection point;

[0038] The collection module is used to collect log data of the target microservice where the data collection point is located through the data collection point;

[0039] A processing module, used to perform data integration processing on the log data of at least two target microservices to obtain test overview report data of the data link;

[0040] The first display module is used to display a visual interface corresponding to the test overview report data according to the test overview report data.

[0041] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the data processing method as described in any one of the first aspects is implemented.

[0042] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon, and when the computer program instructions are executed by a processor, a data processing method as described in any one of the first aspects is implemented.

[0043] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, they implement the data processing method as described in any one of the first aspects.

[0044] The data processing method, device, equipment, medium and product of the embodiment of the present application can realize the collection of log data on the data link by setting at least two data collection points on at least two target microservices. By comparing the difference between the actually collected log data and the expected log data, it can be verified whether the data link is working properly, that is, the test data corresponding to the data link is determined. Then, the collected log data is processed for data integration, and a relatively complete test overview report data of the data link can be obtained. The method of determining the test overview report data by collecting log data avoids the influence of human factors on the test data collection and improves the accuracy of the test data. Subsequently, a visual interface corresponding to the test overview report data is displayed, which is conducive to intuitively and clearly displaying the operating status and fault problems on the corresponding data link, so that the user can quickly locate the fault problem in the data link, effectively accelerate the process of solving the fault problem, and improve the test efficiency of the data link. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0046] Figure 1 A schematic diagram showing a flow chart of a data processing method provided by an embodiment of the present application is shown;

[0047] Figure 2 An architectural diagram showing the association relationship between a microservice architecture, a data link, and a data processing container provided by an embodiment of the present application is shown;

[0048] Figure 3 A schematic diagram of a process for establishing a data link provided by an embodiment of the present application is shown;

[0049] Figure 4 A flowchart showing a specific implementation of step 310 provided in an embodiment of the present application is shown;

[0050] Figure 5 A flowchart showing a specific implementation of step 130 provided in an embodiment of the present application is shown;

[0051] Figure 6 A flowchart showing a specific implementation of step 140 provided in an embodiment of the present application is shown;

[0052] Figure 7 A schematic diagram of a process of displaying target data provided by an embodiment of the present application is shown;

[0053] Figure 8 A schematic diagram showing the structure of a data processing device provided by an embodiment of the present application is shown;

[0054] Fig. 9 A schematic structural diagram of an electronic device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0055] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0056] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0057] It should be noted that the acquisition, storage, use and processing of data in the embodiments of the present application are in compliance with the relevant provisions of national laws and regulations.

[0058] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0059] Before explaining the technical solutions provided by the embodiments of the present application, in order to facilitate the understanding of the embodiments of the present application, the present application first specifically describes the relevant technologies.

[0060] Microservice architecture is an architectural pattern that splits a large application system into multiple independent microservices and communicates through message queues and other means. When splitting an application system, it can be divided according to business logic or according to the modules of the application system.

[0061] For example, if there is an online shopping platform system, the online shopping platform system provides a series of functions such as user registration, login, product browsing, order purchase, and payment. If the online shopping platform system is divided according to the division method of business logic division, multiple independent microservices can be obtained. Multiple independent microservices may include user management microservices, product management microservices, and order processing microservices. The user management microservice is responsible for functions such as user registration, login, and personal information management. The product management microservice is responsible for functions such as product listing, delisting, and price adjustment. The order processing microservice is responsible for functions such as user order placement, payment, and delivery.

[0062] Each microservice usually has one or more interfaces. For example, the user management microservice is provided with an interface for user registration, an interface for user login, an interface for updating user information, and an interface for users to obtain user information.

[0063] Before the development of the application system and throughout the development cycle, it is necessary to conduct comprehensive testing on multiple independent microservices corresponding to the application system. Specifically, the interfaces of the microservices are tested. These interface tests are designed to ensure the functional correctness and performance of each microservice, thereby improving the overall stability and reliability of the system. When testing a single microservice, the status and behavior of other microservices that interact with it must also be considered. This dependency greatly increases the complexity and difficulty of testing, because changes to any microservice may affect other microservices, triggering a chain reaction. Therefore, testers need to design more complex and sophisticated test cases to cover various possible interaction scenarios and boundary conditions.

[0064] Since each microservice may have multiple interfaces with different functions, in the test case, a corresponding test case should be set for each interface of each microservice to perform interface functional testing, performance testing, security testing, compatibility testing, document consistency testing, etc. Through comprehensive interface testing, potential problems can be discovered and fixed in a timely manner, improving the reliability of the application system and user experience. Specifically, the process of interface testing usually includes determining the interface, writing test cases, preparing the test environment, executing test cases, recording and analyzing test results, and writing test reports, listing the test case results, problems, and suggested solutions.

[0065] In the related art, it is usually necessary to manually record and analyze the test results. This method of manually recording and analyzing the test results is not only inefficient, but also easily affected by the subjective judgment and skill level of the tester, resulting in inaccurate test results.

[0066] In order to solve the problems in the related art, the embodiments of the present application provide a data processing method, device, equipment, medium and product. Figure 1 To Attachment Figure 7 , the data processing method provided in the embodiment of the present application is described in detail through specific embodiments and their application scenarios.

