Multi-information system operation state batch monitoring method and system

Abstract

The invention discloses a multi-information system operation state batch monitoring method and system, belongs to the technical field of system operation state monitoring, and can simultaneously monitor the operation states of a plurality of information systems and provide quantitative data for managers. Comprising the steps of obtaining operation parameters of a plurality of information systems in a target time period; performing timestamp marking on the acquired operation parameters in the target time period, and storing the marked data in a temporary storage unit; according to the data marked by the timestamp corresponding to each system read from the temporary storage unit, the operation state evaluation index of each system is calculated, and the evaluation index comprises a system stability coefficient, a resource utilization rate coefficient and a response time coefficient; ranking the operation states calculated by the information systems according to the system stability coefficient, the resource utilization rate coefficient and the response time coefficient corresponding to each system to obtain a ranking result; and sending the ranking result to a monitoring terminal of an administrator.

Description

Technical Field

[0001] The present invention relates to the technical field of system operation status monitoring, and in particular to a method and system for batch monitoring the operation status of a multi-information system. Background Art

[0002] With the development of information technology, information systems have been widely used in all walks of life. The stable operation of these information systems is crucial to the smooth development of business. Therefore, effective monitoring of the operating status of information systems has become an indispensable part of information management.

[0003] In actual applications, enterprises and institutions involving multiple information systems are widely present, for example: Financial institutions: Banks, securities companies and other financial institutions usually have multiple information systems, involving multiple business links such as account management, transaction processing, and risk control. The stable operation of these systems is related to the normal development of financial business, so monitoring their operating status is particularly important. Government departments: Government departments usually have multiple information systems for managing public services, administrative affairs, etc. Unified monitoring of these systems will help improve the work efficiency and service quality of government departments. Large enterprises: Large manufacturing companies, retail companies, etc. usually use multiple information systems to manage various links such as production, logistics, and sales. The operating status between different systems needs to be uniformly monitored to ensure smooth production and business processes.

[0004] At present, the monitoring methods for the operation status of most related information systems mainly adopt the method of deploying monitoring plug-ins in a single unit, deploying system monitoring programs, and monitoring the operation status of the system. When it is necessary to optimize and upgrade the information system, this monitoring method cannot uniformly monitor the operation status of multiple information systems and provide quantitative data for managers to determine which system among multiple information systems has the worst operation effect.

[0005] The disclosure of the above background technology content is only used to assist in understanding the concept and technical solution of the present invention. It does not necessarily belong to the prior art of this patent application. In the absence of clear evidence that the above content has been disclosed on the filing date of this patent application, the above background technology should not be used to evaluate the novelty and creativity of the present application. Summary of the invention

[0006] The present application provides a method and system for batch monitoring the operating status of multiple information systems, which can simultaneously monitor the operating status of multiple information systems and provide quantitative data for management personnel.

[0007] To achieve the above objectives, the present application discloses the following technical solutions:

[0008] In a first aspect, an embodiment of the present application provides a method for batch monitoring the operating status of a multi-information system, comprising the following steps:

[0009] Obtain the operating parameters of multiple information systems within the target time period;

[0010] Timestamping the acquired operating parameters within the target time period and storing the marked data in a temporary storage unit;

[0011] Calculate the operating status evaluation index of each system according to the data marked with the timestamp corresponding to each system read from the temporary storage unit, the evaluation index including the system stability coefficient, the resource utilization coefficient and the response time coefficient;

[0012] According to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, the operation status calculated by each information system is ranked to obtain the ranking result;

[0013] The ranking results are sent to the administrator's monitoring terminal.

[0014] In the embodiment of the present application, by obtaining the operating parameters of each information system within the target time period and marking them with timestamps, the consistency and timing of the data can be ensured. Using these marked data to calculate the operating status evaluation indicators of each system, and compare and rank these indicators, on the one hand, unified monitoring of multiple information systems can be achieved; on the other hand, quantitative data can be provided to managers, so that managers can make scientific and reasonable decisions based on data, avoid deviations caused by subjective judgment, quickly and accurately find the system with the worst operating effect, and facilitate managers to optimize and upgrade it in a targeted manner.

