Digital base design method and system and electronic equipment

Abstract

The invention relates to the technical field of electronic digital data processing, in particular to a digital base design method and system and electronic device.The method comprises the steps that real-time monitoring data, including infrastructure operation and maintenance data, network environment operation and maintenance data and application performance operation and maintenance data, of operation and maintenance of a digital base are collected; analyzing the real-time monitoring data to obtain an infrastructure health index, a network environment adaptability index and a performance effectiveness evaluation index of the digital base; and performing comprehensive analysis to obtain a comprehensive efficiency index of the digital base, evaluating the digital base, obtaining an evaluation result, and performing feedback processing. According to the digital base design method and system and the electronic equipment, a comprehensive digital base health condition quantitative index is provided, potential risk points can be recognized, opportunities can be optimized, downtime can be shortened, service continuity can be improved, and the performance, stability and safety of the digital base can be guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to a digital base design method, system and electronic equipment. Background Art

[0002] With the rapid advancement of technology, especially the development of the Internet, cloud computing and big data, the digital economy has become the core driving force of economic growth. Data is regarded as a valuable resource in the new era, and its collection, processing and analysis capabilities have become the key to corporate competitive advantage. The traditional business operation model is gradually changing to a more agile and flexible model, and the digital base has emerged.

[0003] For example, the invention patent with announcement number: CN116610516B announces an IoT programming and operation base system and method based on device digital twins, which belongs to the field of IoT application programming and development technology. The method includes: according to the communication protocol type information in the registration information imported when the IoT device is connected to the IoT programming and operation base system, the container image matching the communication protocol is started in the IoT programming and operation base system to create a container running state instance corresponding to the IoT device, thereby generating a device digital twin with the ability to interact with the IoT device in a twin manner; the application programming interface of the device digital twin is opened to the user to allow the user to program the device digital twin by calling the application programming interface, thereby realizing data collection and control operations on the IoT device.

[0004] For example, the invention patent with announcement number: CN115935441B discloses a method for implementing a three-member architecture model of a digital base subdomain in a multi-tenant mode. The method includes: step 1, initializing the three-member data of the root tenant and the three-member data of the subdomains of several sub-tenants, and enabling the three-member subdomains; step 2, creating and configuring the root tenant data, and configuring the sub-tenant data; step 3, configuring the subdomain department data and subdomain personnel data in the respective subdomains of the several sub-tenants, and performing subdomain personnel authorization operations; based on the above method, the three-member architecture model can be implemented in a multi-tenant mode, thereby ensuring the security of the management of the root tenant and the sub-tenant in isolation.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, it was found that the above-mentioned technology has at least the following technical problems: the current digital base provides a unified data management framework and powerful data processing and analysis capabilities, and the three-member architecture model of the digital base subdomain in the multi-tenant mode improves security to a certain extent, but the security management of the digital base system when processing large-scale, high-concurrency data still has certain limitations. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a digital base design method, system and electronic device, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides a digital base design method, including: collecting real-time monitoring data of the operation and maintenance of the digital base, and the real-time monitoring data includes infrastructure operation and maintenance data, network environment operation and maintenance data, and application performance operation and maintenance data.

[0008] The infrastructure operation and maintenance data is analyzed to obtain the infrastructure health index of the digital base, the network environment operation and maintenance data is analyzed to obtain the network environment adaptability index of the digital base, and the application performance operation and maintenance data is analyzed to obtain the performance efficiency evaluation index of the digital base.

[0009] Based on the infrastructure health index, network environment adaptability index and performance efficiency evaluation index of the digital base, a comprehensive analysis is conducted to obtain the comprehensive efficiency index of the digital base. Based on the comprehensive efficiency index of the digital base, the digital base is evaluated to obtain the evaluation results and conduct feedback processing.

[0010] As a further method, the infrastructure operation and maintenance data is analyzed to obtain the infrastructure health index of the digital base. The specific analysis process is: deploy several monitoring cycles, collect the infrastructure operation and maintenance data of the digital base, the infrastructure operation and maintenance data include the network throughput, number of error logs and data backup completion rate of each monitoring cycle, extract the critical network throughput, critical error log number and critical data backup completion rate from the digital base database, and comprehensively analyze to obtain the infrastructure health index of the digital base.

[0011] As a further method, the network environment operation and maintenance data is analyzed to obtain the network environment adaptability index of the digital base. The specific analysis process is: the network environment operation and maintenance data, including the average round-trip time, packet loss rate and bandwidth utilization of each monitoring period, extracts the critical average round-trip time, critical packet loss rate and reference standard bandwidth utilization from the digital base database, matches the reference standard bandwidth utilization to obtain the allowable deviation bandwidth utilization, and comprehensively analyzes to obtain the network environment adaptability index of the digital base.

[0012] As a further method, the application performance operation and maintenance data is analyzed to obtain the performance efficiency evaluation index of the digital base. The specific analysis process is: the application performance operation and maintenance data, including the maximum number of concurrent users, average application response time and resource utilization in each monitoring period, extracts the critical maximum number of concurrent users, critical average application response time, reference standard resource utilization and corresponding allowable deviation resource utilization from the digital base database, and comprehensively analyzes to obtain the performance efficiency evaluation index of the digital base.

[0013] As a further method, the comprehensive analysis obtains the comprehensive performance index of the digital base. The specific analysis process is: based on the infrastructure health index, network environment adaptability index and performance performance evaluation index of the digital base, a comprehensive analysis is performed to obtain the comprehensive performance index of the digital base. The comprehensive performance index of the digital base is used to quantitatively evaluate the performance of the digital base.

