Probe technology-based credential and credential adaptation full-process performance monitoring method and device

Abstract

The embodiment of the invention provides a method and a device for monitoring the performance of a credential and credential adaptation full process based on a probe technology. The method comprises the following steps: determining a migration time node, migration content, a migration mode and a performance monitoring index according to a system architecture, a data volume and a business process of a to-be-migrated business system; a preset monitoring probe tool is deployed on a source system and a target system of the business system to be migrated, and the preset monitoring probe tool is used for collecting and transmitting performance monitoring indexes in real time; in the migration process of the to-be-migrated service system, detecting whether performance monitoring indexes, collected by a preset monitoring probe tool, of a source system and a target system are within a preset threshold range or not; and when the performance monitoring index exceeds the preset threshold range, an alarm notice is sent, so that the stability of the service system in the migration process and after migration can be ensured, the migration efficiency and the operation and maintenance efficiency are improved, and the success of migration of the credential system and the smooth transition of the service are ensured.

Description

Technical Field

[0001] The present application relates to the field of system migration technology, and specifically, to a method, device, computer equipment and storage medium for monitoring the full-process performance of information innovation adaptation based on probe technology. Background Art

[0002] The information and communications technology industry has effectively solved the security issues brought about by the development of information technology, created an infrastructure that can be controlled, researched, developed and produced, and laid a solid foundation for the security of information infrastructure.

[0003] In the process of comprehensive localization, the localization process of core information technology products and key services used in important information systems and key infrastructure is accelerating. The software and hardware information technology industry is developing rapidly. However, in the actual process, it faces a series of problems such as different construction scales, different application states, diverse development languages, and different system architectures, which increase the technical difficulty and migration cost of information technology. Especially in the migration process, there are many performance challenges, which in turn affect the compatibility, resource adaptation and business continuity of the system after migration.

[0004] At present, in the three stages before, during and after the migration, the operating environment information of the current business system, including hardware configuration, software version, network status, etc., is collected through preset information acquisition tools or scripts. According to business needs and system characteristics, a series of key performance monitoring indicators are set, such as response time, throughput, CPU usage, memory occupancy, etc. Professional performance monitoring tools are used to monitor system performance in real time, and monitoring data is collected and analyzed to evaluate whether system performance meets expectations.

[0005] However, the relevant technologies may be too single or fixed in the setting of monitoring indicators, and fail to fully consider the specific needs of different business systems and migration scenarios, which may result in the monitoring results failing to fully reflect the true status of system performance and ignoring certain key performance bottlenecks or abnormal points. The real-time monitoring function may be limited by the data processing speed and the complexity of the system architecture, resulting in time delays in the collection, analysis and display of monitoring data. This delay may prevent operation and maintenance personnel from timely discovering and handling performance problems, thereby affecting the continuity and stability of the business system. There may be a lack of efficient data analysis and processing capabilities, and it is impossible to extract valuable information and trends from a large amount of monitoring data. It is difficult for operation and maintenance personnel to perform effective performance tuning and decision-making based on monitoring data, which affects the optimization effect of system performance. The hardware and software in the information-based innovation environment may be greatly different from those in the traditional environment, and the existing monitoring tools may not be fully adapted to these differences, which may result in the monitoring tools failing to work properly or failing to accurately obtain system performance data in the information-based innovation environment, thereby affecting the accuracy and effectiveness of monitoring. There may be deficiencies in automation and intelligence, and it is impossible to automatically adjust system parameters or perform corresponding optimization operations based on monitoring results, which increases the workload of operation and maintenance personnel and reduces the efficiency and accuracy of system performance optimization. During the migration process, due to the constant changes in the system environment and the complexity of the migration steps, existing technologies may not be able to ensure the continuity of performance monitoring. This may lead to a gap in performance monitoring during the critical stage of the migration, increasing the risk of performance problems in the system. Summary of the invention

[0006] The embodiments of the present application provide a method, device, computer equipment and storage medium for monitoring the full-process performance of trusted innovation adaptation based on probe technology.

