WO2021012481A1 - Procédé et appareil de surveillance de performances de système, dispositif et support d'informations - Google Patents

Procédé et appareil de surveillance de performances de système, dispositif et support d'informations Download PDF

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Publication number
WO2021012481A1
WO2021012481A1 PCT/CN2019/116483 CN2019116483W WO2021012481A1 WO 2021012481 A1 WO2021012481 A1 WO 2021012481A1 CN 2019116483 W CN2019116483 W CN 2019116483W WO 2021012481 A1 WO2021012481 A1 WO 2021012481A1
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Prior art keywords
monitoring
optimized
information
optimization
model
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PCT/CN2019/116483
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English (en)
Chinese (zh)
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朱洲
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平安科技（深圳）有限公司
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Publication of WO2021012481A1 publication Critical patent/WO2021012481A1/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
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/3024—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a central processing unit [CPU]
    • 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
    • G06F11/3037—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a memory, e.g. virtual memory, cache
    • 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
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance

Definitions

  • This application relates to the technical field of system performance optimization, and in particular to a system performance monitoring method, device, equipment, and computer-readable storage medium.
  • direct banking is a new type of banking operation model that emerged in the Internet era.
  • the current direct banking system uses the direct banking system for During operation, the direct banking system cannot inform the operation and maintenance personnel of its own performance load, nor can it display the overall architecture performance of the direct bank, such as system load, network trend, scheduling relationship, etc., which makes the operation and maintenance personnel have the The performance load is not known.
  • the existing direct banking system usually waits for the operation to fail and notify the operation and maintenance personnel by means of alarms. At this time, the operation and maintenance personnel know that there is a problem with the direct bank system, but what is the specific failure? The system itself cannot quickly and accurately locate and display it to the operation and maintenance personnel, so that the operation and maintenance personnel need to spend more time to find the cause of the failure, and the operation and maintenance personnel cannot solve the failure problem of the direct banking system in time.
  • the main purpose of this application is to provide a system performance monitoring method, device, equipment, and computer-readable storage medium, aiming to solve the technical problem that the existing direct banking system cannot be quickly and accurately located and cannot be displayed.
  • the system performance monitoring method includes the following steps:
  • the abnormal information is sent to the terminal corresponding to the terminal address.
  • the method before the step of determining the monitoring object corresponding to the agent through the agent corresponding to the monitoring service when the instruction to start the monitoring service is received, the method further includes:
  • the updated problem to be optimized is used as the input of the optimization model, and the optimization strategy corresponding to the updated problem to be optimized is used as the output of the optimization model, a new optimization model is obtained by training, and the new optimization Model as the optimization model.
  • the step of collecting monitoring information corresponding to the monitoring object, and determining whether the monitoring object is in a normal state based on the monitoring information includes:
  • the method further includes:
  • the monitoring information exceeding the safety value is marked in bright colors in the dynamic monitoring chart.
  • the determining the monitoring object corresponding to the agent through the agent corresponding to the monitoring service includes:
  • the monitoring object is determined according to preset configuration information, and the configuration information is preset information used to indicate the type of the monitoring object.
  • the determining the monitoring object corresponding to the agent through the agent corresponding to the monitoring service includes:
  • the corresponding monitoring object is determined according to the user adding instruction.
  • the problem to be optimized includes an internal host level problem, an internal code level problem, and the external related party adjustment problem.
  • the present application also provides a system performance monitoring device, the system performance monitoring device includes:
  • the monitoring module is configured to determine the monitoring object corresponding to the agent through the agent corresponding to the monitoring service when an instruction to start the monitoring service is received;
  • the collection module is used to collect monitoring information corresponding to the monitored object, and based on the monitoring information, determine whether the monitored object is in a normal state;
  • the judgment module is configured to determine the problem to be optimized corresponding to the monitoring information if it is determined that the monitored object is in an abnormal state;
  • a determining module configured to input the problem to be optimized into an optimization model, and determine an optimization strategy corresponding to the monitoring object through the optimization model;
  • the judgment module is also used for judging whether the problem to be optimized is a problem of adjusting external related parties;
  • the output module is used to output the abnormal information corresponding to the abnormal state and the optimization strategy if not;
  • the output module is also used to, if yes, obtain the terminal address corresponding to the external related party
  • the sending module is used to send the abnormal information to the terminal corresponding to the terminal address.
