Full-link voltage measurement method and device, electronic equipment and storage medium

Abstract

The invention provides a full-link pressure measurement method and device, electronic equipment and a storage medium. The method comprises the following steps: collecting service data of a target link in a production environment and production time consumption data of each node; in a voltage measurement environment, constructing a full-link voltage measurement simulation model based on the data; performing pressure measurement based on the verification task until a result meets a condition, and generating baseline data; and if it is detected that the target link is updated, calling the model to carry out pressure measurement, and generating a result in combination with the baseline data. Thus, by constructing the full-link voltage measurement simulation model matched with the production environment and generating the baseline data, when the link is updated, full-link voltage measurement is performed by using the full-link voltage measurement simulation model, and the voltage measurement result is generated in combination with the baseline data, so that the problem of insufficient performance verification before online is effectively solved; and meanwhile, a basis is provided for quantitative evaluation of the link saturation.

Description

Technical Field

[0001] This application relates to the field of Internet of Things technology, and in particular, to a full-link stress testing method, device, electronic device, and storage medium. Background Art

[0002] In the field of Internet finance business, the golden link refers to the end-to-end full-link path that supports the core business process, covering all process nodes such as front-end business triggering, business logic processing, data interaction, and back-end service response. Given that the golden link undertakes high-frequency transactions and key processes of the core business, its performance and stability directly affect the service capabilities and user experience of the entire business system. Therefore, comprehensive performance stress testing and monitoring of the golden link are key means to ensure the stable operation of the system and cope with high-concurrency pressure. However, there are many deficiencies in the existing golden link stress testing methods. On the one hand, there is a lack of effective means to quantitatively evaluate the saturation (i.e., carrying capacity) of the golden link. For example, when the channel party suddenly proposes a business volume increase requirement (such as an increase in transaction scale), it is difficult to quickly estimate the saturation of the link during the volume increase, and it is impossible to determine whether the link can bear it, resulting in challenges to the system stability. On the other hand, it is difficult for new products to complete performance tests for all transaction scenarios before going online. The full-link business transactions rely on production discovery and then optimization, resulting in uncertainty in the performance of the golden link of new products. Summary of the Invention

[0003] This application provides a full-link stress testing method, device, electronic device, and storage medium to at least solve the above technical problems existing in the prior art.

[0004] According to the first aspect of this application, a full-link stress testing method is provided, and the method includes: Collect business data of the target link in the production environment and production time-consuming data of each node of the target link. The nodes include internal systems and external interfaces, and the production time-consuming data includes interface call time, data processing time, and communication time; In the stress testing environment, based on the business data, production single-center standard, and production time-consuming data of each node, construct a full-link stress testing simulation model of the target link. The production single-center standard is used to show the resource configuration data of the production environment; Based on multiple verification tasks and the full-link stress testing simulation model, perform stress testing on the target link until the stress testing results meet the set conditions, obtain business indicator data and performance indicator data, and generate baseline data; If it is detected that the target link is updated, call the full-link stress test simulation model to perform a stress test on the updated target link, obtain the business metric data and performance metric data during the stress test, and generate a stress test result in combination with the baseline data. The stress test result is used to show the business metric data and performance metric data during the stress test and the deviation between the business metric data and performance metric data during the stress test and the baseline data.

[0005] In an implementable manner, the method further includes: Receive a target task, perform a stress test on the target link based on the target task and the full-link stress test simulation model, and collect the target business metric data and target performance metric data during the stress test; Compare the target business metric data and the target performance metric data with the baseline data, and determine whether the target link can execute the target task according to the comparison result.

[0006] In an implementable manner, in a stress test environment, based on the service data, the production single-center standard, and the production time-consuming data of each node, construct the full-link stress test simulation model of the target link, including: Synchronize the service data collected in the production environment to the stress test environment based on the desensitized data synchronization policy. The desensitized data synchronization policy includes that the data volume level in the stress test environment deviates from that in the production environment by less than a set deviation threshold and is synchronized at a set period; In the stress test environment, construct an initial full-link stress test simulation model of the target link. The initial full-link stress test simulation model includes simulation nodes of each node of the target link, and a baffle is deployed on the simulation node of the external interface. The baffle is used to simulate the interface behavior and response time of the external interface; Configure resources for the initial full-link stress test simulation model based on the production single-center standard; Determine the 90th percentile time-consuming data of each external interface according to the production time-consuming data of each external interface, and configure the response time for the baffle of the corresponding simulation node in the initial full-link stress test simulation model according to the 90th percentile time-consuming data of each external interface to obtain the full-link stress test simulation model.

