A device detection method, apparatus and device

Abstract

Embodiments of the present application disclose a device detection method, device and equipment, the method comprising: receiving a state detection request for a target service device, in response to the state detection request, obtaining neighbor relationship information, routing table data and a management information base corresponding to the target service device based on a preset network communication protocol, constructing a network topology corresponding to the target service device based on the neighbor relationship information, routing table data and the management information base corresponding to the target service device, and performing a performance test on the target service device based on the network topology to obtain first performance test data, obtaining second performance test data of the target service device in an acceptance stage, and determining a state detection result of the target service device based on the first performance test data and the second performance test data.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method, apparatus, and device for testing equipment. Background Technology

[0002] With the rapid development of new-generation information technologies such as cloud computing, big data, and the Internet of Things, the scale of cloud resource pools continues to expand, and the number of cloud resource service devices such as servers in the pools is increasing exponentially. In order to ensure the user experience of network services, the operation and maintenance management of cloud resource service devices has become crucial.

[0003] While manual inspections and on-site checks can be used to manage and maintain devices within a cloud resource pool, this involves manually monitoring the status data of each cloud resource service device, along with documentation such as design plans and physical connection tables. Testing tools and checking cable labels at both ends can be used to manually inspect interconnecting cables and identify problematic cloud resource service devices. However, due to the large number of devices in a cloud resource pool and the complex connections between them, manual inspections and on-site checks can lead to low efficiency and accuracy in managing the status of service devices. Therefore, a technical solution is needed to improve the efficiency and accuracy of status management for service devices in situations with complex connections. Summary of the Invention

[0004] The purpose of this invention is to provide a technical solution to improve the efficiency and accuracy of status management of service devices when the connection relationships between service devices are complex.

[0005] To solve the above-mentioned technical problems, the embodiments of the present invention are implemented as follows: In a first aspect, embodiments of the present invention provide a device detection method, the method comprising: receiving a status detection request for a target service device; responding to the status detection request, acquiring neighbor relationship information, routing table data, and management information database corresponding to the target service device based on a preset network communication protocol; constructing a network topology corresponding to the target service device based on the neighbor relationship information, routing table data, and management information database corresponding to the target service device, and performing performance testing on the target service device based on the network topology to obtain first performance test data; acquiring second performance test data of the target service device during the acceptance phase, and determining the status detection result of the target service device based on the first performance test data and the second performance test data.

[0006] Secondly, embodiments of the present invention provide a device detection apparatus, the apparatus comprising: a request receiving module, configured to receive a status detection request for a target service device; a data acquisition module, configured to respond to the status detection request and, based on a preset network communication protocol, acquire neighbor relationship information, routing table data, and management information database corresponding to the target service device; a structure construction module, configured to construct a network topology structure corresponding to the target service device based on the neighbor relationship information, routing table data, and management information database corresponding to the target service device, and perform performance testing on the target service device based on the network topology structure to obtain first performance test data; and a device detection module, configured to acquire second performance test data of the target service device during the acceptance phase, and determine the status detection result of the target service device based on the first performance test data and the second performance test data.

[0007] Thirdly, embodiments of the present invention provide a device detection device, including a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the device detection method provided in the above embodiments.

[0008] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the device detection method provided in the above embodiments.

[0009] Fifthly, embodiments of the present invention provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the device detection method provided in the above embodiments. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a schematic flowchart of a device testing method according to the present invention; Figure 2 This is a schematic diagram illustrating the construction process of a network topology according to the present invention; Figure 3 This is a flowchart illustrating the acceptance process of a target service device according to the present invention. Figure 4 This is a schematic diagram of the system framework of an acceptance management system according to the present invention; Figure 5 This is a schematic diagram of the data acquisition process of an acceptance management system according to the present invention; Figure 6 This is a schematic diagram of the structure of an acceptance management system according to the present invention; Figure 7 This is a schematic diagram of the acceptance management process of an acceptance management system according to the present invention; Figure 8 This is a schematic diagram of the internal structure of an acceptance management system according to the present invention; Figure 9 This is a flowchart illustrating the process of determining a state detection result according to the present invention. Figure 10 This is a schematic diagram of the structure of a device testing apparatus according to the present invention; Figure 11 This is a schematic diagram of the structure of a device testing equipment according to the present invention. Detailed Implementation

[0012] This invention provides a device testing method, apparatus, and device.

[0013] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0014] like Figure 1 As shown, this embodiment of the invention provides a device detection method. The execution subject of this method can be a server, which can be a standalone server or a server cluster composed of multiple servers. Specifically, the method may include the following steps: In step S102, a status detection request for the target service device is received.

[0015] The target service device can be any device that can provide business services to users. For example, the target service device can be a server device that can provide cloud resource services to users.

[0016] In practice, taking the target service device as a service device within the cloud resource pool as an example, the server can trigger a status detection request for the server device within the cloud resource pool according to the status detection cycle. The server device within the cloud resource pool is the target service device. Alternatively, the server can also receive status detection requests triggered by the user for one or more target service devices.

[0017] In step S104, in response to the status detection request, the neighbor relationship information, routing table data and management information database corresponding to the target service device are obtained based on the preset network communication protocol.

[0018] The preset network communication protocols may include protocols used to obtain neighbor relationship information, routing table data, and management information base data. For example, preset network communication protocols may include preset Link Layer Discovery Protocol (LLDP), preset Address Resolution Protocol (ARP), MAC address table protocol, routing addressing protocol, etc.

[0019] In step S106, based on the neighbor relationship information, routing table data and management information database corresponding to the target service device, a network topology corresponding to the target service device is constructed, and based on the network topology, the performance of the target service device is tested to obtain the first performance test data.