[0007] The first aspect of the embodiment of the present application provides a method for monitoring the performance of the entire process of the ICT adaptation based on the probe technology, including:

[0008] Determine the migration time node, migration content, migration method and performance monitoring indicators based on the system architecture, data volume and business process of the business system to be migrated;

[0009] Deploy a preset monitoring probe tool on the source system and the target system of the service system to be migrated, wherein the preset monitoring probe tool is used to collect and transmit performance monitoring indicators in real time;

[0010] During the migration of the business system to be migrated, detect whether the performance monitoring indicators of the source system and the target system collected by the preset monitoring probe tool are within the preset threshold range;

[0011] When the performance monitoring indicator exceeds the preset threshold range, an alarm notification will be issued.

[0012] In an optional embodiment of the present application, determining the migration time node, migration content, migration method and performance monitoring indicators according to the system architecture, data volume and business process of the business system to be migrated includes:

[0013] Analyze the system architecture of the business system to be migrated and determine the migration content of the business system to be migrated;

[0014] Migrate the contents of the business systems to be migrated in batches according to the data volume of the business systems to be migrated, and determine the migration time node for each batch;

[0015] Determine the migration method for each batch of migration content based on the business process of the business system to be migrated;

[0016] Determine the performance monitoring indicators required for the system's database, middleware, and application server during the entire migration process based on the migration time node, migration content, and migration method of the business system to be migrated.

[0017] In an optional embodiment of the present application, the performance monitoring indicator includes at least one of CPU usage, memory occupancy, disk input and output, and network bandwidth.

[0018] In an optional embodiment of the present application, the deploying of a preset monitoring probe tool on a source system and a target system of the business system to be migrated includes:

[0019] Select corresponding monitoring probe tools for the source system and the database, middleware, and application server of the target system of the business system to be migrated, so that all monitoring probe tools cover all aspects of the entire migration process.

[0020] In an optional embodiment of the present application, the method further includes:

[0021] Test whether the functions of the migrated business system are running normally;

[0022] Test whether the performance of the migrated business system meets the preset business requirements, where the preset business requirements include stress testing and concurrency testing.

[0023] In an optional embodiment of the present application, the method further includes:

[0024] Obtain performance monitoring indicators of the source system and the target system, and extract feature vectors of the preprocessed performance monitoring indicators;

[0025] Construct a performance monitoring indicator sensitivity scoring model to evaluate the sensitivity of performance monitoring indicators and classify them, and encrypt sensitive data of performance monitoring indicators based on the classification results;

[0026] The exchanged data is decrypted and stored as performance monitoring indicators, and a visual interface is built to display the performance monitoring indicators in real time.

[0027] In an optional embodiment of the present application, the construction of a performance monitoring indicator sensitivity scoring model to evaluate the sensitivity of performance monitoring indicators and classify them refers to collecting historical performance monitoring indicators and extracting historical feature vectors, calculating the mean of the historical feature vectors and setting them as the benchmark data vector;

[0028] Collect performance monitoring indicators in real time and extract real-time feature vectors. Use the K-means clustering analysis algorithm to cluster the real-time feature vectors, and select the center point of each cluster as the reference data vector.

[0029] Combining the RBF kernel function with the integral, the cumulative similarity A(x) between the benchmark data vector and the performance monitoring indicator feature vector is calculated. The formula is:

[0030]

[0031] Where x is the performance monitoring indicator feature vector, x0 is the benchmark data vector, and x i is the historical feature vector of the i-th performance monitoring indicator;

[0032] Perform logarithmic transformation B(x) on the accumulated similarity A, the formula is:

[0033] B(x)=log(1+A(x));

[0034] The hyperbolic tangent function is introduced to smooth the accumulated similarity of the reference feature vector to obtain the accumulated similarity C(x) after smoothing. The formula is:

[0035]

[0036] Where M is the number of reference eigenvectors, x j is the jth reference eigenvector;

[0037] A sensitivity scoring model is constructed to evaluate the sensitivity score S(x) of the performance monitoring indicator feature vector. The formula is:

[0038]

[0039] Collect the sensitivity scores of historical performance monitoring indicators and set the evaluation threshold. Compare the sensitivity score of the performance monitoring indicator feature vector with the evaluation threshold. If the sensitivity score of the performance monitoring indicator feature vector is greater than and equal to the evaluation threshold, it is determined to be sensitive data. If the sensitivity score of the performance monitoring indicator feature vector is less than the evaluation threshold, it is determined to be ordinary data.