[0007] In an implementable manner, the set condition includes one of the following: The fluctuation of business metrics is less than the first set threshold and the fluctuation of performance metrics is less than the second set threshold in continuously set rounds of stress tests; The fluctuation of the 95th percentile approval time-consuming is less than the third set threshold in continuously set rounds of stress tests.

[0008] In one implementable manner, the service metric data includes the 95th percentile approval time, the throttling queue number, the abnormal incoming application number, and the upstream and downstream system difference data; The performance metric data includes the number of transactions processed per second by the link and the link performance.

[0009] In one implementable manner, if it is detected that the target link is updated, the full-link stress test simulation model is called to perform a stress test on the updated target link, and the service metric data and performance metric data during the stress test are obtained. Combining with the baseline data, a stress test result is generated, including: Detect whether the target link is updated based on the continuous integration and continuous delivery mechanism; If the target link is updated, obtain the service metric data and performance metric data during the stress test, call the full-link stress test simulation model to perform a stress test on the updated target link, and combine with the baseline data to generate a stress test result. The stress test result is used to show the service metric data and performance metric data during the stress test and the deviation between the service metric data and performance metric data during the stress test and the baseline data.

[0010] According to a second aspect of the present application, a full-link stress test device is provided. The device includes: An acquisition module, configured to acquire the service data of the target link in the production environment and the production time-consuming data of each node of the target link. The nodes include internal systems and external interfaces, and the production time-consuming data includes interface call time, data processing time, and communication time; A construction module, configured to construct a full-link stress test simulation model of the target link in the stress test environment based on the service data, the production single-center standard, and the production time-consuming data of each node. The production single-center standard is used to show the resource configuration data of the production environment; An acquisition module, configured to perform a stress test on the target link based on multiple verification tasks and the full-link stress test simulation model until the stress test result meets the set conditions, obtain service metric data and performance metric data, and generate baseline data; A call module, configured to, if it is detected that the target link is updated, call the full-link stress test simulation model to perform a stress test on the updated target link, obtain the service metric data and performance metric data during the stress test, and combine with the baseline data to generate a stress test result. The stress test result is used to show the service metric data and performance metric data during the stress test and the deviation between the service metric data and performance metric data during the stress test and the baseline data.

[0011] In one implementable manner, the device further includes: A receiving module, configured to receive a target task, perform stress testing on the target link based on the target task and the full-link stress testing simulation model, and collect target service metric data and target performance metric data during the stress testing; A comparison module, configured to compare the target service metric data and the target performance metric data with the baseline data, and determine whether the target link can execute the target task according to the comparison result.

[0012] According to a third aspect of the present application, there is provided an electronic device, including: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method of the present application.

[0013] According to a fourth aspect of the present application, there is provided a non-transitory computer-readable storage medium storing computer instructions, and the computer instructions are used to cause a computer to execute the method of the present application.

[0014] The full-link stress testing method, apparatus, electronic device and storage medium of the present application collect service data of a target link in a production environment and production time-consuming data of each node of the target link, the nodes include an internal system and an external interface, and the production time-consuming data includes interface call time, data processing time and communication time; in a stress testing environment, based on the service data, production single-center standard and production time-consuming data of each node, a full-link stress testing simulation model of the target link is constructed, and the production single-center standard is used to show resource configuration data of the production environment; based on multiple verification tasks and the full-link stress testing simulation model, stress testing is performed on the target link to obtain service metric data and performance metric data during the stress testing until the stress testing result meets the set conditions, service metric data and performance metric data are obtained, and baseline data is generated; if it is detected that the target link is updated, the full-link stress testing simulation model is called to perform stress testing on the updated target link, and combined with the baseline data, a stress testing result is generated, and the stress testing result is used to show the service metric data and performance metric data during the stress testing and the deviation between the service metric data and performance metric data during the stress testing and the baseline data. By constructing a full-link stress testing simulation model matching the production environment and generating baseline data, when the link is updated, the full-link stress testing simulation model is used for full-link stress testing, and combined with the baseline data to generate a stress testing result, effectively solving the problem of insufficient performance verification before going online, and at the same time providing a basis for the quantitative evaluation of link saturation.