  • the present application also provides a monitoring device, the monitoring device including a processor, a memory, and computer-readable instructions stored on the memory and executable by the processor, wherein the When the computer-readable instructions are executed by the processor, the steps of the above-mentioned system performance monitoring method are realized.
  • the present application also provides a computer-readable storage medium having computer-readable instructions stored on the computer-readable storage medium, and when the computer-readable instructions are executed by a processor, the implementation is as described above The steps of the system performance monitoring method.
  • FIG. 1 is a schematic diagram of the hardware structure of the monitoring device involved in the solution of the embodiment of the application;
  • FIG. 2 is a schematic flowchart of the first embodiment of the system performance monitoring method of this application.
  • the system performance monitoring method involved in the embodiments of the present application is mainly applied to monitoring equipment, and the monitoring equipment may be a PC, a portable computer, a mobile terminal, or other equipment with display and processing functions.
  • Fig. 1 is a schematic diagram of the hardware structure of the monitoring device involved in the solution of the embodiment of the application.
  • the monitoring device may include a processor 1001 (for example, 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 realize the connection and communication between these components;
  • the user interface 1003 may include a display (Display), an input unit such as a keyboard (Keyboard);
  • the network interface 1004 may optionally include a standard wired interface, a wireless interface (Such as WI-FI 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 aforementioned processor 1001.
  • FIG. 1 does not constitute a limitation on the monitoring device, and may include more or fewer components than shown in the figure, or a combination of certain components, or different component arrangements.
  • the memory 1005 as a computer-readable storage medium in FIG. 1 may include an operating system, a network communication module, and computer-readable instructions.
  • the network communication module is mainly used to connect to the server and perform data communication with the server; and the processor 1001 can call computer-readable instructions stored in the memory 1005 and execute the system performance monitoring method provided in the embodiment of the present application.
  • the embodiment of the application provides a system performance monitoring method, which can be used in a direct banking system and is also applicable in a system system similar to the direct banking system.
  • the following will take the direct banking system as an example for illustration.
  • FIG. 2 is a schematic flowchart of a first embodiment of a system performance monitoring method of this application.
  • the system performance monitoring method includes the following steps:
  • Step S10 when receiving the instruction to start the monitoring service, determine the monitoring object corresponding to the agent through the agent corresponding to the monitoring service;
  • Step S20 collecting monitoring information corresponding to the monitoring object, and judging whether the monitoring object is in a normal state based on the monitoring information;
  • Step S30 if it is determined that the monitoring object is in an abnormal state, determine the problem to be optimized corresponding to the monitoring information
  • Step S40 input the problem to be optimized into an optimization model, and determine an optimization strategy corresponding to the monitored object through the optimization model;
  • Step S50 judging whether the problem to be optimized is an external related party adjustment problem
  • Step S60 if not, output abnormal information corresponding to the abnormal state and the optimization strategy
  • Step S70 if yes, obtain the terminal address corresponding to the external related party
  • Step S80 Send the abnormal information to the terminal corresponding to the terminal address.
  • the agent determines the monitored object and collects the monitoring information of the monitored object. Based on the monitoring information, it is determined whether the monitored object is in a normal state. When it is determined that the monitored object is in an abnormal state, it is further determined whether it is a problem of transferring external related parties. Then output the corresponding abnormal information and the corresponding optimization strategy, so that the operation and maintenance personnel can locate the problem to be optimized in time, and optimize the direct banking system according to the optimization strategy; if so, send the abnormal information to the terminal corresponding to the external related party. There is no requirement for the professional ability of operation and maintenance personnel.
  • Step S10 When an instruction to start a monitoring service is received, the agent corresponding to the monitoring service determines the monitoring object corresponding to the agent.
  • monitoring equipment before performing system performance monitoring on the direct banking system, monitoring equipment needs to be deployed in the direct banking system.
  • the corresponding agent refers to software or hardware entities capable of autonomous activity
  • the agent runs on the host as a process.
  • the agent is started, and the monitoring object that needs to be monitored is determined through the agent.
  • the monitoring object includes the host memory, CPU (Central Processing Unit, central processing unit), jvm (Java Virtual Machine Java virtual machine), process, thread, disk io, network traffic and other low-level physical performance information, as well as the call response time of program interfaces, classes, libraries, jar packages, etc.
  • the monitoring objects can be monitored after the agent is deployed on the host. Add in the monitoring device. To
  • the first method includes: the configuration information of the relevant monitoring object is preset in the agent. After the agent is deployed on the host to be monitored, the agent is started. The agent determines the corresponding monitoring object according to the preset configuration information. Such as agent The preset monitoring objects are the host memory, CPU, jvm and process information. After pushing the agent to the corresponding host, start the agent At the time, the monitoring objects can be determined as host memory, CPU, jvm and process information.
