A method and apparatus for automatic optimization control of system performance

Abstract

The application discloses a kind of automatic optimization regulation and control method and device of system performance, the method includes: when detecting that there is for triggering execution interface stress measurement instruction to target system, the interface running data of target system in preset test period is collected;Determine a plurality of performance indicators for analyzing interface running data and each performance indicator corresponding indicator data in preset test period;According to each performance indicator corresponding indicator data combined with stress measurement analysis algorithm, interface running data is compared and analyzed, and the indicator analysis result corresponding to each performance indicator is obtained;When determining that there is target performance indicator needing to execute performance optimization operation in all indicator analysis results, according to the indicator analysis result corresponding to target performance indicator, the optimization regulation and control scheme for target performance indicator is generated, and performance optimization operation is executed to target performance indicator. Visible, the performance optimization of product interface, product system can be realized by implementing the present application.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of performance optimization, in particular to an automatic optimization and regulation method and device for system performance. BACKGROUND

[0002] With the development of enterprise products, the expansion of scenarios and the increase of the number of audiences, the data access volume of product interfaces will inevitably increase, and the increase in access volume means that the access performance of the interface needs to be updated and iterated. However, after the design of a product is completed, the performance of the product interface is basically fixed, or the product interface needs to be redesigned, which has a very low cost performance, or the performance optimization is improved on the basis of the original performance algorithm, so as to improve the performance of the product interface and the overall performance of the product. This performance optimization direction is also the current mainstream research scheme. In order to better adapt to the iterative update of the product and meet the access requirements of the product users, it is particularly important to provide a method for realizing the performance optimization of the interface and the product system. SUMMARY

[0003] The technical problem to be solved by the present application is to provide an automatic optimization and regulation method and device for system performance, which can adapt to the iterative update of the product, meet the access requirements of the product, and realize the performance optimization of the product interface and the product system.

[0004] In order to solve the above technical problems, the present application discloses an automatic optimization and regulation method for system performance, which comprises the following steps:

[0005] When it is detected that there is an interface stress test instruction for triggering the execution of the interface stress test instruction for the target system, the interface running data of the target system in a preset test period is collected according to the interface stress test instruction;

[0006] A plurality of performance indicators for analyzing the interface running data and the corresponding indicator data of each performance indicator in the preset test period are determined;

[0007] According to the corresponding indicator data of each performance indicator and the preset stress test analysis algorithm, the interface running data is compared and analyzed to obtain the stress test analysis data corresponding to the target system, and the stress test analysis data comprises the indicator analysis result corresponding to each performance indicator;

[0008] When it is determined that there is a target performance indicator that needs to perform a preset performance optimization operation in all the indicator analysis results, an optimization and regulation scheme for the target performance indicator is generated according to the indicator analysis result corresponding to the target performance indicator, and the performance optimization operation is performed on the target performance indicator according to the optimization and regulation scheme, so that the indicator analysis result corresponding to the target performance indicator is adjusted to meet the performance requirement corresponding to the target performance indicator.

[0009] As an optional implementation, in the first aspect of the present application, the target system corresponding stress test analysis data is obtained by comparing and analyzing the interface running data according to the index data corresponding to each performance indicator and a preset stress test analysis algorithm, comprising:

[0010] determining the interface data interaction record corresponding to the target system according to the interface running data;

[0011] determining the data interaction amount corresponding to each performance indicator according to the interface data interaction record;

[0012] for each performance indicator, the actual running data corresponding to the performance indicator in the preset test period is obtained by comparing and analyzing according to the data interaction amount corresponding to the performance indicator and a preset stress test analysis algorithm;

[0013] analyzing the actual running data corresponding to each performance indicator and the index data corresponding to each performance indicator to obtain the index analysis data corresponding to each performance indicator, wherein the index analysis data corresponding to each performance indicator comprises a standard or non-standard identifier for indicating that the actual running data corresponding to the performance indicator is within the index data corresponding to the performance indicator;

[0014] determining the target system corresponding stress test analysis data according to the index analysis data corresponding to each performance indicator.

[0015] As an optional implementation, in the first aspect of the present application, when the index analysis data corresponding to a certain performance indicator comprises the non-standard identifier, the index analysis data corresponding to the performance indicator further comprises an index difference value and a difference value type corresponding to the index difference value, and the difference value type comprises an excess type indicating that the actual running data corresponding to the performance indicator is greater than the index data corresponding to the performance indicator or a complementary difference type opposite to the excess type;

[0016] the index difference value corresponding to any target performance indicator comprising the non-standard identifier is calculated by the following method:

[0017] determining two data interval endpoints corresponding to the index data corresponding to the target performance indicator, denoted as a first endpoint and a second endpoint, wherein the value of the first endpoint is less than the value of the second endpoint;

[0018] When the actual operating data corresponding to the target performance indicator is less than the indicator data corresponding to the target performance indicator, the difference between the first endpoint and the actual operating data corresponding to the target performance indicator is calculated as the indicator difference of the target performance indicator, and the indicator type of the indicator difference is the difference compensation type.

[0019] When the actual operating data corresponding to the target performance indicator is greater than the indicator data corresponding to the target performance indicator, the numerical difference between the actual operating data corresponding to the target performance indicator and the second endpoint is calculated as the indicator difference value of the target performance indicator, and the indicator type of the indicator difference value is the excess type.

[0020] As an optional implementation, in the first aspect of the present invention, after performing the performance optimization operation on the target performance index according to the optimization control scheme, the method includes:

[0021] Obtain the actual optimization effect and expected optimization data after performing the performance optimization operation on the target performance index, wherein the expected optimization data is the pre-estimated optimization data obtained by optimizing the target performance index based on the optimization control scheme;

[0022] When the actual optimization effect is higher than the expected optimization data, the stress test analysis algorithm and the optimization prediction model used to determine the expected optimization data are updated according to the actual optimization effect.

[0023] When the actual optimization effect is lower than the expected optimization data, the optimization control scheme, the actual optimization effect, and the expected optimization data are analyzed according to the optimization prediction model to obtain scheme adjustment information for the optimization control scheme. The optimization control scheme is then adjusted according to the scheme adjustment information so that the actual optimization effect corresponding to the adjusted optimization control scheme is higher than the expected optimization data.

