Method and device for testing computing resources of cloud computing platform and related equipment

Abstract

The invention provides a computing resource testing method and device for a cloud computing platform and related equipment, and the method comprises the steps: determining the total number of service requests needing to be executed by the cloud computing platform in unit time, the cloud computing platform can execute multiple types of service requests, and the total number of the service requests is the sum of the number of the multiple types of service requests; based on the number of times of calling the target system component when the various types of service requests are executed, the total number of times of calling the target system component in unit time is obtained, the cloud computing platform comprises a plurality of system components, and the target system component is any one of the plurality of system components; obtaining a resource consumption value of the target system component based on the total calling frequency of the target system component; and comparing the resource consumption value of the target system component with the available resource value of the target system component to generate a test result. According to the method and the device, the testing effect of computing resource testing on the cloud computing platform is improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of cloud computing platform, and particularly relate to a computing resource testing method and device of a cloud computing platform and related equipment. BACKGROUND

[0002] With the continuous development of cloud computing technology, cloud computing platforms have been widely applied in various fields. Current cloud computing platforms are usually composed of multiple system components, such as databases, gateways, and the like.

[0003] In the process of executing a business of a cloud computing platform, it will sequentially pass through multiple system components. When a certain system component has insufficient computing resources, it will affect the stability of the entire cloud computing platform. Therefore, testing the computing resources of the system component is very important. The existing testing method is generally to simulate a large number of request flows to discover system components with poor computing resources through a large number of request flows. However, this method usually consumes a large amount of computing resources and cannot accurately discover the computing resource bottleneck of each system component, thereby causing poor testing results. SUMMARY

[0004] Embodiments of the present application provide a computing resource testing method and device of a cloud computing platform and related equipment to solve the problem of poor testing results when testing the computing resources of a cloud computing platform in the prior art.

[0005] In a first aspect, the embodiments of the present application provide a computing resource testing method of a cloud computing platform, the method comprising:

[0006] determining a total number of business requests that need to be executed by the cloud computing platform in a unit of time, wherein the cloud computing platform can execute multiple types of business requests, and the total number of business requests is the sum of the number of business requests of the multiple types;

[0007] based on the number of calls to the target system component when executing each type of business request, obtaining a total number of calls to the target system component in a unit of time, wherein the cloud computing platform includes multiple system components, and the target system component is any one of the multiple system components;

[0008] based on the total number of calls to the target system component, obtaining a resource consumption value of the target system component;

[0009] comparing the resource consumption value of the target system component with an available resource value of the target system component to generate a test result, the test result indicating whether the target system component meets the total number of business requests processed by the cloud computing platform.

[0010] Optionally, based on the number of calls to the target system component when each type of business request is executed, the total number of calls to the target system component in a unit of time is obtained, including:

[0011] According to the total number of business requests that the cloud computing platform needs to execute in a unit of time, the number of each type of business request that the cloud computing platform needs to execute in a unit of time is determined;

[0012] According to the number of each type of business request and the number of calls to the target system component when the corresponding type of business request is executed, the number of calls to the target system component by each type of business request in a unit of time is obtained;

[0013] The number of calls to the target system component by each type of business request in a unit of time is summed to obtain the total number of calls to the target system component in a unit of time.

[0014] Optionally, according to the total number of business requests that the cloud computing platform needs to execute in a unit of time, the number of each type of business request that the cloud computing platform needs to execute in a unit of time is determined, including:

[0015] According to the historical data included by the cloud computing platform, the proportion of each type of business request in the total business request is determined, and based on the proportion of each type of business request in the total business request and the total number of business requests, the number of each type of business request is obtained;

[0016] And / or,

[0017] Real-time monitoring of data received by the cloud computing platform, according to the data received in a predetermined period, the proportion of each type of business request in the total business request is determined, and based on the proportion of each type of business request in the total business request and the total number of business requests, the number of each type of business request is obtained.

[0018] Optionally, before the method further comprises:

[0019] The business source code is parsed to obtain the call relationship between each type of business request, wherein the business source code is the source code corresponding to the plurality of types of business requests;

[0020] According to the number of each type of business request and the number of calls to the target system component when the corresponding type of business request is executed, the number of calls to the target system component by each type of business request in a unit of time is obtained, including:

[0021] According to the call relationship between each type of business request, the number of each type of business request is updated;

[0022] According to the number of each type of business request and the number of calls to the target system component when executing the corresponding type of business request, the number of calls to the target system component by each type of business request in a unit of time is obtained.

[0023] Optionally, before obtaining the resource consumption value of the target system component based on the total number of calls to the target system component, the method further comprises:

[0024] The business source code is parsed to obtain the call means to the target system component and the number of times of using the call means, wherein the business source code is the source code corresponding to the multiple types of business requests;

[0025] Then, obtaining the resource consumption value of the target system component based on the total number of calls to the target system component comprises:

[0026] Obtaining the resource consumption value of the target system component based on the total number of calls to the target system component, the call means, and the number of times of using the call means.