  • the second method includes: after deploying the agent to the host that needs to be monitored, start the agent, and manually add the monitoring object that needs to be monitored in the corresponding add interface. For example, after starting the agent, the user manually adds the relevant configuration information corresponding to the host memory, CPU, jvm, process, thread, and disk io in the corresponding adding interface. When starting the service, determine the monitoring object as the host memory, CPU, jvm, process, thread, head and disk io.
  • Step S20 Collect monitoring information corresponding to the monitoring object, and based on the monitoring information, determine whether the monitoring object is in a normal state.
  • the monitoring information corresponding to the monitored object is collected in real time through the agent. If the monitored object is the host memory, the host memory occupancy rate is collected; if the monitored object is the CPU, the CPU usage rate is collected.
  • the monitoring information corresponding to the monitoring object is collected, based on the monitoring information collected by the monitoring, it is judged whether the monitoring object is in a normal state. Specifically, a safety value is preset for the monitoring information corresponding to each monitoring object. After the monitoring information is collected Then, the monitoring information is compared with the safety value to determine whether the monitoring information corresponding to the current monitoring object exceeds the safety value. If so, it is determined that the current monitoring object is in an abnormal state; if not, it is determined that the current monitoring object is in a normal state. For example, the security value of the host memory is 70%, and when the current host memory usage rate is 85%, it is determined that the current host is in an abnormal state.
  • the preset security value of each monitored object is also different.
  • An empirical value can be preset, and the security value can be set according to actual experience. Specifically, if the host memory exceeds 80% , The operation will be stuck. At this time, according to the experience value, the safety value of the host memory can be set to 70%, leaving room for operation, rather than simply setting it to 80%.
  • step S20 includes:
  • Step S21 Collect monitoring information corresponding to the monitored object, and determine a graphic style corresponding to the monitored object.
  • a kind of monitoring information has a corresponding image style.
  • the CPU usage rate uses the image style of a line graph
  • the memory usage of the host uses the image style of a fan graph.
  • the types of specific graph styles are not limited here.
  • Step S22 Generate a dynamic monitoring chart from the monitoring information, and the dynamic monitoring chart is displayed in a graphic style corresponding to the monitoring object.
  • the collected monitoring information is generated into a dynamic monitoring chart, where the dynamic monitoring icon is displayed in a determined graphic style, that is, monitoring information is collected in real time, and the monitoring information is generated into a monitoring chart, and the monitoring chart is in a real-time update state.
  • Step S23 based on the dynamic monitoring chart, determine in real time whether the monitored object is in a normal state.
  • the generated dynamic monitoring chart it is determined in real time whether the monitored object is in a normal state, that is, in the dynamic monitoring chart, the status of the monitored object can be displayed.
  • step S23 includes:
  • Step a Obtain the safety value of the monitored object.
  • each monitored object corresponds to a safety value, which can be set in advance based on experience, and the safety value of each monitored object is different.
  • Step b comparing the monitoring information with the safety value.
  • the collected monitoring information is compared with the safety value. Specifically, the collected monitoring information is numerically converted to obtain the monitoring data value, and the monitoring data value is compared with the safety value.
  • the monitoring information such as the host memory is the occupancy of the host memory.
  • the host memory occupancy can be converted to Host memory occupancy rate, and compare the host memory occupancy rate with the security value corresponding to the host memory. If it exceeds the security value, the host memory usage is high, which is likely to cause freezes. Make sure that the host memory is in an abnormal state; if the security value is not exceeded Value, it means that the host's memory usage is not high, and it is operating normally, and it is determined that the host's memory contributes to the normal state.
  • Step c Mark the monitoring information exceeding the safety value in bright colors in the dynamic monitoring chart.
  • the monitoring information is generated into a dynamic monitoring chart, and in the dynamic monitoring chart, the monitoring information that exceeds the safety value is marked in bright colors, such as warning red, and the monitoring information that does not exceed the safety value is marked in normal green, or In the dynamic monitoring icon, only the monitoring information exceeding the safety value is displayed and marked in bright colors, while the monitoring information not exceeding the safety value does not need to be displayed, which reduces the operating load and saves storage.
  • Step S30 If it is determined that the monitored object is in an abnormal state, determine the problem to be optimized corresponding to the monitoring information.
  • the corresponding problem to be optimized is determined according to the monitoring information. It is understandable that if each monitored object is abnormal, its corresponding problem to be optimized is different, then its corresponding optimization The strategies are also different, so when it is determined that the monitored object is in an abnormal state, it is necessary to further determine the specific problem to be optimized.
  • Step S40 Input the problem to be optimized into an optimization model, and determine an optimization strategy corresponding to the monitored object through the optimization model.
  • the problem to be optimized is input into the optimization model trained in advance, and the optimization strategy corresponding to the monitored object is determined through the optimization model.
