An intelligent control system for IT operation and maintenance services

Abstract

The present invention discloses an intelligent control system for IT operation and maintenance services, belonging to the technical field of IT operation and maintenance services, and comprising a monitoring and analysis module, a monitoring module and a management module; the monitoring and analysis module is used for analyzing the operation and maintenance monitoring of users, establishing a blind area library, analyzing the operation and maintenance detail data of users to determine operation and maintenance blind areas; analyzing each operation and maintenance blind area to determine each blind area to be overcome; and performing monitoring supplementation on each blind area to be overcome; the monitoring module is used for performing operation and maintenance monitoring, and acquiring the 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; and performing operation and maintenance analysis on each monitoring target based on the operation and maintenance display model to obtain the operation and maintenance analysis results of each monitoring target; the management module is used for performing operation and maintenance management, establishing an operation and maintenance management library; identifying the operation and maintenance analysis results of each monitoring target in real time; matching operation and maintenance treatment measures according to the operation and maintenance analysis results, and performing corresponding operation and maintenance management according to the operation and maintenance treatment measures.

Description

Technical Field

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

[0002] With the rapid development of information technology, enterprise IT systems have become increasingly complex, covering multiple aspects such as network devices, servers, virtualization platforms, databases, and application services. Traditional IT operation and maintenance methods often rely on manual inspections, fault troubleshooting, and manual repairs. This method is not only inefficient but also error-prone, making it difficult to meet the requirements of modern enterprises for the high availability and stability of IT systems. Moreover, traditional monitoring can often only cover some key devices or performance indicators, there are monitoring blind spots, and it cannot comprehensively reflect the overall health status of the IT system, resulting in certain operation and maintenance vulnerabilities.

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

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

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

[0006] An intelligent control system for IT operation and maintenance services includes a monitoring and analysis module, a monitoring module, and a management module;

[0007] The monitoring and analysis module is used to analyze the operation and maintenance monitoring of users, establish a blind spot library, and the blind spot library is used to store various blind spot data, and the blind spot data includes blind spot types, blind spot identification features, and blind spot impacts;

[0008] Obtain the operation and maintenance detail data of users, analyze the operation and maintenance detail data to determine operation and maintenance blind spots; analyze each of the operation and maintenance blind spots to determine each overcoming blind spot; and perform monitoring supplementation on each of the overcoming blind spots.

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

[0010] Based on the blind spot library, establish a blind spot identification model, and the expression of the blind spot identification model is:

[0011]

[0012] In the formula: s is the input data, and the input data is the operation and maintenance detail data of users; the output data is the blind spot identification value MQ(s);

[0013] Analyze the operation and maintenance detail data of users through the blind spot identification model to determine operation and maintenance blind spots.

[0014] Further, the method for establishing the blind area database includes:

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

[0016] Establish a database, integrate each blind area type, blind area recognition feature, and blind area impact into blind area data; input each blind area data into the database for storage, and mark the current database as the blind area database.

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

[0018] Obtain the on-site data of each operation and maintenance blind area, match the corresponding blind area data according to the operation and maintenance blind area, identify each blind area impact in the blind area data, and analyze each blind area impact according to the on-site data to obtain each operation and maintenance hidden danger corresponding to the operation and maintenance blind area.

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

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

[0021] In the formula: PL is the blind area 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] Classify and count each operation and maintenance blind area according to the blind area adjustment value to obtain a blind area detail list, send the blind area detail list to the user, and determine each blind area to be overcome.

[0023] The monitoring module is used to perform operation and maintenance monitoring, determine each monitoring target, and obtain the 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, perform operation and maintenance analysis 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.

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

[0026] Conduct a relevance assessment on each monitoring target to determine the monitoring targets with relevance; classify the monitoring targets with relevance to each other into one category and label it as the associated category;

[0027] Identify the monitoring data of each monitoring target, conduct anomaly analysis on the monitoring data based on the associated category corresponding to the monitoring target, and obtain the anomaly analysis results corresponding to each monitoring target within the associated category;

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

[0029] Furthermore, the method for conducting anomaly analysis on the monitoring data based on the associated category corresponding to the monitoring target includes:

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

[0031]

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

[0033] Analyze the monitoring data corresponding to the monitoring targets within the associated category through the association evaluation model to obtain the anomaly association values between the monitoring data; determine the anomaly analysis results of each monitoring target according to the anomaly association values.

