A server monitoring system with abnormal alarm function

Abstract

The present invention relates to a server monitoring system with abnormal alarm function, and in particular to the field of server monitoring technology, including an information collection module for collecting server operation information; a real-time monitoring module for real-time monitoring of the server after collecting the server operation information, the real-time monitoring module is connected to the information collection module; a statistical monitoring module for statistically monitoring the server after collecting the server operation information, the statistical monitoring module is connected to the information collection module; a safety guarantee module for warning users when the server is in a dangerous state and taking safeguard measures for the server data, the safety guarantee module is connected to the real-time monitoring module and the statistical monitoring module. The present invention improves the server monitoring efficiency by performing real-time monitoring and statistical monitoring on the server, and performing safety guarantee on the server according to the real-time monitoring and statistical monitoring results.

Description

Technical Field

[0001] The present invention relates to the technical field of server monitoring, and in particular to a server monitoring system with an abnormal alarm function. Background Art

[0002] A server refers to a dedicated computer that provides certain services to clients in a network environment. It has high-speed CPU computing power, long-term reliable operation, strong I / O external data throughput capacity and better scalability. By real-time monitoring of the server, server failures or anomalies can be discovered in time, so that corresponding measures can be taken, such as emergency repairs or switching to backup servers, to ensure business continuity and avoid business interruptions. By monitoring the server, any possible security risks or violations can be discovered and reported, such as unauthorized access, malware infection, etc., so that corresponding security measures can be taken in time to protect the security of the server and data. By monitoring and analyzing server performance data, the performance bottlenecks and causes of the server can be understood, so as to carry out targeted performance optimization and improve the response speed and throughput of the server. By monitoring the usage of server resources, server resources can be reasonably allocated and scheduled to avoid resource waste and cost overruns. By monitoring and analyzing server operation data, server failures and problems can be quickly located and eliminated, shortening fault recovery time and reducing losses.

[0003] Chinese Patent Publication No.: CN111679958A discloses a server monitoring system, in which the data acquisition module transmits the collected server information data to the data processing module, the data processing module identifies, analyzes, processes the obtained server information data and transmits the processed data to the data storage module for storage, the data of the data storage module is summarized and visualized through the data display module, the data processing module transmits the abnormal information to the alarm module to trigger the alarm when identifying the server abnormality, and the operation and maintenance assistant module is connected to the data processing module through the data transmission module and monitors the system operation. However, this solution does not perform statistical monitoring on the server in combination with the server's statistical information, and does not perform pre-alarm monitoring on the server, and cannot improve the monitoring efficiency of the server. Summary of the invention

[0004] To this end, the present invention provides a server monitoring system with an abnormal alarm function to overcome the problem of low efficiency of server monitoring in the prior art.

[0005] To achieve the above object, the present invention provides a server monitoring system with abnormal alarm function, comprising:

[0006] Information collection module, used to collect server operation information;

[0007] A real-time monitoring module is used to monitor the server in real time after collecting the server operation information. The real-time monitoring module is provided with a pre-alarm monitoring unit, which is used to calculate the pre-alarm coefficient according to the CPU utilization rate and pre-alarm the user according to the pre-alarm coefficient. The real-time monitoring module is also provided with a compensation unit, which is used to compensate the calculation process of the pre-alarm coefficient according to the memory utilization rate. The real-time monitoring module is also provided with an adjustment unit, which is used to adjust the compensation process according to the server temperature. The real-time monitoring module is also provided with an actual alarm unit, which is used to alarm the user according to the status light signal;

[0008] A statistical monitoring module is used to perform statistical monitoring on the server after collecting the server operation information. The statistical monitoring module is provided with a statistical model unit, which is used to build a statistical model according to the historical fault data of the server. The statistical monitoring module is provided with a result output unit, which is used to output the possibility of fault according to the operation of the statistical model. The statistical monitoring module is provided with a statistical alarm unit, which is used to analyze according to the possibility of fault and alarm the user;

[0009] The security module is used to warn users when the server is in a dangerous state and take security measures for server data. The security module is provided with a risk assessment unit, which is used to assess the server risk based on the number of invalid pre-warnings and the number of invalid statistical alarms. The security module is provided with a correction unit, which is used to correct the server risk assessment process based on the server running time. The security module is provided with an adjustment unit, which is used to adjust the correction process based on the server memory usage. The security module is provided with a risk protection unit, which is used to take security measures for the server based on the server risk assessment results.