[0024] As an optional implementation, in the first aspect of the present invention, generating an optimized control scheme for the target performance index based on the index analysis results corresponding to the target performance index includes:

[0025] Based on the analysis results of the indicators corresponding to the target performance indicators, determine the indicator difference corresponding to the target performance indicators and the indicator type corresponding to the indicator difference;

[0026] Several performance optimization schemes that match the index type of the target performance index are determined from a preset performance optimization scheme library to obtain a set of alternative schemes;

[0027] From the set of alternative solutions, select the solutions with a higher fit to the target performance index than the baseline fit, based on the index difference and the index type corresponding to the index difference.

[0028] As an optional implementation, in the first aspect of the present invention, the step of selecting from the set of alternative solutions a solution whose solution fit for the target performance indicator is higher than the baseline fit for the indicator type corresponding to the target performance indicator, and which has a solution difference value corresponding to the indicator difference value, as an optimization and control solution for the target performance indicator, includes:

[0029] From the set of alternative solutions, select all alternative solutions whose optimization performance ranks within a preset ranking in the preset historical optimization records. The historical optimization records contain operation records after performing the performance optimization operation on a performance indicator of the same type as the target performance indicator.

[0030] Calculate the first fit value between each of the alternative solutions and the index difference corresponding to the target performance index, and the second fit value between each alternative solution and the index type corresponding to the index difference. Combine the first fit value and the second fit value corresponding to each alternative solution to obtain the comprehensive fit value corresponding to each alternative solution.

[0031] The alternative with the highest overall fit value among all the alternative options is determined as the optimized control scheme for the target performance index.

[0032] As an optional implementation, in the first aspect of the present invention, the second adaptation value corresponding to each of the alternative schemes includes a first sub-value or a second sub-value for representing the alternative scheme, and when the second adaptation value corresponding to any of the alternative schemes is the second sub-value, it is determined that the comprehensive adaptation value corresponding to the alternative scheme is lower than the benchmark adaptation degree.

[0033] The performance optimization scheme library includes several performance optimization schemes for optimizing the performance indicators, and all the performance optimization schemes include performance optimization schemes corresponding to at least one of the following types: code optimization type, database optimization type, cache optimization type, multi-threading optimization type, batch processing type, and asynchronous processing type.

[0034] A second aspect of the present invention discloses an automatic optimization and control device for system performance, the device comprising:

[0035] The data acquisition module is used to collect interface operation data of the target system within a preset test period according to the interface stress test command when an interface stress test command for triggering the execution of the target system is detected.

[0036] The determination module is used to determine several performance indicators for analyzing the interface operation data and the corresponding indicator data for each performance indicator within the preset test period.

[0037] The comparison and analysis module is used to compare and analyze the interface operation data based on the indicator data corresponding to each performance indicator and a preset stress test analysis algorithm to obtain the stress test analysis data corresponding to the target system. The stress test analysis data includes the indicator analysis results corresponding to each performance indicator.

[0038] The generation module is used to generate an optimization and control scheme for the target performance indicator based on the indicator analysis results corresponding to the target performance indicator when it is determined that there is a target performance indicator among all the indicator analysis results that requires the execution of a preset performance optimization operation.

[0039] An optimization module is used to perform the performance optimization operation on the target performance index according to the optimization and control scheme, so as to adjust the index analysis result corresponding to the target performance index to meet the performance requirements corresponding to the target performance index.

[0040] As an optional implementation, in the second aspect of the present invention, the comparison and analysis module compares and analyzes the interface operation data based on the index data corresponding to each performance indicator and a preset stress test analysis algorithm to obtain the stress test analysis data corresponding to the target system. Specifically, this includes:

[0041] Determine the interface data interaction records corresponding to the target system based on the interface operation data;

[0042] The amount of data interaction corresponding to each performance indicator is determined based on the interface data interaction record.

[0043] For each performance indicator, based on the data interaction volume corresponding to the performance indicator and combined with a preset stress test analysis algorithm, the actual running data corresponding to the performance indicator within the preset test period is obtained by comparison and analysis.

[0044] Analyze the actual operating data and the indicator data corresponding to each performance indicator to obtain indicator analysis data corresponding to each performance indicator. The indicator analysis data corresponding to each performance indicator includes a compliance identifier or non-compliance identifier to indicate that the actual operating data corresponding to the performance indicator is within the indicator data corresponding to the performance indicator.

[0045] Based on the index analysis data corresponding to each of the aforementioned performance indicators, the stress test analysis data corresponding to the target system is determined.

[0046] As an optional implementation, in the second aspect of the present invention, when the indicator analysis data corresponding to a certain performance indicator includes the non-compliance identifier, the indicator analysis data corresponding to the performance indicator further includes an indicator difference and a difference type corresponding to the indicator difference. The difference type includes an excess type indicating that the actual operating data corresponding to the performance indicator is greater than the indicator data corresponding to the standard performance indicator, or a compensation type opposite to the excess type.

[0047] The difference in the target performance index corresponding to any one of the non-compliant identifiers is calculated in the following way:

[0048] Determine the two data interval endpoints corresponding to the target performance index, denoted as the first endpoint and the second endpoint, wherein the value of the first endpoint is less than the value of the second endpoint;

[0049] When the actual operating data corresponding to the target performance indicator is less than the indicator data corresponding to the target performance indicator, the difference between the first endpoint and the actual operating data corresponding to the target performance indicator is calculated as the indicator difference of the target performance indicator, and the indicator type of the indicator difference is the difference compensation type.

[0050] When the actual operating data corresponding to the target performance indicator is greater than the indicator data corresponding to the target performance indicator, the numerical difference between the actual operating data corresponding to the target performance indicator and the second endpoint is calculated as the indicator difference value of the target performance indicator, and the indicator type of the indicator difference value is the excess type.

[0051] As an optional implementation, in a second aspect of the invention, the apparatus further includes:

[0052] The acquisition module is used to acquire the actual optimization effect and expected optimization data after the optimization module performs the performance optimization operation on the target performance index according to the optimization control scheme, wherein the expected optimization data is the optimization data obtained by optimizing the target performance index based on the optimization control scheme in advance.