[0040] A second aspect of the embodiment of the present application provides a device for monitoring the performance of the entire process of information innovation adaptation based on probe technology, including:

[0041] The determination module is used to determine the migration time node, migration content, migration method and performance monitoring indicators according to the system architecture, data volume and business process of the business system to be migrated;

[0042] A deployment module, used to deploy a preset monitoring probe tool on a source system and a target system of the business system to be migrated, wherein the preset monitoring probe tool is used to collect and transmit performance monitoring indicators in real time;

[0043] The detection module is used to detect whether the performance monitoring indicators of the source system and the target system collected by the preset monitoring probe tool are within the preset threshold range during the migration process of the business system to be migrated;

[0044] The alarm module is used to issue an alarm notification when the performance monitoring indicator exceeds the preset threshold range.

[0045] The third aspect of an embodiment of the present application provides a computer device, including: a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the steps of any of the above-mentioned methods for monitoring the full-process performance of the trusted innovation adaptation based on probe technology.

[0046] The fourth aspect of the embodiments of the present application provides a computer-readable storage medium on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the full-process performance monitoring method of the trusted innovation adaptation based on probe technology as described above are implemented.

[0047] The above technical solution provided by the embodiment of the present application has at least some or all of the following advantages compared with the prior art:

[0048] The probe technology-based full-process performance monitoring method for trusted innovation adaptation described in the embodiment of the present application determines the migration time node, migration content, migration method and performance monitoring indicators according to the system architecture, data volume and business process of the business system to be migrated; deploys a preset monitoring probe tool on the source system and the target system of the business system to be migrated, wherein the preset monitoring probe tool is used to collect and transmit performance monitoring indicators in real time; during the migration process of the business system to be migrated, detects whether the performance monitoring indicators of the source system and the target system collected by the preset monitoring probe tool are within the preset threshold range; when the performance monitoring indicator exceeds the preset threshold range, issues an alarm notification, which can ensure the stability of the business system during and after the migration process, improve the migration efficiency and operation and maintenance efficiency, and ensure the success of the trusted innovation system migration and the smooth transition of the business. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0050] Figure 1 A flowchart of a method for monitoring the performance of the entire process of trusted innovation adaptation based on probe technology provided in one embodiment of the present application;

[0051] Figure 2 A schematic diagram of an application scenario of a business system and a full-process performance monitoring platform provided in one embodiment of the present application;

[0052] Figure 3 A schematic diagram of the structure of a full-process performance monitoring device for trusted innovation adaptation based on probe technology provided for an embodiment of the present application;

[0053] Figure 4 A schematic diagram of the computer device structure provided for one embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the technical solutions and advantages in the embodiments of the present application more clearly understood, the exemplary embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than an exhaustive list of all the embodiments. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0055] See also Figure 1 The full-process performance monitoring method of the ICT adaptation based on the probe technology provided in the embodiment of the present application includes the following steps 100 to 400:

[0056] Step 100: Determine the migration time node, migration content, migration method and performance monitoring indicators according to the system architecture, data volume and business process of the business system to be migrated;

[0057] Step 200: deploying a preset monitoring probe tool on the source system and the target system of the service system to be migrated, wherein the preset monitoring probe tool is used to collect and transmit performance monitoring indicators in real time;

[0058] Step 300: During the migration process of the business system to be migrated, detect whether the performance monitoring indicators of the source system and the target system collected by the preset monitoring probe tool are within the preset threshold range;

[0059] Step 400: When the performance monitoring indicator exceeds a preset threshold range, an alarm notification is issued.