[0020] In implementation, for example, the server can construct a "device-port" connection graph based on the LLDP protocol. For instance, all LLDP neighbor relationships obtained from the LLDP protocol can be resolved as undirected edges (e.g., there can be an undirected edge between node A corresponding to interface 1 and node B corresponding to interface 2, i.e., A:port1—B:port2). Furthermore, server devices can be identified based on the neighbor relationship information. For example, if a device does not issue LLDP or only acts as a "remote end" of LLDP, and its ChassisID is the server's MAC address, then this device can be marked as a server device in the connection graph.

[0021] Then, the server can locate the IP address of each server device based on the ARP protocol and MAC address table protocol. For example, for each server device's MAC address, the corresponding IP address can be looked up in the ARP table. If it does not appear directly in the ARP table, the access port can be determined by combining it with the MAC table of the switch it belongs to, and then the subnet to which it belongs can be inferred through the ARP of the switch's Layer 3 interface or gateway.

[0022] Next, the server can determine the server device's affiliation (i.e., VLAN or subnet). The server can determine the logical network to which the server device belongs by using the VLAN information in the MAC table and the directly connected subnets in the routing table.

[0023] For example: The MAC address of the server device is on Gi1 / 0 / 10 of switch SW1, VLAN 100; the SVIIP of VLAN 100 on SW1 is 192.168.100.1 / 24, which means that the IP address of the server device should be in this subnet.

[0024] Finally, the server can construct the network topology corresponding to the target service device. The node types in this network topology can include: server devices, access switches, aggregation / core switches, and routers / firewalls. The edge types can include: physical links (LLDP discovery), logical affiliation (server → access switch port), and Layer 3 reachability (inferring gateway relationships through routing tables).

[0025] Furthermore, the method for determining the network topology corresponding to the aforementioned target service device is an optional and implementable method. In actual application scenarios, there can be a variety of different methods. Different methods can be selected according to different actual application scenarios. This embodiment of the invention does not impose specific limitations on this.

[0026] Once the network topology corresponding to the target service device is obtained, the server can perform comprehensive tests on the CPU, memory, disk, and network performance of the target service device based on the network topology to obtain the first performance test data.

[0027] In step S108, the second performance test data of the target service device during the acceptance phase is obtained, and the status detection result of the target service device is determined based on the first performance test data and the second performance test data.

[0028] In implementation, the server can use a pre-trained detection model to determine the status detection result of the target service device based on the first performance test data and the second performance test data. The detection model can be a model built based on a preset machine learning algorithm such as a vector machine or a neural network.

[0029] Alternatively, the server can determine the status detection result of the target service device based on the service status requirements of the cloud resource pool to which the target service device belongs, using both the first and second performance test data. For example, the server can filter out performance indicator data from the first performance test data where the difference between the first and second performance test data is greater than a preset difference threshold, and determine whether the target service device meets the service status requirements of the cloud resource pool to which it belongs, based on the filtered performance indicator data, thus obtaining the status detection result of the target service device.

[0030] This invention provides a device detection method. It receives a status detection request for a target service device, responds to the request, and, based on a preset network communication protocol, acquires neighbor relationship information, routing table data, and management information database corresponding to the target service device. Based on these resources, it constructs a network topology corresponding to the target service device and performs performance testing on it, obtaining first performance test data. It then acquires second performance test data for the target service device during the acceptance phase and determines the status detection result based on both data. This approach offers several advantages. First, based on the preset network communication protocol, it allows for the analysis and calculation of the server network architecture, forming a visualized network topology. This enables adaptive allocation of the server network, avoiding the high labor costs and low efficiency and accuracy of determining device connections inherent in manual on-site verification. Second, by comparing the first performance test data with the second performance test data from the acceptance phase, it allows for the rapid and accurate identification of server hardware changes and operational status, thus accurately determining the operational status of the target service device and improving the efficiency and accuracy of service device status management.

[0031] In practical applications, the specific processing methods for obtaining the neighbor relationship information, routing table data, and management information database corresponding to the target service device in step S104 based on the preset network communication protocol can be varied. The network communication protocol includes preset link layer discovery protocols, preset address resolution protocols, and preset network management protocols. Accordingly, the following provides one optional processing method, such as... Figure 2 As shown, the specific process may include the following steps S1042 to S1046.

[0032] In step S1042, based on a preset link layer discovery protocol, the neighbor relationship information corresponding to the target service device is obtained through the switching device connected to the target service device.

[0033] The neighbor relationship information may include device identifier, link address, and interface address.

[0034] In step S1044, based on a preset address resolution protocol, the routing table data corresponding to the target service device is obtained through a routing device connected to the target service device.

[0035] In step S1046, the management information database corresponding to the target service device is obtained based on the object identifier of the preset network management protocol.

[0036] In implementation, the server can acquire network layer device information, analyze and calculate the network topology corresponding to the target service device, enabling visualized structure management, real-time control of network relationships between network devices, and real-time monitoring and management of connection failures and status between devices. Specifically, this can include the following implementation process: (1) Use a preset network management protocol (such as SNMPv3) to configure the management end and the monitored end.

[0037] (2) Using Python's paramiko module, batch connections to the monitored end are made, and the monitored end and device information are captured.

[0038] (3) Execute the Python script to start LLDP on the monitored end of the connected SW switch and send the command display lldp neighbor brief to read the direct neighbor relationship information.

[0039] (4) Send the ARP command display arp to the monitored end of the router to capture routing table data.

[0040] (5) By introducing the pysnmp module in Python, configure the OID and read MIB data information. Analyze and obtain the MIB tree structure data, or obtain a generator through getCmd to implement SNMP get message operation to obtain interface information, and GetBulk information group information query and capture.

[0041] (6) Analyze the data information captured above and connect it into a topological relationship, store it in the database, and restore the network topology structure using Vue3, D3.js and Django. Realize the network topology visualization monitoring and management of the device.