[0053] The update module is used to update the stress test analysis algorithm and the optimization prediction model for determining the expected optimization data based on the actual optimization effect when the actual optimization effect is higher than the expected optimization data.

[0054] The comparison and analysis module is also used to analyze the optimization control scheme, the actual optimization effect, and the expected optimization data according to the optimization prediction model when the actual optimization effect is lower than the expected optimization data, and to obtain scheme adjustment information for the optimization control scheme.

[0055] The adjustment module is used to adjust the optimization control scheme according to the scheme adjustment information, so that the actual optimization effect corresponding to the adjusted optimization control scheme is higher than the expected optimization data.

[0056] As an optional implementation, in the second aspect of the present invention, the method by which the generation module generates an optimized control scheme for the target performance index based on the index analysis results corresponding to the target performance index specifically includes:

[0057] Based on the analysis results of the indicators corresponding to the target performance indicators, determine the indicator difference corresponding to the target performance indicators and the indicator type corresponding to the indicator difference;

[0058] Several performance optimization schemes that match the index type of the target performance index are determined from a preset performance optimization scheme library to obtain a set of alternative schemes;

[0059] From the set of alternative solutions, select the solutions with a higher fit to the target performance index than the baseline fit, based on the index difference and the index type corresponding to the index difference.

[0060] As an optional implementation, in a second aspect of the present invention, the generation module selects from the set of alternative solutions a scheme whose scheme fit is higher than the baseline fit for the target performance index, based on the index difference corresponding to the index type corresponding to the index difference. This specifically includes the following methods for optimizing and controlling the target performance index:

[0061] From the set of alternative solutions, select all alternative solutions whose optimization performance ranks within a preset ranking in the preset historical optimization records. The historical optimization records contain operation records after performing the performance optimization operation on a performance indicator of the same type as the target performance indicator.

[0062] Calculate the first fit value between each of the alternative solutions and the index difference corresponding to the target performance index, and the second fit value between each alternative solution and the index type corresponding to the index difference. Combine the first fit value and the second fit value corresponding to each alternative solution to obtain the comprehensive fit value corresponding to each alternative solution.

[0063] The alternative with the highest overall fit value among all the alternative options is determined as the optimized control scheme for the target performance index.

[0064] As an optional implementation, in a second aspect of the present invention, the second adaptation value corresponding to each of the alternative schemes includes a first sub-value or a second sub-value for representing the alternative scheme, and when the second adaptation value corresponding to any of the alternative schemes is the second sub-value, it is determined that the comprehensive adaptation value corresponding to the alternative scheme is lower than the benchmark adaptation degree.

[0065] The performance optimization scheme library includes several performance optimization schemes for optimizing the performance indicators, and all the performance optimization schemes include performance optimization schemes corresponding to at least one of the following types: code optimization type, database optimization type, cache optimization type, multi-threading optimization type, batch processing type, and asynchronous processing type.

[0066] A third aspect of the present invention discloses another automatic optimization and control device for system performance, the device comprising:

[0067] Memory containing executable program code;

[0068] A processor coupled to the memory;

[0069] The processor calls the executable program code stored in the memory to execute the automatic optimization and control method for system performance disclosed in the first aspect of the present invention.

[0070] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the automatic optimization and control method for system performance disclosed in the first aspect of the present invention.

[0071] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0072] This invention provides an automatic optimization and control method for system performance. The method includes: when an interface stress test command for a target system is detected, collecting interface operation data of the target system within a preset test period according to the interface stress test command; determining several performance indicators for analyzing the interface operation data and the corresponding indicator data for each performance indicator within the preset test period; comparing and analyzing the interface operation data based on the indicator data corresponding to each performance indicator and a preset stress test analysis algorithm to obtain stress test analysis data corresponding to the target system, the stress test analysis data including the indicator analysis results corresponding to each performance indicator; when a target performance indicator requiring preset performance optimization operations is identified among all indicator analysis results, generating an optimization and control scheme for the target performance indicator based on the indicator analysis results corresponding to the target performance indicator, and performing performance optimization operations on the target performance indicator according to the optimization and control scheme, so that the indicator analysis results corresponding to the target performance indicator are adjusted to meet the performance requirements corresponding to the target performance indicator. As can be seen, implementing this invention enables the analysis of interface operation data item by item based on several determined performance indicators, obtaining the analysis results corresponding to each performance indicator in the interface operation data. Then, for the target performance indicators that require performance optimization operations, the invention automatically generates and executes the corresponding optimization and control scheme, realizing performance optimization based on interface data, and thereby optimizing system performance through interface performance optimization. This improves the optimization efficiency, reliability, and accuracy of performance optimization. Attached Figure Description

[0073] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0074] Figure 1 This is a flowchart illustrating an automatic optimization and control method for system performance disclosed in an embodiment of the present invention;

[0075] Figure 2 This is a flowchart illustrating another automatic optimization and control method for system performance disclosed in an embodiment of the present invention;

[0076] Figure 3 This is a schematic diagram of the structure of an automatic system performance optimization and control device disclosed in an embodiment of the present invention;

[0077] Figure 4 This is a schematic diagram of another automatic system performance optimization and control device disclosed in an embodiment of the present invention;

[0078] Figure 5This is a schematic diagram of the structure of another automatic system performance optimization and control device disclosed in the embodiments of the present invention;

[0079] Figure 6 This is a flame diagram illustrating the analysis and optimization effect of program memory usage as disclosed in an embodiment of the present invention. Detailed Implementation

[0080] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0081] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0082] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0083] This invention discloses an automatic optimization and control method and apparatus for system performance. Based on several determined performance indicators, it analyzes interface operation data item by item to obtain the analysis results corresponding to each performance indicator in the interface operation data. Then, for the target performance indicator requiring performance optimization, it automatically generates and executes the corresponding optimization and control scheme. This achieves performance optimization based on interface data, and ultimately optimizes system performance through interface performance optimization, improving the optimization efficiency, reliability, and accuracy. Detailed descriptions follow.