[0027] Optionally, obtaining the resource consumption value of the target system component based on the total number of calls to the target system component, the call means, and the number of times of using the call means comprises:

[0028] Inputting the total number of calls to the target system component, the call means, and the number of times of using the call means into a machine learning model to output the resource consumption value of the target system component;

[0029] The machine learning model is used to predict the computing resources required when the target system component executes each type of business request, and generate the resource consumption value.

[0030] Optionally, after comparing the resource consumption value of the target system component with the available resource value of the target system component to generate a test result, the method further comprises:

[0031] The test result is parsed to generate a system optimization measure, and the system optimization measure is used to increase the total number of business requests executed by the cloud computing platform in a unit of time.

[0032] The system optimization measure comprises at least one of the following: increasing the central processing unit (CPU) capacity, increasing the memory capacity, increasing the network occupancy, and increasing the graphics processing unit (GPU) capacity of the target system component.

[0033] Optionally, the system component comprises at least one of the following: a gateway, a container orchestration platform, a container scheduling unit, and a database.

[0034] In a second aspect, an embodiment of the present application provides a computing resource testing device of a cloud computing platform, comprising:

[0035] The determination module is used to determine the total number of business requests that the cloud computing platform needs to execute within a unit of time. The cloud computing platform can execute multiple types of business requests, and the total number of business requests is the sum of the number of business requests of multiple types.

[0036] The statistics module is used to obtain the total number of calls to the target system component per unit time based on the number of calls to the target system component when executing various types of business requests. The cloud computing platform includes multiple system components, and the target system component is any one of the multiple system components.

[0037] The calculation module is used to obtain the resource consumption value of the target system component based on the total number of calls to the target system component;

[0038] The generation module compares the resource consumption value of the target system component with the available resource value of the target system component, generates test results, and the test results indicate whether the target system component meets the total number of business requests that the cloud computing platform can process.

[0039] Thirdly, embodiments of this application also provide an electronic device, including: a memory, a processor, and a program stored in the memory and executable on the processor; the processor is configured to read the program in the memory to implement the steps of the method described in the first aspect above.

[0040] Fourthly, embodiments of this application also provide a readable storage medium for storing a program, which, when executed by a processor, implements the steps of the method described in the first aspect above.

[0041] Fifthly, embodiments of this application also provide a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps in the method described in the first aspect above. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 One of the flowcharts illustrating a computing resource testing method for a cloud computing platform provided in this application embodiment;

[0044] Figure 2 A second flowchart illustrating a method for testing computing resources on a cloud computing platform, provided as an embodiment of this application;

[0045] Figure 3 A flowchart illustrating a method for testing computing resources on a cloud computing platform, as provided in an embodiment of this application, is shown in Figure 3.

[0046] Figure 4 A flowchart illustrating a method for testing computing resources on a cloud computing platform, as provided in an embodiment of this application, is shown in Figure 4.

[0047] Figure 5 The fifth flowchart illustrates a method for testing computing resources on a cloud computing platform, as provided in this application embodiment.

[0048] Figure 6 A flowchart illustrating a method for testing computing resources on a cloud computing platform, provided as an embodiment of this application, is shown in Figure 6.

[0049] Figure 7 The seventh flowchart illustrates a method for testing computing resources on a cloud computing platform, as provided in this application embodiment.

[0050] Figure 8 This is the eighth flowchart illustrating a method for testing computing resources on a cloud computing platform, provided as an embodiment of this application.

[0051] Figure 9 A schematic diagram of the structure of a computing resource testing device for a cloud computing platform provided in an embodiment of this application;

[0052] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0053] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0054] The terms "first," "second," etc., used in the embodiments of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices. Additionally, the use of "and / or" in this application indicates at least one of the connected objects, such as A and / or B and / or C, representing seven possibilities: including A alone, B alone, C alone, and the presence of both A and B, both B and C, both A and C, and the presence of A, B, and C.

[0055] See Figure 1 , Figure 1 This is one of the flowcharts illustrating the computing resource testing method for a cloud computing platform provided in this application embodiment. Figure 1 The computing resource testing method for the cloud computing platform shown can be executed by a computer. For example... Figure 1 As shown, the testing method for computing resources on a cloud computing platform may include the following steps:

[0056] Step 200: Determine the total number of business requests that the cloud computing platform needs to execute per unit time. The cloud computing platform can execute multiple types of business requests, and the total number of business requests is the sum of the number of business requests of multiple types.

[0057] In this embodiment, a cloud computing platform is a collection of infrastructure and services that provide cloud computing services. The cloud computing platform allows users to remotely access and use computing resources, storage, networks, and applications via the Internet.

[0058] The total number of business requests that a cloud computing platform needs to process per unit of time is the sum of the number of various types of business requests that the cloud computing platform needs to execute per unit of time. The unit of time can be 10 minutes, 1 hour, etc. Business requests can include order query requests, payment order requests, and order placement requests, etc. It should be noted that the total number of business requests can include multiple identical business requests; for example, 300 order query requests and 200 payment order requests within 1 hour, etc. In this embodiment, the cloud computing platform is tested based on the determined total number of business requests to determine whether the cloud computing platform can support the total number of business requests per unit of time. Specifically, the total number of business requests that the cloud computing platform needs to execute per unit of time can be a set overall request volume for testing the cloud computing platform, i.e., the query rate per second (QPS), thereby constructing a request model simulating a real business scenario.

