WO2020048047A1 - Procédé d'avertissement de défaut de système, appareil, et dispositif, et support d'informations - Google Patents

Procédé d'avertissement de défaut de système, appareil, et dispositif, et support d'informations Download PDF

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Publication number
WO2020048047A1
WO2020048047A1 PCT/CN2018/122807 CN2018122807W WO2020048047A1 WO 2020048047 A1 WO2020048047 A1 WO 2020048047A1 CN 2018122807 W CN2018122807 W CN 2018122807W WO 2020048047 A1 WO2020048047 A1 WO 2020048047A1
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Prior art keywords
parameters
early warning
parameter
monitored
system failure
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PCT/CN2018/122807
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English (en)
Chinese (zh)
Inventor
王伟
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平安科技（深圳）有限公司
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Publication of WO2020048047A1 publication Critical patent/WO2020048047A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
    • G06F11/324—Display of status information
    • G06F11/327—Alarm or error message display
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system

Definitions

  • the present application relates to the field of computer communications, and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for early warning of system failure.
  • a system failure refers to a state in which the system is unable to perform specified functions, or performance degradation does not meet specified requirements.
  • faults may occur. Therefore, fault prediction becomes one of the effective ways to provide system reliability.
  • the existing fault alarm method can only alarm after a fault occurs, that is, when the system parameters exceed a set threshold, thereby giving a fault prompt message, so that the operation and maintenance personnel can take corresponding measures to resolve the fault through manual intervention. For example, migrate the faulty node, replace the faulty node, and so on. However, when the system parameters have exceeded the set threshold, the system abnormality problem has occurred, so the existing failure prediction method cannot achieve the purpose of early warning.
  • the main purpose of this application is to provide a method, device, equipment and computer-readable storage medium for early warning of system failure, which aims to solve the technical problems that the existing failure prediction technology requires manual verification and cannot be early-warned.
  • the present application provides a method for early warning of a system failure.
  • the method for early warning of a system failure includes the following steps:
  • the preset time unit obtain the current parameters to be monitored of the target system in the current time unit;
  • an alarm message is generated according to the abnormal parameter in the current parameter to be monitored and the standard parameter, and the alarm message is reported.
  • the step of obtaining standard parameters in a preset monitoring model and judging whether there is an abnormal parameter in the current parameter to be monitored according to the standard parameters includes:
  • the step of obtaining standard parameters in a preset monitoring model and judging whether there is an abnormal parameter in the current parameter to be monitored according to the standard parameters includes:
  • the method before the step of obtaining the current parameter to be monitored of the target system in the current time unit according to a preset time unit, the method further includes:
  • the abnormal monitoring parameters and the normal monitoring parameters in the parameters to be monitored are classified and stored, and the preset monitoring model is generated by training according to the abnormal monitoring parameters and the normal monitoring parameters.
  • ,Also includes:
  • generating an early warning message according to the abnormal parameter in the current parameter to be monitored and the standard parameter, and reporting the early warning message further includes:
  • an emergency warning message is generated according to the abnormal parameters of the continuous abnormality, and the emergency warning message is sent to a management end.
  • the method further includes:
  • the corresponding target repair strategy is searched in a preset policy library according to the existing anomaly parameters, and abnormality processing is performed according to the target repair strategies.
  • system failure early warning device which is characterized in that the system failure early warning device includes:
  • a parameter acquisition module configured to acquire the current parameters to be monitored of the target system in the current time unit according to a preset time unit
  • a parameter monitoring module configured to obtain standard parameters in a preset monitoring model, and determine whether there are abnormal parameters in the current parameters to be monitored according to the standard parameters;
  • the abnormality early warning module is configured to generate an early warning message according to the abnormal parameter in the current to-be-monitored parameter and the standard parameter if it is determined that the abnormal parameter exists in the current to-be-monitored parameter, and report the early-warning message.
  • the present application also provides a system failure early warning device.
  • the system failure early warning device includes a processor, a memory, and a system failure stored in the memory and executable by the processor.
  • the early-warning program of the method wherein when the early-warning program of the system failure is executed by the processor, the steps of the early-warning method of the system failure are implemented.
  • the present application also provides a computer-readable storage medium, where the computer-readable storage medium stores an early-warning program for system failure, and the early-warning program for system failure is implemented when the early-warning program for system failure is executed by a processor.