[0084] Example 1

[0085] Please see Figure 1 , Figure 1This is a flowchart illustrating an automatic optimization and control method for system performance disclosed in an embodiment of the present invention. Figure 1 The described automatic optimization and control method for system performance can be applied to automatic optimization and control devices for system performance, and the embodiments of the present invention are not limited thereto. Figure 1 As shown, the automatic optimization and control method for the system performance may include the following operations:

[0086] 101. When an interface stress test command for the target system is detected, the interface operation data of the target system within the preset test period is collected according to the interface stress test command.

[0087] In this embodiment of the invention, the preset test period can refer to 1 / 3 / 5 hours after receiving the interface stress test command as a preset test period; or it can refer to the collection and storage of interface operation data of the target system under normal conditions. In this case, the preset test period refers to 1 / 3 / 5 hours before the detection time corresponding to the interface stress test command is detected as a preset test period. In this case, the interface operation data stored in the database can be directly called. This embodiment of the invention does not limit the scope.

[0088] In this embodiment of the invention, optionally, the operation execution corresponding to the interface operation data of the target system can be resident, that is, the interface operation data of the target system is collected and monitored in real time, so as to issue an alarm in a timely manner when a performance bottleneck occurs.

[0089] 102. Determine several performance metrics used to analyze the interface's runtime data, as well as the corresponding metric data for each performance metric within a preset test period.

[0090] In this embodiment of the invention, the performance metric can be the server's CPU, memory usage, network I / O, disk I / O, JVM garbage collection, etc. The metric data corresponding to each performance metric within a preset test period is used to determine whether the performance metric is overloaded within the preset test period. For example, when the CPU usage exceeds 60%, it indicates that there is CPU-intensive code in the program.

[0091] 103. Based on the index data corresponding to each performance indicator and the preset stress test analysis algorithm, compare and analyze the interface running data to obtain the stress test analysis data corresponding to the target system.

[0092] In this embodiment of the invention, step 103, which involves comparing and analyzing interface running data based on the index data corresponding to each performance indicator with a preset stress test analysis algorithm to obtain the stress test analysis data corresponding to the target system, specifically includes:

[0093] Determine the corresponding interface data interaction records of the target system based on the interface operation data;

[0094] Determine the amount of data interaction corresponding to each performance indicator based on the interface data interaction records;

[0095] For each performance metric, based on the data interaction volume corresponding to that performance metric, and combined with the preset stress test analysis algorithm, the actual running data corresponding to that performance metric within the preset test period is obtained through comparative analysis.

[0096] Analyze the actual operating data and indicator data corresponding to each performance indicator to obtain the indicator analysis data corresponding to each performance indicator. The indicator analysis data corresponding to each performance indicator includes a compliance identifier or non-compliance identifier to indicate that the actual operating data corresponding to the performance indicator is within the indicator data corresponding to the performance indicator.

[0097] Based on the analysis data corresponding to each performance indicator, determine the stress test analysis data corresponding to the target system.

[0098] In this embodiment of the invention, the analysis data corresponding to each performance indicator can be presented in the form of visual reports, charts, etc. For example, intelligent analysis comparing QPS and CPU memory usage can analyze the impact of program execution on CPU, memory, or network. Specifically, assuming that CPU usage exceeds 60%, it indicates that there is CPU-intensive code in the program. A flame graph can be automatically generated to analyze the program's CPU time slices, allowing for the identification and optimization of high-CPU-consuming code. Please refer to the flame graph example. Figure 6 .

[0099] As can be seen, in this embodiment of the invention, each performance indicator is used as a benchmark, and the actual operating data and indicator data corresponding to each performance indicator are intelligently compared and analyzed to obtain the indicator analysis data corresponding to each performance indicator, thereby determining the comprehensive stress test analysis data of the target system, which improves the accuracy of determining the stress test analysis data for the target system.

[0100] 104. When it is determined that there is a target performance indicator among all the indicator analysis results that requires the execution of preset performance optimization operations, an optimization and control scheme for the target performance indicator is generated based on the indicator analysis results corresponding to the target performance indicator.

[0101] 105. Perform performance optimization operations on the target performance indicators according to the optimization and control plan, so that the indicator analysis results corresponding to the target performance indicators are adjusted to meet the performance requirements corresponding to the target performance indicators.

[0102] It is evident that implementation Figure 1The described automatic optimization and control method for system performance can analyze interface operation data item by item based on several determined performance indicators, obtain the analysis results corresponding to each performance indicator in the interface operation data, and then automatically generate and execute the corresponding optimization and control scheme for the target performance indicator that needs to perform performance optimization operations. This realizes performance optimization based on interface data, and then optimizes the system performance by optimizing the interface performance, thereby improving the optimization efficiency, reliability and accuracy of performance optimization.

[0103] Example 2

[0104] Please see Figure 2 , Figure 2 This is a flowchart illustrating another automatic optimization and control method for system performance disclosed in an embodiment of the present invention. Figure 2 The described automatic optimization and control method for system performance can be applied to automatic optimization and control devices for system performance, and the embodiments of the present invention are not limited thereto. Figure 2 As shown, the automatic optimization and control method for the system performance may include the following operations:

[0105] 201. When an interface stress test command for the target system is detected, the interface operation data of the target system within the preset test period is collected according to the interface stress test command.

[0106] 202. Determine several performance metrics used to analyze the interface operation data and the corresponding metric data for each performance metric within a preset test period.

[0107] 203. Based on the index data corresponding to each performance indicator and the preset stress test analysis algorithm, compare and analyze the interface running data to obtain the stress test analysis data corresponding to the target system.

[0108] 204. When it is determined that there is a target performance indicator among all the indicator analysis results that requires the execution of preset performance optimization operations, an optimization and control plan for the target performance indicator is generated based on the indicator analysis results corresponding to the target performance indicator.

[0109] 205. Perform performance optimization operations on the target performance indicators according to the optimization and control plan, so that the indicator analysis results corresponding to the target performance indicators are adjusted to meet the performance requirements corresponding to the target performance indicators.

[0110] For further descriptions of steps 201-205 in this embodiment of the invention, please refer to the other specific descriptions of steps 101-105 in Embodiment 1. These descriptions will not be repeated in this embodiment of the invention.