[0034] The management module is used for operation and maintenance management, establishing an operation and maintenance management library, and the operation and maintenance management library is used for storing the operation and maintenance treatment measures corresponding to different operation and maintenance analysis results;

[0035] Real-time identify the operation and maintenance analysis results of each monitoring target; match the corresponding operation and maintenance treatment 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 treatment measures.

[0036] Furthermore, it further includes a prediction analysis module, and the prediction analysis module is used for operation and maintenance prediction analysis, identifying the operation and maintenance analysis results of each monitoring target; marking the monitoring targets with normal operation and maintenance analysis results as candidate targets, calculating the deviation degree between the monitoring data of the candidate targets and the operation and maintenance standards, and marking the candidate targets with a deviation degree less than the threshold X3 as prediction targets;

[0037] Establish a prediction model, predict each prediction target through the prediction model to obtain the corresponding prediction data, and determine the corresponding prediction deviation in real time according to the prediction data and the operation and maintenance standards; generate the corresponding prediction curve according to the prediction deviations 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] Predictive evaluation is carried out according to the prediction curve to obtain the corresponding predictive evaluation result; the predictive evaluation result is input into the operation and maintenance display model for display.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0040] Through the mutual cooperation among the monitoring and analysis module, the monitoring module, the management module and the predictive analysis module, comprehensive monitoring of all levels and dimensions of the IT system is realized, monitoring blind spots are eliminated, and targeted suggestions are provided based on the actual needs of users to achieve comprehensive monitoring; artificial intelligence and machine learning algorithms are used to deeply analyze the monitoring data to identify potential problems and abnormal patterns, providing strong support for operation and maintenance decision-making; through real-time monitoring and intelligent operation and maintenance, the stability and availability of the IT system are ensured, business continuity is improved, and the smooth progress of enterprise business is guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0042] Figure 1 It is a principle block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0044] As Figure 1 shown, an intelligent control system for IT operation and maintenance services includes a monitoring and analysis module, a monitoring module, a management module and a predictive analysis module;

[0045] The monitoring and analysis module is used to analyze the operation and maintenance monitoring of users, establish a blind spot library, and the blind spot library is used to store various blind spot data. The blind spot data includes relevant data such as blind spot type, blind spot identification characteristics, and blind spot impact. The blind spot type is the type of operation and maintenance monitoring blind spot; the blind spot identification characteristics are the operation and maintenance monitoring characteristics that can determine the blind spot type, generally determined by unmonitored devices; the blind spot impact is the potential hazards that the blind spot type may have;

[0046] Establish a blind area recognition model based on the blind area library, that is, recognize based on the blind area recognition features in the data of each blind area. The expression of the blind area recognition model is In the formula: s is the input data, and the input data is the operation and maintenance detail data of the user; the output data is the blind area recognition value MQ(s); meeting the recognition requirements means having blind area recognition features; the operation and maintenance detail data is the detail data of each IT device that can be operated and maintained determined by analyzing each IT device in the user enterprise, and is integrated into the operation and maintenance detail data; it can be integrated into the operation and maintenance detail data in the form of an information graph, which is more intuitive and three-dimensional;

[0047] Obtain the operation and maintenance detail data of the user, analyze the operation and maintenance detail data of the user through the blind area recognition model, and determine the operation and maintenance blind areas;

[0048] Identify the on-site data of the operation and maintenance blind areas, such as relevant data on usage, function, device model, type, etc.; match the corresponding blind area data according to the operation and maintenance blind areas, identify each blind area impact in the blind area data, match each blind area impact according to the on-site data, and obtain the possible blind area impacts of the operation and maintenance blind areas at the user's place, which are marked as operation and maintenance hidden dangers;

[0049] Analyze the impact magnitude of each operation and maintenance hidden danger to obtain the corresponding impact value and the corresponding hidden danger probability. The value range of the impact value is [0, 100]; the impact value that has 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 corresponding impact values are set according to the degree of impact, that is, combined with the operation of the user enterprise for actual judgment. The actual situation after the occurrence of the hidden danger can be assumed, and then the impact value is set; the hidden danger probability is the probability of the occurrence of the operation and maintenance hidden danger. According to the actual situation of the device, etc., statistical analysis is carried out to determine the probability of the occurrence of the operation and maintenance hidden danger, which is marked as the hidden danger probability;

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

[0051] In the formula: PL is the blind area adjustment value; i represents the operation and maintenance hidden danger, i = 1, 2,..., n, and 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 area according to the blind area adjustment value to obtain a blind area detail list. If the blind area adjustment value is 1, it is marked as recommended to overcome, otherwise it is not recommended to solve; send the blind area detail list to the user, and the user determines the operation and maintenance blind areas that need to be solved, which are marked as overcome blind areas;

[0053] Monitor and supplement each overcome blind area to achieve operation and maintenance monitoring of each overcome blind area.