[0042] Through the above implementation process, network topology can be automatically discovered in a non-intrusive manner. By visualizing the network topology, the operational efficiency of service equipment can be improved.

[0043] In practical applications, the first performance test data and the second performance test data may include one or more of the following: CPU performance test data, memory performance test data, disk performance test data, network card performance test data, database application performance test data, distributed object storage throughput performance test data, and distributed object storage performance test data.

[0044] In implementation, servers can undergo a series of automated testing and evaluation steps to comprehensively improve the efficiency and accuracy of server performance acceptance. The following are the specific implementation steps for the above test items: 1. CPU performance test data: The server can automatically install and run testing tools such as SPECCPU2017 through automated scripts, execute RUNSPEC commands to comprehensively evaluate the CPU performance of the target service device, and automatically collect floating-point and integer test data to calculate the accurate server computing power value, achieving high efficiency, automation and accuracy in the testing process.

[0045] 2. Memory performance test data: The server acceptance management device can automatically install the required drivers upon startup, enter the BIOS interface to automatically record key information such as memory capacity, quantity, frequency, and ECC check, and then execute the dmidecode-tmemory command to automatically record the actual operating frequency of the memory. Through intelligent algorithms, it compares the errors and determines whether the memory performance meets the preset acceptance standards, thus realizing fully automated and high-precision evaluation of memory performance acceptance.

[0046] 3. Disk performance test data: The server acceptance management device can automatically collect detailed information such as disk type, manufacturer, model, interface type, serial number, RAID card and chip when it starts up, and execute specific commands to further collect RAID card information, store this data, and use intelligent analysis to determine whether these parameters meet the server acceptance standards, thereby achieving comprehensive automated collection and accurate acceptance of disk information.

[0047] 4. Disk RAID performance test data: The server acceptance management device can automatically configure the disk to RAID1, RAID5, or RAID10 mode upon startup and launch the Vdbench stress testing tool. Then, the system configures the IO stress model, sets the block size to 4K and 128K, performs sequential write and read bandwidth tests on the disk, and automatically records all test results to ensure a comprehensive evaluation and accurate recording of disk performance.

[0048] 5. Network card hardware test data: The server acceptance management device can automatically detect and store the network configuration and driver information of the network card at startup. Then it enters the server BIOS interface to record the detailed information of the network adapter and uses an automated comparison process to determine whether this information meets the preset acceptance criteria, thereby achieving accurate acceptance of network card performance and configuration.

[0049] 6. Network card performance test data: The server acceptance management device can automatically install the Netperf tool and configure network interface card (NIC) parameters after startup to test the performance of gigabit, 10-gigabit, and Fibre Channel NICs. The system performs TCP long-connection and short-connection performance tests, as well as batch transmission tests of TCP and UDP data throughput, comprehensively evaluating the performance and stability of network equipment.

[0050] 7. Virtualization performance metrics data test: (1) Automated database and test environment configuration: MariaDB 10.3.9 is automatically installed on a Linux virtual machine and the tpcc database is created. At the same time, the TPCCRunner test software is installed on the stress test machine, and the loader.properties, master.properties, and slave.properties files are automatically modified, the initialization tables are imported, and the database stress test environment is prepared.

[0051] (2) Concurrency performance test settings: Automatically set the number of concurrent slaves and configure the slaves list in the master.properties file of TPCCRunner, start stress test on the server to evaluate its ability to handle concurrent operations.

[0052] (3) Distributed Web Service Stress Testing: Deploy Apache web services on other Linux virtual machines and install Besim in conjunction with the equipment to verify the normal operation of Besim. Record stress scripts using Avalanche instruments, and gradually increase the stress according to the Load model, set the running time, and conduct stress tests on multiple virtual machines simultaneously to simulate real-world web service requests and processing.

[0053] (4) Performance data recording and analysis: Automatically record the performance and system resource usage of each virtual machine during the test process, such as CPU usage, memory usage, network throughput, etc., to provide detailed data support for subsequent performance evaluation and optimization.

[0054] 8. (Relational) Database Application Performance Test Data: (1) Automated database deployment and configuration: MariaDB 10.3.9 is automatically installed on all data disks of the server using dual instances in RAID10 groups, and the tpcc database is created to ensure high availability and security of the data.

[0055] (2) Stress test environment setup: The TPCCRunner testing software is automatically installed on the stress tester, and the loader.properties, master.properties, slave.properties, and slaves.properties files are automatically modified to initialize the data. The system also automatically sets the number of concurrent slaves in preparation for comprehensive performance stress testing.

[0056] (3) Performance monitoring and recording: During the test, the system automatically records and stores the peak data of the test performance, and records in detail the system resource usage of the server under test, including key indicators such as CPU utilization, memory utilization, and hard disk I / O. This data helps to analyze the server's performance and stability under high load conditions.

[0057] 9. Distributed object storage throughput performance test data: (1) Automatic deployment of Cosbench testing tool: The system automatically installs and configures Cosbench, a tool specifically designed for testing object storage performance, to ensure the consistency and accuracy of the testing environment.

[0058] (2) File upload and bandwidth test: Automatically upload multiple files and record the bandwidth value (MB / s) during the upload process to evaluate the performance of the storage system under standard operation.

[0059] (3) Concurrent upload test: Perform concurrent upload of multiple files to test the system’s performance under high concurrency conditions and record the completion time of the entire test.

[0060] (4) Bandwidth calculation: Based on the amount of data in the uploaded file and the test time, the actual bandwidth (throughput) is automatically calculated, providing intuitive and quantitative data on system performance.

[0061] 10. Distributed object storage performance test data: (1) Automatic deployment of Vdbench tool: The system automatically deploys Vdbench tool on the stress tester. This is a widely used storage performance testing tool used to simulate file operations and measure storage performance.