[0015] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understandable through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] By referring to the accompanying drawings and reading the following detailed description, the above and other objects, features, and advantages of the exemplary embodiments of the present application will become easily understandable. In the drawings, several embodiments of the present application are shown in an exemplary rather than restrictive manner, where: In the drawings, the same or corresponding reference numerals represent the same or corresponding parts.

[0017] Figure 1 FIG. shows a schematic implementation flow diagram of the full-link stress testing method provided by an embodiment of the present application; Figure 2 FIG. shows a schematic implementation flow diagram of the operation of constructing a full-link simulation model of the full-link stress testing method provided by an embodiment of the present application; Figure 3 FIG. shows a schematic composition structure diagram of the full-link stress testing device provided by an embodiment of the present application; Figure 4 FIG. shows a schematic composition structure diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] In order to make the objectives, features, and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present application.

[0019] First, the application scenarios of the embodiments of the present application are described. Among many system performance evaluation methods, the full-link stress testing of the golden link has significant advantages. Different from single-system stress testing, it can simulate real business scenarios, comprehensively identify the performance bottlenecks of the entire link, and discover the dependency problems between systems in advance. At the same time, this stress testing method can also simulate the production fault diffusion scenario, so as to formulate a comprehensive fault handling plan in advance. Based on the highly reliable golden link stress testing results, it can provide an accurate capacity planning reference for the system group and a reliable basis for the performance evaluation of the production environment, thereby effectively reducing the performance risks in the production environment. In view of this, the embodiments of the present application provide a full-link stress testing method to achieve comprehensive coverage stress testing of multi-system links.

[0020] Figure 1The figure shows a schematic implementation process diagram of the full-link stress testing method provided by the embodiments of the present application.

[0021] Referring to Figure 1 , the embodiments of the present application provide a full-link stress testing method, which includes: Operation 101: Collect the business data of the target link in the production environment and the production time-consuming data of each node of the target link. The nodes include internal systems and external interfaces, and the production time-consuming data includes interface call time, data processing time, and communication time.

[0022] The business data of the target link and the production time-consuming data of each node of the target link can be obtained by conducting a full-link investigation of the target link. To build a stress testing environment that is as close as possible to the production environment and provide a highly credible full-link stress testing result for production operation, the investigation of the target link in the embodiments of the present application is carried out in the actual production environment.

[0023] Among them, different core business processes correspond to different target links. The target link can be understood as the golden link to be stress-tested specified by the user or the golden link of the core business process to be tested specified by the user. It includes all process nodes from the front-end business trigger to the completion of the back-end processing. These nodes are constituted in sequence and include internal systems (such as credit-granting systems, risk control middle platforms, business management systems, etc.) and external interfaces (such as third-party payment channels, public service platforms, etc.) involved in the core business.

[0024] Conducting an investigation of the target link in the actual production environment mainly covers the following operations: First, comprehensively sort out the business process of the target link and clarify the interaction logic of each link; second, detailedly count the business data of the target link and the production time-consuming data of each node.

[0025] In an embodiment of the present application, the business data refers to various data generated during the actual business operation of the target link in the production environment. The business data is used to comprehensively reflect key information such as the real traffic characteristics, business logic execution situation, and user behavior patterns of the business in the production environment. Among them, the business data includes, but is not limited to, transaction records, user request information, operation logs, and interaction information between internal systems, etc.

[0026] In an embodiment of the present application, the production time-consuming data includes interface call time, data processing time, and communication time. Among them, the interface call time refers to the time consumed from initiating an interface request to receiving an interface response. The data processing time refers to the time when the internal system processes data during the execution of the core business, such as the time consumed for data analysis, conversion, calculation, and approval, etc. The time consumed for approval can be regarded as the time waiting for manual or automatic review in the approval process. The communication time refers to the time consumed for data transmission between systems or between the system and external services, such as network transmission time, message queue communication time, etc.

[0027] Operation 102: In the stress testing environment, based on the business data, the production single-center standard, and the production time-consuming data of each node, construct a full-link stress testing simulation model for the target link. The production single-center standard is used to show the resource configuration data of the production environment.

[0028] After the full-link investigation work of the target link is completed, in order to accurately simulate the operation of the target link in the production environment, such as the business processes and system interactions in the actual production environment, it is necessary to finely simulate the stress testing environment of the target link. The embodiment of the present application concretizes this simulation process as constructing a full-link stress testing simulation model that can execute stress testing logic in the stress testing environment.

