IT operation and maintenance service intelligent management and control system

Abstract

The invention discloses an IT operation and maintenance service intelligent management and control system, which belongs to the technical field of IT operation and maintenance services and comprises a monitoring analysis module, a monitoring module and a management module. The monitoring analysis module is used for analyzing operation and maintenance monitoring of the user, establishing a blind area library, analyzing operation and maintenance detail data of the user, and determining an operation and maintenance blind area; analyzing each operation and maintenance blind area, and determining each overcome blind area; monitoring supplement is carried out on each overcome blind area; the monitoring module is used for carrying out operation and maintenance monitoring and acquiring monitoring data of each monitoring target in real time; inputting the monitoring data of each monitoring target into an operation and maintenance display model for real-time display; performing operation and maintenance analysis on each monitoring target based on the operation and maintenance display model to obtain an operation and maintenance analysis result of each monitoring target; the management module is used for performing operation and maintenance management and establishing an operation and maintenance management library; identifying an operation and maintenance analysis result of each monitoring target in real time; and matching operation and maintenance processing measures according to the operation and maintenance analysis result, and performing corresponding operation and maintenance management according to the operation and maintenance processing measures.

Description

Technical Field

[0001] The present invention belongs to the technical field of IT operation and maintenance services, and specifically is an IT operation and maintenance service intelligent management and control system. Background Art

[0002] With the rapid development of information technology, enterprise IT systems are becoming increasingly complex, covering network equipment, servers, virtualization platforms, databases, application services and other aspects. Traditional IT operation and maintenance methods often rely on manual inspections, troubleshooting and manual repairs. This method is not only inefficient, but also prone to errors, and it is difficult to meet the requirements of modern enterprises for high availability and stability of IT systems. In addition, traditional monitoring can only cover some key equipment or performance indicators, and there are blind spots in monitoring. It cannot fully reflect the overall health of the IT system, resulting in certain operation and maintenance loopholes.

[0003] Based on this, in order to solve IT operation and maintenance problems, the present invention provides an IT operation and maintenance service intelligent management and control system. Summary of the invention

[0004] In order to solve the problems existing in the above-mentioned solutions, the present invention provides an IT operation and maintenance service intelligent management and control system.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] An IT operation and maintenance service intelligent management and control system, including a monitoring and analysis module, a monitoring module and a management module;

[0007] The monitoring and analysis module is used to analyze the user's operation and maintenance monitoring and establish a blind spot library. The blind spot library is used to store the data of each blind spot. The blind spot data includes the blind spot type, blind spot identification characteristics, and blind spot impact;

[0008] Obtain the user's operation and maintenance detailed data, analyze the operation and maintenance detailed data, and determine the operation and maintenance blind spots; analyze each of the operation and maintenance blind spots and determine how to overcome the blind spots; and perform monitoring supplements on each of the overcoming blind spots.

[0009] Furthermore, the method for analyzing the operation and maintenance detail data includes:

[0010] A blind spot recognition model is established based on the blind spot library. The expression of the blind spot recognition model is:

[0011]

[0012] Where: s is the input data, which is the user's operation and maintenance details data; the output data is the blind spot identification value MQ(s);

[0013] The blind spot identification model is used to analyze the user's operation and maintenance details data to determine the operation and maintenance blind spots.

[0014] Furthermore, the method for establishing the blind area library includes:

[0015] Determine various blind spot operation and maintenance data, identify the blind spot operation and maintenance data, and determine various blind spot types; obtain feature data corresponding to each blind spot type, perform feature recognition on the feature data, and obtain blind spot recognition features corresponding to the blind spot type; and count various blind spot impacts of the blind spot type according to the feature data;

[0016] A database is established to integrate various blind spot types, blind spot identification features and blind spot impacts into blind spot data; each blind spot data is input into the database for storage, and the current database is marked as a blind spot library.

[0017] Furthermore, the method for analyzing the operation and maintenance detail data includes:

[0018] Acquire the field data of each operation and maintenance blind spot, match the corresponding blind spot data according to the operation and maintenance blind spot, identify the impact of each blind spot in the blind spot data, analyze the impact of each blind spot according to the field data, and obtain each operation and maintenance hidden danger corresponding to the operation and maintenance blind spot;

[0019] Perform an impact analysis on each operation and maintenance hidden danger to obtain the impact value of each operation and maintenance hidden danger and the corresponding hidden danger probability; the value range of the impact value is [0, 100];

[0020] According to the formula Calculate the blind spot adjustment value of each operation and maintenance blind spot;

[0021] Where: PL is the blind zone adjustment value; i represents the operation and maintenance hidden danger, i = 1, 2, ..., n, n is a positive integer; YCi is the impact value; ηi is the hidden danger probability;

[0022] According to the blind spot adjustment value, each operation and maintenance blind spot is classified and counted to obtain a blind spot detail list, which is sent to the user to determine each blind spot to be overcome.