  • the application provides a method for early warning of a system failure, that is, obtaining a current parameter to be monitored of a target system in a current time unit according to a preset time unit; obtaining a standard parameter in a preset monitoring model, and judging a location based on the standard parameter. Whether there is an abnormal parameter in the current to-be-monitored parameter; if it is determined that the abnormal parameter exists in the currently-to-be-monitored parameter, generating an early warning message according to the abnormal parameter in the currently-to-be-monitored parameter and the standard parameter, and reporting the early-warning Message.
  • the present application can set the core indicator data of the system as parameters to be monitored, such as memory parameters, application parameters, and business parameters, and perform real-time monitoring of the core monitoring data according to a preset time unit, so that the abnormal core can be detected in time. Monitor the data, so as to provide early warning of system data that is about to occur abnormally, to realize early warning when anomalies are about to occur, and to improve system efficiency.
  • FIG. 1 is a schematic diagram of a hardware structure of a system failure early warning device involved in a solution according to an embodiment of the present application
  • FIG. 2 is a schematic flowchart of a first embodiment of a method for early warning of a system fault in this application;
  • FIG. 3 is a schematic flowchart of a second embodiment of an early warning method for a system fault of the present application
  • FIG. 4 is a schematic flowchart of a third embodiment of an early warning method for a system fault of the present application.
  • FIG. 5 is a schematic diagram of functional modules of a first embodiment of an early warning device for a system failure of the present application.
  • the method for early warning of a system failure is mainly applied to an early warning device for a system failure.
  • the early warning device for the system failure may be a device with display and processing functions such as a PC, a portable computer, or a mobile terminal.
  • FIG. 1 is a schematic diagram of a hardware structure of a system failure early-warning device involved in a solution according to an embodiment of the present application.
  • the early warning device for system failure may include a processor 1001 (such as a CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005.
  • the communication bus 1002 is used to implement connection and communication between these components.
  • the user interface 1003 may include a display and an input unit such as a keyboard.
  • the network interface 1004 may optionally include a standard wired interface and a wireless interface.
  • the memory 1005 can be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory, the memory 1005 may optionally be a storage device independent of the foregoing processor 1001.
  • FIG. 1 does not constitute a limitation on early warning equipment for system failure, and may include more or fewer components than shown in the figure, or combine some components, or different components. Layout.
  • the memory 1005 as a computer-readable storage medium in FIG. 1 may include an operating system, a network communication module, and an early warning program for system failure.
  • the network communication module is mainly used to connect to a server and perform data communication with the server; and the processor 1001 can call a system failure early warning program stored in the memory 1005 and execute the system failure early warning method provided in the embodiment of the present application. .
  • the embodiment of the present application provides a method for early warning of system failure.
  • FIG. 2 is a schematic flowchart of a first embodiment of a system fault early warning method according to the present application.
  • the method for early warning of system failure includes the following steps:
  • Step S10 Acquire the current parameters to be monitored of the target system in the current time unit according to the preset time unit;
  • fault prediction methods are usually rule-based prediction technologies, that is, by collecting system operation information and matching with early warning rules, if there are preset rules that match the system operation information, such as detecting that system parameters are greater than a certain threshold , Indicating that the system has malfunctioned, and thus gives a fault prompt message, so that the operation and maintenance personnel can take corresponding measures to resolve the malfunction through manual intervention, such as migrating the faulty node, replacing the faulty node, etc.
  • detecting that the system parameter is greater than a certain threshold it means that a system failure has occurred, so it is not possible to give early warning of the failure, and the early warning effect cannot be achieved. Therefore, how to solve the problem of untimely warning of existing prediction technology has become a technical problem that needs to be solved at present.
  • a system failure early warning method is provided.
  • the core indicator data of the system such as memory parameters, application parameters, and business parameters, are monitored in real time so that the system that is about to encounter an abnormality can be timely.
  • Data for early warning is Specifically, the historical system data of the target system is collected.
  • the historical system data may be related historical data of the target system for one year or longer, and may include: memory parameters, such as CPU, memory occupation data, disk space data, etc., application parameters. , Such as the number of threads, requests, logs, etc., and business parameters, such as the number of online users, transactions, and the number of uploaded pictures. Counting each parameter in the historical system data according to a preset time unit.
  • the preset time unit refers to a preset time period as a time unit.
  • the preset time unit may be 1 minute, Time set of 5 minutes or 10 minutes. For example, starting at 00:00, 00: 00-00: 01 is a time period, or 00: 00-00: 05 is a time period. If the current time is 12:02, the current time unit is 12: 00-12: 05.
  • each parameter in the historical system data may be correspondingly stored in a time series database, the above parameters are quantified and a two-dimensional table is generated.