[0015] In some possible implementations of the first aspect, the operating parameters include CPU usage, memory usage, disk read and write rates, and network bandwidth utilization.

[0016] In some possible implementations of the first aspect, the step of calculating the system stability coefficient of each system according to reading the data marked with a timestamp corresponding to each system from the temporary storage unit includes:

[0017] Classify the operating parameters of each system within the target time period according to the set time windows, and set a first time window and a second time window; wherein the duration of the second time window is greater than that of the first time window;

[0018] Calculate the first average value in the first time window and the second average value in the second time window for each system; wherein the general calculation formula of the first average value and the second average value is as follows:

[0019]

[0020] Where:

[0021] μ: average value, indicating the average value in a given time window (first time window or second time window)

[0022] The central tendency of all data points within

[0023] N: the number of data points, which represents the total number of data points collected within a given time window;

[0024] x i : The i-th data point, which represents the i-th operating parameter data point within a given time window;

[0025] The first standard deviation in the first time window and the second standard deviation in the second time window are calculated according to the first average value and the second average value; wherein the general calculation formulas for the first standard deviation and the second standard deviation are as follows:

[0026]

[0027] σ: standard deviation, which indicates the dispersion or volatility of data points around the mean;

[0028] μ: mean, which represents the central tendency of all data points in a given time window;

[0029] N: the number of data points, which represents the total number of data points collected within a given time window;

[0030] According to the first standard deviation and the second standard deviation system stability coefficient; the specific formula is as follows:

[0031]

[0032] In this way, by setting up multiple time windows, system fluctuations at different time scales can be captured, providing more comprehensive monitoring, thereby improving the accuracy of system stability assessment and making the assessment results more reliable.

[0033] In some possible implementations of the first aspect, the operation status calculated by each information system is ranked according to the system stability coefficient, resource utilization coefficient, and response time coefficient corresponding to each system, and the step of obtaining the ranking result includes:

[0034] According to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, the system stability score, resource utilization score and response time score are calculated respectively;

[0035] Use predefined weights to perform weighted calculations on the system stability score, resource utilization score, and response time score to obtain a comprehensive score for each information system;

[0036] The systems are sorted according to their comprehensive scores to generate ranking results. This can more accurately reflect the operating status of the information system. In addition, the influence of each score in the comprehensive evaluation can be flexibly adjusted by setting weights of different proportions to meet the optimization needs in specific scenarios.

[0037] In some possible implementations of the first aspect, the method for batch monitoring the operating status of a multi-information system further includes the following steps:

[0038] Compare each system operation status evaluation indicator with its corresponding preset reference threshold value. If an evaluation indicator exceeds the preset reference threshold value, the corresponding information system operation status is determined to be abnormal, and a corresponding abnormal signal is generated;

[0039] In response to the abnormal signal, an information system that is determined to be in an abnormal operating state generates an early warning message, and sends the early warning message to the administrator's monitoring terminal through the network. In this way, system abnormalities can be quickly discovered, making it easier for administrators to take timely measures, thereby improving the reliability and stability of system operation.

[0040] In some possible implementations of the first aspect, in response to the abnormal signal, a system log of the corresponding information system determined to have an abnormal operating state is obtained;

[0041] Use natural language processing technology to perform semantic analysis on the data in the system log and generate anomaly analysis reports;

[0042] Based on the abnormal analysis report, a system optimization suggestion report is generated using the preset large language model;

[0043] Send the system optimization suggestion report to the administrator's monitoring terminal. In this way, the information in the log can be quickly understood through automated semantic analysis technology, and a detailed exception analysis report can be automatically generated, reducing the time and human resources required for manual analysis. The exception analysis report and optimization suggestions generated by the system can provide managers with a scientific basis for decision-making, which is conducive to managers optimizing and maintaining the system more efficiently, scientifically, and reasonably.