[0062] (2) Configure test parameters: Automatically define host settings, including default path, user, shell used, etc., as well as the configuration of multiple storage nodes (such as node1, node2, node3, etc.). Set the test file size to 200MB, the total number to 20,000, and the file operation ratio to 6:4 read-write ratio to simulate actual workload.

[0063] (3) Performance data collection: During the test, the system automatically records the aggregated network throughput, average file access response time, and hard disk utilization of each storage node. Finally, the system will calculate and record the overall test throughput.

[0064] By conducting automated performance testing across multiple dimensions, the efficiency and accuracy of server equipment acceptance during the acceptance phase, as well as the efficiency and accuracy of status testing during the operational phase, can be improved.

[0065] In practical applications, equipment acceptance testing can also be performed on the target service equipment. The specific methods for equipment acceptance testing can vary; the following provides one optional method, such as... Figure 3 As shown, the specific process may include the following steps S302 to S308.

[0066] In step S302, an equipment acceptance request for the target service equipment is received.

[0067] In practice, to improve equipment acceptance efficiency, servers can automate task creation. For example, through an integrated management platform, users can select or input the specific scope of acceptance (such as the number of servers to be accepted, the physical unit where the service is located, etc.) and standards.

[0068] like Figure 4 As shown, the server can automatically create acceptance tasks based on the constructed acceptance management system, using preset templates and intelligent recommendation algorithms, reducing manual operations and improving the speed and accuracy of task setting.

[0069] In step S304, in response to the equipment acceptance request, a performance test is performed on the target service equipment to obtain second performance test data.

[0070] In implementation, the server can utilize automated testing software and performance testing tools based on open-source frameworks to comprehensively test the CPU, memory, disk, and network performance of the target service device, obtaining secondary performance test data. Furthermore, highly pre-defined data cleaning algorithms can be used to cleanse the secondary performance test data, ensuring that only valid data relevant to the acceptance criteria is retained, thus improving the accuracy and reliability of the data.

[0071] In step S306, the acceptance requirement data and preset error data corresponding to the target service device are obtained, and the acceptance result corresponding to the target service device is determined based on the second performance test data, acceptance requirement data and preset error data using a pre-trained verification model.

[0072] The preset error data is determined based on the data batch, allowable error range, equipment manager, and equipment description information of the target service equipment.

[0073] In implementation, the acceptance management system can use technologies such as OCR to identify key information in specified documents (such as acceptance standards), and use natural language processing (NLP) technology to parse the identified text content and automatically fill it into relevant fields.

[0074] In addition, the methods for determining the preset error data may include: (1) The system automatically reads four fields: data batch, allowable error range, person in charge, and equipment description information. Then, the acceptance management system can determine the preset error data based on these four fields. For example, the acceptance management system can automatically generate the error threshold (i.e., the preset error data) based on the acceptance task corresponding to the target service equipment. Alternatively, the acceptance personnel can set the error threshold. Or, after the acceptance management system automatically generates the error threshold, the server acceptance personnel can adjust it according to the maintenance requirements to obtain the preset error data. (2) Upload the preset error data to the system database for storage to obtain the reasonable error when the server is running normally. The reasonable error varies for different data batches.

[0075] By using various methods to determine preset error data, the accuracy of acceptance errors can be improved while taking into account the actual requirements of the acceptance task. This makes the preset error data corresponding to the acceptance equipment more accurate and can effectively prevent problems such as unreasonable error settings.

[0076] In addition, users can customize error thresholds (i.e. preset error data), which can be used for subsequent performance comparisons to ensure that the acceptance process can be flexibly adjusted according to actual needs.

[0077] like Figure 5 As shown, the server can utilize a verification model built based on machine learning algorithms such as Vector Machines (SVM) or Neural Networks to automatically compare actual performance data (i.e., second performance test data) with a preset set of acceptance information (acceptance requirement data). The acceptance management system can automatically determine whether the target service equipment meets the acceptance criteria based on the set error data and generate a detailed acceptance report, including performance analysis and a detailed description of potential problems, providing practical operational suggestions for the maintenance team.

[0078] In addition, such as Figure 6 As shown in Figure 7, the acceptance management system can include a creation and input module, a data acquisition and testing module, a data parsing and processing module, a comparative analysis module, and a visualization display module. This acceptance management system can improve the efficiency of service equipment maintenance. As shown in Figure 7, the acceptance management system can implement the following steps: 1. Create an acceptance task: First, define the acceptance task and clarify the specific scope of the acceptance.

[0079] 2. Enter acceptance information: Based on the determined acceptance scope, enter the relevant acceptance information and set the allowable error value.

[0080] 3. Performance index testing: Automatically test and collect hardware configuration and performance index data of the server during acceptance, and form a performance index data set after data cleaning and processing.

[0081] 4. Data Comparison and Analysis: Based on the preset error value, the performance data obtained from the test is compared with the acceptance information set to determine whether the server meets the acceptance criteria.

[0082] 5. Acceptance Report Generation: Automatically generates a detailed acceptance report and analyzes server performance.

[0083] 6. Hardware and operational status monitoring: Automatically identify and upload changes to server hardware and operational status data, and monitor the server's operational status in real time by comparing it with the data collected during acceptance testing.

[0084] 7. Power Consumption Data Acquisition: Automatically collects the server's power consumption data and determines whether it meets the energy consumption standard based on the set error value.

[0085] The acceptance management system can integrate Internet of Things (IoT) technology to monitor changes and operational status of server (i.e., target service equipment) hardware in real time. For example, the system can use edge computing technology to perform preliminary analysis on networked sensor data to filter out sensor data with large fluctuations (such as temperature data that fluctuates frequently in a short period of time), and collect the filtered sensor data to reduce data transmission latency and improve response speed. Furthermore, through a big data analytics platform, the system can predict hardware failures and performance degradation, and promptly notify the maintenance team to intervene.