[0067] Figure 1 FIG. 1 is a flow chart of a data processing method provided by an embodiment of the present application. Figure 1 As shown, the data processing method may include steps 110 to 140.

[0068] Step 110: Acquire a data link, where the data link includes at least two target microservices and a data transmission relationship between the at least two target microservices, and each of the at least two target microservices is provided with a data collection point.

[0069] Step 120: Collect log data of the target microservice where the data collection point is located through the data collection point.

[0070] Step 130: perform data integration processing on the log data of at least two target microservices to obtain test overview report data of the data link.

[0071] Step 140: displaying a visualization interface corresponding to the test overview report data according to the test overview report data.

[0072] Thus, the collection of log data on the data link can be realized by setting at least two data collection points on at least two target microservices. By comparing the difference between the actually collected log data and the expected log data, it is possible to verify whether the data link is working properly, that is, to determine the test data corresponding to the data link. Then, the collected log data is processed for data integration, and a relatively complete test overview report data of the data link can be obtained. The method of determining the test overview report data by collecting log data avoids the influence of human factors on the test data collection and improves the accuracy of the test data. Subsequently, a visual interface corresponding to the test overview report data is displayed, which is conducive to intuitively and clearly displaying the operating status and fault problems on the corresponding data link, so that users can quickly locate the fault problems in the data link, effectively accelerate the process of solving the fault problems, and improve the test efficiency of the data link.

[0073] The above steps are described in detail below, as shown below.

[0074] First, the meanings of the data link, target microservice, data transmission relationship and data collection point involved in step 110 of the embodiment of the present application are specifically explained.

[0075] A data link refers to a link for intercommunication of data, which allows data exchange and communication between different target microservices. It can be understood that one data link corresponds to one of the aforementioned test cases.

[0076] Target microservices refer to microservices that are selected as data link participants in a specific application scenario or business process. These target microservices may be used to process specific business logic, data storage, or data conversion. Referring to the online shopping platform system mentioned above, the target microservices participating in a data link may include user management microservices, product management microservices, and order processing microservices.

[0077] Data transmission relationship refers to the rules on how data flows, exchanges, and processes between at least two target microservices. Specifically, it can include the direction of data flow, the type of data transmitted, the logic of data processing, etc. By defining the data transmission relationship, the collaborative work between at least two target microservices can be ensured to achieve smooth execution of data transmission.

[0078] Data collection points refer to specific components set up inside the target microservice to collect, monitor, and analyze the flow of data during data transmission. These data collection points can capture various data generated by the target microservice when processing business logic, including but not limited to input data, processing results, exception information, etc.

[0079] Next, we will combine the above online shopping platform system and Figure 2 The data link in step 110 of the embodiment of the present application is described in detail.

[0080] like Figure 2 As shown in the figure, microservice A (user management microservice) is the starting point of the data link and is responsible for verifying the user identity and extracting user information. After receiving the user request from microservice A (user management microservice), microservice B (product management microservice) is responsible for retrieving the product information corresponding to the user request. This step is reflected by arrow a, which represents the data flow from microservice A (user management microservice) to microservice B (product management microservice), and also represents the logical association between user request and product information. After receiving user information and product information, microservice C (order processing microservice) is responsible for a series of operations such as generating orders, executing inventory deductions, and initiating payment requests. This step is reflected by arrow b, which represents the data flow from microservice B (product management microservice) to microservice C (order processing microservice), that is, the transfer of product information to the order processing process. This data link realizes the automated process from user order placement to order processing through the close collaboration between microservices A, B, and C.

[0081] In some embodiments of the present application, in order to improve the efficiency of data link acquisition, it is necessary to pre-build multiple data links corresponding to multiple test cases. Then, in the process of testing the microservice architecture, the pre-built multiple data links can be directly used to perform one-to-one testing. Based on this, before the aforementioned step 110, Figure 3 As shown, the data processing method may further include steps 310 to 320, which are specifically as follows.

[0082] Step 310: Determine at least two target microservices participating in the data link and a data transmission relationship between the at least two target microservices according to the test task requirements.

[0083] For example, the test task requirements refer to the specific test objectives and requirements formulated to ensure that the entire application system or a part of the application system (such as a business process, function or feature) can work as expected. The test task requirements formulated with reference to the aforementioned online shopping platform system may specifically include:

[0084] Functional testing: ensure that users can successfully place orders and pay;

[0085] Integration test: Verify that after receiving the order creation request from the product management microservice, the order processing microservice can correctly transmit the order information to the order processing microservice to check the inventory, and at the same time trigger the payment process of the payment microservice;

[0086] Performance testing: Test the processing capability and response time of the order processing microservice in a high-concurrency scenario.

[0087] Step 320: construct a data link corresponding to the test task requirement according to at least two target microservices and the data transmission relationship between at least two target microservices.

[0088] In an embodiment of the present application, the test task requirements define the scope and content of the test. The test task requirements are used to determine at least two target microservices participating in the data link and the data transmission relationship between at least two target microservices. A data link that meets the test task requirements (i.e., specific business scenario requirements) can be flexibly constructed. The data link constructed corresponding to the test task requirements is actually simulating the test environment corresponding to the test task requirements, thereby verifying whether the functions and performance of each target microservice on the data link under the test environment meet expectations.