[0060] In an optional embodiment of the present application, Xinchuang, i.e., the information technology application innovation industry, is a concept covering the entire industry chain of the IT industry. It includes the entire industry chain from IT underlying hardware and software to upper-level application software, and aims to achieve independent research and development and production of safe and controllable information technology products and services. Xinchuang adaptation is a key link in information technology application innovation. It involves adaptation work at multiple levels, from core chip protocols to matching basic hardware, operating systems, databases, middleware, servers, and application software. Xinchuang adaptation is to migrate the application software currently used by customers from the traditional X86 instruction set architecture to the Xinchuang instruction set architecture (such as ARM, LoongArch, SW_64, C86, etc.), and ensure that it is available, easy to use, and safe under the new instruction set architecture. The probe technology in performance monitoring is a technology that realizes real-time monitoring and diagnosis of application execution processes and performance indicators without modifying or minimizing the modification of application code. This technology is widely used in various software development and operation and maintenance environments to help developers and operation and maintenance personnel quickly locate and solve performance problems and improve the stability and performance of applications.

[0061] In an optional embodiment of the present application, in step 100, determining the migration time node, migration content, migration method and performance monitoring indicators according to the system architecture, data volume and business process of the business system to be migrated includes:

[0062] Analyze the system architecture of the business system to be migrated and determine the migration content of the business system to be migrated;

[0063] Migrate the contents of the business systems to be migrated in batches according to the data volume of the business systems to be migrated, and determine the migration time node for each batch;

[0064] Determine the migration method for each batch of migration content based on the business process of the business system to be migrated;

[0065] Determine the performance monitoring indicators required for the system's database, middleware, and application server during the entire migration process based on the migration time node, migration content, and migration method of the business system to be migrated.

[0066] In an optional embodiment of the present application, in step 100, the performance monitoring indicator includes at least one of CPU usage, memory occupancy, disk input and output, and network bandwidth.

[0067] This application conducts a comprehensive assessment and planning of the business system to be migrated, including analysis of system architecture, data volume, business processes, etc., to determine the performance monitoring indicators that need to be paid attention to in the database, middleware, and application server during the migration process, such as CPU utilization, memory usage, disk input and output, network bandwidth, concurrency, response time, etc., and uses these indicators as the basis for post-migration performance testing. During the entire information and innovation migration process before, during, and after the migration, the performance of the application system is monitored with indicators in multiple dimensions to ensure that the application system can operate normally after the migration is completed, and all performance indicators are normal to achieve the expected results.

[0068] In an optional embodiment of the present application, in step 200, the step of deploying a preset monitoring probe tool on the source system and the target system of the business system to be migrated includes:

[0069] Select corresponding monitoring probe tools for the database, middleware, and application server of the source system and target system of the business system to be migrated, so that all monitoring probe tools cover all links in the entire migration process. You can select appropriate monitoring probe tools from monitoring probe tools such as Java probes, Golang probes, Node.js probes, .NET probes, Python probes, etc., and deploy them on the database, middleware, and application server of the source system and target system of the business system to be migrated, respectively, to ensure that the monitoring tools can cover all links in the migration process, including databases, middleware, application servers, etc.

[0070] In an optional embodiment of the present application, in step 400, when the performance monitoring indicator exceeds a preset threshold range, an alarm notification is issued, an emergency response mechanism is established, the problem is quickly located and solved, and the interruption time during the migration process is reduced.

[0071] In an optional embodiment of the present application, the method further includes:

[0072] Test whether the functions of the migrated business system are running normally;

[0073] Test whether the performance of the migrated business system meets the preset business requirements, wherein the preset business requirements include stress testing and concurrency testing;

[0074] Based on the test results, the business system is performance tuned, system configuration is optimized, resource allocation is adjusted, code logic is improved, etc. to improve system performance.