[0059] Step 400: Based on the number of times the target system component is called when executing various types of business requests, obtain the total number of times the target system component is called per unit time. The cloud computing platform includes multiple system components, and the target system component is any one of the multiple system components.

[0060] In this embodiment, the cloud computing platform includes multiple system components. In some embodiments, the system components include at least one of the following: gateway, container orchestration platform, container scheduling unit, and database. Each system component may include one or more, and the number of them is not specifically limited in this embodiment.

[0061] It should be noted that executing each type of business request requires calling any system component, i.e., the target system component. Therefore, the number of calls is counted during the process of calling system components. By counting the number of calls to each system component when executing each type of business request within a unit of time, the total number of calls to the target system component within a unit of time is finally obtained.

[0062] Step 600: Based on the total number of calls to the target system components, obtain the resource consumption value of the target system components.

[0063] In this embodiment, the resource consumption value of the target system component is generated by calculating the total number of calls to all system components obtained from statistics. The resource consumption value may include CPU utilization, memory usage, network bandwidth, disk consumption, etc.

[0064] Step 800: Compare the resource consumption value of the target system component with the available resource value of the target system component, generate test results, and the test results indicate whether the target system component meets the total number of business requests that the cloud computing platform can process.

[0065] In this embodiment, the available resource value of the target system component is the resource value that the target system component can use, such as the CPU utilization, memory usage, network bandwidth, disk consumption, etc. that the target system component can provide.

[0066] By comparing the resource consumption of a target system component with its available resources, test results are generated. This allows the system to determine whether the target component meets the total number of business requests that the cloud computing platform can handle, thus enabling the testing of the target system component. Specifically, for example, if a system component requires 80 CPU cores but only has 64, it is determined that this component may be a bottleneck, and the test results indicate that the component needs optimization.

[0067] This application determines the total number of business requests that a cloud computing platform needs to execute within a unit of time, thereby statistically analyzing the number of times the target system component executes business requests, and calculating the resource consumption value of the corresponding target system component. Based on the resource consumption value and available resource value of the target system component, it determines whether the target system component meets the testing requirements, thus improving the testing effect when computing resources are used to test the target system component.

[0068] In some feasible implementations, optionally, step 400, based on the number of calls to the target system component when executing various types of business requests, obtains the total number of calls to the target system component per unit time, including:

[0069] Step 410: Based on the total number of business requests that the cloud computing platform needs to execute within a unit of time, determine the number of each type of business request that the cloud computing platform needs to execute within a unit of time.

[0070] Step 420: Based on the number of business requests of each type and the number of times the target system component is called when executing the corresponding business request, obtain the number of times the target system component is called by each type of business request per unit time.

[0071] Step 430: Sum the number of times each type of business request calls to the target system component within a unit of time to obtain the total number of times the target system component is called within a unit of time.

[0072] In this embodiment, as Figure 2 As shown, Figure 2 This is the second flowchart illustrating the computing resource testing method for a cloud computing platform provided in this application embodiment. The total number of all business requests that the cloud computing platform needs to execute within a unit of time is used to determine the number of each type of business request that the cloud computing platform needs to execute within a unit of time. For example, if the total number of business requests that the cloud computing platform needs to execute within one hour is 200, then it can include 100 order query requests, 50 payment order requests, and 50 order placement requests.

[0073] After determining the number of each type of business request, the system generates the number of times the target system component is called for each business request per unit time, based on the number of times the target system component is called when executing the corresponding type of business request. For example, executing a query order request requires calling system component A 100 times, executing a payment order request requires calling system component A 50 times, and executing an order placement request requires calling system component A 100 times.

[0074] By summing the number of times each type of business request calls to the target system component within a unit of time, the total number of calls to the target system component within that unit of time is obtained. It should be noted that in this embodiment, there can be one or more target system components; therefore, in the case of multiple components, the total number of calls corresponding to each target system component will be calculated.

[0075] In the cloud computing environment of this embodiment, the total number of calls is calculated by the number of business requests and the number of times they call the target system components. This allows for more effective management and optimization of system performance on the cloud computing platform, ensuring that users are provided with fast and reliable services.

[0076] Optionally, step 410 involves determining the number of various types of business requests that the cloud computing platform needs to execute within a unit of time, based on the total number of business requests that need to be executed by the cloud computing platform within a unit of time, including:

[0077] Step 411: Based on the historical data included in the cloud computing platform, determine the proportion of each type of business request in the total business requests. Based on the proportion of each type of business request in the total business requests and the total number of business requests, obtain the number of each type of business request.

[0078] And / or,

[0079] Step 412: Monitor the data received by the cloud computing platform in real time. Based on the data received within the preset period, determine the proportion of each type of business request in the total business requests. Based on the proportion of each type of business request in the total business requests and the total number of business requests, obtain the number of each type of business request.