[0010] Furthermore, the pre-alarm monitoring unit calculates the pre-alarm coefficient B according to the CPU utilization A, and sets B=1 / [1+e -(A-A0)^2 ], and compare the warning coefficient B with the preset warning coefficient B0, and issue a warning to the user according to the comparison result, where:

[0011] When B≤B0, the pre-warning monitoring unit does not issue a pre-warning to the user;

[0012] When B>B0, the pre-warning monitoring unit issues a pre-warning to the user.

[0013] Further, the compensation unit compares the memory usage rate C with the preset memory usage rate C0, and determines the compensation of the pre-warning coefficient according to the comparison result, wherein:

[0014] When C≤C0, the compensation unit determines not to compensate the pre-warning coefficient;

[0015] When C>C0, the compensation unit determines to compensate the pre-warning coefficient, and the compensation coefficient is D, and D=1+[1- e -C ] / C, the pre-warning coefficient after compensation is Bd, and Bd=B×D is set.

[0016] Further, the adjustment unit compares the server temperature F with the preset server temperature F0, and determines the adjustment of the compensation process according to the comparison result, wherein:

[0017] When F≤F0, the adjustment unit determines not to adjust the compensation process;

[0018] When F>F0, the adjustment unit determines to adjust the compensation process, the adjustment coefficient is G, and G=2-e -2F , the adjusted compensation coefficient is Dg, set Dg=D×G.

[0019] Furthermore, the actual alarm unit determines the server status according to the status light signal, wherein:

[0020] When the status light signal is in the on state, the actual alarm unit determines that the server is in a normal state;

[0021] When the status light signal is in an off state, the actual alarm unit determines that the server is in an abnormal state, the actual alarm unit warns the user, and pushes hardware detection information to the user end.

[0022] Furthermore, the statistical model unit obtains historical fault data of the server, cleans the historical fault data, extracts features related to hardware faults from the historical fault data, and builds a statistical model based on the historical fault data of the server;

[0023] The result output unit inputs the server operation information into the statistical model and outputs the failure possibility of the server;

[0024] The statistical alarm unit compares the fault probability R with the preset fault probability R0, and warns the user according to the comparison result, wherein:

[0025] When R≤R0, the statistical alarm unit determines not to issue an alarm to the user;

[0026] When R>R0, the statistical alarm unit determines to issue an alarm to the user, and pushes the time point as the fault time point to the user.

[0027] Further, the risk assessment unit calculates the risk coefficient L according to the number of invalid pre-alarms H and the number of invalid statistical alarms K within a preset assessment period, and sets L=0.7×H+0.3×K. The risk assessment unit compares the risk coefficient L with the preset risk coefficient L0, and assesses the server risk according to the comparison result, wherein:

[0028] When L≤L0, the risk assessment unit determines that the server is in a safe operating state;

[0029] When L>L0, the risk assessment unit determines that the server is in a dangerous operating state.

[0030] Further, the correction unit compares the server running time M with the preset server running time M0, and judges the correction of the server risk assessment process according to the comparison result, wherein:

[0031] When M≤M0, the correction unit determines not to correct the server risk assessment process;

[0032] When M>M0, the correction unit determines to correct the server risk assessment process and sets the correction coefficient N=2-e -M +sin(M), the corrected risk factor is LN, and LN=L×N is set.

[0033] Further, the adjustment unit compares the server memory usage P with the preset server memory usage P0, and judges the adjustment status of the correction process according to the comparison result, wherein:

[0034] When P≤P0, the adjustment unit determines not to adjust the correction process;

[0035] When P>P0, the adjustment unit determines to adjust the correction process and sets the adjustment coefficient Q=1+[1 - e （p -p0） ] / p, the correction coefficient after adjustment is NQ, set NQ=Q×N.