  • the optimization strategy corresponding to the monitored object is determined.
  • the monitored object has only two states: abnormal and normal. Therefore, the corresponding optimization strategy can be set in advance for the abnormal state of each monitored object.
  • the corresponding optimization strategy can be obtained. For example, the CPU usage rate is too high and the load pressure is high, resulting in cpu abnormal alarm, then determine the cpu The optimization strategy is to expand the cpu and increase the number of cores, so that the operation and maintenance personnel can optimize the cpu according to the optimization strategy.
  • Step S50 judging whether the problem to be optimized is an external related party adjustment problem
  • the monitoring device determines whether the problem to be optimized is a problem of adjusting external related parties.
  • the problem to be optimized is divided into internal host-level problems and internal code. There are three types of issues: level issues and external related party issues.
  • internal host-level issues include host memory, CPU, jvm, processes, threads, disk io, and network traffic.
  • the corresponding optimization problems and optimization strategies are:
  • the cpu usage rate is too high and the load pressure is high: expand the cpu and increase the number of cores;
  • Jvm configuration exception (stack size is too small, persistent generation is too small, new generation, old generation configuration problems): Modify the configuration file corresponding to the java container and modify the parameters of the jvm;
  • Process or thread configuration is too large or insufficient: Adjust the number of processes and threads of the system layer and application layer according to the actual situation;
  • the disk io is too large and the read and write performance is low: Optimize the disk performance of the corresponding physical host;
  • a certain interface responds slowly: transfer the problems detected by the monitoring equipment to the corresponding development, optimize the code, optimize the algorithm, and accelerate the interface response speed;
  • the program calls a microservice exception: Quickly locate the error log, optimize the code for code problems, and handle other problems according to the actual situation.
  • the problems of adjusting external related parties include adjusting the response time of the related party interface, the packet loss rate of the related party network, etc.
  • the corresponding problems to be optimized and optimization strategies are:
  • Severe packet loss is detected in the network of the related party: contact the related party and network personnel for processing.
  • the monitoring equipment determines the problem to be optimized corresponding to the monitored object based on the collected monitoring information, and further determines whether the problem to be optimized is a problem of adjusting external related parties.
  • Step S60 if not, output abnormal information corresponding to the abnormal state and the optimization strategy.
  • the monitoring equipment determines that the current problem to be optimized is not an external related party problem, it means that the problem to be optimized is an internal host-level problem or an internal code-level problem, which can be solved by operation and maintenance personnel, and the corresponding abnormal information and optimization strategy are output. , For operation and maintenance personnel to optimize the monitoring objects.
  • the monitoring equipment is only responsible for displaying abnormal information and corresponding optimization strategies to the operation and maintenance personnel, and does not have the ability to self-repair. This is because regardless of internal host-level problems or internal code-level problems, manual intervention is required. solve.
  • Step S70 if yes, obtain the terminal address corresponding to the external related party.
  • the monitoring equipment determines that the current problem to be optimized is a problem of adjusting external related parties, it means that the problem to be optimized needs to be handled by related personnel of external related parties, and does not require internal operation and maintenance personnel, and it is possible that internal operation and maintenance personnel do not have the authority to optimize , Then obtain the terminal address corresponding to the external related party.
  • Step S80 Send the abnormal information to the terminal corresponding to the terminal address.
  • the monitoring device displays the corresponding abnormal information, and sends the abnormal information to the terminal corresponding to the terminal address, so that the external related party can receive the abnormal information and deal with the problem to be optimized corresponding to the abnormal information.
  • the agent is deployed to determine the monitored object and monitor the monitored object to collect monitoring information of the monitored object, and determine whether the monitored object is normal by analyzing the monitoring information. If the monitored object is in an abnormal state, it is further judged whether it is a mediator. For external related party issues, if not, output abnormal information and corresponding optimization strategies for operation and maintenance personnel to locate system bottlenecks in a timely manner, and optimize according to optimization strategies to achieve rapid positioning and display of system abnormalities; if so, the abnormal The information is sent to the terminal corresponding to the external related party.
  • a second embodiment of the system performance monitoring method of this application is proposed based on the first embodiment.
  • the difference between the second embodiment of the system performance monitoring method and the first embodiment of the system performance monitoring method is that the training step of the optimization model includes:
  • Step d receiving the solved problem to be optimized and the optimization strategy corresponding to the solved problem to be optimized;
  • the monitoring equipment also includes a machine learning module.
  • the operation and maintenance personnel can input the solved problems to be optimized and the corresponding optimization strategies into the monitoring equipment, and the monitoring equipment learns through the machine learning module.