[0080] In this embodiment, as Figure 3 and Figure 4 As shown, Figure 3 This is the third flowchart illustrating the computing resource testing method for a cloud computing platform provided in this application embodiment. Figure 4 This is the fourth flowchart illustrating the computing resource testing method for a cloud computing platform provided in this application embodiment. The number of various types of business requests that the cloud computing platform needs to execute per unit time can be determined using historical data included in the cloud computing platform. Specifically, the historical data includes the total number of various types of business requests over a period of time. Based on the historical data, the proportion of each type of business request in the total requests is calculated. By combining the calculated proportion with the determined total number of business requests, the number of each type of business request is obtained. In other words, by using the historical data of the cloud computing platform, the current number of each type of business request can be deduced. This helps to grasp user behavior trends in real time, optimize overall system performance, and thus improve user experience and business efficiency.

[0081] Furthermore, by monitoring data received by the cloud computing platform in real time, the proportion of each type of business request within the total business requests can be determined based on the data received within a preset period. Specifically, for example, the preset period could be one hour; monitoring the cloud computing platform within one hour would then determine the proportion of each type of business request within the total business requests. By calculating the proportion of each type of business request within the total business requests and the total number of business requests, the quantity of each type of business request can be obtained. Through real-time monitoring and data analysis, the proportion and quantity of different types of business requests can be effectively obtained.

[0082] It should be noted that in this embodiment, the number of various types of business requests can be calculated using historical data or real-time monitoring of the cloud computing platform. Alternatively, the number of various types of business requests can be calculated using both historical data and real-time monitoring of the cloud computing platform to obtain two calculation results. The number of various types of business requests can then be generated by combining the two calculation results. Compared to the method of using historical data or real-time monitoring of the cloud computing platform, the comprehensive calculation method is more accurate, and the number of various types of business requests obtained is more accurate.

[0083] Optionally, before step 400, which calculates the total number of calls to the target system component per unit time based on the number of calls made to the target system component when executing various types of business requests, the method further includes:

[0084] Step 300: Parse the business source code to obtain the calling relationship between various types of business requests. The business source code consists of the source code corresponding to multiple types of business requests.

[0085] Then, step 420, based on the number of business requests of each type and the number of times the target system component is called when executing the corresponding business request, obtain the number of times the target system component is called by each type of business request per unit time, including:

[0086] Step 421: Update the number of business requests of each type according to the calling relationship between them;

[0087] Step 422: Based on the number of updated business requests of each type and the number of times the target system component is called when executing the corresponding business request, obtain the number of times the target system component is called by each type of business request per unit time.

[0088] In this embodiment, as Figure 5 As shown, Figure 5This is the fifth flowchart illustrating the computing resource testing method for a cloud computing platform provided in this application embodiment. Before counting the number of calls to the target system components, this application parses the business source code of the cloud computing platform to obtain the call relationships between various types of business requests. Specifically, the business source code consists of the source code corresponding to multiple types of business requests. By parsing the business source code, the call relationships between different types of requests can be identified, including, for example, which requests might trigger other requests or depend on other requests.

[0089] In this embodiment, by parsing the business code, the calling relationships between various types of business requests are obtained. Based on the total number of business requests the cloud computing platform needs to execute per unit time, the number of each type of business request needs to be determined. Then, the number of each type of business request is updated according to the calling relationships between them. Specifically, this embodiment needs to consider the impact on the number of each type of request. For example, if a request is a dependency of another request, then when the number of dependent requests increases, the number of related requests should also be updated accordingly. For instance, if the original number of payment requests is 100 and the number of inventory query requests is 100, and the execution of the payment request requires calling the inventory query request, then the number of inventory query requests is updated to 200.

[0090] Based on the updated number of business requests of each type, these numbers are used in conjunction with the previously determined number of calls to the target system component corresponding to each request type to calculate the number of calls to the target system component by each type of business request per unit time.

[0091] This embodiment, by parsing the business source code and understanding the call relationships between requests, can more accurately statistically analyze different types of business requests and their calls to target system components. This enhances the system's visual management, improves the accuracy of load prediction, and provides data support for business decisions, effectively improving system performance and user experience.

[0092] Optionally, before step 600, obtaining the resource consumption value of the target system component based on the total number of calls to the target system component, the method further includes:

[0093] Step 500: Parse the business source code to obtain the calling methods of the target system components and the number of times the calling methods are used. The business source code consists of the source code corresponding to multiple types of business requests.

[0094] Then, step 600, based on the total number of calls to the target system component, obtains the resource consumption value of the target system component, including:

[0095] Step 610: Based on the total number of calls to the target system component, the calling methods, and the number of times the calling methods were used, obtain the resource consumption value of the target system component.

[0096] Steps 500 and 300 can be executed together or separately.