[0075] In an optional embodiment of the present application, the method further includes:

[0076] Obtain performance monitoring indicators of the source system and the target system, and extract feature vectors of the preprocessed performance monitoring indicators;

[0077] Construct a performance monitoring indicator sensitivity scoring model to evaluate the sensitivity of performance monitoring indicators and classify them, and encrypt sensitive data of performance monitoring indicators based on the classification results;

[0078] The exchanged data is decrypted and stored as performance monitoring indicators, and a visual interface is built to display the performance monitoring indicators in real time.

[0079] In an optional embodiment of the present application, the construction of a performance monitoring indicator sensitivity scoring model to evaluate the sensitivity of performance monitoring indicators and classify them refers to collecting historical performance monitoring indicators and extracting historical feature vectors, calculating the mean of the historical feature vectors and setting them as the benchmark data vector;

[0080] Collect performance monitoring indicators in real time and extract real-time feature vectors. Use the K-means clustering analysis algorithm to cluster the real-time feature vectors, and select the center point of each cluster as the reference data vector.

[0081] Combining the RBF kernel function with the integral, the cumulative similarity A(x) between the benchmark data vector and the performance monitoring indicator feature vector is calculated. The formula is:

[0082]

[0083] Where x is the performance monitoring indicator feature vector, x0 is the benchmark data vector, and x i is the historical feature vector of the i-th performance monitoring indicator;

[0084] Perform logarithmic transformation B(x) on the accumulated similarity A, the formula is:

[0085] B(x)=log(1+A(x));

[0086] The hyperbolic tangent function is introduced to smooth the accumulated similarity of the reference feature vector to obtain the accumulated similarity C(x) after smoothing. The formula is:

[0087]

[0088] Where M is the number of reference eigenvectors, x j is the jth reference eigenvector;

[0089] A sensitivity scoring model is constructed to evaluate the sensitivity score S(x) of the performance monitoring indicator feature vector. The formula is:

[0090]

[0091] Collect the sensitivity scores of historical performance monitoring indicators and set the evaluation threshold. Compare the sensitivity score of the performance monitoring indicator feature vector with the evaluation threshold. If the sensitivity score of the performance monitoring indicator feature vector is greater than and equal to the evaluation threshold, it is determined to be sensitive data. If the sensitivity score of the performance monitoring indicator feature vector is less than the evaluation threshold, it is determined to be ordinary data.

[0092] In an optional embodiment of the present application, a feature vector of the preprocessed performance monitoring indicator is extracted by presetting an autoencoder network model.

[0093] In an optional embodiment of the present application, encrypting sensitive data based on the classification result of the performance monitoring indicator refers to randomly generating a key K using a random number generator;

[0094] Use exponential function and sine function to perform nonlinear transformation on sensitive data to obtain the nonlinear transformation result H(x′), the formula is:

[0095]

[0096] Where x′ is sensitive data;

[0097] The sensitive data is transformed nonlinearly using logarithmic function and smooth inverse tangent function to obtain the multi-level nonlinear transformation result E(x′), the formula is:

[0098] E(x′)=tan -1 (x′ 2 k+log(x′+k));

[0099] Construct the encryption formula:

[0100] S(x′)=H(x′)+E(x′);

[0101] Bring sensitive data into the encryption formula for encryption.

[0102] In an optional embodiment of the present application, the decryption of the exchanged data to store the performance monitoring indicator refers to receiving the transmitted encrypted data and the corresponding key K;

[0103] Use the decryption formula to decrypt the received data and obtain the decrypted sensitive data O(S). The formula is:

[0104]

[0105] The collected application system information and sensitive data generated by the analysis are stored in the database, the application system information and sensitive data generated by the analysis in the database are backed up in the cloud, and the backup data are regularly checked for integrity.