[0014] As a further method, the digital base is evaluated according to the comprehensive performance index of the digital base, and the evaluation results are obtained and feedback processing is performed. The specific evaluation process is: extracting the digital base comprehensive performance index threshold from the digital base database, comparing the digital base comprehensive performance index with the digital base comprehensive performance index threshold, if the digital base comprehensive performance index is higher than or equal to the digital base comprehensive performance index threshold, then the comprehensive performance of the digital base is evaluated as qualified; if the digital base comprehensive performance index is lower than the digital base comprehensive performance index threshold, then the comprehensive performance of the digital base is evaluated as unqualified, and feedback processing is performed on the digital base according to the evaluation result.

[0015] As a further method, the performance efficiency evaluation index of the digital base is specifically expressed as:

[0016]

[0017] Where τN represents the performance evaluation index of the digital base, n represents the number of each monitoring cycle, n = 1, 2, 3, ..., m, m represents the total number of monitoring cycles, e represents a natural constant, and Z n Indicates the resource utilization rate of the nth monitoring cycle, F n Indicates the maximum number of concurrent users in the nth monitoring cycle, Y n represents the average application response time of the nth monitoring cycle, Z 0 represents the reference standard resource utilization, ΔZ represents the allowable deviation resource utilization, Indicates the critical maximum number of concurrent users, represents the critical average application response time, σ1 represents the performance efficiency impact factor corresponding to the set resource utilization, σ2 represents the performance efficiency impact factor corresponding to the set maximum number of concurrent users, and σ3 represents the performance efficiency impact factor corresponding to the set average application response time.

[0018] As a further method, the digital base comprehensive performance index, the specific numerical expression is:

[0019]

[0020] In the formula, represents the comprehensive performance index of the digital base, τX represents the infrastructure health index of the digital base, τH represents the network environment adaptability index of the digital base, τN represents the performance efficiency evaluation index of the digital base, ω1 represents the comprehensive performance impact weight factor corresponding to the preset infrastructure health index of the digital base, ω2 represents the comprehensive performance impact weight factor corresponding to the preset network environment adaptability index of the digital base, and ω3 represents the comprehensive performance impact weight factor corresponding to the preset performance efficiency evaluation index of the digital base.

[0021] The second aspect of the present invention provides a digital base design system, including: a data acquisition module for collecting real-time monitoring data of digital base operation and maintenance, the real-time monitoring data including infrastructure operation and maintenance data, network environment operation and maintenance data and application performance operation and maintenance data.

[0022] The data analysis module is used to analyze the infrastructure operation and maintenance data to obtain the infrastructure health index of the digital base, analyze the network environment operation and maintenance data to obtain the network environment adaptability index of the digital base, and analyze the application performance operation and maintenance data to obtain the performance efficiency evaluation index of the digital base.

[0023] The comprehensive analysis and evaluation module is used to obtain the comprehensive efficiency index of the digital base based on the infrastructure health index, network environment adaptability index and performance efficiency evaluation index of the digital base through comprehensive analysis, evaluate the digital base based on the comprehensive efficiency index of the digital base, obtain the evaluation results and perform feedback processing.

[0024] The digital base database is used to store data related to the operation and maintenance of the digital base.

[0025] A third aspect of the present invention provides a digital base design electronic device, comprising: a receiver, a processor, a server, a memory and a display;

[0026] The receiver is used to receive relevant data on the operation and maintenance of the digital base in real time.

[0027] The memory is used to connect to the digital base database and store data related to the operation and maintenance of the digital base.

[0028] The processor is used to obtain data from the receiver and the memory, and evaluate the comprehensive performance of the digital base.

[0029] The display is used to receive and display the evaluation result of the comprehensive performance of the digital base of the processor.

[0030] The server is used to adjust basic parameters related to the digital base according to the evaluation results displayed on the display.

[0031] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0032] (1) The present invention provides a digital base design method, system and electronic equipment, and obtains a comprehensive performance index of the digital base through comprehensive analysis, thereby providing a comprehensive quantitative indicator of the health status of the digital base, which can help identify potential risk points and optimization opportunities, identify and solve possible problems in advance, reduce downtime, improve business continuity, and help ensure the performance, stability and security of the digital base, thereby promoting digital transformation.

[0033] (2) By analyzing the infrastructure health of the digital base, the present invention helps to identify potential system failures or performance degradation signs at an early stage, thereby improving the stability of the system. It can also guide resource allocation and system optimization, and help to promptly discover security vulnerabilities and prevent data leakage and other security incidents.

[0034] (3) The present invention provides a basis for system optimization by analyzing the environmental adaptability and performance of the digital base, which is conducive to maintaining the continuity of key services, reducing the risk of business interruption, improving overall business continuity and reliability, and helping to dynamically adjust resource allocation according to network conditions to avoid resource waste, thereby reducing operating costs and improving resource utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0036] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0037] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0038] Figure 3It is a schematic diagram of the functional relationship between the infrastructure health index and the comprehensive performance index of the digital base according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0040] Reference Figure 1 As shown, the first aspect of the present invention provides a digital base design method, including: collecting real-time monitoring data of the operation and maintenance of the digital base, the real-time monitoring data including infrastructure operation and maintenance data, network environment operation and maintenance data and application performance operation and maintenance data.