[0086] The acceptance management system can also use high-precision energy consumption monitoring equipment to automatically record the real-time power consumption of the target service equipment. Through data analysis software, the system can not only monitor the total power consumption of the target service equipment, but also analyze the energy efficiency of each component, helping to optimize server configuration and operating strategies, and achieve energy savings and cost reduction.

[0087] The specific content of each module in this acceptance management system may include: (1) Create Input Module: Used to create acceptance tasks, define the scope of acceptance, and enter acceptance information and set errors; (2) Data Acquisition and Testing Module: Used to acquire hardware configuration and performance index data of the server during server acceptance testing, and to collect server acceptance test data, working status data and power consumption data; (3) Data parsing and processing module: used to parse the acquired server working status data and clean the data; (4) Comparison and analysis module: It is used to compare the performance test data and acceptance information set with the preset error data to determine whether the server acceptance meets the requirements, automatically generate an acceptance report, analyze the performance of the accepted server, and determine the working status of the server by comparing it with the server hardware data and performance test data collected during acceptance to realize the management of the working status of the server equipment. It also analyzes whether the server power consumption meets the standard based on the error judgment of the automatically collected server power consumption data.

[0088] In addition, the internal structure of the aforementioned acceptance management system can be as follows: Figure 8 As shown.

[0089] In step S308, based on the acceptance results of the target service equipment, it is determined whether the target service equipment meets the acceptance requirements, and if it is determined that the target service equipment meets the acceptance requirements, the target service equipment is run.

[0090] During implementation, during the operational phase of the target service equipment, such as Figure 5 As shown, the server can automatically collect the operating status data of the target service device through the data collection template provided by the acceptance management system. Then, the server can clean and preprocess the collected server operating data, and parse the preprocessed data. Maintenance personnel can configure preset error data according to the error configuration rules using four fields, including description information, provided by the system. Based on the server operating status data and preset error data, the server's operating status can be visualized, enabling tracking, monitoring, and management of the server's operating status.

[0091] The data processing procedure of the acceptance module (i.e., the process of cleaning and processing the collected work status data, etc.) may include: (1) The acceptance management system can use the Pandas module to automatically edit the collected data and obtain server working status data; (2) Store the preprocessed data into the database of the management system for later querying, exporting, and visualization.

[0092] The built-in computer program in the acceptance management system automatically filters, processes, analyzes, and stores the data to be processed, avoiding the tedious processing procedures and data screening processes of maintenance personnel. This makes data cleaning and processing more efficient and provides reliable data support for data visualization. By performing multi-faceted preprocessing on the data to be processed, it can be ensured that the collected server operating status data can more accurately reflect the server's operating status, thereby further improving work efficiency.

[0093] Visualization of performance acceptance data can include: (1) Use VUE3 to build a visual front-end framework to provide user interface design, interaction and data presentation; (2) Use Django to build a backend framework to provide query and interaction operations between the web frontend and the database, simplify the development process of web applications, and provide the underlying architecture for data visualization; (3) Connect Vue and django modules according to the rules to achieve data visualization.

[0094] Through the above visualization operations, the underlying architecture of data visualization can be made more stable and reliable, ensuring accurate feedback and timely response to the server's working status, and effectively improving the efficiency of server management and maintenance.

[0095] Leveraging the characteristics of adaptive network architecture and connection compliance, a highly operable and cost-effective automated server acceptance method is constructed that supports cross-platform and multi-vendor comprehensive indicator data. This method enables convenient, efficient, and one-click inspection of servers for network access, saving significant manpower costs while improving the compliance and accuracy of project acceptance work.

[0096] In practical applications, the specific processing method for determining the status detection result of the target service device based on the first performance test data and the second performance test data in step S108 above can be varied. The following provides one optional processing method, such as... Figure 9 As shown, the specific process may include the following steps S1082 to S1088.

[0097] In step S1082, the network topology is checked for compliance with connectivity requirements, and the first detection result is obtained.

[0098] During implementation, the server can use a preset compliance detection algorithm to perform connection compliance detection on the network topology and obtain the first detection result. In this way, through the automated detection module built into the acceptance management system, network protocol analysis, real-time feedback and data verification technology can ensure the accuracy and compliance of the server connection status.

[0099] In step S1084, a second detection result is determined based on the comparison results of the first performance test data and the second performance test data.

[0100] In step S1086, a third detection result is determined based on the energy consumption data of the target service device.

[0101] In step S1088, the status detection result of the target service device is determined based on the first detection result, the second detection result, and the third detection result.

[0102] In implementation, by combining intelligent identification and automatic configuration, multi-protocol adaptation, network topology detection, and software-defined networking (SDN) technology, it can be ensured that service devices can be seamlessly connected and optimized for various network environments.

[0103] By using a built-in automated detection module, network protocol analysis, real-time feedback, and data verification technologies, the accuracy and compliance of server connection status can be ensured based on connection compliance checks.

[0104] By using a unified data interface (RESTful API), data standardization (JSON, XML), middleware integration (MQTT, RabbitMQ), and multi-source data fusion technology, we can achieve cross-platform and multi-vendor comprehensive indicator data collection capabilities, ensuring data consistency and comprehensiveness.

[0105] By leveraging user-friendly interfaces (HTML5, CSS3), one-click functionality (JavaScript), automated processes (Ansible, Jenkins), and data-driven decision-making (Tableau, Power BI), high operability and cost-effectiveness can be achieved, optimizing user experience and reducing costs.

[0106] By using data analysis algorithms (decision trees, random forests) and automated testing technologies, we can ensure the compliance and accuracy of project acceptance, and guarantee the precision and compliance of the acceptance process.