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

[0055] Determine various blind - area operation and maintenance data based on big data, that is, historical relevant data related to blind areas; identify the blind - area operation and maintenance data to determine various blind - area types; obtain the characteristic data corresponding to each blind - area type, that is, the relevant data corresponding to this blind - area type, perform feature recognition on the characteristic data to obtain the blind - area recognition features corresponding to the blind - area type; and statistically analyze various blind - area impacts of this blind - area type based on the characteristic data.

[0056] Establish a database, integrate each blind - area type, blind - area recognition features, and blind - area impacts into blind - area data; input each blind - area data into the database for storage, and mark the current database as the blind - area database.

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

[0058] Perform operation and maintenance analysis on each monitoring target based on the operation and maintenance display model 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.

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

[0060] Perform a relevance assessment on each monitoring target to determine the monitoring targets with relevance; that is, assess according to whether there is an associated impact between the monitoring data of each monitoring target. For example, if there is an association between the monitoring data of a certain monitoring target and the monitoring data of other monitoring targets, and when one changes, the other changes according to the corresponding rule, it can be determined that there is a relevance between the two. That is, for monitoring targets with relevance, their monitoring data has a certain relevance, which is used to verify whether each monitoring data is abnormal when another monitoring problem occurs, such as whether the monitoring is abnormal due to monitoring equipment; the platform can list the monitoring targets with relevance to establish a relevance list, and subsequent matching can be performed.

[0061] Classify the monitoring targets with relevance to each other into one category and mark it as the associated category.

[0062] Identify the monitoring data of each monitoring target, and perform anomaly analysis on the monitoring data based on the associated class corresponding to the monitoring target; obtain the corresponding anomaly analysis results; specifically, determine the relevant monitoring targets based on the relevance detailed list, establish an association evaluation model based on the association of the monitoring data between the monitoring targets, which is used to evaluate the monitoring data to be analyzed based on the association in the normal state, and judge whether the monitoring data meets the relevance requirements. It is established and trained by the platform side; the expression of the association evaluation model is In the formula: q is the input data, and the input data is each monitoring data; the output data is the anomaly association value GL(q);

[0063] Analyze the monitoring data of each monitoring target through the association evaluation model to obtain the anomaly association values between the monitoring data; determine the anomaly analysis results of each monitoring target according to the anomaly association values, that is, whether the monitoring is abnormal.

[0064] Obtain the corresponding operation and maintenance standards of each monitoring target. The operation and maintenance standards are the operating states that the monitoring targets need to achieve and are preset data; check the corresponding monitoring data according to each operation and maintenance standard to obtain the corresponding operation and maintenance check results, and integrate the operation and maintenance check results and the anomaly analysis results into the operation and maintenance analysis results of the monitoring target.

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

[0066] Real-time identify the operation and maintenance analysis results of each monitoring target; match the corresponding operation and maintenance treatment 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 treatment measures.

[0067] The prediction analysis module is used for operation and maintenance prediction analysis to identify the operation and maintenance analysis results of each monitoring target; mark the monitoring targets with normal operation and maintenance analysis results as candidate targets, calculate the deviation degree between the monitoring data of the candidate targets and the operation and maintenance standards. For example, if the operation and maintenance standard is 100 and the monitoring data is 90, the deviation degree is 10; mark the candidate targets with a deviation degree less than the threshold X3 as prediction targets; establish a corresponding prediction model based on the existing prediction technology, predict each prediction target through the prediction model to obtain the corresponding prediction data, and determine the corresponding prediction deviation in real time according to the prediction data and the operation and maintenance standards; generate the 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. The prediction deviation corresponding to t = 0 is the deviation degree;

[0068] Conduct prediction evaluation according to the prediction curve to obtain the corresponding prediction evaluation result; input the prediction evaluation result into the operation and maintenance display model for display.