[0097] In this embodiment, as Figure 6 As shown, Figure 6 This is the sixth flowchart illustrating the computing resource testing method for a cloud computing platform provided in this application. Before counting the number of calls to the target system components, this application parses the business source code of the cloud computing platform to obtain the call relationships between various types of business requests. Specifically, the business source code consists of the source code corresponding to multiple types of business requests. By parsing the business source code, the calling methods between different types of requests can be identified. These calling methods can be function calls, API requests, database queries, etc., specifically related to the cloud computing platform. Source code parsing can use static code analysis tools, regular expressions, abstract syntax tree parsing, and other technologies to identify calling patterns and count usage frequencies.

[0098] Record the parsed calling methods and their corresponding usage counts. For example: calling method A: 300 times, calling method B: 150 times, calling method C: 500 times. Combine the recorded usage counts of each calling method to obtain the total number of calls to the target system component. For example, if calling method A is called 300 times, B is called 150 times, and C is called 500 times, then the total number of calls is 950.

[0099] For a target system component, the overall resource consumption value of the component can be derived by analyzing the frequency and corresponding resource consumption data of each invocation method. It should be noted that different invocation functions or methods, different numbers of invocations, and different frequencies can result in different resource consumption values. For example, the more complex the invocation function or method, the more frequent the invocations, and the higher the frequency, the higher the resource consumption value. For instance, if invocation method A consumes 0.5 CPU resources per call, B consumes 0.2 CPU resources, and C consumes 0.8 CPU resources, then: Total resource consumption = (300 × 0.5) + (150 × 0.2) + (500 × 0.8) = 580.

[0100] By analyzing the business source code, the calling methods and usage times of the target system components can be accurately obtained. Then, combined with the resource consumption model, the resource consumption value of the target system can be calculated, which can provide strong data support for performance optimization, resource management and business decision-making. Therefore, this embodiment helps to improve the overall efficiency and responsiveness of the system.

[0101] Optionally, in addition to the above-described method of calculating resource consumption values, step 610, obtaining the resource consumption value of the target system component based on the total number of calls to the target system component, the calling methods, and the number of times the calling methods were used, may also include:

[0102] Step 611: Input the total number of calls to the target system component, the call method, and the number of times the call method was used into the machine learning model, and output the resource consumption value of the target system component;

[0103] Among them, the machine learning model is used to predict the computing resources required by the target system components when executing various types of business requests, and generate resource consumption values.

[0104] In this embodiment, as Figure 7 As shown, Figure 7 This is the seventh flowchart illustrating the computing resource testing method for a cloud computing platform provided in this application embodiment. In this embodiment, the total number of calls to the target system component, the calling method, and the number of times the calling method was used can be input into a pre-trained machine learning model to output the resource consumption value corresponding to the target system component. Specifically, the machine learning model can be a regression model, such as linear regression, support vector regression, random forest regression, or a neural network. The model training process can involve dividing the dataset into a training set and a test set, using the training set to train the model, and using the test set to verify the model's accuracy. During training, the model parameters are continuously adjusted, the loss function is optimized, the model's performance on the dataset is improved, and methods such as cross-validation are used to optimize the model, ultimately resulting in a well-trained machine learning model.

[0105] Using machine learning models to predict the resource consumption of target system components enables real-time monitoring of their performance and timely identification of potential bottlenecks and overloads. In this embodiment, the predicted resource consumption can be used for resource planning, such as determining the required computing resources, memory, and storage to ensure system performance.

[0106] This embodiment inputs the total number of calls, call methods, and usage frequency of the target system components into a machine learning model, which can effectively predict the resource consumption of the target system components. By combining the model output with continuously monitored data, the efficiency and responsiveness of the cloud computing platform can be improved.

[0107] Optionally, after step 800, comparing the resource consumption value of the target system component with the available resource value of the target system component and generating test results, the method further includes:

[0108] Step 900: Analyze the test results and generate system optimization measures. These measures are used to increase the total number of business requests executed by the cloud computing platform per unit time.

[0109] The system optimization measures include at least one of the following: increasing the CPU capacity, memory capacity, network usage, and GPU capacity for the target system components.

[0110] In this embodiment, as Figure 8 As shown, Figure 8 This is the eighth flowchart illustrating the computing resource testing method for a cloud computing platform provided in this application embodiment.

[0111] In this embodiment, after obtaining the test results, the results are analyzed to generate system optimization measures. Specifically, the test results may include request response time, failure rate, resource usage (such as CPU, memory, network bandwidth, etc.), and the total number of business requests, etc. By comparing these indicators, bottlenecks in the system can be identified. For example, if CPU utilization is high but the response time is long, then the CPU may be the bottleneck, affecting the total number of business requests.

[0112] System optimization measures include increasing CPU capacity by increasing the number of CPU cores or frequency, thereby improving processing power, reducing task processing time, increasing concurrent request processing capabilities, and boosting overall throughput. Increasing memory capacity allows more data and computation to be performed in memory, reducing disk access, significantly improving the system's ability to handle large datasets, and reducing performance bottlenecks caused by insufficient memory during request processing. Increasing network capacity allows for the use of higher-speed network interfaces and optimized network architecture, accelerating the transmission speed of request and response data. Increasing GPU capacity significantly improves request processing speed by increasing the GPU's computing power.