[0106] The probe-based full-process performance monitoring method for trusted innovation adaptation of this application can achieve comprehensive monitoring and accurate analysis of the entire trusted innovation system process by simplifying probe deployment and improving data analysis accuracy, helping operation and maintenance personnel to quickly locate and solve performance problems; by enhancing real-time performance and improving early warning accuracy, it can timely discover and warn of system performance problems, allowing operation and maintenance personnel to respond quickly and take measures to ensure the continuity and stability of business systems. By improving the level of intelligence, it can provide operation and maintenance personnel with more accurate and timely decision-making support, reduce the difficulty and cost of operation and maintenance, and improve operation and maintenance efficiency. By deeply optimizing and adapting the trusted innovation environment, it can provide more comprehensive and reliable technical support for the performance monitoring of trusted innovation systems, and promote the rapid development of the trusted innovation industry.

[0107] The whole process performance monitoring method of the information innovation adaptation based on the probe technology of this application is Figure 2 The application process in the business system and the full-process performance monitoring platform is as follows:

[0108] Step 1: Preparation before migration

[0109] 1. System evaluation and planning

[0110] Before migration, a comprehensive assessment of the business system is required, including analysis of system architecture, data volume, business processes, etc. The system architecture includes Figure 2 The first and second businesses in the project. According to the evaluation results, a detailed migration plan is formulated, including the time node, content and method of migration. At the same time, the performance indicators to be monitored are clearly defined, such as CPU usage, memory usage, disk input and output, network bandwidth and other key performance indicators.

[0111] 2. Monitoring probe preparation

[0112] Set up appropriate performance monitoring probes on the primary business, secondary business and application servers of the business system, such as Java probes, Golang probes, Node.js probes, .NET probes, Python probes, etc. These probe tools can cover all aspects of the migration process, including databases, middleware, application servers, etc.

[0113] Deploy monitoring probe tools on the source and target systems to ensure that performance data can be collected and transmitted in real time.

[0114] Step 2: Monitoring the migration process

[0115] 1. Real-time performance monitoring

[0116] Data collection: Use monitoring probe tools to collect real-time data on the performance of the source and target systems.

[0117] Data display: Key performance indicators such as CPU usage, memory usage, etc. are displayed in real time through the monitoring interface.

[0118] Anomaly detection: Set performance thresholds and automatically issue warning notifications when performance indicators exceed the thresholds.

[0119] Step 3: Post-migration verification and optimization

[0120] 1. Functional testing and performance testing

[0121] Functional testing: Conduct comprehensive functional testing on the migrated business system to ensure that all functions operate normally.

[0122] Performance testing: Perform performance testing to verify whether the performance of the business system meets business requirements. The testing content may include stress testing, concurrency testing, etc.

[0123] 2. Performance Tuning

[0124] Problem location: Locate performance bottlenecks based on test results and monitoring data.

[0125] Optimization measures: Optimize performance bottlenecks, such as adjusting system configuration, optimizing code logic, etc.

[0126] Continuous optimization: After the business system is put into use, continue to monitor and optimize performance to ensure stable operation of the system.

[0127] The probe technology-based full-process performance monitoring method for trusted innovation adaptation of this application comprehensively monitors all aspects of the entire trusted innovation migration process, including pre-migration preparation, migration process, post-migration verification and optimization, etc. At the same time, real-time collection and display of performance data are realized to timely discover and deal with potential performance problems. Comprehensive monitoring can ensure the transparency and controllability of the migration process, and real-time performance is the key to rapid response and problem solving. Probe technology is used to perform all-round performance monitoring and abnormal warning of the migration process, obtain the operating status and performance of the application before and after migration in real time, and generate alarm information through the alarm model, which is convenient for operation and maintenance personnel to perform fault diagnosis, performance optimization and decision-making, realize rapid fault analysis and disposal, and reduce operation and maintenance risks. Monitor and evaluate multi-dimensional performance indicators, such as CPU utilization, memory usage, disk I / O, network bandwidth, response time, etc., to fully understand the system performance status. Multi-dimensional performance indicators can more comprehensively reflect the system performance status, which helps to accurately identify performance bottlenecks and optimization directions.