[0023] The monitoring module is used to perform operation and maintenance monitoring, determine each monitoring target, and obtain monitoring data of each monitoring target in real time; establish an operation and maintenance display model, and input the monitoring data of each monitoring target into the operation and maintenance display model for real-time display;

[0024] Based on the operation and maintenance display model, operation and maintenance analysis is performed on each monitoring target to obtain operation and maintenance analysis results of each monitoring target; the operation and maintenance analysis results are input into the operation and maintenance display model for display.

[0025] Furthermore, the method for performing operation and maintenance analysis on each monitoring target based on the operation and maintenance display model includes:

[0026] Conduct correlation evaluation on each monitoring target and determine the related monitoring targets; classify the related monitoring targets into one category and mark them as the related category;

[0027] Identify the monitoring data of each monitoring target, perform anomaly analysis on the monitoring data based on the association class corresponding to the monitoring target, and obtain the anomaly analysis results corresponding to each monitoring target in the association class;

[0028] Obtain the operation and maintenance standards of each monitoring target, calibrate the corresponding monitoring data according to each operation and maintenance standard, obtain the corresponding operation and maintenance verification results, and integrate the operation and maintenance verification results and abnormal analysis results into the operation and maintenance analysis results of the monitoring target.

[0029] Furthermore, the method for performing abnormal analysis on monitoring data based on the association class corresponding to the monitoring target includes:

[0030] Establish an associated evaluation model, the expression of the associated evaluation model is:

[0031]

[0032] In the formula: q is the input data, the input data is each monitoring data; the output data is the abnormal correlation value GL(q);

[0033] The monitoring data corresponding to the monitoring targets in the association class are analyzed through the association evaluation model to obtain the abnormal association values ​​between the monitoring data; the abnormal analysis results of each monitoring target are determined according to the abnormal association values.

[0034] The management module is used to perform operation and maintenance management and establish an operation and maintenance management library, and the operation and maintenance management library is used to store operation and maintenance processing measures corresponding to different operation and maintenance analysis results;

[0035] Identify the operation and maintenance analysis results of each monitoring target in real time; match the corresponding operation and maintenance processing measures from the operation and maintenance management library according to the operation and maintenance analysis results, and perform corresponding operation and maintenance management according to the operation and maintenance processing measures.

[0036] Furthermore, it also includes a prediction analysis module, which is used to perform operation and maintenance prediction analysis and identify the operation and maintenance analysis results of each monitoring target; mark each monitoring target whose operation and maintenance analysis result is a normal state as a candidate target, calculate the degree of deviation between the monitoring data of the candidate target and the operation and maintenance standard, and mark the candidate target whose deviation degree is less than a threshold value X3 as a prediction target;

[0037] Establish a prediction model, predict each prediction target through the prediction model, obtain the corresponding prediction data, and determine the corresponding prediction deviation in real time according to the prediction data and operation and maintenance standards; generate a corresponding prediction curve according to the prediction deviation corresponding to each time, with the horizontal axis being time and the vertical axis being the prediction deviation, and the prediction deviation corresponding to t=0 being the deviation degree;

[0038] Perform forecast evaluation according to the forecast curve to obtain corresponding forecast evaluation results; input the forecast evaluation results into the operation and maintenance display model for display.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] Through the coordination among monitoring and analysis modules, monitoring modules, management modules and predictive analysis modules, comprehensive monitoring of all levels and dimensions of IT systems can be achieved, blind spots in monitoring can be eliminated, and targeted suggestions can be made based on the actual needs of users to achieve comprehensive monitoring. Artificial intelligence and machine learning algorithms can be used to conduct in-depth analysis of monitoring data, identify potential problems and abnormal patterns, and provide strong support for operation and maintenance decisions. Through real-time monitoring and intelligent operation and maintenance, the stability and availability of IT systems can be ensured, business continuity can be improved, and the smooth progress of corporate business can be guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0043] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] like Figure 1 As shown, an IT operation and maintenance service intelligent management and control system includes a monitoring and analysis module, a monitoring module, a management module and a prediction and analysis module;