[0113] It should be noted that multiple system optimization measures can be performed simultaneously in this embodiment. For example, network links can be optimized while increasing CPU and memory, resulting in a more comprehensive improvement in system performance. In some embodiments, a monitoring and feedback mechanism can also be established to monitor system performance in real time and adjust resource configuration according to actual conditions.

[0114] This embodiment, through in-depth analysis of test results, can generate system optimization measures to address performance bottlenecks in the cloud computing platform. These optimization measures can increase the total number of business requests processed per unit time. Combined with real-time monitoring and dynamic adjustments, this ensures the system maintains efficient and stable operation under constantly changing business demands.

[0115] See Figure 9 , Figure 9This is a structural diagram of the computing resource testing device for the cloud computing platform provided in this application embodiment. Figure 9 As shown, the computing resource testing device 1000 for the cloud computing platform includes:

[0116] The determination module 1010 is used to determine the total number of business requests that the cloud computing platform needs to execute within a unit of time. The cloud computing platform can execute multiple types of business requests, and the total number of business requests is the sum of the number of business requests of multiple types.

[0117] The statistics module 1020 is used to obtain the total number of calls to the target system component per unit time based on the number of calls to the target system component when executing various types of business requests. The cloud computing platform includes multiple system components, and the target system component is any one of the multiple system components.

[0118] The calculation module 1030 is used to obtain the resource consumption value of the target system component based on the total number of calls to the target system component;

[0119] The generation module 1040 is used to compare the resource consumption value of the target system component with the available resource value of the target system component, generate test results, and the test results indicate whether the target system component meets the total number of business requests that the cloud computing platform can process.

[0120] Optionally, the statistics module 1020 includes:

[0121] The determination submodule is used to determine the number of each type of business request that the cloud computing platform needs to execute within a unit of time, based on the total number of business requests that the cloud computing platform needs to execute within a unit of time.

[0122] The calculation submodule is used to obtain the number of times each type of business request calls to the target system component per unit time, based on the number of each type of business request and the number of times the corresponding type of business request is called.

[0123] The summation submodule is used to sum the number of times each type of business request calls to the target system component within a unit of time, and obtain the total number of times the target system component is called within a unit of time.

[0124] Optionally, the submodules to be determined include:

[0125] The first determining unit is used to determine the proportion of each type of business request in the total business requests based on the historical data included in the cloud computing platform, and to obtain the number of each type of business request based on the proportion of each type of business request in the total business requests and the total number of business requests.

[0126] And / or,

[0127] The second determining unit is used to monitor the data received by the cloud computing platform in real time, determine the proportion of each type of business request in the total business requests based on the data received within a preset period, and obtain the number of each type of business request based on the proportion of each type of business request in the total business requests and the total number of business requests.

[0128] Optional, also includes:

[0129] The first parsing module is used to parse the business source code to obtain the calling relationship between various types of business requests. The business source code consists of the source code corresponding to multiple types of business requests.

[0130] The calculation submodule includes:

[0131] The update unit is used to update the number of business requests of each type based on the calling relationship between them.

[0132] The calculation unit is used to obtain the number of times each type of business request calls to the target system component per unit time, based on the number of updated business requests of each type and the number of times the corresponding business request is called to the target system component.

[0133] Optional, also includes:

[0134] The second parsing module is used to parse the business source code to obtain the calling methods of the target system components and the number of times the calling methods are used. The business source code consists of the source code corresponding to multiple types of business requests.

[0135] Therefore, the calculation module 1030 includes:

[0136] The prediction module is used to obtain the resource consumption value of the target system component based on the total number of calls to the target system component, the call method, and the number of times the call method was used.

[0137] Optionally, the prediction module includes:

[0138] The prediction submodule is used to input the total number of calls to the target system component, the call method, and the number of times the call method was used into the machine learning model, and output the resource consumption value of the target system component.

[0139] Among them, the machine learning model is used to predict the computing resources required by the target system components when executing various types of business requests, and generate resource consumption values.

[0140] Optional, also includes:

[0141] The third analysis module is used to analyze the test results and generate system optimization measures. These system optimization measures are used to increase the total number of business requests executed by the cloud computing platform per unit time.

[0142] The system optimization measures include at least one of the following: increasing the CPU capacity, memory capacity, network usage, and GPU capacity for the target system components.

[0143] Optionally, the system components include at least one of the following: gateway, container orchestration platform, container scheduling unit, and database.

[0144] This application determines the total number of business requests that a cloud computing platform needs to execute within a unit of time, thereby statistically analyzing the number of times the target system component executes business requests, and calculating the resource consumption value of the corresponding target system component. Based on the resource consumption value and available resource value of the target system component, it determines whether the target system component meets the testing requirements, thus improving the testing effect when computing resources are used to test the target system component.

[0145] This application also provides an electronic device. Please refer to [link to relevant documentation]. Figure 10 The electronic device may include a processor 1101, a memory 1102, and a program 11021 stored in the memory 1102 and executable on the processor 1101.