[0044] In a second aspect, an embodiment of the present application provides a system for batch monitoring the operating status of a multi-information system, including:

[0045] A first acquisition module is used to acquire the operating parameters of multiple information systems within a target time period;

[0046] A first marking module, used for timestamping the acquired operating parameters and storing the marked data in a temporary storage unit;

[0047] A first calculation module, configured to calculate an operating status evaluation index of each system according to the data marked with a timestamp corresponding to each system read from the temporary storage unit, the evaluation index including a system stability coefficient, a resource utilization coefficient and a response time coefficient;

[0048] The first ranking module is used to rank the operation status calculated by each information system according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, and obtain a ranking result;

[0049] The first sending module is used to send the ranking result to the monitoring terminal of the administrator.

[0050] In some possible implementations of the second aspect, the operating parameters include CPU usage, memory usage, disk read and write rates, and network bandwidth utilization.

[0051] In some possible implementations of the second aspect, the first calculation module is specifically used to: classify the operating parameters of each system within the target time period according to the set time window, and set the first time window and the second time window; wherein the duration of the second time window is greater than the first time window; calculate the first average value of each system within the first time window and the second average value within the second time window; wherein the general calculation formula for the first average value and the second average value is as follows:

[0052]

[0053] Where:

[0054] μ: average value, indicating the average value in a given time window (first time window or second time window)

[0055] The central tendency of all data points within

[0056] N: the number of data points, which represents the total number of data points collected within a given time window;

[0057] x i : The i-th data point, which represents the i-th operating parameter data point within a given time window;

[0058] The first standard deviation in the first time window and the second standard deviation in the second time window are calculated according to the first average value and the second average value; wherein the general calculation formulas for the first standard deviation and the second standard deviation are as follows:

[0059]

[0060] σ: standard deviation, which indicates the dispersion or volatility of data points around the mean;

[0061] μ: mean, which represents the central tendency of all data points in a given time window;

[0062] N: the number of data points, which represents the total number of data points collected within a given time window;

[0063] According to the first standard deviation and the second standard deviation system stability coefficient; the specific formula is as follows:

[0064]

[0065] In some possible implementations of the second aspect, the first sorting module is specifically used to: calculate the system stability score, resource utilization score and response time score respectively according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system; use predefined weights to perform weighted calculations on the system stability score, resource utilization score and response time score to obtain a comprehensive score for each information system; sort the systems according to their comprehensive scores to generate ranking results.

[0066] In some possible implementations of the second aspect, the batch monitoring system for the operating status of multiple information systems also includes a first monitoring module, which is used to compare each system operating status evaluation indicator with its corresponding preset reference threshold value. If a certain evaluation indicator exceeds the preset reference threshold value, the corresponding information system operating status is judged to be abnormal, and a corresponding abnormal signal is generated; in response to the abnormal signal, an early warning message is generated for the information system judged to have an abnormal operating status, and the early warning message is sent to the administrator's monitoring terminal via the network.

[0067] In some possible implementations of the second aspect, the first monitoring module is specifically used to: in response to an abnormal signal, obtain the corresponding system log of the information system that is determined to have an abnormal operating status; perform semantic analysis on the data in the system log through natural language processing technology to generate an abnormal analysis report; based on the abnormal analysis report, use a preset large language model to generate a system optimization suggestion report; and send the system optimization suggestion report to the administrator's monitoring terminal.

[0068] In a third aspect, an embodiment of the present application provides an electronic device, comprising one or more processors; a storage device on which one or more programs are stored; when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any technical solution of the second aspect.

[0069] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in any technical solution of the second aspect is implemented.

[0070] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the method described in any technical solution of the second aspect.

[0071] Among them, the technical effects brought about by any design method in the second to fifth aspects can refer to the technical effects brought about by different design methods in the second aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0073] Figure 1 A flowchart of a method for batch monitoring the operating status of a multi-information system provided in some embodiments of the present application;

[0074] Figure 2 A schematic diagram of the structure of a method for batch monitoring the operating status of a multi-information system provided in some embodiments of the present application;

[0075] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present application. DETAILED DESCRIPTION

[0076] Specific embodiments of the present invention will now be mentioned in detail. Although the present invention is described in conjunction with these specific embodiments, it should be appreciated that it is not intended to limit the present invention to these specific embodiments. On the contrary, these embodiments are intended to cover substitutions, changes or equivalent embodiments that may be included in the spirit and scope of the invention defined by the claims. In the following description, a large number of specific details are set forth in order to provide a comprehensive understanding of the present invention. The present invention may be implemented without some or all of these specific details.