[0036] Furthermore, the risk protection unit determines the security status of the server according to the server risk assessment result, wherein:

[0037] When the server risk assessment result is a safe operation state, the risk protection unit determines not to take protection measures for the server;

[0038] When the server risk assessment result is a dangerous operating state, the risk protection unit determines to take protection measures for the server.

[0039] Compared with the prior art, the beneficial effect of the present invention lies in that the system collects server operation information through the information collection module to facilitate subsequent analysis based on the server operation information, the system also performs real-time analysis on the server operation information through the real-time monitoring module to monitor the server in real time, thereby improving the monitoring efficiency of the server, the system also analyzes the historical fault data of the server through the statistical monitoring module to perform statistical monitoring of the server, thereby monitoring the possibility of server failure, further improving the monitoring efficiency of the server, the system also warns servers in dangerous states through the security assurance module, and takes security measures for server data to ensure data security, thereby further improving the monitoring efficiency of the server.

[0040] In particular, the pre-alarm monitoring unit calculates the pre-alarm coefficient according to the CPU utilization, and issues a pre-alarm to the user according to the pre-alarm coefficient, so as to prompt the user before the failure occurs, so that the user has sufficient time to respond to the failure, reducing the possibility of server failure, thereby improving server monitoring efficiency.

[0041] In particular, the compensation unit compensates the pre-warning coefficient when the memory usage rate is greater than the preset memory usage rate to improve the calculation accuracy of the pre-warning coefficient, thereby improving the accuracy of pre-warning judgment and further improving the server monitoring efficiency.

[0042] In particular, the adjustment unit adjusts the compensation process when the server temperature is greater than a preset server temperature, so as to add the impact of the server temperature on server failure when the server temperature is too high, improve the accuracy of the compensation process, and thus improve the monitoring efficiency of the server.

[0043] In particular, the statistical model unit cleans the historical fault data to eliminate abnormal values, missing values, duplicate values, etc., thereby improving the quality and accuracy of the data, so as to improve the accuracy of the statistical model building, thereby improving the monitoring efficiency of the server.

[0044] In particular, the statistical alarm unit warns the user when the failure possibility is greater than the preset failure possibility, and pushes the time point as the failure time point to the user, so that the user can prevent the server failure, thereby predicting the server failure and further improving the server monitoring efficiency.

[0045] In particular, the risk assessment unit calculates the risk coefficient by combining the number of invalid pre-alarms and the number of invalid statistical alarms to predict the dangerous state of the server, thereby jointly monitoring the server and further improving the server monitoring efficiency.

[0046] In particular, the correction unit corrects the server risk assessment process when the server running time is greater than the preset server running time to improve the accuracy of the risk assessment process, thereby improving the accuracy of predicting the server's dangerous state and further improving the server monitoring efficiency.

[0047] In particular, the adjustment unit adjusts the correction process when the server memory usage is greater than the preset server memory usage to improve the accuracy of the correction, thereby improving the accuracy of predicting the dangerous state of the server and further improving the server monitoring efficiency.

[0048] In particular, when the server is in a dangerous operating state, the risk protection unit takes protection measures on the server to ensure the security of the server data, thereby improving the server monitoring efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a schematic diagram of the structure of the server monitoring system with abnormal alarm function in this embodiment;

[0050] Figure 2 This is a structural diagram of the real-time monitoring module of this embodiment;

[0051] Figure 3 This is a schematic diagram of the structure of the statistical monitoring module of this embodiment;

[0052] Figure 4 Schematic diagram of the structure of the security module of this embodiment. Implementation

[0053] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0054] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0055] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] See also Figure 1As shown, it is a structural diagram of a server monitoring system with abnormal alarm function, and the system includes:

[0057] Information collection module, used to collect server operation information;

[0058] A real-time monitoring module is used to monitor the server in real time after collecting the server operation information, and the real-time monitoring module is connected to the information collection module;

[0059] A statistical monitoring module is used to perform statistical monitoring on the server after collecting the server operation information, and the statistical monitoring module is connected to the information collection module;

[0060] The security module is used to warn users when the server is in a dangerous state and take security measures for server data. The security module is connected to the real-time monitoring module and the statistical monitoring module.