[0029] The construction of the full-link stress testing simulation model may include the following operations: First, use the collected business data to restore the real business scenario and traffic characteristics; then, combine the production time-consuming data of each node to configure the performance of each node in the full-link stress testing simulation model, including the processing time of the internal system and the response time of external interfaces, etc.; at the same time, to ensure that the operating environment of the full-link stress testing simulation model is as close as possible to the production environment, the full-link stress testing simulation model is also resource-configured according to the production single-center standard.

[0030] In an embodiment of the present application, the production single-center standard refers to a set of specifications and guidelines formulated in advance in the production environment to ensure the stable operation of the system and the reasonable allocation of resources, that is, the resource configuration data of the pre-configured production environment.

[0031] Operation 103: Perform stress testing on the target link based on multiple verification tasks and the full-link stress testing simulation model until the stress testing results meet the set conditions, obtain business metric data and performance metric data, and generate baseline data.

[0032] To ensure the accuracy and reliability of the stress testing results, it is necessary to comprehensively evaluate the target link through multiple verification tasks to fully identify potential performance bottlenecks and problems of the target link. Among them, the verification task refers to the performance test of the target link under different business scenarios and load conditions, aiming to simulate various actual situations that may be encountered, so as to comprehensively examine the stability and processing ability of the target link.

[0033] In order to ensure the stability and credibility of the stress test results, preset conditions are also configured in advance. Only when the stress test results meet the preset conditions can it be determined that the stress test process has been stable. At this time, business metric data and performance metric data are obtained to ensure that the obtained business metric data and performance metric data have sufficient credibility, so that reliable baseline data can be generated based on this.

[0034] In an embodiment of the present application, the baseline data may include the obtained business metric data and performance data, or may be any one of the business metric data and performance metric data, or other comprehensive metrics extended and calculated based on the business metric data and performance data. Among them, the role of the baseline data is to provide a reference standard for subsequent performance evaluation and optimization. For example, when the target link changes due to system updates or other changes, the new stress test results can be compared with the baseline data to quickly evaluate the impact of the changes on the system performance.

[0035] In an embodiment of the present application, the business metric data includes the 95th percentile (P95) approval time, the number of rate-limiting queues, the number of abnormal incoming items, and the upstream and downstream system difference data; the performance metric data includes the link TPS (Transactions Per Second) and the link performance. Among them, the 95th percentile approval time represents the value at the 95% position after sorting a set of approval time data from smallest to largest, that is, 95% of the approval times are less than this value, and only 5% of the approval times exceed this value.

[0036] Specifically, the business metric data and the performance metric data respectively reflect the performance of the target link in terms of business processing ability and system performance. Among them, the business metric data includes the P95 of the approval time, the number of rate-limiting queues, the number of abnormal incoming items, and the upstream and downstream system difference data, etc., and the performance metric data includes the link TPS and the link performance, etc.

[0037] Among them, in view of the fact that the P95 of the approval time can better reflect the performance of the system when processing most business requests and can better reflect the user experience in the actual use process, the baseline data in this embodiment of the present application is preferably the P95 of the approval time.

[0038] In an embodiment of the present application, corresponding to the baseline data, the preset conditions can be configured to include one of the following: the business metric fluctuation is less than the first preset threshold and the performance metric fluctuation is less than the second preset threshold in consecutive preset rounds of stress tests; the P95 fluctuation of the approval time is less than the third preset threshold in consecutive preset rounds of stress tests.

[0039] Specifically, to ensure the stability and reliability of the baseline data, it is necessary to conduct multiple stress tests on the target link based on the verification task. Only when the metrics in the set number of stress test rounds remain within a relatively stable range, that is, when the metric fluctuations are small, will the stress test be stopped. Among them, when the business metric fluctuation is less than the first set threshold and the performance metric fluctuation is less than the second set threshold in consecutive set rounds of stress tests, or when the P95 of the approval time consumption in consecutive set rounds of stress tests fluctuates less than the third set threshold, it can be determined that the metric fluctuations are small. The set number of rounds can be configured according to historical experience or actual situations, and this application does not make specific limitations.