[0089] In some embodiments of the present application, the test task requirements may include a first test task requirement and a second test task requirement. The first test task requirement is used to determine which microservices are participants in the test scenario, that is, microservices whose functions and performance need to be verified. The second test task requirement is used to define how the participants in these test scenarios interact with each other. Based on this, Figure 4 As shown, the aforementioned step 310 may specifically include steps 311 to 312.

[0090] Step 311: select at least two target microservices from multiple microservices according to the first test task requirement.

[0091] Step 312: Generate a data transmission relationship between at least two target microservices according to the second test task requirement.

[0092] For example, continue to refer to Figure 2 ,exist Figure 2In the figure, an exemplary microservice architecture 210 includes a service gateway S, microservices A to E. As an intermediary between the client and the microservices, the service gateway S is responsible for routing, filtering, security and other functions to simplify the communication between the client and each microservice. Referring to the above-mentioned online shopping platform system, an exemplary test task requirement is to test the function of creating an order after the user logs in. Based on this, the two target microservices are determined to be microservice A and microservice B. The data transmission relationship between microservice A and microservice B is that the user first performs login verification through microservice A. After successful verification, microservice A passes the user information (such as user identity, permissions, order information, etc.) to microservice B, and microservice B creates an order based on this information.

[0093] Based on the above test task requirements, the interfaces that microservice A needs to call are the user login interface and the forwarding order creation request interface. The interface that microservice B needs to call is the creation order interface. Therefore, the data link 220 constructed for the test task requirements should involve the user login interface of microservice A → the forwarding order creation request interface of microservice A → the creation order interface of microservice B. The specific process corresponding to the data link is: the client calls the user login interface of microservice A through the service gateway S to send a login request to microservice A, and microservice A verifies the login request. After the verification is successful, it sends a valid instruction to the client. After obtaining the valid instruction, the client sends the order information and the valid instruction together to the forwarding order creation request interface of microservice A. After receiving the request information, the forwarding order creation request interface of microservice A will forward the request information to the creation order interface of microservice B. After receiving the request, the creation order interface of microservice B verifies the validity of the order information and creates the order. Through the above steps, it can be tested whether the functions of microservice A and microservice B and the data transmission relationship between them meet expectations.

[0094] In an embodiment of the present application, by screening target microservices and generating data transmission relationships according to the first test task requirements and the second test task requirements respectively, it is possible to ensure that the testing work focuses on key target microservices, which helps to improve the pertinence and effectiveness of the target microservice testing and improve the testing efficiency.

[0095] Next, the meaning of the log data involved in step 120 of the embodiment of the present application is specifically described.

[0096] Log data is text data generated by microservices during operation, used to record information such as system operations, transaction processing, and error occurrence. Specifically, it includes but is not limited to microservice metadata, downstream interface metadata, response time of downstream interfaces, and interface call results. As an example, microservice metadata may include: service name, service version, microservice instance identifier, timestamp, and log level of the microservice. The service name and microservice instance identifier of the microservice are used to distinguish the running instances of the same microservice under different data links. The downstream interface metadata includes the name identifier of the downstream interface called by the microservice, the type of operation performed on the downstream interface, and the request parameters sent to the downstream interface, which may specifically include query parameters, request body, etc. The response time of the downstream interface may include the response time from sending a request to receiving a response, the timeout time of the request timeout, and related processing information. The interface call result may include the response result, the response content returned by the downstream interface, and the exception information.

[0097] It is worth noting that each target microservice will automatically create and maintain log data. By collecting log data on the target microservice, it is possible to monitor and troubleshoot the target microservice on the data link. Figure 2 For example, microservice A, microservice B, and microservice C in the microservice architecture each deploy corresponding data collection points, namely data collection point 1, data collection point 2, and data collection point 3, forming a collaborative data monitoring network. Specifically: Data collection point 1 is used to collect all log data generated by microservice A during operation. Data collection point 2: used to collect all log data generated by microservice B during operation. Data collection point 3: used to collect all log data generated by microservice C during operation.

[0098] By analyzing log data in real time, you can monitor the running status, performance indicators, and health of microservices. When a problem occurs in a data link, log data is the key basis for locating the cause of the problem and tracking the problem trajectory. In addition, by analyzing indicators such as response time and resource consumption in log data, you can identify performance bottlenecks and optimize system performance.

[0099] In one embodiment, when the executor of the data processing method involved above is a test system, and the test system includes at least two target microservices, before the aforementioned step 110, the data processing method may further include setting a data collection point on each of the at least two target microservices by means of plug-in embedding, and the data collection point is configured with a collection rule, and the collection rule is determined based on the test task requirements and the data transmission relationship between the at least two target microservices.

[0100] Exemplarily, plug-in tracking refers to inserting data collection points (i.e., tracking points) through external plug-ins in each of at least two target microservices. These data collection points (tracking points) exist in the form of independent modules, so that each external plug-in can be independently developed and deployed without modifying the main code of each target microservice. This means that testing activities can be carried out independently of production activities without affecting the stability and performance of the production environment. At the same time, since there is no need to modify the production code, potential risks and problems introduced by testing are also avoided. The collection rules define how to capture data from data collection points, including what data to capture, how to format the data, when to trigger the collection (such as event triggering, timed collection, etc.), and how the collected data will be processed and stored.