  • the optimization problem can be the problem to be optimized that is actually solved by the operation and maintenance personnel, or it can be the problem to be optimized that the public can obtain that is solved by others.
  • the corresponding optimization strategy is associated with the input, so that when the monitoring device receives the solved problem to be optimized, the corresponding optimization strategy is received, instead of a certain optimization strategy.
  • the problem is related to other unrelated optimization strategies.
  • Step e using the solved problem to be optimized as the input of the initial model, and the optimization strategy corresponding to the solved problem to be optimized as the output of the initial model, and training the initial model into the optimized model ;
  • the monitoring device uses the received solved problem to be optimized as the input of the initial model, and uses the corresponding optimization strategy as the output of the initial model, and trains the initial model into an optimized model.
  • Step f receiving the imported learning website, based on crawler technology, monitoring whether the learning website has an updated problem to be optimized and an optimization strategy corresponding to the updated problem to be optimized;
  • the optimization model currently trained cannot meet daily needs.
  • the monitored object is likely to have abnormal conditions that the operation and maintenance personnel have not encountered.
  • the monitoring equipment can also receive the learning URL imported by the operation and maintenance personnel, and use crawler technology to monitor whether there is another upload on the learning URL, which is different from the existing optimization model, the updated problem to be optimized and the updated problem to be optimized The optimization strategy corresponding to the problem.
  • Step g if it exists, obtain the updated problem to be optimized and the optimization strategy corresponding to the updated problem to be optimized;
  • the machine learning module can get the updated problem to be optimized and the corresponding optimization strategy. Optimization strategy.
  • step h the updated problem to be optimized is used as the input of the optimization model, and the optimization strategy corresponding to the updated problem to be optimized is used as the output of the optimization model, a new optimization model is obtained through training, and the A new optimization model is used as the optimization model.
  • the monitoring device uses the updated problem to be optimized as the input of the optimization model, and uses the corresponding optimization strategy as the output of the optimization model, and continuously updates the optimization model. Make the optimization model have the ability to grow and learn.
  • the learning methods of the machine learning module include:
  • the machine learning module crawls to obtain information and learn
  • the abnormality of the monitored object is divided into various problems to be optimized.
  • the problem to be optimized corresponding to the monitored object needs to be determined first, and then the optimization model obtained through training is based on For optimization problems, further determine the corresponding optimization strategies to improve the growth and learning capabilities of monitoring equipment to cope with the rapid iteration of the Internet field.
  • the embodiment of the present application also provides a system performance monitoring device.
  • the system performance monitoring device includes:
  • the monitoring module is configured to determine the monitoring object corresponding to the agent through the agent corresponding to the monitoring service when an instruction to start the monitoring service is received;
  • the collection module is used to collect monitoring information corresponding to the monitored object, and based on the monitoring information, determine whether the monitored object is in a normal state;
  • the judgment module is configured to determine the problem to be optimized corresponding to the monitoring information if it is determined that the monitored object is in an abnormal state;
  • a determining module configured to input the problem to be optimized into an optimization model, and determine an optimization strategy corresponding to the monitoring object through the optimization model;
  • the judgment module is also used for judging whether the problem to be optimized is a problem of adjusting external related parties;
  • the output module is used to output the abnormal information corresponding to the abnormal state and the optimization strategy if not;
  • the output module is also used to, if yes, obtain the terminal address corresponding to the external related party
  • the sending module is used to send the abnormal information to the terminal corresponding to the terminal address.
  • system performance monitoring device further includes a machine learning module, and the machine learning module is used for:
  • the updated problem to be optimized is used as the input of the optimization model, and the optimization strategy corresponding to the updated problem to be optimized is used as the output of the optimization model, a new optimization model is obtained by training, and the new optimization Model as the optimization model.
  • collection module is also used for:
  • collection module is also used for:
  • the monitoring information exceeding the safety value is marked in bright colors in the dynamic monitoring chart.
  • monitoring module is also used for:
  • the monitoring object is determined according to preset configuration information, and the configuration information is preset information used to indicate the type of the monitoring object.
  • each module and unit in the above system performance monitoring device corresponds to each step in the above system performance monitoring method embodiment, and their functions and implementation processes will not be repeated here.
  • the embodiments of the present application also provide a computer-readable storage medium, and the computer-readable storage medium may be a non-volatile readable storage medium.
  • the computer-readable storage medium of the present application stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the above-mentioned system performance monitoring method are implemented.
  • the method implemented when the computer-readable instruction is executed can refer to the various embodiments of the system performance monitoring method of the present application, which will not be repeated here.