[0040] In an embodiment of this application, the fluctuation can be represented by the metric deviation of different rounds of stress tests, that is, by calculating statistics such as the standard deviation, variance, or percentage change of business metrics and / or performance metrics in multiple stress test rounds to measure its fluctuation. The first set threshold, the second set threshold, and the third set threshold can be configured according to actual situations. For example, if the business has extremely high requirements for approval timeliness, the third set threshold for the approval time consumption P95 can be configured to be smaller (such as 50 milliseconds) to strictly control the time consumption fluctuation of the approval process. Similarly, if the system has high requirements for the stability of business metrics, the first set threshold and the second set threshold can be configured to be smaller (such as the business metric fluctuation is less than 10% and the performance metric fluctuation is less than 5%) to ensure that all metrics remain as stable as possible during the stress test.

[0041] Operation 104, if it is detected that the target link has been updated, call the full-link stress test simulation model to conduct a stress test on the updated target link, obtain the business metric data and performance metric data during the stress test, and generate a stress test result in combination with the baseline data. The stress test result is used to show the business metric data and performance metric data during the stress test and the deviation between the business metric data and performance metric data during the stress test and the baseline data.

[0042] In an actual production environment, the target link may be updated for various reasons (such as internal system upgrades, internal system function optimizations, configuration adjustments, etc.). To ensure that these updates do not have a negative impact on the performance and business processing capabilities of the target link, it is necessary to re-conduct a stress test on the updated target link in a timely manner.

[0043] When it is detected that the target link has an update, trigger the automatic stress test process. At this time, call the full-link stress test simulation model again to conduct a stress test based on the updated target link. And obtain the business metric data and performance metric data during the stress test and compare them with the previously generated baseline data to obtain the stress test result. Among them, the stress test result includes the business metric data and performance metric data during the stress test and the deviation between the business metric data and performance metric data during the stress test and the baseline data.

[0044] In an embodiment of the present application, if the deviation of each index is within the set range, it indicates that the performance of the updated system is stable and can be safely deployed to the production environment; if the deviation exceeds the set range, a warning for optimizing the target link is issued so that developers can further analyze and optimize the system performance to ensure the reliability and stability of the system.

[0045] Among them, the set range includes the deviation range of each index, and the deviation range can be determined comprehensively according to factors such as historical data, business requirements, performance goals, and industry standards. For example, combined with the past stable performance and the business's requirements for response time, the deviation range of the P95 of the approval time is set to ±10% of the baseline data, and the deviation range of the TPS is set to ±5% of the baseline data, etc.

[0046] In an embodiment of the present application, when receiving a target task for a target link, the following operations are also performed: receiving the target task, performing stress testing on the target link based on the target task and the full-link stress testing simulation model, and collecting target business index data and target performance index data during the stress testing process; comparing the target business index data and the target performance index data with the baseline data, and determining whether the target link can execute the target task according to the comparison result.

[0047] Specifically, the target task can refer to a volume increase task, and the volume increase task can be understood as a business volume increase requirement. For example, expanding the business processing scale of the target link, increasing the transaction scale of the target link, or increasing the data transmission scale of the target link, etc. After receiving the target task, quickly call the full-link stress testing simulation model to perform stress testing on the target link. During the stress testing process, collect the target business index data and the target performance index data, and compare the target business index data and the target performance index data with the baseline data, and determine whether the current target link has the ability to execute the target task according to the comparison result, that is, quickly estimate the link saturation situation during volume increase, and judge whether the link can carry the target task, so as to judge whether the volume increase task can be executed.

[0048] Among them, the comparison result shows the deviation of each index from the baseline data, and whether the target link has the ability to execute the target task can be judged based on whether the deviation conforms to the set range of the deviation. If it does not conform to the set deviation range, it does not have the ability to execute the target task; if it conforms to the set range, it has the ability to execute the target task.

[0049] Thus, in the embodiment of the present application, a full-link stress test simulation model matching the production environment is constructed, and baseline data is generated therefrom. When the link is updated, a full-link stress test is carried out by using the full-link stress test simulation model, and the stress test results are generated in combination with the baseline data, effectively solving the problem of insufficient performance verification before going online. In addition, when a traffic increase task is received, the stress test operation is executed by calling the full-link stress test simulation model, so as to accurately evaluate the bearing capacity of the current link before a large-scale business traffic increase, avoid performance problems caused by exceeding the system bearing capacity, and realize the quantitative evaluation of the link saturation during the traffic increase.