[0101] As an optional implementation method, you can configure collection rules inside the plug-in. Then, these data collection points can capture the log data of the target microservice based on the corresponding collection rules. Then, the log data of these target microservices is generated in the data analysis container. This plug-in embedding method effectively avoids the potential risks that may be caused by directly modifying the business code, including but not limited to version generation and release.

[0102] In another embodiment, when the execution subject of the data processing method involved above is a test management system, and the test management system does not include at least two target microservices, before the aforementioned step 110, the data processing method may further include sending an instruction to the target microservice, the instruction carrying an installation package containing a data collection point. The instruction instructs the target microservice to install the data collection point according to the installation package, thereby setting the data collection point on the target microservice. Specifically, the installation package includes a collection of necessary components such as software programs, configuration files, and library files, which are used to install and configure the data collection point on the target microservice.

[0103] In the embodiment of the present application, by sending an installation package carrying data collection points, data collection points can be quickly set on the target microservice, shortening the test preparation time. For situations where the target microservice code cannot be directly accessed or modified, a simple and fast data collection point setting solution is provided.

[0104] In another embodiment, when the executor of the data processing method involved above is a test system and the test system includes multiple microservices, before the aforementioned step 110, the data processing method above may further include the following steps of setting a data collection point on each of the multiple microservices by means of plug-in embedding.

[0105] In an embodiment of the present application, by setting a data collection point on each of multiple microservices in advance, it can be reused in multiple microservices without having to perform different data links each time, but the data collection point repeated setting work covering the same microservice effectively improves the efficiency of data collection.

[0106] Furthermore, the meaning of the data integration processing involved in step 130 of the embodiment of the present application is specifically described.

[0107] Data integration processing specifically refers to data integration and data analysis of log data of different target microservices to provide a unified and consistent data view, namely the above-mentioned test overview report data. Specifically, it can include selecting the required log data from each target microservice. Then, the extracted data is preprocessed by data cleaning, data conversion, data integration, etc. to obtain preprocessed data. Then, data analysis is performed based on the preprocessed data to obtain the test overview report data of the data link based on the preprocessed data.

[0108] In the embodiments of the present application, Figure 2 As shown, the embodiment of the present application also provides a data processing container 230 for data processing. Specifically, the data processing container 230 may include a data acquisition module 231, a data preprocessing module 232, a data analysis module 233 and a visualization module 234. After the log data of microservice A, microservice B and microservice C are collected through data acquisition point 1, data acquisition point 2 and data acquisition point 3, the log data is sent to the data acquisition module 231, and the data acquisition module 231 sends the collected log data to the data preprocessing module 232, so that the data preprocessing module 232 performs data integration processing on the collected log data. Then, the data preprocessing module 232 sends the integrated data to the data analysis module 233, so as to further analyze and process the integrated data to obtain the test profile report data. After that, the test profile report data can be sent to the visualization module 234 to display the relevant information of the test profile report data.

[0109] The embodiment of the present application collects the log data of each target microservice through an external plug-in, and sends the log data of each target microservice to a data processing container 200 dedicated to data processing, aiming to achieve zero intrusion to the running production environment or the main application under development. Specifically, the collection, integration and analysis of log data are achieved without modifying the main project code or configuration, thereby effectively avoiding the impact on the stability of the main project.

[0110] In some embodiments, in order to improve the real-time and reliability of data, the above-mentioned data processing method may also include updating the log data of at least two target microservices based on the new log data when new log data is collected through the data collection point of the i-th target microservice among the at least two target microservices, so as to perform data integration processing on the updated log data to obtain test overview report data of the data link, where i is a positive integer.

[0111] In an embodiment of the present application, log data is collected and updated in real time, and then data integration processing is performed based on the instantly updated log data to generate a test overview report that accurately reflects the current performance status of the data link. This greatly enhances the timeliness and completeness of the test overview report data and ensures that users can instantly obtain the latest performance updates of the target microservice.

[0112] Then, the meanings of the test overview report data and the visual interface involved in step 140 of the embodiment of the present application are specifically described.

[0113] The test profile report data can be presented in the form of tables, charts, etc. to fully display the operation status of the data link. The visualization interface is an interface that displays complex data to users in an intuitive way such as graphics and images. The visualization interface corresponding to the test profile report data helps testers quickly understand the operation status of the data link, find faults, and make corresponding decisions.

[0114] In some embodiments of the present application, the log data of the at least two target microservices include first log data and second log data. The first log data is the log data generated by each of the at least two target microservices within a first time period. The second log data is the log data generated by each of the at least two target microservices within a second time period. The second time period is earlier than the first time period in time, that is, the second log data corresponding to the second time period is historical data. The first time period and the second time period respectively represent two different time periods, which are used to distinguish the collection time of the log data. These two time periods can be set according to actual needs, for example, they can be different time units such as days and hours. The number of second time periods can be set to multiple to further enrich the content of the second test profile report data and improve the depth and breadth of data analysis.

[0115] In some embodiments of the present application, the test overview report data may include first test overview report data and second test overview report data. The first test overview report data and the second test overview report data are test overview report data obtained by integrating the first log data and the second log data, respectively. The first test overview report data and the second test overview report data respectively reflect the performance and operation status of each microservice on the data link in two different time periods. Based on this, if Figure 5 As shown, the aforementioned step 130 may specifically include steps 131 to 134.