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Abstract

L'invention concerne un procédé et un appareil de surveillance de performances de système, un dispositif et un support d'informations. Le procédé comprend les étapes suivantes : lors de la réception d'une instruction de démarrage d'un service de surveillance, déterminer un objet de surveillance correspondant à un agent au moyen de la correspondance de l'agent avec le service de surveillance (S10) ; acquérir des informations de surveillance correspondant à l'objet de surveillance, et déterminer, sur la base des informations de surveillance, si l'objet de surveillance est dans un état normal (S20) ; s'il est déterminé que l'objet de surveillance est dans un état anormal, déterminer un problème à optimiser correspondant aux informations de surveillance (S30) ; entrer ledit problème dans un modèle d'optimisation, et déterminer une politique d'optimisation correspondant à l'objet de surveillance au moyen du modèle d'optimisation (S40) ; déterminer si ledit problème est un problème de partie associée à un ajustement externe (S50) ; si ce n'est pas le cas, délivrer en sortie des informations anormales correspondant à l'état anormal et à la politique d'optimisation (S60) ; si tel est le cas, obtenir une adresse de terminal correspondant à une partie associée à un ajustement externe (S70) ; et envoyer les informations anormales à un terminal correspondant à l'adresse de terminal (S80). Le procédé permet un positionnement et un affichage rapides des phénomènes anormaux d'un système.
PCT/CN2019/116483 2019-07-23 2019-11-08 Procédé et appareil de surveillance de performances de système, dispositif et support d'informations WO2021012481A1 (fr)