[0041] Specifically, the real-time monitoring data of the operation and maintenance of the digital base can be obtained through agent-based monitoring. Agent is a software installed on the target host, which can collect the operating status information of the system and application and send the data to the monitoring platform. The information that the agent can collect includes but is not limited to CPU usage, memory usage, disk I / O, network traffic, process status, log files, etc. It is also possible to collect and analyze the log files of the system and application to gain an in-depth understanding of the details of the system operation. Log monitoring can capture events at the error, warning, information and debugging levels to help quickly locate problems. Modern log management systems such as Elasticsearch, Logstash, Kibana, Splunk, etc. can achieve real-time log analysis and visualization. Network monitoring tools such as Wi reshark, Nagi os, and Zabbix can also be used to monitor the status of network devices, including network bandwidth usage, latency, packet loss rate, etc., as well as network traffic analysis to help identify network bottlenecks and abnormal behaviors. APM tools such as NewRe lic, Dynatrace, and AppDynamics can also be used to focus on monitoring the performance of applications and provide code-level performance analysis, including transaction tracking, response time, error rate and other data.

[0042] The infrastructure operation and maintenance data is analyzed to obtain the infrastructure health index of the digital base, the network environment operation and maintenance data is analyzed to obtain the network environment adaptability index of the digital base, and the application performance operation and maintenance data is analyzed to obtain the performance efficiency evaluation index of the digital base.

[0043] Specifically, the infrastructure operation and maintenance data is analyzed to obtain the infrastructure health index of the digital base. The specific analysis process is: deploy several monitoring cycles, collect the infrastructure operation and maintenance data of the digital base, the infrastructure operation and maintenance data includes the network throughput, number of error logs and data backup completion rate of each monitoring cycle, extract the critical network throughput, critical number of error logs and critical data backup completion rate from the digital base database, and comprehensively analyze to obtain the infrastructure health index of the digital base.

[0044] It should be understood that the infrastructure health index of the digital base is a quantitative assessment data obtained through a comprehensive analysis of the network throughput, number of error logs and data backup completion rate of each monitoring cycle. It is used to quantitatively assess the health of the digital base infrastructure and provide a basis for evaluating the effectiveness of the digital base.

[0045] In a specific embodiment, the specific numerical expression of the infrastructure health index of the digital base is:

[0046]

[0047] Where τX represents the infrastructure health index of the digital base, n represents the number of each monitoring cycle, n = 1, 2, 3, ..., m, m represents the total number of monitoring cycles, W n represents the network throughput of the nth monitoring cycle, R n Indicates the number of error logs in the nth monitoring cycle, S n Indicates the data backup completion rate of the nth monitoring cycle, represents the critical network throughput, Indicates the number of critical error logs. represents the critical data backup completion rate, ρ1 represents the infrastructure health impact factor corresponding to the preset network throughput, ρ2 represents the infrastructure health impact factor corresponding to the preset error log, and ρ3 represents the infrastructure health impact factor corresponding to the preset data backup completion rate.

[0048] It should be understood that, as shown in the above formula, when the other values ​​remain unchanged, the greater the network throughput, the greater the infrastructure health index of the digital base, and the two are positively correlated. When the number of error logs increases, the smaller the infrastructure health index of the digital base, and the two are negatively correlated. When the data backup completion rate is higher, the greater the infrastructure health index of the digital base, and the two are also positively correlated.

[0049] It needs to be explained that the value range of the infrastructure health impact factor corresponding to the network throughput, the infrastructure health impact factor corresponding to the error log and the infrastructure health impact factor corresponding to the data backup completion rate is between 0 and 1. The infrastructure health impact factor corresponding to the network throughput, the infrastructure health impact factor corresponding to the error log and the infrastructure health impact factor corresponding to the data backup completion rate are established by collecting the relationship between the network throughput, error log and data backup completion rate and the infrastructure health index in the historical data, and a mapping set of network throughput, error log and data backup completion rate and their corresponding infrastructure health impact factors is established. The real-time network throughput, error log and data backup completion rate are input, and the infrastructure health impact factor corresponding to the network throughput, the infrastructure health impact factor corresponding to the error log and the infrastructure health impact factor corresponding to the data backup completion rate are obtained from the mapping set. It should be understood that all the impact factors in this embodiment are extracted from the digital base database.

[0050] It should be explained that network throughput refers to the data transmission speed of the network interface, usually measured in bits per second. Network throughput reflects the health and performance of the network infrastructure. High throughput usually means that network devices such as switches, routers, and network links are in good condition without obvious bottlenecks or failures. Low throughput or frequent packet loss may indicate problems with network devices, such as overload, hardware failure, or improper configuration, which directly affect the overall health of the infrastructure. Data backup completion rate is an important part of disaster recovery and backup parameters, which reflects data protection and disaster recovery capabilities. A high completion rate means that the backup system is operating normally and data security is guaranteed; conversely, a low completion rate may indicate defects in the backup strategy or backup system, such as insufficient backup windows, backup media failure, or backup software errors. Error logs provide insights into the health of the digital base and are a key source of information for troubleshooting, performance tuning, security protection, and maintenance plans.

[0051] It should be explained that since the amount of relevant data processed by the digital base is too large, there is no time when the error log is 0.

[0052] It should be explained that in this embodiment, by analyzing the infrastructure health index of the digital base, potential system failures or performance degradation signs can be identified early, and unplanned downtime can be reduced by setting up an early warning mechanism to improve system stability. It can also help identify bottlenecks, guide resource allocation and system optimization. The security indicators included in the infrastructure health index of the digital base can help timely discover security vulnerabilities, enhance defense mechanisms, and prevent data leaks and other security incidents.