[0050] In an embodiment of the present application, for the above operation 104, if it is detected that the target link is updated, the updated target link is stress-tested by calling the full-link stress test simulation model, and in combination with the baseline data, the stress test results are generated, including: detecting whether the target link is updated based on the continuous integration and continuous delivery mechanism; if the target link is updated, the updated target link is stress-tested by calling the full-link stress test simulation model, the business metric data and performance metric data during the stress test are obtained, and in combination with the baseline data, the stress test results are generated, and the stress test results are used to show the business metric data and performance metric data during the stress test and the deviation between the business metric data and performance metric data during the stress test and the baseline data.

[0051] Specifically, in order to perform timely stress testing on the updated target link, that is, the target link of the new version, the embodiment of the present application integrates the stress test process of the above operations 101 to 104 with CI / CD (Continuous Integration / Continuous Delivery). Thus, based on the CI / CD mechanism, once it is detected that the target link is updated, the stress test process can be automatically triggered, the link stress test and baseline comparison are performed, the stress test results are generated, and based on the deviation shown in the stress test results, the link performance performance is identified in advance.

[0052] Figure 2 The figure shows a schematic implementation flow diagram of the full-link simulation model construction operation of the full-link stress test method provided by the embodiment of the present application.

[0053] Refer to Figure 2 , in an embodiment of the present application, for the above operation 102, in the stress test environment, based on the business data, the production single-center standard, and the production time-consuming data of each node, a full-link stress test simulation model of the target link is constructed, including: Operation 201, synchronize the business data collected in the production environment to the stress test environment based on the desensitized data synchronization strategy, and the desensitized data synchronization strategy includes that the data volume level in the stress test environment deviates from that in the production environment by less than the set deviation threshold and synchronize at the set period.

[0054] The simulation of the stress testing environment includes the simulation of the production environment, and the simulation of the production environment includes the configuration at the data level, so as to ensure that the data volume level in the stress testing environment is consistent with that in the actual production environment through data configuration.

[0055] The configuration of the stress testing environment at the data level can be based on the desensitized data synchronization strategy. The business data collected in the actual production environment is synchronized to the stress testing environment through the desensitized data synchronization strategy. Among them, the desensitized data synchronization strategy includes that the deviation of the data volume level in the stress testing environment from that in the production environment is less than the set deviation threshold and synchronization is performed at a set period. That is, desensitized data synchronization is implemented once every set period to keep the data volume level in the stress testing environment consistent with that in the production environment, providing a solid guarantee for the accuracy and reliability of the stress testing results. Among them, the set period can be configured according to the actual situation, such as two months.

[0056] In this embodiment of the present application, if the deviation of the data volume level in the stress testing environment from that in the production environment is less than the set deviation threshold, it is determined that the data volume level in the stress testing environment is consistent with that in the production environment, and the set deviation threshold can be configured according to the actual situation.

[0057] Operation 202: In the stress testing environment, construct an initial full-link stress testing simulation model for the target link. The initial full-link stress testing simulation model includes simulation nodes of each node of the target link, and a baffle is deployed on the simulation node of the external interface. The baffle is used to simulate the interface behavior and response time of the external interface.

[0058] In the stress testing environment, construct an initial full-link stress testing simulation model for the target link. Among them, the initial full-link stress testing simulation model is configured with simulation nodes of each node of the target link, and the interaction logic between the simulation nodes remains consistent with that of the target link.

[0059] Furthermore, for the external interface, since it usually depends on the external service provider, in order to be able to test independently and stably in the stress testing environment, it is necessary to deploy a baffle on the simulation node. Among them, the baffle, that is, the peripheral system baffle, is used to simulate the interface behavior and response time of the external interface, and simulate the behavior of the external interface through preset rules and logics.

[0060] Operation 203: Configure resources for the initial full-link stress testing simulation model based on the production single-center standard.

[0061] In the production environment, the allocation of resources follows a certain standard, that is, there is a production single-center standard to ensure the stable operation of the link. When constructing a full-link stress testing simulation model in the stress testing environment, in order to ensure that the running state of the simulation model in the stress testing environment is as close as possible to that in the production environment, it is also necessary to configure resources according to the production single-center standard. Among them, configuring resources can include allocating corresponding computing, storage, and network resources to each simulation node, setting parameters and configuration items, etc.