[0045] The monitoring and analysis module is used to analyze the user's operation and maintenance monitoring and establish a blind spot library. The blind spot library is used to store the data of each blind spot. The blind spot data includes blind spot type, blind spot identification characteristics, blind spot impact and other related data. The blind spot type indicates what type of operation and maintenance monitoring blind spot it is; the blind spot identification characteristics are which operation and maintenance monitoring characteristics can be determined as the blind spot type, generally determined by unmonitored equipment; the blind spot impact is which hidden dangers may be caused by the blind spot type;

[0046] A blind spot recognition model is established based on the blind spot library, that is, blind spot recognition features in each blind spot data are used for recognition. The expression of the blind spot recognition model is: In the formula: s is the input data, which is the user's operation and maintenance details data; the output data is the blind spot identification value MQ(s); meeting the identification requirements means having the blind spot identification feature; the operation and maintenance details data is to analyze the IT equipment in the user's enterprise, determine the details of each device that can be operated and maintained, and integrate them into the operation and maintenance details data; it can be integrated into the operation and maintenance details data in the form of information graphics, which is more intuitive and three-dimensional;

[0047] Obtain the user's operation and maintenance details data, analyze the user's operation and maintenance details data through the blind spot identification model, and determine the operation and maintenance blind spots;

[0048] Identify the field data of operation and maintenance blind spots, such as purpose, function, equipment model, type and other related data; match the corresponding blind spot data according to the operation and maintenance blind spots, identify the impact of each blind spot in the blind spot data, match the impact of each blind spot according to the field data, obtain the blind spot impact that may occur in the operation and maintenance blind spot at the user's location, and mark it as an operation and maintenance hidden danger;

[0049] Analyze the impact of each operation and maintenance hidden danger to obtain the corresponding impact value and corresponding hidden danger probability. The value range of the impact value is [0, 100]. The impact value of no impact on the operation of the user enterprise is 0, and the impact value that causes the user enterprise to be unable to operate is 100. Other impact values ​​are set according to the impact degree, that is, actual judgment is made in combination with the operation of the user enterprise. The actual situation after the hidden danger occurs can be assumed, and then the impact value is set; the hidden danger probability is the probability of the operation and maintenance hidden danger occurring. According to the actual situation of the equipment, etc., statistical analysis is performed to determine the probability of the operation and maintenance hidden danger occurring, which is marked as the hidden danger probability;

[0050] According to the formula Calculate the blind spot adjustment value of each operation and maintenance blind spot;

[0051] Where: PL is the blind zone adjustment value; i represents the operation and maintenance hidden danger, i = 1, 2, ..., n, n is a positive integer; YCi is the impact value; ηi is the hidden danger probability;

[0052] Classify and count each operation and maintenance blind spot according to the blind spot adjustment value to obtain a blind spot list. If the blind spot adjustment value is 1, it is marked as recommended to be overcome, otherwise it is not recommended to be solved. The blind spot list is sent to the user, and the user determines the operation and maintenance blind spot that needs to be solved and marks it as a blind spot to be overcome.

[0053] Supplement monitoring of each blind spot to achieve operation and maintenance monitoring of each blind spot.

[0054] The method for establishing a blind area library includes:

[0055] Based on big data, various blind spot operation and maintenance data are determined, that is, historical data related to blind spots; blind spot operation and maintenance data are identified to determine various blind spot types; characteristic data corresponding to each blind spot type is obtained, that is, relevant data corresponding to the blind spot type, characteristic data is identified, and blind spot identification features corresponding to the blind spot type are obtained; and various blind spot impacts of the blind spot type are counted according to the characteristic data;

[0056] A database is established to integrate various blind spot types, blind spot identification features and blind spot impacts into blind spot data; each blind spot data is input into the database for storage, and the current database is marked as a blind spot library.

[0057] The monitoring module is used to perform operation and maintenance monitoring, determine each monitoring target, which is the IT equipment that needs to be monitored; obtain the monitoring data of each monitoring target in real time; establish an operation and maintenance display model according to user needs, and the operation and maintenance display model is used to display the monitoring data and subsequent analysis results according to user needs; input the monitoring data of each monitoring target into the operation and maintenance display model for real-time display;

[0058] Based on the operation and maintenance display model, operation and maintenance analysis is performed on each monitoring target to obtain operation and maintenance analysis results of each monitoring target; the operation and maintenance analysis results are input into the operation and maintenance display model for display.