[0061] Specifically, the system is arranged at the server operation end, and monitors the server operation process by collecting server operation information and performing real-time analysis and statistical analysis on the server operation information, so as to improve the server monitoring efficiency. The system collects the server operation information through the information collection module, so as to facilitate the subsequent analysis based on the server operation information. The system also performs real-time analysis on the server operation information through the real-time monitoring module to perform real-time monitoring of the server, so as to improve the monitoring efficiency of the server. The system also analyzes the historical fault data of the server through the statistical monitoring module to perform statistical monitoring on the server, so as to monitor the possibility of server failure, and further improve the monitoring efficiency of the server. The system also issues an alarm to the server in a dangerous state through the security module, and takes security measures for the server data to ensure data security, so as to further improve the monitoring efficiency of the server.

[0062] Specifically, the server operation information includes CPU utilization, memory usage, server temperature, status light signal, server operation time and server memory usage.

[0063] See also Figure 2 As shown, it is a structural diagram of a real-time monitoring module, and the real-time monitoring module includes:

[0064] A pre-alarm monitoring unit is used to calculate a pre-alarm coefficient according to CPU utilization and issue a pre-alarm to the user according to the pre-alarm coefficient;

[0065] A compensation unit, used for compensating the calculation process of the pre-alarm coefficient according to the memory usage rate, and the compensation unit is connected to the pre-alarm monitoring unit;

[0066] An adjustment unit, used for adjusting the compensation process according to the server temperature, the adjustment unit being connected to the compensation unit;

[0067] The actual alarm unit is used to alarm the user according to the status light signal, and the actual alarm unit is connected to the pre-alarm monitoring unit.

[0068] See also Figure 3 As shown, it is a structural diagram of a statistical monitoring module, and the statistical monitoring module includes:

[0069] A statistical model unit, used to build a statistical model based on the historical failure data of the server;

[0070] A result output unit, used to output the possibility of failure according to the operation of the statistical model, and the result output unit is connected to the statistical model unit;

[0071] The statistical alarm unit is used to analyze according to the possibility of failure and warn the user. The statistical alarm unit is connected to the result output unit.

[0072] See also Figure 4 As shown, it is a schematic diagram of the structure of the security module, and the security module includes:

[0073] A risk assessment unit, used to assess the risk of the server based on the number of invalid pre-alarms and the number of invalid statistical alarms;

[0074] A correction unit, used to correct the server risk assessment process according to the server running time, the correction unit is connected to the risk assessment unit;

[0075] An adjustment unit, used for adjusting the correction process according to the memory usage of the server, the adjustment unit is connected to the correction unit;

[0076] The risk protection unit is used to take protection measures for the server according to the server risk assessment result, and the risk protection unit is connected to the risk assessment unit.

[0077] Specifically, the pre-alarm monitoring unit calculates the pre-alarm coefficient B according to the CPU utilization A, and sets B=1 / [1+e -(A-A0)^2 ], e is the base of the natural logarithm, and the warning coefficient B is compared with the preset warning coefficient B0, and a warning is issued to the user according to the comparison result, where:

[0078] When B≤B0, the pre-warning monitoring unit does not issue a pre-warning to the user;

[0079] When B>B0, the pre-warning monitoring unit issues a pre-warning to the user.

[0080] Specifically, the CPU utilization refers to the degree to which the central processing unit of a computer occupies CPU resources during working hours. This embodiment does not limit the method for collecting CPU utilization, and technical personnel in this field can set it freely, as long as the need for accurate collection of CPU utilization is met. For example, the CPU utilization can be collected by using tools provided by the operating system, such as the top command or htop command in Linux. The pre-alarm refers to an alarm reminder to the user before a server failure occurs. This embodiment does not limit the method for pre-alarm, and technical personnel in this field can set it freely, as long as the need for users to pay full attention is met. For example, the pre-alarm method can be set to pop up a pre-alarm window to prompt the user to prevent server failures.

[0081] Specifically, the pre-alarm monitoring unit calculates the pre-alarm coefficient according to the CPU utilization, and issues a pre-alarm to the user according to the pre-alarm coefficient, so as to prompt the user before the failure occurs, so that the user has sufficient time to respond to the failure, reduce the possibility of server failure, and thus improve server monitoring efficiency.