[0128] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0129] See also Figure 3 An embodiment of the present application provides a full-process performance monitoring device 300 for ICT adaptation based on probe technology, including:

[0130] The determination module 310 is used to determine the migration time node, migration content, migration method and performance monitoring indicators according to the system architecture, data volume and business process of the business system to be migrated;

[0131] A deployment module 320, configured to deploy a preset monitoring probe tool on a source system and a target system of the business system to be migrated, wherein the preset monitoring probe tool is configured to collect and transmit performance monitoring indicators in real time;

[0132] The detection module 330 is used to detect whether the performance monitoring indicators of the source system and the target system collected by the preset monitoring probe tool are within the preset threshold range during the migration process of the business system to be migrated;

[0133] The alarm module 340 is used to issue an alarm notification when the performance monitoring indicator exceeds a preset threshold range.

[0134] The probe technology-based full-process performance monitoring device of the present application can obtain performance data in the migration process in real time, such as CPU usage, memory usage, network bandwidth, etc., through full-process performance monitoring, timely discover performance bottlenecks or potential problems, and give early warnings. This helps to quickly locate the cause of the problem, reduce troubleshooting time, and thus improve migration efficiency. Based on monitoring data, the migration process can be accurately optimized, such as adjusting resource allocation, optimizing system configuration, etc., to ensure that the system performance after migration meets business needs and improve the success rate of migration. Through performance monitoring, a more reasonable migration plan can be formulated, the migration steps can be optimized, and the downtime of key systems can be reduced, thereby ensuring business continuity. During the migration process, if an unexpected situation occurs that causes system performance to decline or fail, performance monitoring can quickly locate the problem and assist in rapid recovery, reducing business interruption time. Performance monitoring can collect various performance data during the migration process, combine historical data and business characteristics, conduct risk assessment, identify potential migration risk points, and formulate corresponding countermeasures. Performance monitoring can also be used as part of a security audit to record all operations and data changes during the migration process, providing a basis for subsequent security audits and compliance checks. After the migration is completed, performance monitoring can be used to continuously optimize the system's performance, ensuring that the system can maintain stable performance under high load, thereby improving user experience. After the business system is launched, performance monitoring can be used to monitor the availability of the business system in real time, ensuring the stable operation of the business system and further improving user experience.

[0135] For the specific limitations of the above-mentioned device 300, please refer to the limitations of the full-process performance monitoring method of the trusted innovation adaptation based on probe technology in the above text, which will not be repeated here. Each module in the above-mentioned device 300 can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0136] In one embodiment, a computer device is provided, the internal structure diagram of which can be as follows: Figure 4As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for monitoring the performance of the entire process of the trusted innovation adaptation based on probe technology as described above is implemented. It includes: a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, any step in the method for monitoring the performance of the entire process of the trusted innovation adaptation based on probe technology as described above is implemented.

[0137] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, any step in the above-mentioned method for monitoring the full-process performance of the trusted innovation adaptation based on probe technology can be implemented.

[0138] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0139] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0140] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0141] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0142] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0143] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for monitoring the performance of the entire process of information innovation adaptation based on probe technology, characterized in that: include: Determine the migration time node, migration content, migration method and performance monitoring indicators based on the system architecture, data volume and business process of the business system to be migrated; Deploy a preset monitoring probe tool on the source system and the target system of the service system to be migrated, wherein the preset monitoring probe tool is used to collect and transmit performance monitoring indicators in real time; During the migration of the business system to be migrated, detect whether the performance monitoring indicators of the source system and the target system collected by the preset monitoring probe tool are within the preset threshold range; When the performance monitoring indicator exceeds the preset threshold range, an alarm notification will be issued.

2. The method according to claim 1, characterized in that Determining the migration time node, migration content, migration method and performance monitoring indicators according to the system architecture, data volume and business process of the business system to be migrated includes: Analyze the system architecture of the business system to be migrated and determine the migration content of the business system to be migrated; Migrate the contents of the business systems to be migrated in batches according to the data volume of the business systems to be migrated, and determine the migration time node for each batch; Determine the migration method for each batch of migration content based on the business process of the business system to be migrated; Determine the performance monitoring indicators required for the system's database, middleware, and application server during the entire migration process based on the migration time node, migration content, and migration method of the business system to be migrated.