[0111] 206. Obtain the actual optimization effect and expected optimization data after performing performance optimization operations on the target performance index.

[0112] In this embodiment of the invention, the expected optimization data is the optimized data obtained by pre-estimating the target performance index based on the optimized control scheme.

[0113] 207. When the actual optimization effect is higher than the expected optimization data, update the stress test analysis algorithm and the optimization prediction model used to determine the expected optimization data based on the actual optimization effect.

[0114] In this embodiment of the invention, optionally, when it is determined that the actual optimization effect is higher than the expected optimization data, the method of updating the stress test analysis algorithm and the optimization prediction model used to determine the expected optimization data based on the actual optimization effect specifically includes:

[0115] The target optimization performance index is determined when the actual optimization effect is higher than the expected optimization data. This index is denoted as the target index. The corresponding optimization control scheme is also determined and denoted as the target scheme.

[0116] Based on the target indicator, the target solution, and the actual optimization effect and expected optimization data corresponding to the target indicator, determine the optimization information for the target indicator; the optimization information includes at least one of the specific optimization measures corresponding to the target solution, the parameters adopted by the target solution, and the optimization effect.

[0117] The stress test analysis algorithm and the optimization prediction model used to determine the expected optimization data are updated based on the optimization information.

[0118] In this optional embodiment, when the actual optimization effect is higher than the expected optimization data, the system can intelligently generate optimization information corresponding to the good optimization effect of the solution, thereby updating the stress test analysis algorithm and optimizing the prediction model; thus realizing intelligent iteration of performance optimization, improving the accuracy and efficiency of subsequent execution interface performance optimization and system performance optimization.

[0119] 208. When the actual optimization effect is lower than the expected optimization data, the optimization control scheme, the actual optimization effect and the expected optimization data are analyzed based on the optimization prediction model to obtain the scheme adjustment information for the optimization control scheme.

[0120] 209. Adjust and optimize the control scheme according to the scheme adjustment information so that the actual optimization effect corresponding to the adjusted optimized control scheme is higher than the expected optimization data.

[0121] It is evident that implementation Figure 2The described automatic optimization and control method for system performance includes a verification process for the optimization effect after each target performance indicator is optimized. This process involves obtaining the actual optimization effect and expected optimization data for each target performance indicator, comparing the two, and determining the difference. If the actual optimization effect is higher than the expected optimization data, it indicates that the optimization and control scheme for a specific target performance indicator is highly effective and can be used as auxiliary data for updating the stress testing analysis algorithm and optimizing the prediction model. If the actual optimization effect is lower than the expected optimization data, it indicates that the performance optimization for that target performance indicator has not met the requirements of the expected optimization data, and the optimization and control scheme needs to be automatically adjusted and re-optimized. This improves the accuracy and reliability of interface performance optimization and system performance optimization based on interface data.

[0122] In an optional embodiment, after obtaining the indicator analysis data corresponding to each performance indicator in step 203, and when the indicator analysis data corresponding to a certain performance indicator includes a non-compliance identifier, the indicator analysis data corresponding to that performance indicator also includes an indicator difference and a difference type corresponding to the indicator difference. The difference type includes an excess type indicating that the actual operating data corresponding to that performance indicator is greater than the indicator data corresponding to that performance indicator, or a compensation type opposite to the excess type.

[0123] The difference in any target performance indicator that includes a non-compliant identifier is calculated as follows:

[0124] Determine the endpoints of the two data intervals corresponding to the target performance index, denoted as the first endpoint and the second endpoint, where the value of the first endpoint is less than the value of the second endpoint.

[0125] When the actual operating data corresponding to the target performance indicator is less than the indicator data corresponding to the target performance indicator, the difference between the first endpoint and the actual operating data corresponding to the target performance indicator is calculated as the indicator difference of the target performance indicator. The indicator type of the indicator difference is the difference compensation type.

[0126] When the actual operating data corresponding to the target performance indicator is greater than the indicator data corresponding to the target performance indicator, the numerical difference between the actual operating data corresponding to the target performance indicator and the second endpoint is calculated as the indicator difference value of the target performance indicator. The indicator type of the indicator difference value is the excess type.

[0127] As can be seen, in this optional embodiment, for each target performance indicator, the difference between the actual operating data and the indicator data of the target performance indicator can be automatically calculated, and the data relationship between the two can be determined, thereby accurately determining the detailed data of the target performance indicator including non-compliant identifiers, and improving the data accuracy of the stress test analysis data of the determined target system.

[0128] In another optional embodiment, step 204, which generates an optimized control scheme for the target performance index based on the index analysis results corresponding to the target performance index, specifically includes the following methods:

[0129] Based on the analysis results of the indicators corresponding to the target performance indicators, determine the indicator difference corresponding to the target performance indicators and the indicator type corresponding to the indicator difference;

[0130] Several performance optimization schemes matching the target performance index type are determined from the preset performance optimization scheme library to obtain a set of alternative schemes;

[0131] From the set of alternative solutions, select the solutions with the index difference corresponding to the target performance index and the solution fit degree corresponding to the index type of the index difference that is higher than the benchmark fit degree, and use them as the optimization and control solutions for the target performance index.

[0132] In this optional embodiment, the method of selecting schemes from the set of alternative schemes whose index difference corresponding to the target performance index and whose scheme fit for the index type corresponding to the index difference is higher than the benchmark fit, as optimization and control schemes for the target performance index, specifically includes:

[0133] Filter out all alternative solutions from the set of alternative solutions that are ranked within a preset order in the preset historical optimization records. The historical optimization records contain operation records after performing performance optimization operations on performance indicators of the same type as the target performance indicator.

[0134] Calculate the first fit value between each alternative solution and the index difference corresponding to the target performance index, and the second fit value between each alternative solution and the index type corresponding to the index difference. Combine the first fit value and the second fit value of each alternative solution to obtain the comprehensive fit value of each alternative solution.

[0135] The option with the highest overall fit value among all alternative options is selected as the optimized control scheme for the target performance index.

[0136] In this optional embodiment, optionally, the second adaptation value corresponding to each alternative solution includes a first sub-value or a second sub-value for representing the alternative solution, and when the second adaptation value corresponding to any alternative solution is the second sub-value, it is determined that the comprehensive adaptation value corresponding to the alternative solution is lower than the benchmark adaptation degree.