  • the horizontal axis of the two-dimensional table is each system parameter (CPU, memory occupation data, disk space data, number of threads, requests, number of logs ...), and the vertical axis is each independent time segment (1 minute or 5 minutes is One time slice), the two-dimensional table stores the system parameter data of each system parameter at each time segment. Annotate the status of each system parameter data. If it is abnormal, you can add an abnormal identification to the abnormal system parameter data. Normalize the abnormal system parameters and non-anomalous system parameters respectively, and then train the preset monitoring model according to the random forest algorithm, the processed abnormal system parameters, and the non-anomalous system parameters, thereby implementing the system through the preset monitoring model Automatic identification of parameter anomalies.
  • changes in system parameters corresponding to system abnormalities can be summarized, such as abnormal network delays, that is, when the network starts to delay but there is no interruption, it will cause the business system's business volume (reduction) and abnormal log volume (increase). Changes in system parameters such as application threads (increase). If the memory usage is abnormal, the system parameters such as CPU (occupancy increase), memory usage (increase), and disk space ratio (increase) will change.
  • step S10 the method further includes:
  • the abnormal monitoring parameters and the normal monitoring parameters in the parameters to be monitored are classified and stored, and the preset monitoring model is generated by training according to the abnormal monitoring parameters and the normal monitoring parameters.
  • each parameter in the historical system data is correspondingly stored in a time series database, and the above parameters are quantized and a two-dimensional table is generated.
  • the horizontal axis of the two-dimensional table is each system parameter (CPU, memory occupation data, disk space data, number of threads, requests, number of logs ...)
  • the vertical axis is each independent time unit (1 minute or 5 minutes is One time slice)
  • the two-dimensional table stores the system parameter data of each system parameter at each time segment. Annotate the status of each system parameter data. If it is abnormal, you can add an abnormal identification to the abnormal system parameter data.
  • Step S20 Obtain a standard parameter in a preset monitoring model, and determine whether there is an abnormal parameter in the current parameter to be monitored according to the standard parameter;
  • the current parameters to be monitored of the target system in the current time period are obtained.
  • the abnormality monitoring of the system parameters can be performed in both horizontal and vertical directions.
  • the horizontal direction may be a system parameter that compares the parameters to be monitored corresponding to each time segment to determine whether there are abnormal fluctuations.
  • the network when the network starts to delay without interruption, it will cause abnormal changes in system parameters such as the business system's business volume (reduction), abnormal log volume (increase), and application threads (increase).
  • system parameters such as the business system's business volume (reduction), abnormal log volume (increase), and application threads (increase).
  • it is difficult to trigger the alarm information because the parameter change does not reach the preset change threshold.
  • each abnormal parameter and corresponding standard data are pushed to the management terminal for abnormal confirmation. Vertically, the current to-be-monitored parameters of the current time segment are compared with the standard to-be-monitored parameters of the corresponding time segment.
  • step S30 if it is determined that the abnormal parameter exists in the current parameter to be monitored, an early warning message is generated according to the abnormal parameter in the current parameter to be monitored and the standard parameter, and the early warning message is reported.
  • an abnormality is found when the data is compared horizontally, it is determined that the current parameter to be monitored is abnormally fluctuated, or an abnormality occurs when the data is compared vertically, it is determined that the current parameter to be monitored is deviated from the standard parameter.
  • step S30 the method further includes:
  • some commonly used exception handling strategies can be associated with exception parameters and stored in a preset strategy library.
  • abnormal parameters of abnormal memory usage that is, CPU (occupation rate is increased), memory usage (increased), and disk space ratio (increased)
  • CPU occupation rate is increased
  • memory usage increased
  • disk space ratio increased
  • the monitoring parameters corresponding to the original abnormal parameters after the abnormal processing are obtained, and the monitoring parameters are fed back to the management end, so that the administrator can determine whether the abnormal situation is resolved.
  • This embodiment provides a method for early warning of a system failure, that is, acquiring a current parameter to be monitored of a target system in a current time unit according to a preset time unit; acquiring a standard parameter in a preset monitoring model, and judging according to the standard parameter Whether there is an abnormal parameter in the current parameter to be monitored; if it is determined that the abnormal parameter exists in the current parameter to be monitored, an early warning message is generated according to the abnormal parameter in the current parameter to be monitored and the standard parameter and reported to the Warning message.
  • the present application can set the core indicator data of the system as parameters to be monitored, such as memory parameters, application parameters, and business parameters, and perform real-time monitoring of the core monitoring data according to a preset time unit, so that the abnormal core can be detected in time. Monitor the data, so as to provide early warning of system data that is about to occur abnormally, to realize early warning when anomalies are about to occur, and to improve system efficiency.