[0082] Specifically, the compensation unit compares the memory usage rate C with the preset memory usage rate C0, and determines the compensation of the pre-warning coefficient according to the comparison result, wherein:

[0083] When C≤C0, the compensation unit determines not to compensate the pre-warning coefficient;

[0084] When C>C0, the compensation unit determines to compensate the pre-warning coefficient, and the compensation coefficient is D, and D=1+[1- e -C ] / C, e is the base of the natural logarithm, the compensated warning coefficient is Bd, and Bd=B×D is set.

[0085] Specifically, the memory usage of the server refers to the amount of memory used by the server within a specific period of time. This embodiment does not limit the method for collecting the memory usage, and those skilled in the art can set it freely as long as the collection requirements for the memory usage are met. For example, the memory usage can be collected through server monitoring software, such as Zabbix, Nagios, Prometheus, etc.

[0086] Specifically, the compensation unit compensates the pre-warning coefficient when the memory usage rate is greater than the preset memory usage rate to improve the calculation accuracy of the pre-warning coefficient, thereby improving the accuracy of the pre-warning judgment and further improving the server monitoring efficiency.

[0087] Specifically, the adjustment unit compares the server temperature F with the preset server temperature F0, and determines the adjustment of the compensation process according to the comparison result, wherein:

[0088] When F≤F0, the adjustment unit determines not to adjust the compensation process;

[0089] When F>F0, the adjustment unit determines to adjust the compensation process, the adjustment coefficient is G, and G=2-e -2F , e is the base of the natural logarithm, the adjusted compensation coefficient is Dg, and Dg=D×G is set.

[0090] Specifically, the server temperature refers to the temperature state maintained by the server hardware equipment when it is working. The server hardware equipment includes CPU, memory, hard disk, motherboard, etc. These devices will generate heat when working. If the internal temperature of the server is too high, it will affect the performance and stability of the server. In severe cases, it may cause the server to crash or be damaged. This embodiment does not limit the method for collecting the server temperature. Technical personnel in this field can set it freely as long as the accurate collection requirements of the server temperature are met. For example, the server temperature can be collected by using hardware detection tools, such as Intel's Hardware Monitor, AMD's PC Health Check, etc.

[0091] Specifically, the adjustment unit adjusts the compensation process when the server temperature is greater than a preset server temperature, so as to add the impact of the server temperature on server failure when the server temperature is too high, improve the accuracy of the compensation process, and thus improve the monitoring efficiency of the server.

[0092] Specifically, the actual alarm unit determines the server status according to the status light signal, wherein:

[0093] When the status light signal is in the on state, the actual alarm unit determines that the server is in a normal state;

[0094] When the status light signal is in an off state, the actual alarm unit determines that the server is in an abnormal state, the actual alarm unit warns the user, and pushes hardware detection information to the user end.

[0095] It is understandable that the present embodiment does not limit the way in which the actual alarm unit warns the user, and those skilled in the art can freely set it, and it is only necessary to meet the need to prompt the user with the alarm information that the server has failed, such as setting a high-frequency flashing alarm on the user side to warn the user.

[0096] Specifically, the status light refers to a signal light that displays the operating status of the server. This embodiment does not limit the method for collecting the status light signal, and technical personnel in this field can set it freely as long as the collection requirements for the status light signal are met. For example, hardware detection tools can be used to collect status light signals, for example, Intel's Hardware Monitor, AMD's PC Health Check. The hardware detection information refers to the detection information when a server failure occurs, such as the server's fault log.

[0097] Specifically, the statistical model unit obtains historical fault data of the server, cleans the historical fault data, extracts features related to hardware failures from the historical fault data, and builds a statistical model based on the historical fault data of the server.