[0137] The performance optimization scheme library includes several performance optimization schemes for optimizing performance metrics. All performance optimization schemes include performance optimization schemes corresponding to at least one of the following types: code optimization, database optimization, caching optimization, multithreading optimization, batch processing, and asynchronous processing.

[0138] As can be seen, in this optional embodiment, when generating an optimized control scheme for each target performance indicator, multiple performance optimization schemes from the performance optimization scheme library can be integrated to obtain a set of candidate schemes. Then, by integrating the indicator difference and indicator type of the target performance indicator, schemes with a higher fit than the benchmark fit are selected as the required optimized control schemes. In calculating the fit of the schemes, the ranking in the historical optimization records can also be referenced, and the first fit value of the indicator difference and the second fit value of the indicator type for each candidate scheme can be calculated to comprehensively select the optimized control scheme. The multi-level progressive screening method improves the accuracy and reliability of the final determined optimized control scheme.

[0139] Example 3

[0140] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an automatic system performance optimization and control device disclosed in an embodiment of the present invention. The automatic system performance optimization and control device can be an automatic system performance optimization and control terminal, equipment, system, or server. The server can be a local server, a remote server, or a cloud server (also known as a cloud-based server). When the server is a non-cloud server, it can communicate with the cloud server; this embodiment of the present invention does not impose any limitations. Figure 3 As shown, the automatic performance optimization and control device of the system may include a data acquisition module 301, a determination module 302, a comparison and analysis module 303, a generation module 304, and an optimization module 305, wherein:

[0141] The data acquisition module 301 is used to collect interface operation data of the target system within a preset test period according to the interface stress test command when an interface stress test command for triggering the execution of the target system is detected.

[0142] The determination module 302 is used to determine several performance indicators for analyzing the interface operation data and the corresponding indicator data of each performance indicator within a preset test period.

[0143] The comparison and analysis module 303 is used to compare and analyze the interface running data based on the index data corresponding to each performance index and the preset stress test analysis algorithm to obtain the stress test analysis data corresponding to the target system. The stress test analysis data includes the index analysis results corresponding to each performance index.

[0144] In this embodiment of the invention, optionally, the comparison and analysis module 303 compares and analyzes the interface running data based on the index data corresponding to each performance indicator and a preset stress test analysis algorithm to obtain the stress test analysis data corresponding to the target system. Specifically, this includes:

[0145] Determine the corresponding interface data interaction records of the target system based on the interface operation data;

[0146] Determine the amount of data interaction corresponding to each performance indicator based on the interface data interaction records;

[0147] For each performance metric, based on the data interaction volume corresponding to that performance metric, and combined with the preset stress test analysis algorithm, the actual running data corresponding to that performance metric within the preset test period is obtained through comparative analysis.

[0148] Analyze the actual operating data and indicator data corresponding to each performance indicator to obtain the indicator analysis data corresponding to each performance indicator. The indicator analysis data corresponding to each performance indicator includes a compliance identifier or non-compliance identifier to indicate that the actual operating data corresponding to the performance indicator is within the indicator data corresponding to the performance indicator.

[0149] Based on the analysis data corresponding to each performance indicator, determine the stress test analysis data corresponding to the target system.

[0150] In this embodiment of the invention, optionally, when the indicator analysis data corresponding to a certain performance indicator includes a non-compliance identifier, the indicator analysis data corresponding to the performance indicator also includes an indicator difference and a difference type corresponding to the indicator difference. The difference type includes an excess type indicating that the actual operating data corresponding to the performance indicator is greater than the indicator data corresponding to the standard performance indicator, or a compensation type opposite to the excess type.

[0151] The difference in any target performance indicator that includes a non-compliant identifier is calculated as follows:

[0152] Determine the endpoints of the two data intervals corresponding to the target performance index, denoted as the first endpoint and the second endpoint, where the value of the first endpoint is less than the value of the second endpoint.

[0153] When the actual operating data corresponding to the target performance indicator is less than the indicator data corresponding to the target performance indicator, the difference between the first endpoint and the actual operating data corresponding to the target performance indicator is calculated as the indicator difference of the target performance indicator. The indicator type of the indicator difference is the difference compensation type.

[0154] When the actual operating data corresponding to the target performance indicator is greater than the indicator data corresponding to the target performance indicator, the numerical difference between the actual operating data corresponding to the target performance indicator and the second endpoint is calculated as the indicator difference value of the target performance indicator. The indicator type of the indicator difference value is the excess type.

[0155] As can be seen, in this optional embodiment, for each target performance indicator, the difference between the actual operating data and the indicator data of the target performance indicator can be automatically calculated, and the data relationship between the two can be determined, thereby accurately determining the detailed data of the target performance indicator including non-compliant identifiers, and improving the data accuracy of the stress test analysis data of the determined target system.

[0156] The generation module 304 is used to generate an optimization and control scheme for the target performance indicator based on the indicator analysis results corresponding to the target performance indicator when it is determined that there is a target performance indicator among all indicator analysis results that requires the execution of a preset performance optimization operation.

[0157] The optimization module 305 is used to perform performance optimization operations on the target performance index according to the optimization and control scheme, so as to adjust the index analysis results corresponding to the target performance index to meet the performance requirements corresponding to the target performance index.

[0158] It is evident that implementation Figure 3 The described automatic system performance optimization and control device can analyze interface operation data item by item based on several determined performance indicators, obtain the analysis results corresponding to each performance indicator in the interface operation data, and then automatically generate and execute the corresponding optimization and control scheme for the target performance indicator that needs to perform performance optimization operation. This realizes performance optimization based on interface data, and then optimizes the system performance by optimizing the interface performance, thereby improving the optimization efficiency, reliability and accuracy of performance optimization.

[0159] In an optional embodiment, such as Figure 4 As shown, the device also includes an acquisition module 306, an update module 307, and an adjustment module 308, wherein:

[0160] The acquisition module 306 is used to acquire the actual optimization effect and expected optimization data after the optimization module 305 performs performance optimization operation on the target performance index according to the optimization control scheme. The expected optimization data is the optimization data obtained by optimizing the target performance index based on the optimization control scheme in advance.