[0053] Furthermore, the network environment operation and maintenance data is analyzed to obtain the network environment adaptability index of the digital base. The specific analysis process is as follows: the network environment operation and maintenance data, including the average round-trip time, packet loss rate and bandwidth utilization of each monitoring period, extracts the critical average round-trip time, critical packet loss rate and reference standard bandwidth utilization from the digital base database, and obtains the allowable deviation bandwidth utilization according to the reference standard bandwidth utilization matching, and obtains the network environment adaptability index of the digital base through comprehensive analysis.

[0054] It should be understood that the network environment adaptability index of the digital base is a quantitative evaluation data obtained through a comprehensive analysis of the average round-trip time, packet loss rate and bandwidth utilization of each monitoring cycle. It is used to quantitatively evaluate the adaptability of the digital base to the corresponding network environment and provide a basis for evaluating the effectiveness of the digital base.

[0055] In a specific embodiment, the specific numerical expression of the network environment adaptability index of the digital base is:

[0056]

[0057] Where, τH represents the network environment adaptability index of the digital base, P n represents the average round trip time of the nth monitoring cycle, D n Indicates the packet loss rate of the nth monitoring cycle, L n Indicates the bandwidth utilization of the nth monitoring cycle, represents the critical average round trip time, represents the critical packet loss rate, L 0 represents the reference standard bandwidth utilization, ΔL represents the allowable deviation bandwidth utilization, δ1 represents the network environment adaptability impact factor corresponding to the preset average round-trip time, δ2 represents the network environment adaptability impact factor corresponding to the preset packet loss rate, and δ3 represents the network environment adaptability impact factor corresponding to the preset bandwidth utilization.

[0058] It should be understood that the network environment adaptability index of the digital base in this embodiment is jointly determined by the average round-trip time, packet loss rate and bandwidth utilization. When the average round-trip time is smaller, the packet loss rate is smaller, and the bandwidth utilization is closer to the reference standard bandwidth utilization, the infrastructure health index of the digital base will be greater.

[0059] It needs to be explained that the value range of the network environment adaptability influencing factor corresponding to the average round-trip time, the network environment adaptability influencing factor corresponding to the packet loss rate, and the network environment adaptability influencing factor corresponding to the bandwidth utilization is between 0 and 1. The network environment adaptability influencing factor corresponding to the average round-trip time, the network environment adaptability influencing factor corresponding to the packet loss rate, and the network environment adaptability influencing factor corresponding to the bandwidth utilization are established by collecting the relationship between the average round-trip time, packet loss rate, bandwidth utilization and the network environment adaptability index in the historical data, and a mapping set of the average round-trip time, packet loss rate, bandwidth utilization and their corresponding network environment adaptability influencing factors is established. The real-time average round-trip time, packet loss rate and bandwidth utilization are input, and the network environment adaptability influencing factor corresponding to the average round-trip time, the network environment adaptability influencing factor corresponding to the packet loss rate, and the network environment adaptability influencing factor corresponding to the bandwidth utilization are obtained from the mapping set. It should be understood that all the influencing factors in this embodiment are extracted from the digital base database.

[0060] It needs to be explained that the average round-trip time is the time between sending a data packet and receiving a response in a network test. It is an important indicator of network latency. A lower average round-trip time means that the network latency is smaller and the data packets are able to be transmitted faster in the network. Therefore, a low average round-trip time is usually associated with higher network adaptability. A higher average round-trip time may indicate network congestion or problems with long-distance transmission. The packet loss rate is the proportion of sent data packets that fail to successfully reach the destination. It can be measured by sending a group of data packets and counting the number of unreceived responses. A low packet loss rate means that the network is highly reliable and data packets are less likely to be lost during transmission. A higher packet loss rate usually means poor network quality, which may be caused by network congestion, hardware failure, or other network problems. Bandwidth utilization is the ratio of bandwidth actually used by the network to the total available bandwidth. Bandwidth utilization indicates the use of network bandwidth. If the utilization is close to 100%, the network may begin to experience congestion, thereby increasing latency and packet loss. Ideally, the utilization should be maintained at a reasonable level so that even during peak network traffic hours, the network can maintain a certain margin to cope with sudden traffic demands.

[0061] It should be understood that in this embodiment, the resilience of the digital base in the face of network fluctuations, failures or attacks is reflected by analyzing the network environment adaptability index. A highly adaptable digital base can maintain the continuity of key services in these situations, reduce the risk of business interruption, and thus improve overall business continuity and reliability. Good network environment adaptability means that the digital base can maintain consistent performance levels and response times under different network conditions, and can improve user satisfaction while ensuring service quality. A highly adaptable digital base can dynamically adjust resource allocation according to network conditions to avoid resource waste, while ensuring that necessary services can still be provided when resources are limited. This helps to reduce operating costs and improve resource utilization efficiency. The network environment adaptability index also reflects the scalability of the digital base in different scales and scenarios. Whether it is a small enterprise or a large-scale deployment, or a leap from a local network to a wide area network, a highly adaptable base can be flexibly adjusted to meet diverse network needs.

[0062] Furthermore, the application performance operation and maintenance data is analyzed to obtain the performance efficiency evaluation index of the digital base. The specific analysis process is as follows: the application performance operation and maintenance data, including the maximum number of concurrent users, average application response time and resource utilization in each monitoring period, extracts the critical maximum number of concurrent users, critical average application response time, reference standard resource utilization and corresponding allowable deviation resource utilization from the digital base database, and comprehensively analyzes to obtain the performance efficiency evaluation index of the digital base.

[0063] It should be understood that the performance effectiveness evaluation index of the digital base is a quantitative evaluation data obtained through a comprehensive analysis of the maximum number of concurrent users, average application response time and resource utilization in each monitoring cycle. It is used to quantitatively evaluate the health of the digital base infrastructure and provide a basis for evaluating the effectiveness of the digital base.