[0062] Operation 204: Determine the 90th percentile latency data for each external interface based on the production latency data of each external interface, and configure the response latency of the corresponding simulation node in the initial full-link stress test simulation model according to the 90th percentile latency data of each external interface, to obtain the full-link stress test simulation model.

[0063] To ensure the accurate simulation of external interfaces, it is necessary to configure the response latency of the baffle to match the actual production environment, so as to accurately simulate the response behavior of external interfaces, ensure that the stress test environment is close to the actual production, and improve the credibility and reference value of stress test results. Given the stability advantage of the P90 (90th percentile) latency data, it is preferred to use the P90 latency data as the latency data of the baffle. Specifically, comprehensively collect the P90 latency data of requests to external interfaces during production ramp-up, and configure the P90 latency data to the baffle. Among them, the 90th percentile latency data represents the value at the 90% position after sorting a set of latency data from smallest to largest, that is, 90% of the latency data is less than this value, and only 10% of the latency data exceeds this value.

[0064] Figure 3 The composition structure diagram of the full-link stress test device provided by the embodiment of the present application is shown.

[0065] Reference Figure 3 , based on the above full-link stress test method, the embodiment of the present application also provides a full-link stress test device, which includes: A collection module 301, configured to collect service data of the target link and production latency data of each node of the target link in the production environment, the nodes include internal systems and external interfaces, and the production latency data includes interface call time, data processing time, and communication time; A construction module 302, configured to construct a full-link stress test simulation model of the target link in the stress test environment based on the service data, production single-center standard, and production latency data of each node, and the production single-center standard is used to show the resource configuration data of the production environment; An acquisition module 303, configured to perform stress testing on the target link based on multiple verification tasks and the full-link stress test simulation model until the stress test results meet the set conditions, acquire service metric data and performance metric data, and generate baseline data; A call module 304, configured to, if it is detected that the target link has been updated, call the full-link stress test simulation model to perform stress testing on the updated target link, acquire service metric data and performance metric data during the stress test, and combine the baseline data to generate stress test results, and the stress test results are used to show the service metric data and performance metric data during the stress test and the deviation between the service metric data and performance metric data during the stress test and the baseline data.

[0066] In an embodiment of the present application, the apparatus further includes: a receiving module, configured to receive a target task, perform stress testing on a target link based on the target task and a full-link stress testing simulation model, and collect target service metric data and target performance metric data during the stress testing process; a comparison module, configured to compare the target service metric data and the target performance metric data with baseline data, and determine whether the target link can execute the target task according to the comparison result.

[0067] According to an embodiment of the present application, the present application further provides an electronic device and a readable storage medium.

[0068] Figure 4 FIG. shows a schematic block diagram of an exemplary electronic device 400 that can be used to implement the embodiments of the present application. The electronic device is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present application described and / or claimed herein.

[0069] As Figure 4 shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0070] A plurality of components in the device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a magnetic disk, an optical disc, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0071] The computing unit 401 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 executes the various methods and processes described above, such as the full-link stress testing method. For example, in some embodiments, the full-link stress testing method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the full-link stress testing method described above can be executed. Alternatively, in other embodiments, the computing unit 401 can be configured to execute the full-link stress testing method by any other suitable means (e.g., by means of firmware).

[0072] The various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0073] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0074] In the context of this application, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0075] To provide for interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic, speech, or tactile input).

[0076] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of a communication network include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0077] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The relationship of the client and the server is generated by computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

[0078] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this application can be achieved, and no limitations are imposed herein.

[0079] In addition, the terms "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of this application, "a plurality of" means two or more, unless otherwise specifically defined.

[0080] As described above, the above are only specific embodiments of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

Claims

1. A full-link stress testing method, characterized in that, The method includes: Collecting the service data of the target link and the production time-consuming data of each node of the target link in the production environment, where the nodes include internal systems and external interfaces, and the production time-consuming data includes interface call time, data processing time, and communication time; In the stress testing environment, based on the service data, the production single-center standard, and the production time-consuming data of each node, constructing a full-link stress testing simulation model of the target link, where the production single-center standard is used to show the resource configuration data of the production environment; Performing stress testing on the target link based on multiple verification tasks and the full-link stress testing simulation model until the stress testing results meet the set conditions, obtaining service metric data and performance metric data, and generating baseline data; If it is detected that the target link is updated, calling the full-link stress testing simulation model to perform stress testing on the updated target link, obtaining the service metric data and performance metric data during the stress testing process, and combining the baseline data to generate stress testing results, where the stress testing results are used to show the service metric data and performance metric data during the stress testing process and the deviation between the service metric data and performance metric data during the stress testing process and the baseline data.