[0077] When used in conjunction with "including," "methods comprising," or similar language in this specification and the appended claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0078] Application Overview:

[0079] With the development of information technology, information systems have been widely used in all walks of life. The stable operation of these information systems is crucial to the smooth development of business. Therefore, effective monitoring of the operating status of information systems has become an indispensable part of information management.

[0080] In actual applications, enterprises and institutions involving multiple information systems are widely present, for example: Financial institutions: Banks, securities companies and other financial institutions usually have multiple information systems, involving multiple business links such as account management, transaction processing, and risk control. The stable operation of these systems is related to the normal development of financial business, so monitoring their operating status is particularly important. Government departments: Government departments usually have multiple information systems for managing public services, administrative affairs, etc. Unified monitoring of these systems will help improve the work efficiency and service quality of government departments. Large enterprises: Large manufacturing companies, retail companies, etc. usually use multiple information systems to manage various links such as production, logistics, and sales. The operating status between different systems needs to be uniformly monitored to ensure smooth production and business processes.

[0081] At present, the monitoring methods for the operation status of most related information systems mainly adopt the method of deploying monitoring plug-ins in a single unit, deploying system monitoring programs, and monitoring the operation status of the system. When it is necessary to optimize and upgrade the information system, this monitoring method cannot uniformly monitor the operation status of multiple information systems and provide quantitative data for managers to determine which system among multiple information systems has the worst operation effect.

[0082] In response to the above technical problems, the overall idea of ​​the technical solution provided by this application is as follows: a method for batch monitoring the operating status of multiple information systems is provided, comprising the following steps: obtaining the operating parameters of multiple information systems within a target time period; timestamping the acquired operating parameters within the target time period, and storing the marked data in a temporary storage unit; calculating the operating status evaluation index of each system based on the timestamp marked data corresponding to each system read from the temporary storage unit, the evaluation index including the system stability coefficient, resource utilization coefficient and response time coefficient; ranking the operating status calculated by each information system according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, and obtaining a ranking result; sending the ranking result to the administrator's monitoring terminal.

[0083] This solution can ensure the consistency and time sequence of data by obtaining the operating parameters of each information system within the target time period and marking them with timestamps. Using these marked data, the operating status evaluation indicators of each system are calculated, and these indicators are compared and ranked. On the one hand, unified monitoring of multiple information systems can be achieved; on the other hand, quantitative data can be provided to managers, so that managers can make scientific and reasonable decisions based on data, avoid deviations caused by subjective judgment, quickly and accurately find the system with the worst operating effect, and facilitate managers to optimize and upgrade it in a targeted manner.

[0084] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the accompanying drawings. Figure 1 The present application embodiment provides a method for batch monitoring the operating status of a multi-information system, comprising the following steps:

[0085] S101: Obtaining operating parameters of multiple information systems within a target time period;

[0086] Specifically, in some embodiments, a monitoring agent can be deployed on each information system to collect specified operating parameters, including but not limited to CPU usage, memory usage, disk read and write rates, and network bandwidth utilization. The execution subject of the method for batch monitoring the operating status of multiple information systems communicates with each monitoring agent to obtain the operating parameters of multiple information systems within the target time period.

[0087] S102: Timestamp the acquired operating parameters within the target time period, and store the marked data in a temporary storage unit;

[0088] The temporary storage unit may be, but is not limited to, a relational database (such as MySQL, PostgreSQL) or a NoSQL database (such as MongoDB, Cassandra).