[0146] When program 11021 is executed by processor 1101, it can achieve the following: Figure 1 Any step in the corresponding method embodiment:

[0147] Determine the total number of business requests that the cloud computing platform needs to execute per unit of time. The cloud computing platform can execute multiple types of business requests, and the total number of business requests is the sum of the number of business requests of multiple types.

[0148] Based on the number of times the target system component is called when executing various types of business requests, the total number of times the target system component is called per unit time is obtained. The cloud computing platform includes multiple system components, and the target system component is any one of the multiple system components.

[0149] Based on the total number of calls to the target system components, the resource consumption value of the target system components is obtained;

[0150] The resource consumption value of the target system component is compared with the available resource value of the target system component to generate test results. The test results indicate whether the target system component meets the total number of business requests that the cloud computing platform can handle.

[0151] Optionally, based on the number of calls to the target system component when executing various types of business requests, the total number of calls to the target system component per unit time is obtained, including:

[0152] Based on the total number of business requests that the cloud computing platform needs to execute within a unit of time, determine the number of each type of business request that the cloud computing platform needs to execute within a unit of time.

[0153] Based on the number of each type of business request and the number of times the target system component is called when executing the corresponding type of business request, the number of times each type of business request calls the target system component per unit time is obtained;

[0154] The total number of calls to the target system component by various types of business requests within a unit of time is obtained by summing the number of calls to the target system component within a unit of time.

[0155] Optionally, based on the total number of business requests that the cloud computing platform needs to execute per unit time, determine the number of each type of business request that the cloud computing platform needs to execute per unit time, including:

[0156] Based on the historical data included in the cloud computing platform, determine the proportion of each type of business request in the total business requests. Based on the proportion of each type of business request in the total business requests and the total number of business requests, obtain the number of each type of business request.

[0157] And / or,

[0158] The system monitors the data received by the cloud computing platform in real time. Based on the data received within a preset period, it determines the proportion of each type of business request in the total business requests. Based on the proportion of each type of business request in the total business requests and the total number of business requests, it obtains the number of each type of business request.

[0159] Optionally, before obtaining the total number of calls to the target system component per unit time based on the number of calls to the target system component when executing various types of business requests, the method further includes:

[0160] The business source code is parsed to obtain the calling relationship between various types of business requests. The business source code consists of the source code corresponding to multiple types of business requests.

[0161] Based on the number of each type of business request and the number of times the target system component is called when executing the corresponding type of business request, the number of times each type of business request calls the target system component per unit time is obtained, including:

[0162] Update the number of each type of business request based on the calling relationship between different types of business requests;

[0163] Based on the number of business requests of each type updated, and the number of times the target system component is called when executing the corresponding business request, the number of times the target system component is called by each type of business request per unit time is obtained.

[0164] Optionally, before obtaining the resource consumption value of the target system component based on the total number of calls to the target system component, the method further includes:

[0165] The business source code is parsed to obtain the calling methods of the target system components and the number of times the calling methods are used. The business source code consists of the source code corresponding to multiple types of business requests.

[0166] Then, based on the total number of calls to the target system component, the resource consumption value of the target system component is obtained, including:

[0167] Based on the total number of calls to the target system component, the call methods, and the number of times the call methods were used, the resource consumption value of the target system component is obtained.

[0168] Optionally, based on the total number of calls to the target system component, the calling methods, and the number of times the calling methods were used, the resource consumption value of the target system component is obtained, including:

[0169] Input the total number of calls to the target system component, the call methods, and the number of times the call methods were used into the machine learning model, and output the resource consumption value of the target system component;

[0170] Among them, the machine learning model is used to predict the computing resources required by the target system components when executing various types of business requests, and generate resource consumption values.

[0171] Optionally, after comparing the resource consumption value of the target system component with the available resource value of the target system component to generate test results, the method further includes:

[0172] The test results are analyzed to generate system optimization measures, which are used to increase the total number of business requests executed by the cloud computing platform per unit time.

[0173] The system optimization measures include at least one of the following: increasing the CPU capacity, memory capacity, network usage, and GPU capacity for the target system components.

[0174] Optionally, the system components include at least one of the following: gateway, container orchestration platform, container scheduling unit, and database.

[0175] This application determines the total number of business requests that a cloud computing platform needs to execute within a unit of time, thereby statistically analyzing the number of times the target system component executes business requests, and calculating the resource consumption value of the corresponding target system component. Based on the resource consumption value and available resource value of the target system component, it determines whether the target system component meets the testing requirements, thus improving the testing effect when computing resources are used to test the target system component.

[0176] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, this computer program implements the various processes of the above-described cloud computing platform computing resource testing method embodiment and achieves the same technical effect. To avoid repetition, it will not be described again here. The computer-readable storage medium provided in this application embodiment can be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0177] This application also provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described cloud computing platform computing resource testing method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0178] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0179] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of this application.