2. The method according to claim 1, characterized in that, The method further includes: Receiving a target task, performing stress testing on the target link based on the target task and the full-link stress testing simulation model, and collecting the target service metric data and target performance metric data during the stress testing process; Comparing the target service metric data and the target performance metric data with the baseline data, and determining whether the target link can execute the target task according to the comparison result.

3. The method according to claim 1, wherein In the stress testing environment, constructing the full-link stress testing simulation model of the target link based on the service data, the production single-center standard, and the production time-consuming data of each node includes: Synchronizing the service data collected in the production environment to the stress testing environment based on the desensitized data synchronization strategy, where the desensitized data synchronization strategy includes that the data magnitude deviation between the stress testing environment and the production environment is less than the set deviation threshold and synchronization is performed at a set period; In the stress testing environment, constructing an initial full-link stress testing simulation model of the target link, where the initial full-link stress testing simulation model includes simulation nodes of each node of the target link, and a baffle is deployed on the simulation node of the external interface, and the baffle is used to simulate the interface behavior and response time of the external interface; Configuring resources for the initial full-link stress testing simulation model based on the production single-center standard; Determining the 90th percentile time-consuming data of each external interface according to the production time-consuming data of each external interface, and configuring the response time for the baffle of the corresponding simulation node in the initial full-link stress testing simulation model according to the 90th percentile time-consuming data of each external interface to obtain the full-link stress testing simulation model.

4. The method according to claim 1, wherein The set conditions include one of the following: The service metric fluctuation is less than the first set threshold and the performance metric fluctuation is less than the second set threshold in consecutive set rounds of stress testing; The 95th percentile approval time-consuming fluctuation is less than the third set threshold in consecutive set rounds of stress testing.

5. The method according to claim 1, wherein The service metric data includes the 95th percentile approval time, the throttling queue number, the abnormal incoming case number, and the upstream and downstream system difference data; The performance metric data includes the number of transactions processed per second by the link and the link performance.

6. The method according to claim 1, characterized in that, If it is detected that the target link has been updated, call the full-link stress test simulation model to perform a stress test on the updated target link, obtain the service metric data and performance metric data during the stress test, and combine with the baseline data to generate a stress test result, including: Detect whether the target link has been updated based on the continuous integration and continuous delivery mechanism; If the target link has been updated, call the full-link stress test simulation model to perform a stress test on the updated target link, obtain the service metric data and performance metric data during the stress test, and combine with the baseline data to generate a stress test result, where the stress test result is used to show the service metric data and performance metric data during the stress test and the deviation between the service metric data and performance metric data during the stress test and the baseline data.

7. A full-link stress testing device, characterized in that, The device includes: A collection module, configured to collect the service data of the target link in the production environment and the production time-consuming data of each node of the target link, where the node includes an internal system and an external interface, and the production time-consuming data includes interface call time, data processing time, and communication time; A construction module, configured to construct a full-link stress test simulation model of the target link in the stress test environment based on the service data, the production single-center standard, and the production time-consuming data of each node, where the production single-center standard is used to show the resource configuration data of the production environment; An acquisition module, configured to perform a stress test on the target link based on multiple verification tasks and the full-link stress test simulation model until the stress test result meets the set conditions, obtain the service metric data and performance metric data, and generate baseline data; A call module, configured to if it is detected that the target link has been updated, call the full-link stress test simulation model to perform a stress test on the updated target link, obtain the service metric data and performance metric data during the stress test, and combine with the baseline data to generate a stress test result, where the stress test result is used to show the service metric data and performance metric data during the stress test and the deviation between the service metric data and performance metric data during the stress test and the baseline data.

8. The device according to claim 7, characterized in that, The device further includes: A receiving module, configured to receive a target task, perform a stress test on the target link based on the target task and the full-link stress test simulation model, and collect the target service metric data and target performance metric data during the stress test; A comparison module, configured to compare the target service metric data and the target performance metric data with the baseline data, and determine whether the target link can execute the target task according to the comparison result.

9. An electronic device, characterized in that, Includes: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-6.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause a computer to execute the method according to any one of claims 1-6.

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