[0098] Specifically, the historical fault data includes the date, time, type, etc. of the fault. This embodiment does not limit the method for obtaining the historical fault data, and those skilled in the art can freely set it, as long as the demand for obtaining the historical fault data is met. For example, the historical fault data can be obtained through the log file of the server. This embodiment does not limit the cleaning and processing method of the historical fault data, and those skilled in the art can freely set it, as long as the demand for improving the quality of the historical fault data is met. For example, it can be set to remove duplicate data by identifying a unique field or using a deduplication function or a merging function, use the mean, median, mode, etc. to fill in missing values, or use interpolation methods, such as using regression models, random forests, etc. to predict Measure missing values, use statistical methods, such as standard deviation, box plots, etc. to detect outliers, use machine learning techniques, such as clustering methods, classification methods, etc. to identify and process outliers, use z-score or minimum and maximum standardization methods to map data to a specified range and standardize the data to ensure data normalization and consistency. The features related to hardware failures include the frequency, interval time, and type of failures. This embodiment does not limit the way of building a statistical model, and those skilled in the art can set it freely as long as the requirements for building a statistical model are met. For example, the statistical model can be built through machine learning algorithms such as vector machines, neural networks, and decision trees.

[0099] Specifically, the statistical model unit cleans the historical fault data to eliminate abnormal values, missing values, and duplicate values, etc., to improve the quality and accuracy of the data, so as to improve the accuracy of the statistical model building, thereby improving the monitoring efficiency of the server.

[0100] Specifically, the result output unit inputs the server operation information into the statistical model and outputs the failure possibility of the server.

[0101] Specifically, the failure possibility refers to the probability of the server failing at each time point, such as there is a 50% probability that the server will fail in the next 15 minutes.

[0102] Specifically, the statistical alarm unit compares the fault probability R with the preset fault probability R0, and warns the user according to the comparison result, wherein:

[0103] When R≤R0, the statistical alarm unit determines not to issue an alarm to the user;

[0104] When R>R0, the statistical alarm unit determines to issue an alarm to the user, and pushes the time point as the fault time point to the user.

[0105] It is understandable that this embodiment does not set the way in which the statistical alarm unit warns the user. Technical personnel in this field can set it freely, and it is only necessary to meet the need to prompt the user at the time of the fault. For example, a pop-up window prompt at the user end at the time of the fault can be set to warn the user.

[0106] Specifically, when the failure possibility is greater than the preset failure possibility, the statistical alarm unit warns the user and pushes the time point as the failure time point to the user, so that the user can prevent the server failure, thereby predicting the server failure and further improving the server monitoring efficiency.

[0107] Specifically, the risk assessment unit calculates the risk coefficient L according to the number of invalid pre-alarms H and the number of invalid statistical alarms K within a preset assessment period, and sets L=0.7×H+0.3×K. The risk assessment unit compares the risk coefficient L with the preset risk coefficient L0, and assesses the server risk according to the comparison result, wherein:

[0108] When L≤L0, the risk assessment unit determines that the server is in a safe operating state;

[0109] When L>L0, the risk assessment unit determines that the server is in a dangerous operating state.

[0110] Specifically, the preset evaluation period refers to the period for evaluating the server risk, such as one month; the number of invalid pre-alarms refers to the number of times the server is in an abnormal state within the pre-alarm time period after the pre-alarm is issued to the user; the pre-alarm time period refers to the time period during which the pre-alarm is valid, such as two hours; the number of invalid statistical alarms refers to the number of times the server is in an abnormal state at the time of the failure after the statistical alarm unit issues an alarm to the user.

[0111] Specifically, the risk assessment unit calculates the risk coefficient by combining the number of invalid pre-alarms and the number of invalid statistical alarms to predict the dangerous state of the server, thereby jointly monitoring the server and further improving the server monitoring efficiency.

[0112] Specifically, the correction unit compares the server running time M with the preset server running time M0, and determines the correction of the server risk assessment process according to the comparison result, wherein:

[0113] When M≤M0, the correction unit determines not to correct the server risk assessment process;

[0114] When M>M0, the correction unit determines to correct the server risk assessment process and sets the correction coefficient N=2-e -M +sin(M), e is the base of the natural logarithm, the corrected risk factor is LN, and LN=L×N is set.