[0064] In a specific embodiment, the specific numerical expression of the performance effectiveness evaluation index of the digital base is:

[0065]

[0066] In the formula, τN represents the performance evaluation index of the digital base, e represents the natural constant, and Z n Indicates the resource utilization rate of the nth monitoring cycle, F n Indicates the maximum number of concurrent users in the nth monitoring cycle, Y n represents the average application response time of the nth monitoring cycle, Z 0 represents the reference standard resource utilization, ΔZ represents the allowable deviation resource utilization, Indicates the critical maximum number of concurrent users, represents the critical average application response time, σ1 represents the performance efficiency impact factor corresponding to the set resource utilization, σ2 represents the performance efficiency impact factor corresponding to the set maximum number of concurrent users, and σ3 represents the performance efficiency impact factor corresponding to the set average application response time.

[0067] Table 1 Example of performance evaluation index data of digital base

[0068]

[0069] As shown in Table 1, in a specific embodiment, the reference standard resource utilization is set to 90%, the allowable deviation resource utilization is set to 1%, the critical maximum number of concurrent users is set to 1000, the critical average application response time is set to 10s, the performance efficiency impact factor corresponding to the resource utilization is set to 0.5, the performance efficiency impact factor corresponding to the maximum number of concurrent users is set to 0.3, and the performance efficiency impact factor corresponding to the average application response time is set to 0.2. For the sake of ease of calculation, it is assumed that there are 5 monitoring cycles in total, and the values ​​of the performance efficiency evaluation index of the digital base in the 5 monitoring cycles are the same.

[0070] It should be understood that the performance efficiency evaluation index of the digital base in this embodiment is jointly determined by resource utilization, the maximum number of concurrent users and the average application response time, and can be comprehensively considered. When the difference between the resource utilization and the reference standard resource utilization is smaller, the average application response time is shorter, and the maximum number of concurrent users is smaller, the performance efficiency evaluation index of the digital base is larger, indicating that the performance efficiency of the digital base is better.

[0071] It needs to be explained that the performance efficiency impact factor corresponding to resource utilization, the performance efficiency impact factor corresponding to the maximum number of concurrent users, and the performance efficiency impact factor corresponding to the average application response time have a value range of between 0 and 1. The performance efficiency impact factor corresponding to resource utilization, the performance efficiency impact factor corresponding to the maximum number of concurrent users, and the performance efficiency impact factor corresponding to the average application response time are established by collecting the relationship between resource utilization, the maximum number of concurrent users, the average application response time and the performance efficiency evaluation index in the historical data, and establishing a mapping set of resource utilization, the maximum number of concurrent users, the average application response time and their corresponding performance efficiency impact factors. The real-time resource utilization, the maximum number of concurrent users, and the average application response time are input, and the performance efficiency impact factor corresponding to the resource utilization, the performance efficiency impact factor corresponding to the maximum number of concurrent users, and the performance efficiency impact factor corresponding to the average application response time are obtained from the mapping set. It should be understood that all the impact factors in this embodiment are extracted from the digital base database.

[0072] It should be explained that resource utilization is a simple accumulation of CPU utilization, memory utilization, and disk I / O utilization. Ideally, resource utilization should be maintained at an optimal level, neither too high nor too low. Too high utilization, such as close to 100%, may cause performance bottlenecks, affecting the average application response time and the maximum number of concurrent users. Too low utilization means resource waste, which may indicate the need to reconfigure or optimize resource allocation. Therefore, a reasonable range of resource utilization helps to improve the overall performance efficiency evaluation index of the digital base. The average application response time is a measure of the time required for an application to process a request, usually in milliseconds. The average application response time is an important indicator for measuring system performance, which directly affects user experience and business efficiency. A shorter response time usually means a higher performance efficiency evaluation index of the digital base. If the response time is too long, it may indicate resource bottlenecks, network delays, or other performance issues that reduce the performance efficiency evaluation index of the digital base. Maximum number of concurrent users and performance efficiency evaluation index of the digital base The maximum number of concurrent users reflects the number of users that the system can serve simultaneously. A higher maximum number of concurrent users means that the system has better scalability and elasticity, which is usually a sign of a high digital base performance evaluation index. However, if the system begins to experience performance degradation when it reaches a certain number of users, it means that it has limitations in scalability and resource management, which will limit the overall digital base performance evaluation index.

[0073] It should be understood that the algorithm of this embodiment combines resource utilization, the maximum number of concurrent users and the average application response time, and comprehensively analyzes to obtain the performance efficiency evaluation index of the digital base, which includes multiple parameters, and each parameter has a connection. When the number of concurrent users is low, the resource utilization is relatively low. At this time, as the number of concurrent users increases, the resource utilization will gradually increase, because more user requests require more system resources to process. As the number of concurrent users increases, the system resource utilization continues to rise until it reaches a point at which the resource utilization and throughput are optimally balanced. This point is called the "optimal number of concurrent users", at which the system can process requests with the highest efficiency, and the response time remains within an acceptable range. Continue to increase the number of concurrent users, when the resource utilization approaches 100% or exceeds a certain threshold, the system begins to enter a state of resource saturation. At this time, although the resource utilization is high, the increase in user requests no longer brings a significant increase in throughput, but instead leads to a significant increase in response time, because the system resources are not enough to quickly process all requests. At this point, the system reaches the "maximum number of concurrent users". However, if the number of concurrent users increases further and exceeds the maximum number of concurrent users, resource utilization may still be close to the peak, but the system will begin to experience serious performance problems, such as a sharp increase in response time, a decrease in throughput, and even possible service crashes or denial of service. There is a complex balance between resource utilization and the maximum number of concurrent users. In order to maintain good system performance, it is necessary to find a suitable balance between resource utilization and the number of concurrent users to ensure that good response time and throughput can be maintained even under high load.