[0161] The update module 307 is used to update the stress test analysis algorithm and the optimization prediction model used to determine the expected optimization data when the actual optimization effect is higher than the expected optimization data.

[0162] The comparison and analysis module 303 is also used to analyze the optimization and control scheme, the actual optimization effect and the expected optimization data according to the optimization prediction model when the actual optimization effect is lower than the expected optimization data, and to obtain the scheme adjustment information for the optimization and control scheme.

[0163] The adjustment module 308 is used to adjust and optimize the control scheme according to the scheme adjustment information, so that the actual optimization effect corresponding to the adjusted optimized control scheme is higher than the expected optimization data.

[0164] It is evident that implementation Figure 4 The described automatic system performance optimization and control device, after optimizing each target performance indicator, sets up a verification process for the optimization effect: by acquiring the actual optimization effect and expected optimization data for each target performance indicator, the difference between the two is obtained. If the actual optimization effect is higher than the expected optimization data, it means that the optimization and control scheme for a certain target performance indicator is excellent and can be used as auxiliary data for updating the stress test analysis algorithm and optimizing the prediction model; if the actual optimization effect is lower than the expected optimization data, it means that the performance optimization for that target performance indicator has not met the requirements of the expected optimization data, and the optimization and control scheme needs to be automatically adjusted and re-optimized. This improves the accuracy and reliability of interface performance optimization and system performance optimization based on interface data.

[0165] In another optional embodiment, the generation module 304 generates an optimized control scheme for the target performance index based on the index analysis results corresponding to the target performance index, specifically including the following methods:

[0166] Based on the analysis results of the indicators corresponding to the target performance indicators, determine the indicator difference corresponding to the target performance indicators and the indicator type corresponding to the indicator difference;

[0167] Several performance optimization schemes matching the target performance index type are determined from the preset performance optimization scheme library to obtain a set of alternative schemes;

[0168] From the set of alternative solutions, select the solutions with the index difference corresponding to the target performance index and the solution fit degree corresponding to the index type of the index difference that is higher than the benchmark fit degree, and use them as the optimization and control solutions for the target performance index.

[0169] In this optional embodiment, the generation module 304 selects from the set of alternative solutions schemes those with a higher fit between the target performance index and the index type corresponding to the index difference, and the scheme fit is higher than the baseline fit. The specific methods for optimizing and controlling the target performance index include:

[0170] Filter out all alternative solutions from the set of alternative solutions that are ranked within a preset order in the preset historical optimization records. The historical optimization records contain operation records after performing performance optimization operations on performance indicators of the same type as the target performance indicator.

[0171] Calculate the first fit value between each alternative solution and the index difference corresponding to the target performance index, and the second fit value between each alternative solution and the index type corresponding to the index difference. Combine the first fit value and the second fit value of each alternative solution to obtain the comprehensive fit value of each alternative solution.

[0172] The option with the highest overall fit value among all alternative options is selected as the optimized control scheme for the target performance index.

[0173] In this optional embodiment, the second adaptation value corresponding to each alternative solution includes a first sub-value or a second sub-value representing the alternative solution, and when the second adaptation value corresponding to any alternative solution is the second sub-value, it is determined that the comprehensive adaptation value corresponding to the alternative solution is lower than the benchmark adaptation degree.

[0174] The performance optimization scheme library includes several performance optimization schemes for optimizing performance metrics. All performance optimization schemes include performance optimization schemes corresponding to at least one of the following types: code optimization, database optimization, caching optimization, multithreading optimization, batch processing, and asynchronous processing.

[0175] It is evident that implementation Figure 4 The described automatic optimization and control device for system performance generates an optimization and control scheme for each target performance indicator. It integrates multiple performance optimization schemes from a performance optimization scheme library to obtain a set of candidate schemes. Then, it considers the difference between the target performance indicators and the indicator type to select schemes with a higher fit than the benchmark fit, which are then used as the required optimization and control schemes. In calculating the fit, it also refers to the ranking in historical optimization records, calculates the first fit value of each candidate scheme's difference from the indicator, and the second fit value of the indicator type, comprehensively selecting the optimal control scheme. This multi-layered progressive selection method improves the accuracy and reliability of the final determined optimization and control scheme.

[0176] Example 4

[0177] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of another automatic system performance optimization and control device disclosed in an embodiment of the present invention. For example... Figure 5 As shown, the automatic performance optimization and control device of the system may include:

[0178] Memory 401 storing executable program code;

[0179] Processor 402 coupled to memory 401;

[0180] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the automatic optimization and control method for system performance described in Embodiment 1 or Embodiment 2 of the present invention.

[0181] Example 5

[0182] This invention discloses a computer storage medium storing computer instructions. When these computer instructions are invoked, they are used to execute the steps in the automatic optimization and control method for system performance described in Embodiment 1 or Embodiment 2 of this invention.

[0183] Example 6

[0184] This invention discloses a computer program product, which includes a non-transitory computer storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the automatic optimization and control method for system performance described in Embodiment 1 or Embodiment 2.