[0089] S103: Calculate the operation status evaluation index of each system according to the data marked with the timestamp corresponding to each system read from the temporary storage unit, where the evaluation index includes a system stability coefficient, a resource utilization coefficient and a response time coefficient;

[0090] Specifically, in some embodiments, the execution subject may calculate the system stability coefficient of each system by reading the data marked with a timestamp corresponding to each system from the temporary storage unit through the following steps:

[0091] The first step is to classify the operating parameters of each system in the target time period according to the set time window, and set the first time window and the second time window; wherein the duration of the second time window is greater than that of the first time window;

[0092] In the second step, the first average value of each system in the first time window and the second average value in the second time window are calculated; wherein the general calculation formula of the first average value and the second average value is as follows:

[0093]

[0094] Where:

[0095] μ: average value, indicating the average value in a given time window (first time window or second time window)

[0096] The central tendency of all data points within

[0097] N: the number of data points, which represents the total number of data points collected within a given time window;

[0098] x i : The i-th data point, which represents the i-th operating parameter data point within a given time window;

[0099] In the third step, a first standard deviation in the first time window and a second standard deviation in the second time window are calculated based on the first average value and the second average value; wherein the general calculation formulas for the first standard deviation and the second standard deviation are as follows:

[0100]

[0101] σ: standard deviation, which indicates the dispersion or volatility of data points around the mean;

[0102] μ: mean, which represents the central tendency of all data points in a given time window;

[0103] N: the number of data points, which represents the total number of data points collected within a given time window;

[0104] The fourth step is to calculate the system stability coefficient based on the first standard deviation and the second standard deviation; the specific formula is as follows:

[0105]

[0106] It can be understood that the standard deviation is an indicator of data volatility. The smaller the standard deviation, the smaller the data volatility and the more stable the system. In other words, the larger the system stability coefficient, the better. The larger the system stability coefficient, the higher the corresponding score mentioned in the subsequent steps.

[0107] In this way, by setting up multiple time windows, system fluctuations at different time scales can be captured, providing more comprehensive monitoring, thereby improving the accuracy of system stability assessment and making the assessment results more reliable.

[0108] Based on the above embodiment, the above execution subject can calculate the resource utilization coefficient of each system by reading the data marked with the timestamp corresponding to each system from the temporary storage unit through the following steps:

[0109] The first step is to calculate the average utilization of various resources, including but not limited to the average CPU utilization, average memory utilization, and average disk utilization;

[0110] The comprehensive resource utilization is obtained by calculating the average of the utilization rates of various types of resources, that is, summing the utilization rates of various types of resources and dividing them by their total number;

[0111] The resource utilization coefficient is the complement of the resource utilization rate, indicating the idleness of the system in terms of resource utilization. Resource utilization coefficient = 1-average resource utilization rate.

[0112] It can be understood that when the resource utilization coefficient is close to 1, it means that the average resource utilization is close to 0, that is, the more system resources are available, that is, the closer the resource utilization coefficient is to 1, the higher the corresponding score mentioned in the subsequent steps.

[0113] Based on the above embodiment, the above execution subject may calculate each response time coefficient by reading the data marked with a timestamp corresponding to each system from the temporary storage unit through the following steps:

[0114] The first step is to collect the response time data points R when the system processes the request i , where i represents the i-th data point, with a total of K data points.

[0115] The second step is to calculate the average response time μ 响应 :

[0116]

[0117] The third step is to calculate the standard deviation σ of the response time. 响应 :

[0118]

[0119] The fourth step is to calculate the response time coefficient:

[0120]

[0121] The standard deviation is an indicator of data volatility. The smaller the standard deviation, the smaller the difference between data values, that is, the more stable the response time. In other words, the larger the response time coefficient, the better. In other words, the larger the response time coefficient, the higher the corresponding score mentioned in the subsequent steps.

[0122] S104: ranking the operation status calculated by each information system according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, and obtaining a ranking result;

[0123] Specifically, in some embodiments, the execution subject may rank the operation status calculated by each information system according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system through the following steps to obtain a ranking result:

[0124] The first step is to calculate the system stability score, resource utilization score and response time score respectively according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system;

[0125] In the second step, the system stability score, resource utilization score and response time score are weighted and calculated using predefined weights to obtain a comprehensive score for each information system.