[0074] It should be understood that in this embodiment, by monitoring CPU utilization, memory usage, I / O throughput, etc., the performance bottlenecks in the system can be accurately identified. Evaluate the efficiency of resource use, such as whether the CPU and memory of the virtual machine are fully utilized to avoid resource waste. By analyzing the performance efficiency evaluation index of the digital base, resource allocation can be dynamically adjusted to ensure sufficient computing and storage capacity during peak hours. At the same time, potential failures can be predicted, preventive measures can be taken, and service interruptions can be reduced. By analyzing the application response time, it is helpful to ensure that user requests are processed in a timely manner and improve user satisfaction.

[0075] Based on the infrastructure health index, network environment adaptability index and performance efficiency evaluation index of the digital base, a comprehensive analysis is conducted to obtain the comprehensive efficiency index of the digital base. Based on the comprehensive efficiency index of the digital base, the digital base is evaluated to obtain the evaluation results and conduct feedback processing.

[0076] Specifically, a comprehensive analysis is performed to obtain a comprehensive performance index of the digital base. The specific analysis process is as follows: based on the infrastructure health index, network environment adaptability index and performance performance evaluation index of the digital base, a comprehensive analysis is performed to obtain the comprehensive performance index of the digital base. The comprehensive performance index of the digital base is used to quantitatively evaluate the performance of the digital base.

[0077] In a specific embodiment, the specific numerical expression of the digital base comprehensive performance index is:

[0078]

[0079] In the formula, represents the comprehensive performance index of the digital base, τX represents the infrastructure health index of the digital base, τH represents the network environment adaptability index of the digital base, τN represents the performance efficiency evaluation index of the digital base, ω1 represents the comprehensive performance impact weight factor corresponding to the preset infrastructure health index of the digital base, ω2 represents the comprehensive performance impact weight factor corresponding to the preset network environment adaptability index of the digital base, and ω3 represents the comprehensive performance impact weight factor corresponding to the preset performance efficiency evaluation index of the digital base.

[0080] It should be explained that if Figure 3 As shown, the network environment adaptability index of the digital base is set to 0.6, the comprehensive performance impact weight factor corresponding to the infrastructure health index of the digital base is set to 0.5, the comprehensive performance impact weight factor corresponding to the network environment adaptability index of the digital base is set to 0.4, and the comprehensive performance impact weight factor corresponding to the performance efficiency evaluation index of the digital base is set to 0.3. Curve a represents the relationship between the infrastructure health index and the comprehensive performance index of the digital base when the performance efficiency evaluation index of the digital base is 0.042. Curve b represents the relationship between the infrastructure health index and the comprehensive performance index of the digital base when the performance efficiency evaluation index of the digital base is 0.125. Curve c represents the relationship between the infrastructure health index and the comprehensive performance index of the digital base when the performance efficiency evaluation index of the digital base is 0.315. Figure 3 It can be obtained that when the values ​​of other parameters remain unchanged, the larger the performance efficiency evaluation index of the digital base, the larger the comprehensive efficiency index of the digital base, and the two are positively correlated.

[0081] It should be explained that the comprehensive efficiency impact weight factor corresponding to the infrastructure health index of the digital base, the comprehensive efficiency impact weight factor corresponding to the network environment adaptability index of the digital base, and the comprehensive efficiency impact weight factor corresponding to the performance efficiency evaluation index of the digital base range from 0 to 1. The comprehensive efficiency impact weight factor corresponding to the infrastructure health index of the digital base, the comprehensive efficiency impact weight factor corresponding to the network environment adaptability index of the digital base, and the comprehensive efficiency impact weight factor corresponding to the performance efficiency evaluation index of the digital base are obtained by comparing the infrastructure health index, network environment adaptability index, and performance efficiency evaluation index of the digital base collected in the historical data with the digital base. The relationship between the comprehensive performance index of the digital base is established, and a mapping set of the infrastructure health index, network environment adaptability index and performance performance evaluation index of the digital base and their corresponding comprehensive performance influencing factors is established. The real-time infrastructure health index, network environment adaptability index and performance performance evaluation index of the digital base are input, and the comprehensive performance impact weight factor corresponding to the infrastructure health index of the digital base, the comprehensive performance impact weight factor corresponding to the network environment adaptability index of the digital base and the comprehensive performance impact weight factor corresponding to the performance performance evaluation index of the digital base are obtained from the mapping set. It should be understood that all the influencing factors in this embodiment are extracted from the digital base database.

[0082] It should be understood that in this embodiment, by comprehensively analyzing the infrastructure health index, network environment adaptability index and performance efficiency evaluation index of the digital base, a comprehensive view of the health status of the digital base is provided to help identify potential risk points and optimization opportunities. Through continuous monitoring and analysis, possible problems can be identified and resolved in advance, reducing downtime and improving business continuity. Ensure that the performance and stability of the digital base can directly support business goals and promote business innovation and growth. At the same time, protect data and business from threats. Identifying inefficient areas of resource usage through analysis can help optimize resource allocation and reduce total cost of ownership. Analysis of the comprehensive effectiveness of the digital base based on actual performance data and health status will help promote digital transformation.