[0116] Step 131, generating first total indicator data according to the first preset performance indicator and the first summary data, the first summary data including the first log data of each target microservice, the first total indicator data including the first indicator data corresponding to the first log data of each target microservice in at least two target microservices, the first indicator data being used to characterize the test result of the target microservice corresponding to the first preset performance indicator in the first time period.

[0117] Exemplarily, the first preset performance indicator is a predefined indicator for evaluating data link performance, see Figure 2 , specifically including indicators such as test coverage, defect density, defect repair rate, and unrepaired defect statistics. These first preset performance indicators are used to measure the performance and operating status of each target microservice in the data link within the first time period. The first indicator data corresponding to the first log data of each target microservice in at least two target microservices is calculated based on the first preset performance indicator, and is used to reflect the performance of each microservice in the first time period. Next, the above-mentioned first preset performance indicator will be further explained.

[0118] Test coverage indicates the ratio of the number of tested interfaces to the total number of testable interfaces in a given test cycle. This indicator is used to measure the comprehensiveness of the test work and the coverage of system functions. Specifically, test coverage = (number of interfaces tested per day / total number of testable interfaces) * 100%.

[0119] Defect density indicates the number of defects found in a specific amount of code or function points. Lower defect density usually means higher code quality. First, count the total number of newly found defects on that day from the log data. Then, according to the specific situation of the microservice, module or project, select the appropriate unit (such as the number of lines of code, function points, etc.) to estimate its size. Then, calculate the defect density: Defect density = (number of defects found on that day / amount of code or function points).

[0120] The defect repair rate reflects the average or total speed from when the defect is submitted to when it is successfully repaired. First, from the log data, for each repaired defect, record its submission time, repair start time, and repair completion time. Then, for each defect, calculate the time difference from submission to repair completion (i.e., repair cycle). Next, within a specific time period (such as one day), count the number of all defects that have been repaired. After that, you can select the sum of all defect repair cycles, or calculate the average of these cycles as the total repair time. Finally, calculate the repair rate: Repair rate = number of defects repaired / total repair time (sum) or Repair rate = number of defects repaired / (average of all defect repair cycles).

[0121] Step 132: Perform data integration processing on the first indicator data in the first total indicator data to generate first test overview report data of the data link.

[0122] Exemplarily, the data integration process in step 132 has been specifically described in the aforementioned step 130 . For the relevant description of the data integration process, reference may be made to the relevant introduction of the aforementioned embodiment, and no further description is given here.

[0123] Step 133: Generate second total indicator data based on the second preset performance indicator and the second summary data, where the second summary data includes the second log data of each target microservice, and the second total indicator data includes the second indicator data corresponding to the second log data of each target microservice in at least two target microservices.

[0124] Exemplarily, the second preset performance indicator is also an indicator for evaluating the performance of each target microservice in the data link, which covers the first summary data corresponding to the first time period and the second summary data corresponding to the second time period, which helps testers understand the changing trend of the system performance of the data link. The second preset performance indicator may specifically include test defect trends, interface change trends, test situation progress, and test overview statistics. Specifically, the test defect trend is used to evaluate the changing trend of the number of defects found in the system within a cross-day cycle. The interface change trend is used to analyze the changes in indicators such as the frequency of use and response time of the microservice interface to understand the stability and performance of the interface. The test situation progress is used to track the execution progress, coverage, etc. of the data link test, which helps to understand the progress and efficiency of the test activities. The test overview statistics provide a comprehensive performance overview, including but not limited to statistics of key performance indicators such as throughput, response time, and error rate.

[0125] Step 134 , performing data integration processing on the second indicator data in the second total indicator data to generate second test overview report data of the data link.

[0126] In an embodiment of the present application, by collecting the first target test data of the current time period (the Tth time period), and collecting the second target test data of at least one target time period in the past, a multi-scale time series analysis of the test data is achieved, which helps to capture the characteristics and regularities of the test data at different time scales. Then, a first test overview sub-report is generated based on the first target test data, and a second test overview sub-report is generated based on the second target test data. Among them, the first test overview sub-report focuses on the real-time performance of the data link in the current time period (the Tth time period), while the second test overview sub-report provides a performance analysis of the data link with a longer time span, which helps users understand the performance status of each target microservice in the data link from different time scales, and then fully understand the current status and historical trends of the target microservices.

[0127] During specific implementation, through the test overview report data, testers can discover the performance of each microservice on the data link, which not only reveals the current operating status of the microservice, but also discovers the long-term performance change trend of the microservice, which helps to predict and prevent performance problems of the microservice in advance. In addition, based on the analysis of performance indicators, testers can allocate resources more reasonably, optimize the system architecture, and improve resource utilization efficiency. Real-time feedback on test progress and test overview statistics provides a solid data foundation for the dynamic adjustment of test strategies. By analyzing the frequency, duration, and resolution efficiency of interface problems, testers can quickly identify weak links and bottlenecks in the testing process, thereby flexibly adjusting the allocation of test resources, prioritizing the resolution of key issues, and improving the pertinence and effectiveness of testing.

[0128] In some embodiments of the present application, in order to improve the efficiency of data acquisition, the above-mentioned visualization interface may include a first display area and a second display area. Figure 6 As shown, the aforementioned step 140 may specifically include steps 141 to 142.