[0126] The third step is to sort the systems according to their comprehensive scores and generate ranking results. Specifically, the ranking results can be presented in the form of a list or table.

[0127] In this way, the operating status of the information system can be reflected more accurately. In addition, the influence of each score in the comprehensive evaluation can be flexibly adjusted by setting weights of different proportions to meet the optimization needs in specific scenarios.

[0128] S105: Send the ranking results to the administrator's monitoring terminal.

[0129] Preferably, in some embodiments, the method for batch monitoring the operating status of a multi-information system further comprises the following steps:

[0130] In the first step, each system operation status evaluation indicator is compared with its corresponding preset reference threshold. If a certain evaluation indicator exceeds the preset reference threshold, the corresponding information system operation status is judged to be abnormal, and a corresponding abnormal signal is generated;

[0131] The second step is to generate warning information for the information system that is determined to be in abnormal operation status in response to the abnormal signal, and send the warning information to the administrator's monitoring terminal through the network. In this way, system abnormalities can be quickly discovered, which facilitates the administrator to take timely measures, thereby improving the reliability and stability of system operation.

[0132] Based on the above embodiment, in response to the abnormal signal, the execution subject is further used to perform the following steps:

[0133] The first step is to obtain the system log of the corresponding information system that is determined to be in abnormal operation state;

[0134] The second step is to use natural language processing technology to perform semantic analysis on the data in the system log and generate an abnormal analysis report;

[0135] The third step is to generate a system optimization suggestion report based on the abnormal analysis report using the preset large language model;

[0136] The fourth step is to send the system optimization suggestion report to the administrator's monitoring terminal. In this way, the information in the log can be quickly understood through automated semantic analysis technology, and a detailed abnormal analysis report can be automatically generated, reducing the time and human resources required for manual analysis. The abnormal analysis report and optimization suggestions generated by the system can provide managers with a scientific decision-making basis, which is conducive to managers optimizing and maintaining the system more efficiently, scientifically and reasonably.

[0137] See also Figure 2 Based on the same inventive concept as the method for batch monitoring the operating status of a multi-information system in the aforementioned embodiment, the embodiment of the present application provides a system for batch monitoring the operating status of a multi-information system, comprising:

[0138] The first acquisition module 201 is used to acquire the operating parameters of multiple information systems within a target time period;

[0139] A first marking module 202, used to timestamp the acquired operating parameters and store the marked data in a temporary storage unit;

[0140] A first calculation module 203 is used to calculate the operation status evaluation index of each system according to the data marked with the timestamp corresponding to each system read from the temporary storage unit, and the evaluation index includes a system stability coefficient, a resource utilization coefficient and a response time coefficient;

[0141] The first ranking module 204 is used to rank the operation status calculated by each information system according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, and obtain a ranking result;

[0142] The first sending module 205 is used to send the ranking result to the monitoring terminal of the administrator.

[0143] In some embodiments, the operating parameters include CPU usage, memory usage, disk read and write rates, and network bandwidth utilization.

[0144] In some embodiments, the first calculation module 203 is specifically used to: classify the operating parameters of each system in the target time period according to the set time window, set the first time window and the second time window; wherein the duration of the second time window is greater than the first time window; calculate the first average value of each system in the first time window and the second average value in the second time window; wherein the general calculation formula of the first average value and the second average value is as follows:

[0145]

[0146] Where:

[0147] μ: average value, indicating the average value in a given time window (first time window or second time window)

[0148] The central tendency of all data points within

[0149] N: the number of data points, which represents the total number of data points collected within a given time window;

[0150] x i : The i-th data point, which represents the i-th operating parameter data point within a given time window;

[0151] The first standard deviation in the first time window and the second standard deviation in the second time window are calculated according to the first average value and the second average value; wherein the general calculation formulas for the first standard deviation and the second standard deviation are as follows:

[0152]

[0153] σ: standard deviation, which indicates the dispersion or volatility of data points around the mean;

[0154] μ: mean, which represents the central tendency of all data points in a given time window;

[0155] N: the number of data points, which represents the total number of data points collected within a given time window;

[0156] According to the first standard deviation and the second standard deviation system stability coefficient; the specific formula is as follows:

[0157]

[0158] In some embodiments, the first sorting module 204 is specifically used to: calculate the system stability score, resource utilization score and response time score respectively according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system; use predefined weights to perform weighted calculations on the system stability score, resource utilization score and response time score to obtain a comprehensive score for each information system; sort the systems according to their comprehensive scores to generate ranking results.