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CN201910669511.5 2019-07-23
CN201910669511.5A CN110515793B (zh) 2019-07-23 2019-07-23 ***性能监控方法、装置、设备及存储介质

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114509716A (zh) * 2021-08-30 2022-05-17 正泰集团研发中心(上海)有限公司 电能表性能检测方法、装置、设备及计算机可读存储介质
CN116823233A (zh) * 2023-08-30 2023-09-29 青岛巨商汇网络科技有限公司 一种基于全周期运维的用户数据处理方法及***
WO2024023646A1 (fr) 2022-07-29 2024-02-01 3M Innovative Properties Company Adhésifs thermofusibles stabilisés sensibles à la pression

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110995539A (zh) * 2019-12-12 2020-04-10 深圳前海环融联易信息科技服务有限公司 业务***监控方法、装置及计算机设备
CN111651323A (zh) * 2020-05-29 2020-09-11 山东中创软件商用中间件股份有限公司 一种应用软件的监控方法、装置及设备
CN112492632B (zh) * 2020-11-09 2023-02-17 厦门亿联网络技术股份有限公司 一种基于漫游***的异常监控方法、***

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101483545A (zh) * 2008-12-31 2009-07-15 中国建设银行股份有限公司 一种金融业务监控方法及***
CN103116538A (zh) * 2013-01-25 2013-05-22 浪潮电子信息产业股份有限公司 一种用于计算机性能自调***的设计
CN106027328A (zh) * 2016-05-13 2016-10-12 深圳市中润四方信息技术有限公司 一种基于应用容器部署的集群监控的方法及***
CN107239339A (zh) * 2016-03-29 2017-10-10 阿里巴巴集团控股有限公司 ***性能优化参数确定方法、***性能优化方法及装置
CN107992398A (zh) * 2017-12-22 2018-05-04 宜人恒业科技发展（北京）有限公司 一种业务***的监控方法和监控***

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102014407A (zh) * 2010-12-10 2011-04-13 北京交通大学 一种基于snmp的无线传感器网络域委托代理管理机制
US10091131B2 (en) * 2014-07-10 2018-10-02 International Business Machines Corporation Increased network resources in exchange for sharing of device resources
CN108063753A (zh) * 2017-11-10 2018-05-22 全球能源互联网研究院有限公司 一种信息安全监测方法及***
CN110009371B (zh) * 2018-12-27 2023-06-20 创新先进技术有限公司 异常行为确定方法、装置、设备及计算机可读存储介质
CN109948000B (zh) * 2019-01-09 2023-04-07 南方科技大学 异质网络的异常目标检测方法、装置、设备及存储介质

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101483545A (zh) * 2008-12-31 2009-07-15 中国建设银行股份有限公司 一种金融业务监控方法及***
CN103116538A (zh) * 2013-01-25 2013-05-22 浪潮电子信息产业股份有限公司 一种用于计算机性能自调***的设计
CN107239339A (zh) * 2016-03-29 2017-10-10 阿里巴巴集团控股有限公司 ***性能优化参数确定方法、***性能优化方法及装置
CN106027328A (zh) * 2016-05-13 2016-10-12 深圳市中润四方信息技术有限公司 一种基于应用容器部署的集群监控的方法及***
CN107992398A (zh) * 2017-12-22 2018-05-04 宜人恒业科技发展（北京）有限公司 一种业务***的监控方法和监控***

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114509716A (zh) * 2021-08-30 2022-05-17 正泰集团研发中心(上海)有限公司 电能表性能检测方法、装置、设备及计算机可读存储介质
WO2024023646A1 (fr) 2022-07-29 2024-02-01 3M Innovative Properties Company Adhésifs thermofusibles stabilisés sensibles à la pression
CN116823233A (zh) * 2023-08-30 2023-09-29 青岛巨商汇网络科技有限公司 一种基于全周期运维的用户数据处理方法及***
CN116823233B (zh) * 2023-08-30 2023-11-07 青岛巨商汇网络科技有限公司 一种基于全周期运维的用户数据处理方法及***

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