[0129] Step 141: Displaying visualization content corresponding to first test overview report data in a first display area.

[0130] Step 142: Displaying visualization content corresponding to the second test overview report data in the second display area.

[0131] For example, when it is necessary to display the visualization content corresponding to the first test overview report data in the first display area and to display the visualization content corresponding to the second test overview report data in the second display area, it is usually necessary to use a rendering engine to complete the process. Specifically, the rendering engine can convert the provided data into a format suitable for visual display according to the preset rules and algorithms provided, such as generating corresponding graphical representations, so that the data is presented in an intuitive and easy-to-understand manner.

[0132] Specifically for the first display area, this usually refers to a specific interface or window in which users can view and analyze data. By processing the first test overview report data, the rendering engine can convert the first test overview report data into a visual chart, graph or animation, thereby helping users to better understand and analyze the data. As a specific example, when displaying in the form of a chart, the rendering engine will select a suitable chart type according to the characteristics and needs of the data. For example, if you want to show the pass rate of different test stages, you may choose a bar chart; if you want to show the trend of data changes over time, you may choose a line chart; if you want to show the proportional relationship between different test items, you may choose a pie chart, etc. This kind of visualization content not only improves the readability and comprehensibility of the data, but also allows users to quickly obtain information in a visual way. It is worth noting here that the visualization content corresponding to the second test overview report data can refer to the aforementioned description of the visualization content corresponding to the first test overview report data, which will not be repeated here.

[0133] In the embodiment of the present application, by displaying the first test overview sub-report and the second test overview sub-report in the first display area and the second display area respectively, the display of the test results is made clearer and more intuitive. The user does not need to search for the required information in a single display area, but can directly locate the test data of interest through the corresponding display area (the first display area or the second display area), thereby improving the efficiency of data acquisition.

[0134] In some embodiments, the above-mentioned visualization interface may include multiple data element options, and the data element options correspond to the data in the test profile report data. Figure 7 As shown, the above data processing method may further include steps 710 to 730.

[0135] Step 710: receiving a user input on a target data element option, where the target data element option is at least one of a plurality of data element options.

[0136] Exemplarily, the user can select the desired target data element option through a drop-down menu on the visual interface, by checking a checkbox, sliding a slider, or using other intuitive interactive elements. Exemplarily, the target data element option can include but is not limited to the aforementioned first preset performance indicator and second preset performance indicator.

[0137] Step 720 , in response to the input, obtaining target data corresponding to the target data element option from the test profile report data.

[0138] Exemplarily, after receiving the user's input, target data corresponding to the target data element option selected by the user is extracted from the test profile report data according to the user's selection, to ensure that the user can quickly obtain the relevant target data without manually screening through a large amount of data.

[0139] Step 730 , displaying at least one of the following according to the target data: a visualization interface corresponding to the target data, and target content corresponding to the target data.

[0140] For example, after obtaining the target data, various forms of visualization interfaces can be generated and displayed according to the characteristics of the target data. These interfaces may include but are not limited to line charts, bar charts, pie charts, scatter charts, etc., which present the distribution, trend and comparison of the target data in an intuitive way. In order to further enhance the user experience, users can also perform interactive drill-down operations by clicking on elements on the visualization interface, that is, users can drill down from a high-level overview chart to specific interface call details, or even further to the log data of a single request, so that users can switch between different levels of data to obtain comprehensive and in-depth analysis content.

[0141] The target content may include specific values, percentages, ranking information, and explanatory text or suggestions for the data. For example, when a user clicks on the detailed query of a microservice interface call, he can not only see the key indicators such as the response time and success rate of the microservice interface, but also obtain specific request and response details, which helps users to deeply understand the performance and potential problems of the microservice interface.

[0142] In an embodiment of the present application, by allowing the user to select a specific target data element option according to needs, the data corresponding to the target data element option can be directly obtained, and the corresponding visualization interface or target content can be generated based on these data, so that the user no longer needs to browse the entire test profile report data to find the required information, but can directly obtain the relevant data content by selecting the target data element option, thereby improving the efficiency and accuracy of information retrieval.

[0143] Based on the data processing method provided in the above embodiment, the present application also provides a specific implementation of a data processing device. Please refer to the following embodiment.

[0144] See first Figure 8 , the data processing device 800 provided in the embodiment of the present application includes:

[0145] The acquisition module 810 is used to acquire a data link, where the data link includes at least two target microservices and a data transmission relationship between at least two target microservices, and each of the at least two target microservices is provided with a data collection point.

[0146] The collection module 820 is used to collect log data of the target microservice where the data collection point is located through the data collection point.

[0147] The processing module 830 is used to perform data integration processing on the log data of at least two target microservices to obtain test overview report data of the data link.

[0148] The first display module 840 is used to display a visual interface corresponding to the test overview report data according to the test overview report data.