[0069] The above formulas are all calculated by removing the dimension and taking the numerical value. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation 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 of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An intelligent control system for IT operation and maintenance services, characterized in that, It includes a monitoring and analysis module, a monitoring module, and a management module; The monitoring and analysis module is used to analyze the user's operation and maintenance monitoring, establish a blind area library, and the blind area library is used to store various blind area data, and the blind area data includes blind area types, blind area identification features, and blind area impacts; Obtain the operation and maintenance detail data of the user, analyze the operation and maintenance detail data to determine the operation and maintenance blind areas; analyze each of the operation and maintenance blind areas to determine each blind area to be overcome; Perform monitoring supplementation for each of the blind areas to be overcome; The monitoring module is used to perform operation and maintenance monitoring, determine each monitoring target, and obtain the 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; Perform operation and maintenance analysis on each monitoring target based on the operation and maintenance display model 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, establish an operation and maintenance management library, and the operation and maintenance management library is used to store the 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; The method for analyzing the operation and maintenance detail data includes: Obtain the on-site data of each of the operation and maintenance blind areas, match the corresponding blind area data according to the operation and maintenance blind areas, identify each blind area impact in the blind area data, and analyze each of the blind area impacts according to the on-site data to obtain each operation and maintenance hidden danger corresponding to the operation and maintenance blind area; Perform impact analysis on each operation and maintenance hidden danger to obtain the impact value and the corresponding hidden danger probability of each operation and maintenance hidden danger; the value range of the impact value is [0, 100]; According to the formula Calculate the blind area adjustment value of each operation and maintenance blind area; Where: PL is the blind area adjustment value; , i represents the operation and maintenance hidden danger, i = 1, 2,..., n, n is a positive integer; YCi is the influence value; ηi is the hidden danger probability; Perform classification statistics on each operation and maintenance blind area according to the blind area adjustment value to obtain a blind area detail list, send the blind area detail list to the user, and determine each blind area to be overcome.

2. An intelligent control system for IT operation and maintenance services according to claim 1, characterized in that The method for analyzing the operation and maintenance detail data includes: Build a blind area recognition model based on the blind area library, and the expression of the blind area recognition model is: ; Where: s is the input data, and the input data is the operation and maintenance detail data of the user; the output data is the blind area identification value MQ(s); Analyze the operation and maintenance detail data of the user through a blind area identification model to determine the operation and maintenance blind areas.

3. An intelligent control system for IT operation and maintenance services according to claim 1, characterized in that The method for establishing the blind area library includes: Determine various blind area operation and maintenance data available, identify the various blind area types in the blind area operation and maintenance data, and determine the available blind area types; obtain the characteristic data corresponding to each blind area type, perform feature identification on the characteristic data to obtain the blind area identification features corresponding to the blind area type; and count various blind area impacts of the blind area type according to the characteristic data; Establish a database, integrate each blind area type, blind area identification feature, and blind area impact into blind area data; input each of the blind area data into the database for storage, and mark the current database as the blind area library.

4. An intelligent control system for IT operation and maintenance services according to claim 1, characterized in that The method for performing operation and maintenance analysis on each monitoring target based on the operation and maintenance display model includes: Perform a relevance assessment on each monitoring target to determine the monitoring targets with relevance; classify the monitoring targets with relevance to each other into one category and mark it as the associated category; Identify the monitoring data of each monitoring target, perform anomaly analysis on the monitoring data based on the associated class corresponding to the monitoring target, and obtain the anomaly analysis results corresponding to each monitoring target within the associated class; Obtain the operation and maintenance standards of each monitoring target, check the corresponding monitoring data according to each operation and maintenance standard, obtain the corresponding operation and maintenance check results, and integrate the operation and maintenance check results and the anomaly analysis results into the operation and maintenance analysis results of the monitoring target.

5. An intelligent control system for IT operation and maintenance services according to claim 4, characterized in that, The method for performing anomaly analysis on the monitoring data based on the associated class corresponding to the monitoring target includes: Establish an association evaluation model, and the expression of the association evaluation model is: ; In the formula: q is the input data, and the input data is each monitoring data; the output data is the anomaly correlation value GL(q); Analyze the monitoring data corresponding to the monitoring targets within the associated class through the association evaluation model to obtain the anomaly correlation values between the monitoring data; determine the anomaly analysis results of each monitoring target according to the anomaly correlation values.

6. An intelligent control system for IT operation and maintenance services according to claim 1, characterized in that It further 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 the monitoring targets with normal operation and maintenance analysis results as candidate targets, calculate the deviation degree between the monitoring data of the candidate targets and the operation and maintenance standards, and mark the candidate targets with a deviation degree less than the threshold X3 as prediction targets; Establish a prediction model, predict each prediction target through the prediction model to obtain the corresponding prediction data, and determine the corresponding prediction deviation in real time according to the prediction data and the operation and maintenance standards; generate the corresponding prediction curve according to the prediction deviations 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 prediction evaluation according to the prediction curve to obtain the corresponding prediction evaluation result; input the prediction evaluation result into the operation and maintenance display model for display.

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