[0115] Specifically, the server running time refers to the length of time from the start of the server hardware device running to the current moment. This embodiment does not limit the collection method of the server running time. Technical personnel in this field can set it freely as long as the collection requirements of the server running time are met, such as using the command line tools provided by the operating system, such as the uptime command in Linux, the task manager in Windows, etc. to collect the server running time.

[0116] Specifically, the correction unit corrects the server risk assessment process when the server running time is greater than the preset server running time to improve the accuracy of the risk assessment process, thereby improving the accuracy of predicting the server's dangerous state and further improving the server monitoring efficiency.

[0117] Specifically, the adjustment unit compares the server memory usage P with the preset server memory usage P0, and determines the adjustment status of the correction process according to the comparison result, wherein:

[0118] When P≤P0, the adjustment unit determines not to adjust the correction process;

[0119] When P>P0, the adjustment unit determines to adjust the correction process and sets the adjustment coefficient Q=1+[1 - e （p -p0） ] / p, e is the base of the natural logarithm, the adjusted correction coefficient is NQ, and NQ=Q×N is set.

[0120] Specifically, the server memory usage refers to the amount of memory used by the server. This embodiment does not limit the method for collecting the server memory usage. Technical personnel in this field can set it freely as long as the collection requirements for the server memory usage are met. For example, third-party libraries can be used, such as the Boost.Process library and Poco library in C++, the ManagementFactory class in Java, etc. to collect memory usage.

[0121] Specifically, the adjustment unit adjusts the correction process when the server memory usage is greater than the preset server memory usage to improve the accuracy of the correction, thereby improving the accuracy of predicting the server's dangerous state and further improving the server monitoring efficiency.

[0122] Specifically, the risk protection unit determines the security status of the server according to the server risk assessment result, wherein:

[0123] When the server risk assessment result is a safe operation state, the risk protection unit determines not to take protection measures for the server;

[0124] When the server risk assessment result is a dangerous operating state, the risk protection unit determines to take protection measures for the server.

[0125] Specifically, the security measures refer to measures for ensuring the security of server data. This embodiment does not limit the specific content of the security measures, and those skilled in the art can freely set them, such as using a backup storage device to store server data.

[0126] Specifically, when the server is in a dangerous operating state, the danger protection unit takes protection measures on the server to ensure the security of server data, thereby improving the server monitoring efficiency.

[0127] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A server monitoring system with abnormal alarm function, characterized in that: include: Information collection module, used to collect server operation information; A real-time monitoring module is used to monitor the server in real time after collecting the server operation information. The real-time monitoring module is provided with a pre-alarm monitoring unit, which is used to calculate the pre-alarm coefficient according to the CPU utilization rate and pre-alarm the user according to the pre-alarm coefficient. The real-time monitoring module is also provided with a compensation unit, which is used to compensate the calculation process of the pre-alarm coefficient according to the memory utilization rate. The real-time monitoring module is also provided with an adjustment unit, which is used to adjust the compensation process according to the server temperature. The real-time monitoring module is also provided with an actual alarm unit, which is used to alarm the user according to the status light signal; A statistical monitoring module is used to perform statistical monitoring on the server after collecting the server operation information. The statistical monitoring module is provided with a statistical model unit, which is used to build a statistical model according to the historical fault data of the server. The statistical monitoring module is provided with a result output unit, which is used to output the possibility of fault according to the operation of the statistical model. The statistical monitoring module is provided with a statistical alarm unit, which is used to analyze according to the possibility of fault and alarm the user; The security module is used to warn users when the server is in a dangerous state and take security measures for server data. The security module is provided with a risk assessment unit, which is used to assess the server risk based on the number of invalid pre-warnings and the number of invalid statistical alarms. The security module is provided with a correction unit, which is used to correct the server risk assessment process based on the server running time. The security module is provided with an adjustment unit, which is used to adjust the correction process based on the server memory usage. The security module is provided with a risk protection unit, which is used to take security measures for the server based on the server risk assessment results.

2. The server monitoring system with abnormal alarm function according to claim 1 is characterized in that: The pre-alarm monitoring unit calculates the pre-alarm coefficient B according to the CPU utilization A, and sets B=1 / [1+e -(A-A0)^2 ], and compare the warning coefficient B with the preset warning coefficient B0, and issue a warning to the user according to the comparison result, where: When B≤B0, the pre-warning monitoring unit does not issue a pre-warning to the user; When B>B0, the pre-warning monitoring unit issues a pre-warning to the user.