[0149] In an embodiment of the present application, first, the collection module 820 utilizes at least two data collection points set on at least two target microservices to realize the collection of log data on the data link. By comparing the difference between the actually collected log data and the expected log data, it can be verified whether the data link is working properly, that is, the test data corresponding to the data link is determined. Then, the processing module 830 can perform data integration processing on the collected log data to obtain test overview report data that is relatively complete with the data link. The method of collecting log data to determine the test overview report data avoids the influence of human factors on the test data collection and improves the accuracy of the test data. Subsequently, the first display module 840 displays a visual interface corresponding to the test overview report data, which is conducive to intuitively and clearly displaying the operating status and fault problems on the corresponding data link, so that the user can quickly locate the fault problem in the data link, effectively accelerate the process of solving the fault problem, and improve the test efficiency of the data link.

[0150] The data processing device 800 in the embodiment of the present application is described in detail below, as shown below.

[0151] In some embodiments of the present application, the data processing device 800 in the embodiments of the present application may also include a first determination module and a first construction module, as shown below.

[0152] The first determination module is used to determine at least two target microservices participating in the data link and the data transmission relationship between the at least two target microservices according to the test task requirements before acquiring the data link.

[0153] The first construction module is used to construct a data link corresponding to the test task requirement according to at least two target microservices and a data transmission relationship between at least two target microservices, where the test task requirement includes a first test task requirement and a second test task requirement.

[0154] In some embodiments of the present application, the first determination module in the embodiments of the present application may be specifically used for:

[0155] According to the requirements of the first test task, select at least two target microservices from multiple microservices;

[0156] According to the second test task requirement, a data transmission relationship between at least two target microservices is generated.

[0157] In some embodiments of the present application, the data processing device 800 in the embodiments of the present application may also include a first setting module, which is used to set a data collection point on each of the at least two target microservices by means of a plug-in embedding method, and the data collection point is configured with a collection rule, and the collection rule is determined based on the test task requirements and the data transmission relationship between the at least two target microservices.

[0158] In some embodiments of the present application, the aforementioned processing module 830 may be specifically used for:

[0159] The log data of at least two target microservices include first log data and second log data, the first log data is log data of each target microservice in the at least two target microservices within a first time period, and the second log data is log data of each target microservice in the at least two target microservices within a second time period, and the second time period is earlier than the first time period in time; the test overview report data includes first test overview report data and second test overview report data;

[0160] Generate first total indicator data according to the first preset performance indicator and the first summary data, the first summary data including the first log data of each target microservice, the first total indicator data including the first indicator data corresponding to the first log data of each target microservice in at least two target microservices, the first indicator data being used to characterize the test result of the target microservice corresponding to the first preset performance indicator in the first time period;

[0161] Performing data integration processing on the first indicator data in the first total indicator data to generate first test overview report data of the data link;

[0162] Generate second total indicator data according to the second preset performance indicator and the second summary data, where the second summary data includes the second log data of each target microservice, and the second total indicator data includes the second indicator data corresponding to the second log data of each target microservice in at least two target microservices;

[0163] Data integration processing is performed on the second indicator data in the second total indicator data to generate second test overview report data of the data link.

[0164] In some embodiments of the present application, the visual interface includes a first display area and a second display area. Based on this, the aforementioned first display module can be specifically used for:

[0165] Displaying visualization content corresponding to the first test overview report data in the first display area;

[0166] Visual content corresponding to the second test overview report data is displayed in the second display area.

[0167] In some embodiments of the present application, the data processing device 800 in the embodiments of the present application may further include an update module, which is used to update the log data of at least two target microservices based on the new log data when new log data is collected through the data collection point of the i-th target microservice among the at least two target microservices, so as to perform data integration processing on the updated log data to obtain test overview report data of the data link, where i is a positive integer.

[0168] In some embodiments of the present application, the data processing device 800 in the embodiments of the present application may further include a first receiving module, a first responding module and a second display module, as described in detail as follows.

[0169] The visualization interface includes a plurality of data element options, and the data element options correspond to the data in the test profile report data.

[0170] The first receiving module is used to receive a user's input on a target data element option, where the target data element option is at least one of a plurality of data element options.

[0171] The first response module is used for acquiring target data corresponding to the target data element option from the test profile report data in response to the input.

[0172] The second display module is used to display at least one of the following according to the target data:

[0173] A visualization interface corresponding to the target data, and target content corresponding to the target data.

[0174] The data processing device provided in the embodiment of the present application can realize Figures 1 to 7The various processes implemented in the data processing method embodiment shown achieve the same technical effect, and will not be described again here to avoid repetition.

[0175] Fig. 9 A schematic structural diagram of an electronic device provided by an embodiment of the present application is shown.

[0176] The electronic device 900 may include a processor 901 and a memory 902 storing computer program instructions.

[0177] Specifically, the processor 901 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0178] The memory 902 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 902 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 902 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 902 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 902 is a non-volatile solid-state memory.

[0179] In a particular embodiment, the memory 902 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Therefore, generally, the memory 902 includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the data processing method according to the first aspect of the present application.

[0180] The processor 901 implements any one of the data processing methods in the above embodiments by reading and executing computer program instructions stored in the memory 902 .

[0181] In some examples, the electronic device 900 may further include a communication interface 903 and a bus 910. Fig. 9 As shown, the processor 901, the memory 902, and the communication interface 903 are connected via a bus 910 and communicate with each other.

[0182] The communication interface 903 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0183] Bus 910 includes hardware, software or both, and the components of online data flow billing equipment are coupled to each other. For example, but not limitation, bus 910 may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 910 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnection.

[0184] Exemplarily, the electronic device 900 may be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA).