[0185] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0186] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, 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 can be stored in a computer storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0187] Finally, it should be noted that the automatic optimization and control method and apparatus for system performance disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for automatic optimization and control of system performance, characterized in that, The method includes: When an interface stress test command for the target system is detected, the interface operation data of the target system within a preset test period is collected according to the interface stress test command. Determine several performance metrics for analyzing the interface's runtime data, as well as the corresponding metric data for each performance metric within the preset test period; Determine the interface data interaction records corresponding to the target system based on the interface operation data; The amount of data interaction corresponding to each performance indicator is determined based on the interface data interaction record. For each performance indicator, based on the data interaction volume corresponding to the performance indicator and combined with a preset stress test analysis algorithm, the actual running data corresponding to the performance indicator within the preset test period is obtained by comparison and analysis. Analyze the actual operating data and the indicator data corresponding to each performance indicator to obtain indicator analysis data corresponding to each performance indicator. The indicator analysis data corresponding to each performance indicator includes a compliance identifier or non-compliance identifier to indicate that the actual operating data corresponding to the performance indicator is within the indicator data corresponding to the performance indicator. Based on the indicator analysis data corresponding to each of the aforementioned performance indicators, the stress test analysis data corresponding to the target system is determined; the stress test analysis data includes the indicator analysis results corresponding to each of the aforementioned performance indicators. When it is determined that there is a target performance indicator among all the indicator analysis results that requires the execution of a preset performance optimization operation, an optimization and control scheme for the target performance indicator is generated according to the indicator analysis results corresponding to the target performance indicator, and the performance optimization operation is performed on the target performance indicator according to the optimization and control scheme, so that the indicator analysis results corresponding to the target performance indicator are adjusted to meet the performance requirements corresponding to the target performance indicator. Obtain the actual optimization effect and expected optimization data after performing the performance optimization operation on the target performance index, wherein the expected optimization data is the pre-estimated optimization data obtained by optimizing the target performance index based on the optimization control scheme; When the actual optimization effect is higher than the expected optimization data, the stress test analysis algorithm and the optimization prediction model used to determine the expected optimization data are updated according to the actual optimization effect. When the actual optimization effect is lower than the expected optimization data, the optimization control scheme, the actual optimization effect, and the expected optimization data are analyzed according to the optimization prediction model to obtain scheme adjustment information for the optimization control scheme. The optimization control scheme is then adjusted according to the scheme adjustment information so that the actual optimization effect corresponding to the adjusted optimization control scheme is higher than the expected optimization data.

2. The automatic optimization and control method for system performance according to claim 1, characterized in that, When the indicator analysis data corresponding to a certain performance indicator includes the non-compliance identifier, the indicator analysis data corresponding to that performance indicator also includes the indicator difference and the difference type corresponding to the indicator difference. The difference type includes an excess type indicating that the actual operating data corresponding to that performance indicator is greater than the indicator data corresponding to that performance indicator, or a compensation type opposite to the excess type. The difference in the target performance index corresponding to any one of the non-compliant identifiers is calculated in the following way: Determine the two data interval endpoints corresponding to the target performance index, denoted as the first endpoint and the second endpoint, wherein the value of the first endpoint is less than the value of the second endpoint; When the actual operating data corresponding to the target performance indicator is less than the indicator data corresponding to the target performance indicator, the difference between the first endpoint and the actual operating data corresponding to the target performance indicator is calculated as the indicator difference of the target performance indicator, and the indicator type of the indicator difference is the difference compensation type. When the actual operating data corresponding to the target performance indicator is greater than the indicator data corresponding to the target performance indicator, the numerical difference between the actual operating data corresponding to the target performance indicator and the second endpoint is calculated as the indicator difference value of the target performance indicator, and the indicator type of the indicator difference value is the excess type.

3. The automatic optimization and control method for system performance according to claim 2, characterized in that, The step of generating an optimized control scheme for the target performance index based on the index analysis results corresponding to the target performance index includes: Based on the analysis results of the indicators corresponding to the target performance indicators, determine the indicator difference corresponding to the target performance indicators and the indicator type corresponding to the indicator difference; Several performance optimization schemes that match the index type of the target performance index are determined from a preset performance optimization scheme library to obtain a set of alternative schemes; From the set of alternative solutions, select the solutions with a higher fit to the target performance index than the baseline fit, based on the index difference and the index type corresponding to the index difference.

4. The automatic optimization and control method for system performance according to claim 3, characterized in that, The step of selecting from the set of alternative solutions a solution whose solution fit for the target performance indicator is higher than the baseline fit for the indicator type corresponding to the indicator difference, and which is the same as the target performance indicator, as an optimization and control solution for the target performance indicator, includes: From the set of alternative solutions, select all alternative solutions whose optimization performance ranks within a preset ranking in the preset historical optimization records. The historical optimization records contain operation records after performing the performance optimization operation on a performance indicator of the same type as the target performance indicator. Calculate the first fit value between each of the alternative solutions and the index difference corresponding to the target performance index, and the second fit value between each alternative solution and the index type corresponding to the index difference. Combine the first fit value and the second fit value corresponding to each alternative solution to obtain the comprehensive fit value corresponding to each alternative solution. The alternative with the highest overall fit value among all the alternative options is determined as the optimized control scheme for the target performance index.

5. The automatic optimization and control method for system performance according to claim 4, characterized in that, The second adaptation value corresponding to each of the alternative schemes includes a first sub-value or a second sub-value for representing the alternative scheme, and when the second adaptation value corresponding to any of the alternative schemes is the second sub-value, it is determined that the comprehensive adaptation value corresponding to the alternative scheme is lower than the benchmark adaptation degree. The performance optimization scheme library includes several performance optimization schemes for optimizing the performance indicators, and all the performance optimization schemes include performance optimization schemes corresponding to at least one of the following types: code optimization type, database optimization type, cache optimization type, multi-threading optimization type, batch processing type, and asynchronous processing type.

6. An automatic optimization and control device for system performance, characterized in that, The apparatus is used to perform the automatic optimization and control method for system performance as described in any one of claims 1-5, and the apparatus comprises: The data acquisition module is used to collect interface operation data of the target system within a preset test period according to the interface stress test command when an interface stress test command for triggering the execution of the target system is detected. The determination module is used to determine several performance indicators for analyzing the interface operation data and the corresponding indicator data for each performance indicator within the preset test period. The comparison and analysis module is used to compare and analyze the interface operation data based on the indicator data corresponding to each performance indicator and a preset stress test analysis algorithm to obtain the stress test analysis data corresponding to the target system. The stress test analysis data includes the indicator analysis results corresponding to each performance indicator. The generation module is used to generate an optimization and control scheme for the target performance indicator based on the indicator analysis results corresponding to the target performance indicator when it is determined that there is a target performance indicator among all the indicator analysis results that requires the execution of a preset performance optimization operation. An optimization module is used to perform the performance optimization operation on the target performance index according to the optimization and control scheme, so as to adjust the index analysis result corresponding to the target performance index to meet the performance requirements corresponding to the target performance index.

7. An automatic optimization and control device for system performance, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the automatic optimization and control method for system performance as described in any one of claims 1-5.

8. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the automatic optimization and control method for system performance as described in any one of claims 1-5.

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