[0059] In one embodiment, a method for performing operation and maintenance analysis on each monitoring target based on the operation and maintenance display model includes:

[0060] Conduct correlation evaluation on each monitoring target and determine the related monitoring targets; that is, conduct evaluation based on whether the monitoring data between the monitoring targets have a correlation impact. For example, if the monitoring data of a certain monitoring target is correlated with the monitoring data of other monitoring targets, when one changes, the other changes according to the corresponding rules, and it can be determined that there is a correlation between the two. That is, the monitoring data of the related monitoring targets have a certain correlation, which is used to verify whether the monitoring data is abnormal when another monitoring problem occurs, such as monitoring abnormality caused by monitoring equipment; the platform can list the related monitoring targets, establish a detailed correlation list, and then match them;

[0061] Classify the monitoring targets that are associated with each other into one category and mark it as the associated category;

[0062] Identify the monitoring data of each monitoring target, and perform abnormal analysis on the monitoring data based on the association class corresponding to the monitoring target; obtain the corresponding abnormal analysis results; specifically determine the monitoring targets with association based on the association list, and establish an association evaluation model based on the association between the monitoring data of each monitoring target, which is used to evaluate the monitoring data that needs to be analyzed based on the association in the normal state, and determine whether the monitoring data meets the association requirements. The platform party shall establish and train it; the expression of the association evaluation model is In the formula: q is the input data, the input data is each monitoring data; the output data is the abnormal correlation value GL(q);

[0063] The monitoring data of each monitoring target is analyzed through the association evaluation model to obtain the abnormal association value between each monitoring data; the abnormal analysis result of each monitoring target is determined according to the abnormal association value, that is, whether to monitor abnormality.

[0064] Obtain the corresponding operation and maintenance standards for each monitoring target. The operation and maintenance standards are the operating states that the monitoring targets need to achieve, which are preset data. Verify the corresponding monitoring data according to each operation and maintenance standard to obtain the corresponding operation and maintenance verification results. Integrate the operation and maintenance verification results and abnormal analysis results into the operation and maintenance analysis results of the monitoring targets.

[0065] The management module is used to perform operation and maintenance management and establish an operation and maintenance management library. The operation and maintenance management library is used to store operation and maintenance processing measures corresponding to different operation and maintenance analysis results, which are specifically established by the platform according to user needs;

[0066] Identify the operation and maintenance analysis results of each monitoring target in real time; match the corresponding operation and maintenance processing measures from the operation and maintenance management library according to the obtained operation and maintenance analysis results, and perform corresponding operation and maintenance management according to the obtained operation and maintenance processing measures.

[0067] The prediction analysis module is used to perform operation and maintenance prediction analysis and identify the operation and maintenance analysis results of each monitoring target; mark each monitoring target whose operation and maintenance analysis result is a normal state as a candidate target, calculate the degree of deviation between the monitoring data of the candidate target and the operation and maintenance standard, such as the operation and maintenance standard is 100, the monitoring data is 90, and the degree of deviation is 10; mark the candidate target whose deviation degree is less than the threshold value X3 as a prediction target; establish a corresponding prediction model based on the existing prediction technology, predict each prediction target through the prediction model, obtain the corresponding prediction data, and determine the corresponding prediction deviation in real time according to the prediction data and the operation and maintenance standard; generate a corresponding prediction curve according to the prediction deviation corresponding to each time, the horizontal axis is time, the vertical axis is the prediction deviation, and the corresponding prediction deviation at t=0 is the deviation degree;

[0068] Perform forecast evaluation according to the forecast curve to obtain corresponding forecast evaluation results; input the forecast evaluation results into the operation and maintenance display model for display.

[0069] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0070] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An IT operation and maintenance service intelligent management and control system, characterized in that: Including monitoring and analysis module, monitoring module and management module; The monitoring and analysis module is used to analyze the user's operation and maintenance monitoring and establish a blind spot library. The blind spot library is used to store the data of each blind spot. The blind spot data includes the blind spot type, blind spot identification characteristics, and blind spot impact; Obtaining the user's operation and maintenance detailed data, analyzing the operation and maintenance detailed data, and determining the operation and maintenance blind spots; analyzing each of the operation and maintenance blind spots, and determining how to overcome the blind spots; Supplementary monitoring is performed to overcome the blind spots described above; The monitoring module is used to perform operation and maintenance monitoring, determine each monitoring target, and obtain monitoring data of each monitoring target in real time; Establish an operation and maintenance display model, and input the monitoring data of each monitoring target into the operation and maintenance display model for real-time display; Based on the operation and maintenance display model, operation and maintenance analysis is performed on each monitoring target to obtain the operation and maintenance analysis results of each monitoring target; Input the operation and maintenance analysis results into the operation and maintenance display model for display; The management module is used to perform operation and maintenance management and establish an operation and maintenance management library, and the operation and maintenance management library is used to store operation and maintenance processing measures corresponding to different operation and maintenance analysis results; Identify the operation and maintenance analysis results of each monitoring target in real time; match the corresponding operation and maintenance processing measures from the operation and maintenance management library according to the operation and maintenance analysis results, and perform corresponding operation and maintenance management according to the operation and maintenance processing measures.