[0083] Furthermore, the digital base is evaluated according to the comprehensive performance index of the digital base, and the evaluation results are obtained and feedback processing is performed. The specific evaluation process is: extracting the digital base comprehensive performance index threshold from the digital base database, comparing the digital base comprehensive performance index with the digital base comprehensive performance index threshold, if the digital base comprehensive performance index is higher than or equal to the digital base comprehensive performance index threshold, then the comprehensive performance of the digital base is evaluated as qualified; if the digital base comprehensive performance index is lower than the digital base comprehensive performance index threshold, then the comprehensive performance of the digital base is evaluated as unqualified, and feedback processing is performed on the digital base according to the evaluation result.

[0084] In a specific embodiment, the evaluation result of the comprehensive performance of the digital base is fed back through the color of the display indicator light. If the display indicator light is green, it indicates that the comprehensive performance of the digital base is qualified. If the display indicator light is red and an early warning sound is issued, it indicates that the comprehensive performance of the digital base is unqualified. When it is found that the performance is not up to standard, remedial measures should be initiated immediately, including root cause analysis, that is, to find out the specific reasons for low performance through data analysis, which may be data quality problems, system bottlenecks, security vulnerabilities, etc. Then, a detailed action plan is formulated for the problem points found, including short-term and long-term solutions. If necessary, human, financial or technical resources can be increased to speed up problem solving. It is also necessary to strengthen communication and collaboration, promote cross-departmental cooperation, and ensure that all relevant parties have a common understanding and response strategy for the problem. Finally, regular review and adjustment are required.

[0085] Reference Figure 2 As shown, the second aspect of the present invention provides a digital base design system, including: a data acquisition module for collecting real-time monitoring data of the operation and maintenance of the digital base, the real-time monitoring data including infrastructure operation and maintenance data, network environment operation and maintenance data and application performance operation and maintenance data.

[0086] The data analysis module is used to analyze the infrastructure operation and maintenance data to obtain the infrastructure health index of the digital base, analyze the network environment operation and maintenance data to obtain the network environment adaptability index of the digital base, and analyze the application performance operation and maintenance data to obtain the performance efficiency evaluation index of the digital base.

[0087] The comprehensive analysis and evaluation module is used to obtain the comprehensive efficiency index of the digital base based on the infrastructure health index, network environment adaptability index and performance efficiency evaluation index of the digital base through comprehensive analysis, evaluate the digital base based on the comprehensive efficiency index of the digital base, obtain the evaluation results and perform feedback processing.

[0088] The digital base database is used to store data related to the operation and maintenance of the digital base.

[0089] It should be explained that the digital base database described in this embodiment specifically includes the critical network throughput, the critical number of error logs and the critical data backup completion rate, the critical average round-trip time, the critical packet loss rate and the reference standard bandwidth utilization, the allowed deviation bandwidth utilization, the critical maximum number of concurrent users, the critical average application response time and the reference standard resource utilization and the corresponding allowed deviation resource utilization, the digital base comprehensive performance index threshold, the infrastructure health impact factor corresponding to the network throughput, the infrastructure health impact factor corresponding to the error log and the infrastructure health impact factor corresponding to the data backup completion rate, the network environment adaptability impact factor corresponding to the average round-trip time, the network environment adaptability impact factor corresponding to the packet loss rate, and the network environment adaptability impact factor corresponding to the packet loss rate. The environmental adaptability impact factor and the network environment adaptability impact factor corresponding to the bandwidth utilization, the performance efficiency impact factor corresponding to the resource utilization, the performance efficiency impact factor corresponding to the maximum number of concurrent users and the performance efficiency impact factor corresponding to the average application response time, the comprehensive efficiency impact weight factor corresponding to the infrastructure health index of the digital base, the comprehensive efficiency impact weight factor corresponding to the network environment adaptability index of the digital base and the comprehensive efficiency impact weight factor corresponding to the performance efficiency evaluation index of the digital base. These data can be obtained through web crawling, that is, automated tools crawling public data on web pages, or through data source monitoring, regularly collecting data from specific data sources such as sensors and IoT devices.

[0090] A third aspect of the present invention provides a digital base design electronic device, comprising: a receiver, a processor, a server, a memory and a display;

[0091] The receiver is used to receive relevant data on the operation and maintenance of the digital base in real time.

[0092] The memory is used to connect to the digital base database and store data related to the operation and maintenance of the digital base.

[0093] The processor is used to obtain data from the receiver and the memory, and evaluate the comprehensive performance of the digital base.

[0094] The display is used to receive and display the evaluation result of the comprehensive performance of the digital base of the processor.

[0095] The server is used to adjust basic parameters related to the digital base according to the evaluation results displayed on the display.

[0096] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A digital base design method, characterized in that: include: Collecting real-time monitoring data of the operation and maintenance of the digital base, the real-time monitoring data includes infrastructure operation and maintenance data, network environment operation and maintenance data, and application performance operation and maintenance data; The infrastructure operation and maintenance data is analyzed to obtain the infrastructure health index of the digital base, the network environment operation and maintenance data is analyzed to obtain the network environment adaptability index of the digital base, and the application performance operation and maintenance data is analyzed to obtain the performance efficiency evaluation index of the digital base; Based on the infrastructure health index, network environment adaptability index and performance efficiency evaluation index of the digital base, a comprehensive analysis is conducted to obtain the comprehensive efficiency index of the digital base. Based on the comprehensive efficiency index of the digital base, the digital base is evaluated to obtain the evaluation results and conduct feedback processing.