[0159] In some embodiments, the batch monitoring system for the operating status of multiple information systems also includes a first monitoring module 206, which is used to compare each system operating status evaluation indicator with its corresponding preset reference threshold value. If a certain evaluation indicator exceeds the preset reference threshold value, the corresponding information system operating status is judged to be abnormal, and a corresponding abnormal signal is generated; in response to the abnormal signal, an early warning message is generated for the information system judged to have an abnormal operating status, and the early warning message is sent to the administrator's monitoring terminal via the network.

[0160] In some embodiments, the first monitoring module 206 is also specifically used to: in response to an abnormal signal, obtain the corresponding system log of the information system that is determined to have an abnormal operating status; perform semantic analysis on the data in the system log through natural language processing technology to generate an abnormal analysis report; based on the abnormal analysis report, use a preset large language model to generate a system optimization suggestion report; and send the system optimization suggestion report to the administrator's monitoring terminal.

[0161] It is understandable that the modules recorded in the multi-information system operation status batch monitoring system are similar to the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the batch monitoring system for the operation status of multiple information systems and the modules contained therein, and will not be repeated here.

[0162] See also Figure 3, based on the inventive concept of a method for batch monitoring the operating status of a multi-information system in the aforementioned embodiment, an embodiment of the present application provides an electronic device. The electronic device may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), etc., and fixed terminals such as digital TVs, desktop computers, etc. The electronic device includes a processing device 301 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a ROM 302 (read-only memory) or a program loaded from a storage device 308 into a RAM 303 (random access memory). In RAM 303, various programs and data required for the operation of the electronic device are also stored. The processing device 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An input / output interface (i.e., an I / O interface 305) is also connected to the bus 304.

[0163] Typically, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data.

[0164] In particular, according to some embodiments of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of some embodiments of the present application are executed.

[0165] It should be noted that the computer-readable medium recorded in some embodiments of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present application, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In some embodiments of the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0166] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an adhoc peer-to-peer network), as well as any currently known or future developed network.

[0167] The computer-readable medium may be included in the electronic device; or it may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: obtains the operating parameters of multiple information systems within the target time period; timestamps the acquired operating parameters within the target time period, and stores the marked data in a temporary storage unit; calculates the operating status evaluation index of each system based on the timestamp data corresponding to each system read from the temporary storage unit, and the evaluation index includes a system stability coefficient, a resource utilization coefficient, and a response time coefficient; ranks the operating status calculated by each information system according to the system stability coefficient, resource utilization coefficient, and response time coefficient corresponding to each system, and obtains a ranking result; and sends the ranking result to the administrator's monitoring terminal.

[0168] The computer program code for performing the operation of some embodiments of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer, partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0169] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0170] The modules described in some embodiments of the present application may be implemented by software or hardware. The modules described may also be set in a processor: for example, they may be described as: a first acquisition module, a first marking module, a first calculation module, a first sorting module, a first sending module, and a first monitoring module. The names of these modules do not, in some cases, constitute limitations on the modules themselves. For example, the first acquisition module may also be described as a "module for acquiring operating parameters within a target time period."

[0171] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0172] Some embodiments of the present application also provide a computer program product, including a computer program, which implements any of the above-mentioned methods for batch monitoring the operating status of a multi-information system when executed by a processor.