  • FIG. 3 is a schematic flowchart of a second embodiment of an early warning method for a system fault of the present application.
  • the step S20 includes:
  • Step S21 According to the preset monitoring model, obtain a current standard parameter to be monitored corresponding to the target system in the current time unit as the standard parameter;
  • step S22 it is determined whether an abnormal parameter does not match the standard parameter in the current parameters to be monitored.
  • preset standard parameters corresponding to each time unit are set in the preset monitoring model, that is, the parameters to be monitored of each event unit are longitudinally compared, that is, the current monitoring parameters are compared with the corresponding preset standard parameters. Compared. If the parameter to be monitored in a certain time unit is significantly different from the preset standard parameter, an abnormality may occur in the parameter to be monitored corresponding to the time unit, and corresponding abnormal processing is required or continuous monitoring of the abnormal parameter is started from the time unit. To further confirm whether the abnormality persists.
  • step S20 further includes:
  • step S23 according to the preset monitoring model, other standard parameters to be monitored corresponding to the target system at other time units are obtained as standard parameters;
  • step S24 it is determined whether there are abnormal parameters in the current parameters to be monitored that do not match the standard parameters.
  • the parameters to be monitored corresponding to each time unit should be within the same range standard. Compare the current to-be-monitored parameter of the target system with other to-be-monitored parameters corresponding to other time units.
  • the other time unit refers to a non-current time unit, and may be several time units. That is, it is compared with the parameters to be monitored corresponding to the preset time unit before and after. If the parameter to be monitored of a certain time unit is significantly different from the parameter to be monitored corresponding to the preset time unit, the parameter to be monitored corresponding to the time unit Anomalies may occur. You need to perform corresponding exception handling or continuous monitoring of abnormal parameters from this time unit to further confirm whether the abnormality persists.
  • FIG. 4 is a schematic flowchart of a third embodiment of an early warning method for a system fault of the present application.
  • the method further includes:
  • Step S31 acquiring parameters to be monitored corresponding to several time units after the current time unit
  • Step S32 Determine whether the parameter to be monitored corresponding to the several time units is abnormal continuously according to the standard parameters corresponding to the time units in the preset monitoring model;
  • step S33 if the parameters to be monitored corresponding to the several time units continue to be abnormal, an emergency warning message is generated according to the abnormal parameters that continue to be abnormal, and the emergency warning message is sent to the management end.
  • step S34 if the parameters to be monitored corresponding to the several time units are not persistent abnormalities, a corresponding target repair strategy is searched in a preset policy library according to the existing abnormal parameters, and abnormality processing is performed according to the target repair strategies.
  • the parameter to be monitored corresponding to a preset time unit after the time unit is further monitored.
  • the temporary abnormality problem is an abnormality problem that the system can adjust by itself, or an abnormality problem that can be solved according to a preset policy library.
  • continuous monitoring may be performed on core index data corresponding to the abnormal parameter.
  • preset parameters to be monitored corresponding to a time unit are preset, where the preset can be one, three, or five, etc., or the parameters corresponding to system core indicators are continuously monitored, or Continuous monitoring is performed for indicators to be monitored corresponding to abnormal parameters.
  • the judging process of judging whether the parameters to be monitored corresponding to several time units are abnormal continuously is to judge one-to-one correspondence between the standard parameters in the several time units and the parameters to be monitored according to the same time unit. For example, if the parameters to be monitored in the current time unit 12: 00-12: 05 are compared with the standard parameters corresponding to the time unit 12: 00-12: 05 in the model, the next time unit 12: 05-12: 10 corresponds. The parameters to be monitored are compared with the standard parameters corresponding to the time unit of 12: 05-12: 10 in the model, and so on. That is, when an abnormality occurs in a certain indicator to be monitored in the current time unit, the indicator to be monitored can be continuously monitored to determine whether the abnormality continues.
  • an embodiment of the present application further provides a system failure early warning device.
  • FIG. 5 is a schematic diagram of functional modules of a first embodiment of an early warning device for system failure of the present application.
  • the early warning device for system failure includes:
  • a parameter obtaining module 10 configured to obtain a current parameter to be monitored of the target system in a current time unit according to a preset time unit;
  • a parameter monitoring module 20 configured to obtain standard parameters in a preset monitoring model, and determine whether there are abnormal parameters in the current parameters to be monitored according to the standard parameters;
  • the abnormality early warning module 30 is configured to, if it is determined that the abnormal parameter exists in the current parameter to be monitored, generate an early warning message according to the abnormal parameter in the current parameter to be monitored and the standard parameter, and report the early warning message.