3. The server monitoring system with abnormal alarm function according to claim 2 is characterized in that: The compensation unit compares the memory usage rate C with the preset memory usage rate C0, and determines the compensation of the pre-warning coefficient according to the comparison result, wherein: When C≤C0, the compensation unit determines not to compensate the pre-warning coefficient; When C>C0, the compensation unit determines to compensate the pre-warning coefficient, and the compensation coefficient is D, and D=1+[1 - e -C ] / C, the pre-warning coefficient after compensation is Bd, and Bd=B×D is set.

4. The server monitoring system with abnormal alarm function according to claim 3 is characterized in that: The adjustment unit compares the server temperature F with the preset server temperature F0, and determines the adjustment of the compensation process according to the comparison result, wherein: When F≤F0, the adjustment unit determines not to adjust the compensation process; When F>F0, the adjustment unit determines to adjust the compensation process, the adjustment coefficient is G, and G=2-e -2F , the adjusted compensation coefficient is Dg, set Dg=D×G.

5. The server monitoring system with abnormal alarm function according to claim 4 is characterized in that: The actual alarm unit determines the server status according to the status light signal, wherein: When the status light signal is in the on state, the actual alarm unit determines that the server is in a normal state; When the status light signal is in an off state, the actual alarm unit determines that the server is in an abnormal state, the actual alarm unit warns the user, and pushes hardware detection information to the user end.

6. The server monitoring system with abnormal alarm function according to claim 1 is characterized in that: The statistical model unit obtains historical fault data of the server, cleans the historical fault data, extracts features related to hardware faults from the historical fault data, and builds a statistical model based on the historical fault data of the server; The result output unit inputs the server operation information into the statistical model and outputs the failure possibility of the server; The statistical alarm unit compares the failure probability R with the preset failure probability R0, and warns the user according to the comparison result. The failure probability refers to the probability of failure of the server at each time point, where: When R≤R0, the statistical alarm unit determines not to issue an alarm to the user; When R>R0, the statistical alarm unit determines to issue an alarm to the user, and pushes the time point as the fault time point to the user.

7. The server monitoring system with abnormal alarm function according to claim 1 is characterized in that: The risk assessment unit calculates the risk coefficient L according to the number of invalid pre-alarms H and the number of invalid statistical alarms K within a preset assessment period, and sets L=0.7×H+0.3×K. The risk assessment unit compares the risk coefficient L with the preset risk coefficient L0, and assesses the server risk according to the comparison result, wherein: When L≤L0, the risk assessment unit determines that the server is in a safe operating state; When L>L0, the risk assessment unit determines that the server is in a dangerous operating state.

8. The server monitoring system with abnormal alarm function according to claim 7 is characterized in that: The correction unit compares the server running time M with the preset server running time M0, and determines the correction of the server risk assessment process according to the comparison result, wherein: When M≤M0, the correction unit determines not to correct the server risk assessment process; When M>M0, the correction unit determines to correct the server risk assessment process and sets the correction coefficient N=2-e -M +sin(M), the corrected risk factor is LN, and LN=L×N is set.

9. The server monitoring system with abnormal alarm function according to claim 8 is characterized in that: The adjustment unit compares the server memory usage P with the preset server memory usage P0, and determines the adjustment status of the correction process according to the comparison result, wherein: When P≤P0, the adjustment unit determines not to adjust the correction process; When P>P0, the adjustment unit determines to adjust the correction process and sets the adjustment coefficient Q=1+[1 - e （p-p0） ] / p, the correction coefficient after adjustment is NQ, set NQ=Q×N.

10. The server monitoring system with abnormal alarm function according to claim 9, characterized in that: The risk protection unit determines the security status of the server according to the server risk assessment result, wherein: When the server risk assessment result is a safe operation state, the risk protection unit determines not to take protection measures for the server; When the server risk assessment result is a dangerous operating state, the risk protection unit determines to take protection measures for the server.

Images