[0185] The electronic device 900 can execute the data processing method in the embodiment of the present application, thereby realizing the combination Figure 1 and Figure 8 The data processing method and device described.

[0186] In addition, in combination with the data processing method in the above embodiment, the embodiment of the present application also provides a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the data processing methods in the above embodiment is implemented. Examples of computer-readable storage media include non-transitory computer-readable storage media, such as portable disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, etc.

[0187] The embodiment of the present application also provides a computer program product, which is stored in a storage medium and may specifically include a computer program or instruction, and when the computer program or instruction is executed by a processor, any one of the data processing methods in the above embodiments is implemented. The program product is executed by at least one processor to implement the various processes of the above data processing method embodiment, and can achieve the same technical effect, so it will not be repeated here to avoid repetition.

[0188] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0189] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0190] The above are only specific implementation methods of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A data processing method, characterized in that: include: Acquire a data link, wherein the data link includes at least two target microservices and a data transmission relationship between the at least two target microservices, and each of the at least two target microservices is provided with a data collection point; Collect log data of the target microservice where the data collection point is located through the data collection point; Performing data integration processing on the log data of the at least two target microservices to obtain test overview report data of the data link; According to the test overview report data, a visualization interface corresponding to the test overview report data is displayed.

2. The data processing method according to claim 1, characterized in that: Before acquiring the data link, the method further includes: According to the test task requirements, determine at least two target microservices participating in the data link and the data transmission relationship between the at least two target microservices; According to the at least two target microservices and the data transmission relationship between the at least two target microservices, a data link corresponding to the test task requirement is constructed.

3. The data processing method according to claim 2, characterized in that: The test task requirements include a first test task requirement and a second test task requirement; The step of determining at least two target microservices participating in the data link and a data transmission relationship between the at least two target microservices according to the test task requirements includes: According to the first test task requirement, select at least two target microservices from multiple microservices; According to the second test task requirement, a data transmission relationship between the at least two target microservices is generated.

4. The data processing method according to claim 2, characterized in that: Before acquiring the data link, the method further includes: By means of plug-in embedding, a data collection point is set on each of the at least two target microservices, and the data collection point is configured with a collection rule, which is determined based on the test task requirements and the data transmission relationship between the at least two target microservices.

5. The data processing method according to claim 1, characterized in that: The log data of the at least two target microservices include first log data and second log data, the first log data is log data of each of the at least two target microservices in a first time period, the second log data is log data of each of the at least two target microservices in a second time period, and the second time period is earlier than the first time period in time; the test overview report data includes first test overview report data and second test overview report data; The performing data integration processing on the log data of the at least two target microservices to obtain the test overview report data of the data link includes: Generate first total indicator data according to the first preset performance indicator and the first summary data, where the first summary data includes the first log data of each target microservice, and the first total indicator data includes the first indicator data corresponding to the first log data of each target microservice in at least two target microservices, where the first indicator data is used to characterize the test result of the target microservice corresponding to the first preset performance indicator in the first time period; Performing data integration processing on the first indicator data in the first total indicator data to generate first test overview report data of the data link; Generate second total indicator data according to the second preset performance indicator and the second summary data, where the second summary data includes the second log data of each target microservice, and the second total indicator data includes the second indicator data corresponding to the second log data of each target microservice in at least two target microservices; Perform data integration processing on the second indicator data in the second total indicator data to generate second test overview report data of the data link.

6. The data processing method according to claim 5, characterized in that: The visualization interface includes a first display area and a second display area; The step of displaying a visualization interface corresponding to the test overview report data according to the test overview report data includes: Displaying visual content corresponding to the first test overview report data in the first display area; Visual content corresponding to the second test overview report data is displayed in the second display area.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: In the case where new log data is collected through the data collection point of the i-th target microservice among the at least two target microservices, the log data of the at least two target microservices are updated based on the new log data, so as to perform data integration processing on the updated log data to obtain the test overview report data of the data link, where i is a positive integer.

8. The method according to any one of claims 1 to 6, characterized in that: The visualization interface includes a plurality of data element options, and the data element options correspond to the data in the test profile report data; The method further comprises: receiving a user input of a target data element option, wherein the target data element option is at least one of the plurality of data element options; In response to the input, acquiring target data corresponding to the target data element option from the test profile report data; Based on the target data, at least one of the following is displayed: A visualization interface corresponding to the target data, and target content corresponding to the target data.

9. A data processing device, characterized in that: The device comprises: An acquisition module, used to acquire a data link, wherein the data link includes at least two target microservices and a data transmission relationship between the at least two target microservices, and each of the at least two target microservices is provided with a data collection point; A collection module is used to collect log data of a target microservice where the data collection point is located through a data collection point; A processing module, used to perform data integration processing on the log data of the at least two target microservices to obtain test overview report data of the data link; The first display module is used to display a visual interface corresponding to the test overview report data according to the test overview report data.

10. An electronic device, characterized in that: The device comprises: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the data processing method according to any one of claims 1 to 8 is implemented.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the data processing method according to any one of claims 1 to 8 is implemented.

12. A computer program product, characterized in that The computer program product comprises a computer program or instructions, and when the computer program or instructions are executed by a processor, the data processing method according to any one of claims 1 to 8 is implemented.

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