[0107] This application proposes to utilize protocols such as LLDP, ARP, and SNMP to achieve automatic network topology discovery. These protocols collect network layer device information, automatically analyze and calculate the network topology, and use visualization technology to generate a network topology map, displaying the connection relationships and status between devices in real time. It also enables real-time monitoring of network disconnections and device status. Furthermore, based on network data analysis and data modeling, the collected data can be classified and prioritized (i.e., performance test data can be collected sequentially based on the priority of indicators). This allows for a single full collection of indicators across product platforms and system versions, followed by multiple incremental calls, meeting the automated acceptance requirements of server network access construction projects while simultaneously reducing costs and increasing efficiency.

[0108] Automatic identification technology monitors changes and operational status of server hardware, and compares and analyzes real-time data with data collected during acceptance testing to accurately determine the server's working status. Furthermore, the use of Vue-related visualization technologies effectively improves the accuracy and timeliness of server status feedback, thereby enhancing the operational efficiency of service equipment management.

[0109] Traditional methods and device architectures lack flexibility and data analysis is incomplete. Each server and other device under inspection requires pre-installed agent programs or batch processing tools, consuming system resources and offering poor deployment convenience. Static configuration data and dynamic performance testing data require multiple processes for collection, and various data types still require manual aggregation and review. However, the device testing method provided in this invention allows for optimized and customized functional architecture and data collection methods. For example, it can adopt a lightweight and flexible deployment mode, using view drill-down to filter, aggregate, and analyze data, achieving unified collection of all inspection indicators without pre-installation. This overcomes environmental differences such as different manufacturers, models, and operating system versions, enabling one-click acceptance and making the acceptance process more accurate.

[0110] Furthermore, traditional methods and device architectures lack the ability to identify network architectures. Acceptance work involving network architecture and physical connections still requires on-site verification by personnel, resulting in low efficiency, large errors, and high costs. The device testing method provided in this invention, however, incorporates relevant IT network acceptance requirements from the industry. Supported by algorithms, it utilizes network data analysis and data modeling technologies, comprehensively leveraging protocols such as LLDP, ARP, MAC, and routing to analyze and calculate the network topology, forming a visualized network structure. Through graphs, modeling, and causal relationships between objects, it predicts the deviation between the server network architecture and the actual connections, thereby achieving efficient acceptance of massive amounts of equipment and cables.

[0111] The target service equipment in this embodiment of the invention can be service equipment used in the construction of data center clusters, large, medium and small resource pools, business networks, enterprise networks, campus networks, and other related projects. The acceptance management system can be used to verify the hardware and software quality, quantity, performance, and other relevant parameters of purchased IT service equipment such as servers, as well as whether the network architecture and cable connections meet standards. It can also be used for periodic server power consumption and performance stress testing during routine maintenance.

[0112] This invention provides a device detection method. It receives a status detection request for a target service device, responds to the request, and, based on a preset network communication protocol, acquires neighbor relationship information, routing table data, and management information database corresponding to the target service device. Based on these resources, it constructs a network topology corresponding to the target service device and performs performance testing on it, obtaining first performance test data. It then acquires second performance test data for the target service device during the acceptance phase and determines the status detection result based on both data. This approach offers several advantages. First, based on the preset network communication protocol, it allows for the analysis and calculation of the server network architecture, forming a visualized network topology. This enables adaptive allocation of the server network, avoiding the high labor costs and low efficiency and accuracy of determining device connections inherent in manual on-site verification. Second, by comparing the first performance test data with the second performance test data from the acceptance phase, it allows for the rapid and accurate identification of server hardware changes and operational status, thus accurately determining the operational status of the target service device and improving the efficiency and accuracy of service device status management.

[0113] The above describes the equipment testing method provided by the embodiments of the present invention. Based on the same idea, the embodiments of the present invention also provide an equipment testing device, such as... Figure 10 As shown.

[0114] The equipment testing device includes: a request receiving module 1001, a data acquisition module 1002, a structure construction module 1003, and an equipment testing module 1004, wherein: The request receiving module 1001 is used to receive status detection requests for the target service device; The data acquisition module 1002 is used to respond to the status detection request and acquire the neighbor relationship information, routing table data and management information database corresponding to the target service device based on a preset network communication protocol. The structure construction module 1003 is used to construct a network topology structure corresponding to the target service device based on the neighbor relationship information, routing table data and management information database corresponding to the target service device, and to perform performance testing on the target service device based on the network topology structure to obtain first performance test data. The device detection module 1004 is used to acquire the second performance test data of the target service device during the acceptance phase, and determine the status detection result of the target service device based on the first performance test data and the second performance test data.

[0115] In this embodiment of the invention, the network communication protocol includes a preset link layer discovery protocol, a preset address resolution protocol, and a preset network management protocol. The data acquisition module 1002 is used for: Based on the preset link layer discovery protocol, the neighbor relationship information corresponding to the target service device is obtained through the switching device connected to the target service device. The neighbor relationship information includes device identifier, link address and interface address. Based on the preset address resolution protocol, the routing table data corresponding to the target service device is obtained through the routing device connected to the target service device; Based on the object identifier of the preset network management protocol, the management information database corresponding to the target service device is obtained.

[0116] In this embodiment of the invention, the first performance test data includes one or more of the following: CPU performance test data, memory performance test data, disk performance test data, network card performance test data, database application performance test data, distributed object storage throughput performance test data, and distributed object storage performance test data.

[0117] In this embodiment of the invention, the device further includes: The receiving module is used to receive the equipment acceptance request for the target service device; A response module is used to respond to the device acceptance request, perform performance testing on the target service device, and obtain the second performance test data; The acquisition module is used to acquire the acceptance requirement data and preset error data corresponding to the target service device, and use a pre-trained verification model to determine the acceptance result corresponding to the target service device based on the second performance test data, the acceptance requirement data and the preset error data. The acceptance module is used to determine whether the target service device meets the acceptance requirements based on the acceptance results of the target service device, and to run the target service device if it is determined that the target service device meets the acceptance requirements.