2. According to claim 1, an IT operation and maintenance service intelligent management and control system is characterized in that: Methods for analyzing operation and maintenance detail data include: A blind spot recognition model is established based on the blind spot library. The expression of the blind spot recognition model is: Where: s is the input data, which is the user's operation and maintenance details data; the output data is the blind spot identification value MQ(s); The blind spot identification model is used to analyze the user's operation and maintenance details data to determine the operation and maintenance blind spots.

3. The IT operation and maintenance service intelligent management and control system according to claim 1, characterized in that: The method for establishing a blind area library includes: Determine various blind spot operation and maintenance data, identify the blind spot operation and maintenance data, and determine various blind spot types; obtain feature data corresponding to each blind spot type, perform feature recognition on the feature data, and obtain blind spot recognition features corresponding to the blind spot type; and count various blind spot impacts of the blind spot type according to the feature data; A database is established to integrate various blind spot types, blind spot identification features and blind spot impacts into blind spot data; each blind spot data is input into the database for storage, and the current database is marked as a blind spot library.

4. The IT operation and maintenance service intelligent management and control system according to claim 1, characterized in that: Methods for analyzing operation and maintenance detail data include: Acquire the field data of each operation and maintenance blind spot, match the corresponding blind spot data according to the operation and maintenance blind spot, identify the impact of each blind spot in the blind spot data, analyze the impact of each blind spot according to the field data, and obtain each operation and maintenance hidden danger corresponding to the operation and maintenance blind spot; Perform an impact analysis on each operation and maintenance hidden danger to obtain the impact value of each operation and maintenance hidden danger and the corresponding hidden danger probability; the value range of the impact value is [0, 100]; According to the formula Calculate the blind spot adjustment value of each operation and maintenance blind spot; Where: PL is the blind zone adjustment value; i represents the operation and maintenance hidden danger, i = 1, 2, ..., n, n is a positive integer; YCi is the impact value; ηi is the hidden danger probability; According to the blind spot adjustment value, each operation and maintenance blind spot is classified and counted to obtain a blind spot detail list, which is sent to the user to determine each blind spot to be overcome.

5. The IT operation and maintenance service intelligent management and control system according to claim 1, characterized in that: Methods for performing operation and maintenance analysis on each monitoring target based on the operation and maintenance display model include: Conduct correlation evaluation on each monitoring target and determine the related monitoring targets; classify the related monitoring targets into one category and mark them as the related category; Identify the monitoring data of each monitoring target, perform anomaly analysis on the monitoring data based on the association class corresponding to the monitoring target, and obtain the anomaly analysis results corresponding to each monitoring target in the association class; Obtain the operation and maintenance standards of each monitoring target, calibrate the corresponding monitoring data according to each operation and maintenance standard, obtain the corresponding operation and maintenance verification results, and integrate the operation and maintenance verification results and abnormal analysis results into the operation and maintenance analysis results of the monitoring target.

6. The IT operation and maintenance service intelligent management and control system according to claim 1, characterized in that: Methods for performing abnormal analysis on monitoring data based on the association classes corresponding to the monitoring targets include: Establish an associated evaluation model, the expression of the associated evaluation model is: In the formula: q is the input data, the input data is each monitoring data; the output data is the abnormal correlation value GL(q); The monitoring data corresponding to the monitoring targets in the association class are analyzed through the association evaluation model to obtain the abnormal association values ​​between the monitoring data; the abnormal analysis results of each monitoring target are determined according to the abnormal association values.

7. The IT operation and maintenance service intelligent management and control system according to claim 1, characterized in that: It also includes a prediction analysis module, which is used to perform operation and maintenance prediction analysis and identify the operation and maintenance analysis results of each monitoring target; mark each monitoring target whose operation and maintenance analysis result is normal as a candidate target, calculate the degree of deviation between the monitoring data of the candidate target and the operation and maintenance standard, and mark the candidate target whose deviation degree is less than a threshold value X3 as a prediction target; Establish a prediction model, predict each prediction target through the prediction model, obtain the corresponding prediction data, and determine the corresponding prediction deviation in real time according to the prediction data and operation and maintenance standards; generate a corresponding prediction curve according to the prediction deviation corresponding to each time, with the horizontal axis being time and the vertical axis being the prediction deviation, and the prediction deviation corresponding to t=0 being the deviation degree; Perform forecast evaluation according to the forecast curve to obtain corresponding forecast evaluation results; input the forecast evaluation results into the operation and maintenance display model for display.

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