[0173] Although the present invention has been described in detail above by general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made to the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. A method for batch monitoring the operating status of a multi-information system, characterized in that: The following steps are involved: Obtain the operating parameters of multiple information systems within the target time period; Timestamping the acquired operating parameters within the target time period and storing the marked data in a temporary storage unit; Calculate the operating status evaluation index of each system according to the data marked with the timestamp corresponding to each system read from the temporary storage unit, wherein the evaluation index includes a system stability coefficient, a resource utilization coefficient and a response time coefficient; According to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, the operation status calculated by each information system is ranked to obtain the ranking result; The ranking result is sent to the monitoring terminal of the administrator.

2. The method for batch monitoring the operation status of a multi-information system according to claim 1, characterized in that: The operating parameters include CPU usage, memory usage, disk read and write rates, and network bandwidth utilization.

3. The method for batch monitoring the operation status of a multi-information system according to claim 2, characterized in that: The step of calculating the system stability coefficient of each system according to the data marked with the timestamp corresponding to each system read from the temporary storage unit includes: Classify the operating parameters of each system within the target time period according to the set time windows, and set a first time window and a second time window; wherein the duration of the second time window is greater than that of the first time window; Calculate the first average value in the first time window and the second average value in the second time window for each system; wherein the general calculation formula of the first average value and the second average value is as follows: Where: μ: mean value, which represents the central tendency of all data points in a given time window (first time window or second time window); N: the number of data points, which represents the total number of data points collected within a given time window; x i : The i-th data point, which represents the i-th operating parameter data point within a given time window; A first standard deviation in a first time window and a second standard deviation in a second time window are calculated according to the first average value and the second average value; wherein a general calculation formula for the first standard deviation and the second standard deviation is as follows: σ: standard deviation, which indicates the dispersion or volatility of data points around the mean; μ: mean, which represents the central tendency of all data points in a given time window; N: the number of data points, which represents the total number of data points collected within a given time window; The system stability coefficient is determined based on the first standard deviation and the second standard deviation; the specific formula is as follows:

4. The method for batch monitoring the operation status of a multi-information system according to claim 3 is characterized in that: The step of ranking the operation status calculated by each information system according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system to obtain the ranking result comprises: According to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, a system stability score, a resource utilization score and a response time score are calculated respectively; Use predefined weights to perform weighted calculations on the system stability score, resource utilization score, and response time score to obtain a comprehensive score for each information system; The systems are sorted according to their comprehensive scores to generate ranking results.

5. The method for batch monitoring the operation status of a multi-information system according to claim 2, characterized in that: The following steps are also included: Compare each system operation status evaluation indicator with its corresponding preset reference threshold value. If an evaluation indicator exceeds the preset reference threshold value, the corresponding information system operation status is determined to be abnormal, and a corresponding abnormal signal is generated; In response to the abnormal signal, an early warning message is generated for the information system determined to be in an abnormal operating state, and the early warning message is sent to the monitoring terminal of the administrator through the network.

6. The method for batch monitoring the operation status of a multi-information system according to claim 5, characterized in that: In response to the abnormal signal, obtaining a system log of a corresponding information system determined to be in an abnormal operating state; Perform semantic analysis on the data in the system log by natural language processing technology to generate an abnormality analysis report; Based on the abnormal analysis report, a system optimization suggestion report is generated using the preset large language model; The system optimization suggestion report is sent to the administrator's monitoring terminal.

7. A batch monitoring system for the operation status of a multi-information system, characterized in that: include: A first acquisition module is used to acquire the operating parameters of multiple information systems within a target time period; A first marking module, used for timestamping the acquired operating parameters and storing the marked data in a temporary storage unit; A first calculation module, configured to calculate an operating status evaluation index of each system according to the data marked with a timestamp corresponding to each system read from the temporary storage unit, wherein the evaluation index includes a system stability coefficient, a resource utilization coefficient, and a response time coefficient; The first ranking module is used to rank the operation status calculated by each information system according to the system stability coefficient, resource utilization coefficient and response time coefficient corresponding to each system, and obtain a ranking result; The first sending module is used to send the ranking result to the monitoring terminal of the administrator.

8. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processing device, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processing device, the method according to any one of claims 1 to 6 is implemented.

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