2. A digital base design method according to claim 1, characterized in that: The infrastructure operation and maintenance data is analyzed to obtain the infrastructure health index of the digital base. The specific analysis process is as follows: Deploy several monitoring cycles to collect infrastructure operation and maintenance data of the digital base, including the network throughput, number of error logs and data backup completion rate of each monitoring cycle. Extract the critical network throughput, critical number of error logs and critical data backup completion rate from the digital base database, and comprehensively analyze them to obtain the infrastructure health index of the digital base.

3. A digital base design method according to claim 1, characterized in that: The network environment operation and maintenance data is analyzed to obtain the network environment adaptability index of the digital base, and the specific analysis process is as follows: The network environment operation and maintenance data includes the average round-trip time, packet loss rate and bandwidth utilization of each monitoring period. The critical average round-trip time, critical packet loss rate and reference standard bandwidth utilization are extracted from the digital base database. The allowable deviation bandwidth utilization is obtained by matching the reference standard bandwidth utilization, and the network environment adaptability index of the digital base is obtained by comprehensive analysis.

4. A digital base design method according to claim 1, characterized in that: The application performance operation and maintenance data is analyzed to obtain the performance efficiency evaluation index of the digital base. The specific analysis process is as follows: The application performance operation and maintenance data includes the maximum number of concurrent users, average application response time and resource utilization in each monitoring period. The critical maximum number of concurrent users, critical average application response time, reference standard resource utilization and corresponding allowable deviation resource utilization are extracted from the digital base database, and a comprehensive analysis is performed to obtain the performance efficiency evaluation index of the digital base.

5. A digital base design method according to claim 4, characterized in that: The comprehensive analysis obtains the comprehensive performance index of the digital base, and the specific analysis process is as follows: Based on the infrastructure health index, network environment adaptability index and performance effectiveness evaluation index of the digital base, a comprehensive analysis is performed to obtain the digital base comprehensive effectiveness index, which is used to quantitatively evaluate the effectiveness of the digital base.

6. A digital base design method according to claim 5, characterized in that: The digital base is evaluated according to the comprehensive performance index of the digital base, the evaluation result is obtained and feedback is processed. The specific evaluation process is as follows: The comprehensive performance index threshold of the digital base is extracted from the digital base database, and the comprehensive performance index of the digital base is compared with the comprehensive performance index threshold of the digital base. If the comprehensive performance index of the digital base is higher than or equal to the comprehensive performance index threshold of the digital base, the comprehensive performance of the digital base is evaluated as qualified; if the comprehensive performance index of the digital base is lower than the comprehensive performance index threshold of the digital base, the comprehensive performance of the digital base is evaluated as unqualified, and feedback processing is performed on the digital base according to the evaluation result.

7. A digital base design method according to claim 4, characterized in that: The performance efficiency evaluation index of the digital base is specifically expressed as: Where τN represents the performance evaluation index of the digital base, n represents the number of each monitoring cycle, n = 1, 2, 3, ..., m, m represents the total number of monitoring cycles, e represents a natural constant, and Z n Indicates the resource utilization rate of the nth monitoring cycle, F n Indicates the maximum number of concurrent users in the nth monitoring cycle, Y n represents the average application response time of the nth monitoring cycle, Z 0 represents the reference standard resource utilization, ΔZ represents the allowable deviation resource utilization, Indicates the critical maximum number of concurrent users, represents the critical average application response time, σ1 represents the performance efficiency impact factor corresponding to the set resource utilization, σ2 represents the performance efficiency impact factor corresponding to the set maximum number of concurrent users, and σ3 represents the performance efficiency impact factor corresponding to the set average application response time.

8. A digital base design method according to claim 5, characterized in that: The digital base comprehensive performance index, the specific numerical expression is: In the formula, represents the comprehensive performance index of the digital base, τX represents the infrastructure health index of the digital base, τH represents the network environment adaptability index of the digital base, τN represents the performance efficiency evaluation index of the digital base, ω1 represents the comprehensive performance impact weight factor corresponding to the preset infrastructure health index of the digital base, ω2 represents the comprehensive performance impact weight factor corresponding to the preset network environment adaptability index of the digital base, and ω3 represents the comprehensive performance impact weight factor corresponding to the preset performance efficiency evaluation index of the digital base.

9. A digital base design system using a digital base design method according to any one of claims 1 to 8, characterized in that: include: A data collection module is used to collect real-time monitoring data of the operation and maintenance of the digital base, wherein the real-time monitoring data includes infrastructure operation and maintenance data, network environment operation and maintenance data, and application performance operation and maintenance data; The data analysis module is used to analyze the infrastructure operation and maintenance data to obtain the infrastructure health index of the digital base, analyze the network environment operation and maintenance data to obtain the network environment adaptability index of the digital base, and analyze the application performance operation and maintenance data to obtain the performance efficiency evaluation index of the digital base; A comprehensive analysis and evaluation module is used to obtain a comprehensive effectiveness index of the digital base based on the infrastructure health index, network environment adaptability index and performance effectiveness evaluation index of the digital base through comprehensive analysis, and to evaluate the digital base based on the comprehensive effectiveness index of the digital base, obtain the evaluation results and perform feedback processing; The digital base database is used to store data related to the operation and maintenance of the digital base.

10. An electronic device using a digital base design method as claimed in any one of claims 1 to 8, characterized in that: include: receivers, processors, servers, storage and displays; The receiver is used to receive the relevant data of the operation and maintenance of the digital base in real time; The memory is used to connect to the digital base database and store data related to the operation and maintenance of the digital base; The processor is used to obtain data from the receiver and the memory and evaluate the comprehensive performance of the digital base; The display is used to receive and display the evaluation result of the comprehensive performance of the digital base of the processor; The server is used to adjust basic parameters related to the digital base according to the evaluation results displayed on the display.

Images