[0118] In this embodiment of the invention, the preset error data is determined based on the data batch, allowable error range, equipment manager, and equipment description information of the target service device.

[0119] In this embodiment of the invention, the device detection module 1004 is used for: The network topology is subjected to a connection compliance test to obtain a first test result; Based on the comparison results of the first performance test data and the second performance test data, the second detection result is determined; Based on the energy consumption data of the target service device, the third detection result is determined; Based on the first detection result, the second detection result, and the third detection result, the status detection result of the target service device is determined.

[0120] This invention provides a device detection apparatus that receives and responds to a status detection request for a target service device. Based on a preset network communication protocol, it acquires neighbor relationship information, routing table data, and a management information database corresponding to the target service device. Based on these resources, it constructs a network topology corresponding to the target service device and performs performance testing on the device, obtaining first performance test data. It then acquires second performance test data for the target service device during the acceptance phase and determines the status detection result based on both data. This approach offers several advantages. First, by using a preset network communication protocol, the server network architecture can be analyzed and calculated, forming a visualized network topology. This enables adaptive allocation of the server network, avoiding the high labor costs and low efficiency and accuracy of determining device connections inherent in manual on-site verification. Second, by comparing the first performance test data with the second performance test data from the acceptance phase, changes in server hardware and their operational status can be quickly and accurately identified, thus improving the efficiency and accuracy of service device status management.

[0121] The above describes the equipment testing apparatus provided in the embodiments of the present invention. Based on the same concept, the embodiments of the present invention also provide an equipment testing device, such as... Figure 11 As shown.

[0122] The device testing equipment can provide terminal devices or servers, etc., for the above embodiments.

[0123] Device testing devices can vary significantly due to differences in configuration or performance. They may include one or more processors 1101 and memory 1102, with memory 1102 storing one or more application programs or data. Memory 1102 can be temporary or persistent storage. The application programs stored in memory 1102 may include one or more modules (not shown), each module including a series of computer-executable instructions for the device testing device. Furthermore, processor 1101 may be configured to communicate with memory 1102 and execute the series of computer-executable instructions stored in memory 1102 on the device testing device. The device testing device may also include one or more power supplies 1103, one or more wired or wireless network interfaces 1104, one or more input / output interfaces 1105, and one or more keyboards 1106.

[0124] Specifically, in this embodiment, the device detection device includes a memory and one or more programs, wherein one or more programs are stored in the memory, and one or more programs may include one or more modules, and each module may include a series of computer-executable instructions for the device detection device, and is configured to be executed by one or more processors. The one or more programs include computer-executable instructions for performing the following: Receive status detection requests for the target service device; In response to the status detection request, based on a preset network communication protocol, the neighbor relationship information, routing table data, and management information database corresponding to the target service device are obtained; Based on the neighbor relationship information, routing table data and management information database corresponding to the target service device, a network topology corresponding to the target service device is constructed, and based on the network topology, the performance of the target service device is tested to obtain the first performance test data. The second performance test data of the target service device during the acceptance phase is obtained, and the status detection result of the target service device is determined based on the first performance test data and the second performance test data.

[0125] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the device detection device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0126] This invention provides a device detection device that receives and responds to a status detection request for a target service device. Based on a preset network communication protocol, it acquires neighbor relationship information, routing table data, and a management information database corresponding to the target service device. Based on these resources, it constructs a network topology corresponding to the target service device and performs performance testing on the device, obtaining first performance test data. It then acquires second performance test data for the target service device during the acceptance phase and determines the status detection result based on both data. This approach offers several advantages. First, by using a preset network communication protocol, the server network architecture can be analyzed and calculated, forming a visualized network topology. This enables adaptive allocation of the server network, avoiding the high labor costs and low efficiency and accuracy of determining device connections associated with manual on-site verification. Second, by comparing the first performance test data with the second performance test data from the acceptance phase, changes in server hardware and their operational status can be quickly and accurately identified, thus improving the efficiency and accuracy of service device status management.

[0127] Furthermore, based on the above Figures 1 to 9 The method shown in this specification, along with one or more embodiments, also provides a storage medium for storing computer-executable instruction information. In one specific embodiment, the storage medium can be a USB flash drive, optical disc, hard disk, etc. When the computer-executable instruction information stored in the storage medium is executed by a processor, it can achieve the following process: Receive status detection requests for the target service device; In response to the status detection request, based on a preset network communication protocol, the neighbor relationship information, routing table data, and management information database corresponding to the target service device are obtained; Based on the neighbor relationship information, routing table data and management information database corresponding to the target service device, a network topology corresponding to the target service device is constructed, and based on the network topology, the performance of the target service device is tested to obtain the first performance test data. The second performance test data of the target service device during the acceptance phase is obtained, and the status detection result of the target service device is determined based on the first performance test data and the second performance test data.

[0128] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the above-described storage medium embodiment is basically similar to the method embodiment, so the description is relatively simple; relevant parts can be referred to the description of the method embodiment.

[0129] This invention provides a storage medium that receives and responds to a status detection request for a target service device. Based on a preset network communication protocol, it acquires neighbor relationship information, routing table data, and a management information database corresponding to the target service device. Based on these resources, it constructs a network topology corresponding to the target service device and performs performance testing on it, obtaining first performance test data. It then acquires second performance test data for the target service device during the acceptance phase and determines the status detection result based on both data. This approach offers several advantages. First, by using a preset network communication protocol, the server network architecture can be analyzed and calculated, forming a visualized network topology. This enables adaptive allocation of the server network, avoiding the high labor costs and low efficiency and accuracy of determining device connections associated with manual on-site verification. Second, by comparing the first performance test data with the second performance test data from the acceptance phase, changes in server hardware and their operational status can be quickly and accurately identified, thus improving the efficiency and accuracy of service device status management.