[0180] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for testing computing resources on a cloud computing platform, characterized in that, The method includes: Determine the total number of business requests that the cloud computing platform needs to execute within a unit of time, wherein the cloud computing platform can execute multiple types of business requests, and the total number of business requests is the sum of the number of business requests of the multiple types; Based on the number of times the target system component is called when executing various types of business requests, the total number of times the target system component is called per unit time is obtained, wherein the cloud computing platform includes multiple system components, and the target system component is any one of the multiple system components; Based on the total number of calls to the target system component, the resource consumption value of the target system component is obtained; The resource consumption value of the target system component is compared with the available resource value of the target system component to generate a test result, which indicates whether the target system component meets the total number of business requests that the cloud computing platform can process.

2. The method according to claim 1, characterized in that, The total number of calls to the target system component per unit time, based on the number of calls to the target system component when executing various types of business requests, includes: Based on the total number of business requests that the cloud computing platform needs to execute within a unit of time, determine the number of each type of business request that the cloud computing platform needs to execute within a unit of time. Based on the number of business requests of each type and the number of times the target system component is called when executing the corresponding business request, the number of times the target system component is called by each type of business request per unit time is obtained; The total number of calls to the target system component by each type of business request within the unit time period is obtained by summing the number of calls to the target system component within the unit time period.

3. The method according to claim 2, characterized in that, The determination of the number of various types of business requests that the cloud computing platform needs to execute within a unit of time, based on the total number of business requests that the cloud computing platform needs to execute within a unit of time, includes: Based on the historical data included in the cloud computing platform, the proportion of each type of business request in the total business requests is determined. Based on the proportion of each type of business request in the total business requests and the total number of business requests, the number of each type of business request is obtained. And / or, The system monitors the data received by the cloud computing platform in real time, determines the proportion of each type of business request in the total business requests based on the data received within a preset period, and obtains the number of each type of business request based on the proportion of each type of business request in the total business requests and the total number of business requests.

4. The method according to claim 2, characterized in that, Before obtaining the total number of calls to the target system component per unit time based on the number of calls to the target system component when executing various types of business requests, the method further includes: The business source code is parsed to obtain the calling relationship between various types of business requests, wherein the business source code is the source code corresponding to the multiple types of business requests; The step of obtaining the number of times each type of business request calls the target system component per unit time, based on the number of each type of business request and the number of times the target system component is called when executing the corresponding type of business request, includes: Update the number of each type of business request based on the calling relationship between the various types of business requests; Based on the number of updated business requests of each type and the number of times the target system component is called when executing the corresponding business request, the number of times the target system component is called by each type of business request per unit time is obtained.

5. The method according to claim 1, characterized in that, Before obtaining the resource consumption value of the target system component based on the total number of calls to the target system component, the method further includes: The business source code is parsed to obtain the calling methods of the target system components and the number of times the calling methods are used, wherein the business source code is the source code corresponding to the multiple types of business requests; Then, obtaining the resource consumption value of the target system component based on the total number of calls to the target system component includes: Based on the total number of calls to the target system component, the calling method, and the number of times the calling method was used, the resource consumption value of the target system component is obtained.

6. The method according to claim 5, characterized in that, The process of obtaining the resource consumption value of the target system component based on the total number of calls to the target system component, the calling method, and the number of times the calling method was used includes: The total number of calls to the target system component, the calling method, and the number of times the calling method was used are input into the machine learning model, and the resource consumption value of the target system component is output. The machine learning model is used to predict the computing resources required by the target system components when executing the various types of business requests, and to generate the resource consumption value.

7. The method according to claim 1, characterized in that, After comparing the resource consumption value of the target system component with the available resource value of the target system component to generate test results, the method further includes: The test results are analyzed to generate system optimization measures, which are used to increase the total number of business requests executed by the cloud computing platform per unit time. The system optimization measures include at least one of the following: increasing the CPU capacity, memory capacity, network usage, and GPU capacity for the target system components.

8. The method according to any one of claims 1-7, characterized in that, The system components include at least one of the following: a gateway, a container orchestration platform, a container scheduling unit, and a database.

9. A computing resource testing device for a cloud computing platform, characterized in that, include: The determination module is used to determine the total number of business requests that the cloud computing platform needs to execute within a unit of time, wherein the cloud computing platform can execute multiple types of business requests, and the total number of business requests is the sum of the number of business requests of the multiple types; The statistics module is used to obtain the total number of calls to the target system component per unit time based on the number of calls to the target system component when executing various types of business requests, wherein the cloud computing platform includes multiple system components, and the target system component is any one of the multiple system components; The calculation module is used to obtain the resource consumption value of the target system component based on the total number of calls to the target system component; The generation module is used to compare the resource consumption value of the target system component with the available resource value of the target system component, and generate a test result. The test result indicates whether the target system component meets the total number of business requests that the cloud computing platform can process.

10. An electronic device, comprising: A memory, a processor, and a program stored in the memory and executable on the processor; characterized in that the processor is configured to read the program from the memory to implement the steps in the computing resource testing method for a cloud computing platform as described in any one of claims 1 to 8.

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