3. The method according to claim 2, characterized in that The performance monitoring indicator includes at least one of CPU usage, memory usage, disk input and output, and network bandwidth.

4. The method according to claim 2, characterized in that: The step of deploying a preset monitoring probe tool on the source system and the target system of the business system to be migrated includes: Select corresponding monitoring probe tools for the source system and the database, middleware, and application server of the target system of the business system to be migrated, so that all monitoring probe tools cover all aspects of the entire migration process.

5. The method according to claim 1, characterized in that The method further comprises: Test whether the functions of the migrated business system are running normally; Test whether the performance of the migrated business system meets the preset business requirements, where the preset business requirements include stress testing and concurrency testing.

6. The method according to claim 1, characterized in that The method further comprises: Obtain performance monitoring indicators of the source system and the target system, and extract feature vectors of the preprocessed performance monitoring indicators; Construct a performance monitoring indicator sensitivity scoring model to evaluate the sensitivity of performance monitoring indicators and classify them, and encrypt sensitive data of performance monitoring indicators based on the classification results; The exchanged data is decrypted and stored as performance monitoring indicators, and a visual interface is built to display the performance monitoring indicators in real time.

7. The method according to claim 6, characterized in that The construction of the performance monitoring indicator sensitivity scoring model to evaluate the sensitivity of the performance monitoring indicator and classify it refers to collecting historical performance monitoring indicators and extracting historical feature vectors, calculating the mean of the historical feature vectors and setting them as the benchmark data vector; Collect performance monitoring indicators in real time and extract real-time feature vectors. Use the K-means clustering analysis algorithm to cluster the real-time feature vectors, and select the center point of each cluster as the reference data vector. Combining the RBF kernel function with the integral, the cumulative similarity A(x) between the benchmark data vector and the performance monitoring indicator feature vector is calculated. The formula is: Where x is the performance monitoring indicator feature vector, x0 is the benchmark data vector, and x i is the historical feature vector of the i-th performance monitoring indicator; Perform logarithmic transformation B(x) on the accumulated similarity A, the formula is: B(x)=log(1+A(x)); The hyperbolic tangent function is introduced to smooth the accumulated similarity of the reference feature vector to obtain the accumulated similarity C(x) after smoothing. The formula is: Where M is the number of reference eigenvectors, x j is the jth reference eigenvector; A sensitivity scoring model is constructed to evaluate the sensitivity score S(x) of the performance monitoring indicator feature vector. The formula is: Collect the sensitivity scores of historical performance monitoring indicators and set the evaluation threshold. Compare the sensitivity score of the performance monitoring indicator feature vector with the evaluation threshold. If the sensitivity score of the performance monitoring indicator feature vector is greater than and equal to the evaluation threshold, it is determined to be sensitive data. If the sensitivity score of the performance monitoring indicator feature vector is less than the evaluation threshold, it is determined to be ordinary data.

8. A full-process performance monitoring device for ICT adaptation based on probe technology, characterized in that: include: The determination module is used to determine the migration time node, migration content, migration method and performance monitoring indicators according to the system architecture, data volume and business process of the business system to be migrated; A deployment module, used to deploy a preset monitoring probe tool on a source system and a target system of the business system to be migrated, wherein the preset monitoring probe tool is used to collect and transmit performance monitoring indicators in real time; The detection module is used to detect whether the performance monitoring indicators of the source system and the target system collected by the preset monitoring probe tool are within the preset threshold range during the migration process of the business system to be migrated; The alarm module is used to issue an alarm notification when the performance monitoring indicator exceeds the preset threshold range.

9. A computer device comprising: A memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the steps of the full-process performance monitoring method of the trusted innovation adaptation based on probe technology as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the full-process performance monitoring method of the trusted innovation adaptation based on probe technology as described in any one of claims 1 to 7 are implemented.

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