[0130] Furthermore, based on the above Figures 1 to 9 The method shown in this specification, along with one or more embodiments, also provides a computer program product including a computer program that, when executed by a processor, performs the following process: Receive status detection requests for the target service device; In response to the status detection request, based on a preset network communication protocol, the neighbor relationship information, routing table data, and management information database corresponding to the target service device are obtained; Based on the neighbor relationship information, routing table data and management information database corresponding to the target service device, a network topology corresponding to the target service device is constructed, and based on the network topology, the performance of the target service device is tested to obtain the first performance test data. The second performance test data of the target service device during the acceptance phase is obtained, and the status detection result of the target service device is determined based on the first performance test data and the second performance test data.

[0131] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the above-described embodiment of a computer program product is relatively simple in description because it is fundamentally similar to the method embodiment; relevant parts can be referred to the description of the method embodiment.

[0132] This invention provides a computer program product that receives and responds to a status detection request for a target service device. Based on a preset network communication protocol, it acquires neighbor relationship information, routing table data, and a management information database corresponding to the target service device. Based on these resources, it constructs a network topology corresponding to the target service device and performs performance testing on it, obtaining first performance test data. It then acquires second performance test data for the target service device during the acceptance phase and determines the status detection result based on both data. This approach, on the one hand, allows for the analysis and calculation of the server network architecture based on the preset network communication protocol, forming a visualized network topology and enabling adaptive allocation of the server network. This avoids the problems of high labor costs and low efficiency and accuracy in determining device connections associated with manual on-site verification. On the other hand, by comparing the first performance test data with the second performance test data during the acceptance phase, it can quickly and accurately identify changes in server hardware and their operational status, thereby accurately determining the operational status of the target service device and improving the efficiency and accuracy of service device status management.

[0133] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0134] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0135] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) that can be executed by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers.

[0136] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0137] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0138] The embodiments described herein are illustrated with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable parallel device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable parallel device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0139] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable fraud device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0140] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0141] Computer-readable media includes both permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. As defined herein, computer-readable media does not include transient media, such as modulated data signals and carrier waves.

[0142] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0143] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0144] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0145] The above description is merely an embodiment of this specification and is not intended to limit this document. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for testing equipment, characterized in that, The method includes: Receive status detection requests for the target service device; In response to the status detection request, based on a preset network communication protocol, the neighbor relationship information, routing table data, and management information database corresponding to the target service device are obtained; Based on the neighbor relationship information, routing table data and management information database corresponding to the target service device, a network topology corresponding to the target service device is constructed, and based on the network topology, the performance of the target service device is tested to obtain the first performance test data. The second performance test data of the target service device during the acceptance phase is obtained, and the status detection result of the target service device is determined based on the first performance test data and the second performance test data.

2. The method according to claim 1, characterized in that, The network communication protocol includes a preset link layer discovery protocol, a preset address resolution protocol, and a preset network management protocol. The step of acquiring neighbor relationship information, routing table data, and management information database corresponding to the target service device based on a preset network communication protocol includes: Based on the preset link layer discovery protocol, the neighbor relationship information corresponding to the target service device is obtained through the switching device connected to the target service device. The neighbor relationship information includes device identifier, link address and interface address. Based on the preset address resolution protocol, the routing table data corresponding to the target service device is obtained through the routing device connected to the target service device; Based on the object identifier of the preset network management protocol, the management information database corresponding to the target service device is obtained.

3. The method according to claim 1, characterized in that, The first performance test data includes one or more of the following: CPU performance test data, memory performance test data, disk performance test data, network card performance test data, database application performance test data, distributed object storage throughput performance test data, and distributed object storage performance test data.

4. The method according to claim 1, characterized in that, Before receiving the status detection request for the target service device, the method further includes: Receive an equipment acceptance request for the target service device; In response to the device acceptance request, a performance test is performed on the target service device to obtain the second performance test data; Obtain the acceptance requirement data and preset error data corresponding to the target service device, and use a pre-trained verification model to determine the acceptance result corresponding to the target service device based on the second performance test data, the acceptance requirement data and the preset error data. Based on the acceptance results of the target service equipment, it is determined whether the target service equipment meets the acceptance requirements, and if it is determined that the target service equipment meets the acceptance requirements, the target service equipment is operated.

5. The method according to claim 4, characterized in that, The preset error data is determined based on the data batch, allowable error range, equipment manager, and equipment description information of the target service equipment.

6. The method according to claim 5, characterized in that, The step of determining the status detection result of the target service device based on the first performance test data and the second performance test data includes: The network topology is subjected to a connection compliance test to obtain a first test result; Based on the comparison results of the first performance test data and the second performance test data, the second detection result is determined; Based on the energy consumption data of the target service device, the third detection result is determined; Based on the first detection result, the second detection result, and the third detection result, the status detection result of the target service device is determined.

7. A device for testing equipment, characterized in that, The device includes: The request receiving module is used to receive status detection requests for the target service device. The data acquisition module is used to respond to the status detection request and acquire the neighbor relationship information, routing table data and management information database corresponding to the target service device based on a preset network communication protocol. The structure building module is used to construct a network topology corresponding to the target service device based on the neighbor relationship information, routing table data and management information database corresponding to the target service device, and to perform performance testing on the target service device based on the network topology to obtain first performance test data. The device detection module is used to acquire the second performance test data of the target service device during the acceptance phase, and to determine the status detection result of the target service device based on the first performance test data and the second performance test data.

8. A device testing device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the device detection method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the steps of the device detection method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the steps of the device detection method according to any one of claims 1 to 6.

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