  • the early warning device for system failure further includes:
  • a parameter statistics module is configured to obtain historical system data of the target system, and to calculate parameters to be monitored for each time unit in the historical system data according to a preset time unit, where the parameters to be monitored include memory parameters, applications Parameters and business parameters;
  • a model building module is configured to classify and store the abnormal monitoring parameters and the normal monitoring parameters in the parameters to be monitored, and train and generate the preset monitoring model according to the abnormal monitoring parameters and the normal monitoring parameters.
  • the early warning device for system failure further includes:
  • An abnormality repairing module configured to find a corresponding target repairing strategy in a preset policy library according to the abnormality parameters, and perform abnormality processing according to the target repairing strategy;
  • a result feedback module is configured to obtain an abnormal processing result and feed the abnormal processing result to a management end.
  • parameter monitoring module 20 includes:
  • a parameter first obtaining unit configured to obtain, according to the preset monitoring model, a preset standard parameter corresponding to the target system in the current time unit as a standard parameter
  • the parameter first determining unit is configured to determine whether there is an abnormal parameter in the current parameter to be monitored that does not match the standard parameter.
  • a second parameter obtaining unit configured to obtain, according to the preset monitoring model, other standard parameters to be monitored corresponding to the target system at other time units as standard parameters;
  • the second parameter determining unit is configured to determine whether there is an abnormal parameter in the current parameter to be monitored that does not match the standard parameter.
  • abnormality warning module 30 further includes:
  • a third parameter obtaining unit configured to obtain the parameter to be monitored corresponding to several time units after the current time unit if it is determined that the abnormal parameter exists in the current parameter to be monitored;
  • a third parameter judging unit configured to determine whether a parameter to be monitored corresponding to the several time units is continuously abnormal according to standard parameters corresponding to the several time units in the preset monitoring model;
  • the emergency early warning unit is configured to generate an emergency early warning message according to the abnormal parameters of the continuous abnormality if the parameters to be monitored corresponding to the several time units continue to be abnormal, and send the emergency early warning message to a management end.
  • An anomaly repairing unit configured to find a corresponding target repair strategy in a preset policy library according to the existing anomaly parameters if the parameters to be monitored corresponding to the several time units are not persistent anomalies, and perform an exception according to the target repair strategy deal with.
  • each module in the above-mentioned system failure early warning device corresponds to each step in the embodiment of the above-mentioned system failure early warning method, and its functions and implementation processes are not repeated here one by one.
  • an embodiment of the present application further provides a computer-readable storage medium.
  • the computer-readable storage medium of the present application stores an early warning program for system failure, wherein when the early warning program for system failure is executed by a processor, the steps of the early warning method for system failure are implemented.
  • the methods in the above embodiments can be implemented by means of software plus a necessary universal hardware platform, and of course, also by hardware, but in many cases the former is better.
  • Implementation Based on such an understanding, the technical solution of this application that is essentially or contributes to the existing technology can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium (such as ROM / RAM) as described above. , Magnetic disk, optical disc), including a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in the embodiments of the present application.

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Abstract

La présente invention concerne un procédé d'avertissement de défaut de système, un appareil, et un dispositif, et un support d'informations lisible par ordinateur. Le procédé d'avertissement consiste : à acquérir, sur la base d'une unité de temps prédéfinie, des paramètres actuels à surveiller d'un système cible dans une unité de temps actuelle (S10) ; à acquérir un paramètre standard dans un modèle de surveillance prédéfini, et à déterminer, conformément au paramètre standard, s'il existe un paramètre anormal dans les paramètres actuels (S20) ; et s'il est déterminé qu'un paramètre anormal se trouve dans les paramètres actuels, à générer un message d'avertissement conformément au paramètre anormal dans les paramètres actuels et au paramètre standard, et à rapporter le message d'avertissement (S30). Dans le procédé, les données d'indicateur de cœur d'un système sont un paramètre à surveiller, et une surveillance en temps réel est réalisée sur des données de surveillance de cœur sur la base d'une unité de temps prédéfinie, de telle sorte qu'une anomalie dans des données de surveillance de cœur peut être détectée en temps opportun, ce qui permet d'avertir d'une anomalie de données de système d'une manière opportune, de fournir un avertissement d'avance d'une anomalie, et ce qui permet d'améliorer l'efficacité du système.
PCT/CN2018/122807 2018-09-03 2018-12-21 Procédé d'avertissement de défaut de système, appareil, et dispositif, et support d'informations WO2020048047A1 (fr)

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