System monitoring method and device based on OPS and medium

Abstract

The invention discloses an OPS-based system monitoring method and device and a medium, and the method comprises the steps: obtaining config information, a token value and an encrypted character string of a to-be-monitored system to establish a data connection between the OPS and the to-be-monitored system, monitoring a cluster operation index of the to-be-monitored system through OPS cluster management, determining whether the cluster operation index is abnormal or not, and if yes, determining whether the cluster operation index is abnormal or not; and when the cluster operation index is abnormal, alarm information is sent to the client, and when the alarm information is confirmed, abnormity repair processing is performed on an application corresponding to the cluster abnormal index through OPS. According to the invention, only one operating system level lightweight index acquisition service is deployed on the application server, and the application service is directly used to acquire the related alarm information for reporting, so that the communication cost of system alarm processing and monitoring platform management personnel is reduced, the processing timeliness of system faults is improved, and the user experience is improved. And the system failure rate can be effectively reduced.

Description

Technical Field

[0001] The present application relates to the field of computers, and in particular to an OPS-based system monitoring method, device, and medium. Background Art

[0002] In the field of traditional human resource management system monitoring, enterprises often use independent platforms such as Zabbix, Nagios, Prometheus+Grafana to monitor application servers, databases and container services respectively, or use pod dashboard to monitor containers.

[0003] This approach requires separate deployment, and each platform must install an agent to collect data, which increases the resource burden on application servers. Furthermore, different administrators are responsible for each platform, and when an alarm occurs, coordination with the corresponding administrator is required. This process is lengthy and inefficient, and can easily lead to system crashes due to untimely processing. Furthermore, traditional operations and maintenance rely on manual logging into each monitoring platform to obtain information, which is repetitive and labor-intensive, also hindering efficiency. Summary of the Invention

[0004] The embodiments of the present application provide an OPS-based system monitoring method, device, and medium to solve the problem of low efficiency of existing system monitoring methods.

[0005] The embodiments of this application adopt the following technical solutions: On the one hand, an embodiment of the present application provides a system monitoring method based on OPS, which includes: obtaining the config information, token value and encrypted string of the system to be monitored to establish a data connection between OPS and the system to be monitored, monitoring the cluster operation indicators of the system to be monitored through OPS cluster management, determining whether there are any abnormalities in the cluster operation indicators, and when there are abnormalities in the cluster operation indicators, sending an alarm message to the client, and when the alarm message is confirmed, performing abnormal repair processing on the application corresponding to the cluster abnormal indicator through OPS.

[0006] In one example, the cluster operation indicators of the system to be monitored are monitored through OPS cluster management. Before determining whether there is an abnormality in the cluster operation indicators, the method also includes: constructing an indicator trend prediction model through an LSTM neural network based on historical cluster operation indicator data; predicting the cluster operation indicators of the system to be monitored based on the indicator trend prediction model to obtain an indicator prediction value; when the indicator prediction value is greater than a preset indicator threshold, sending an early warning message to the client.

[0007] In one example, when the alarm information is confirmed, the OPS performs abnormal repair processing on the application corresponding to the cluster abnormal indicator, specifically including: if the application corresponding to the abnormal indicator is unresponsive, restart the unresponsive application according to the preset grayscale restart strategy; if the memory usage of the application corresponding to the abnormal indicator exceeds the threshold, perform data migration on the application whose memory usage exceeds the threshold; if the application corresponding to the abnormal indicator does not submit SQL, generate a kill statement and send it to the client.

[0008] In one example, when the alarm information is confirmed, after the application corresponding to the cluster abnormality indicator is repaired through OPS, the method also includes: storing the alarm information in a blockchain hash, and building a distributed alarm record ledger through multi-node consensus; generating a blockchain transaction certificate for the abnormality repair process.

[0009] In one example, the cluster operation indicators of the monitored system are monitored through OPS cluster management to determine whether there are any abnormalities in the cluster operation indicators, specifically including: correlating the business indicators and technical indicators in the cluster operation indicators according to a preset business-technology correlation table to generate business-technology correlation indicators; monitoring the business-technology correlation indicators through OPS cluster management, and determining that the indicators are abnormal only when the correlated business indicators and technical indicators are both greater than the preset indicator thresholds.

[0010] In one example, after obtaining the config information, token value and encrypted string of the system to be monitored to establish a data connection between OPS and the system to be monitored, the method also includes: collecting basic operating indicators of the cluster of the system to be monitored through a Python monitoring script; deploying OPS monitoring components for the system to be monitored through containerized deployment to realize the monitoring function of OPS cluster management.

[0011] In one example, after deploying the OPS monitoring component for the system to be monitored through containerized deployment, the method further includes: preprocessing the basic operating indicators of the cluster of the system to be monitored through the edge computing node to obtain cluster operating indicators; and uploading the cluster operating indicators to the OPS cluster management.

[0012] In one example, when the cluster operation indicator is abnormal, an alarm message is sent to the client, specifically including: sending the alarm message to the client through the communication enhancement architecture, and generating a visual alarm view according to a preset alarm level.

[0013] On the other hand, an embodiment of the present application provides an OPS-based system monitoring device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any one of the above-mentioned OPS-based system monitoring methods.

[0014] On the other hand, an embodiment of the present application provides an OPS-based system monitoring non-volatile computer storage medium storing computer-executable instructions capable of executing any one of the above-mentioned OPS-based system monitoring methods.

[0015] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects: This application deploys only a lightweight, operating system-level metrics collection service on the application server, and directly uses the application service to collect and report relevant alarm information. This reduces the communication costs of system alarm processing and monitoring platform managers, and also reduces the repeated deployment of multiple agents across multiple monitoring platforms. This significantly relieves pressure on the application server, improves the timeliness of system fault handling, and effectively reduces the system failure rate. Furthermore, the system can collect various resource monitoring indicators related to the business. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the present application, some embodiments of the present application will be described in detail below with reference to the accompanying drawings, in which: Figure 1 A flowchart of a system monitoring method based on OPS provided in an embodiment of the present application; Figure 2 A monitoring operation flow chart of a system monitoring method based on OPS provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of an OPS-based system monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0018] Some embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0019] Figure 1 This is a flow chart of an OPS-based system monitoring method provided in an embodiment of the present application. This method can be applied to different business areas. Certain input parameters or intermediate results in this process allow for manual intervention and adjustment to help improve accuracy.

[0020] The analysis method involved in the embodiments of the present application can be implemented by a terminal device or a server, and the present application does not impose any special restrictions on this. For ease of understanding and description, the following embodiments are described in detail using a controller as an example.

[0021] Based on this, Figure 1 The process in may include the following steps: S101: Obtain config information, token value, and encrypted string of the system to be monitored to establish a data connection between the OPS and the system to be monitored.

[0022] In some embodiments of the present application, to monitor the system, it is first necessary to obtain the config information, token value and encrypted string of the system to be monitored, that is, add the config information and token value of the system to be monitored in the OPS system, and then enter the project config file in the OPS interface. After verification through the token value, the encrypted authorization string is obtained to establish a data connection between the OPS and the system to be monitored.

[0023] Furthermore, after establishing the data connection between OPS and the system to be monitored, the first monitoring needs to log in to each server of the system to be monitored and install the Python monitoring script. The Python monitoring script is used to collect the basic operating indicators of the cluster of the system to be monitored. Secondly, OPS monitoring components are deployed for the monitored system through containerized deployment to realize the monitoring function of OPS cluster management. It is convenient and fast, and can be deployed once and used forever.

[0024] Furthermore, through the edge computing node, the basic operating indicators of the monitored system cluster are preprocessed (data cleaning, noise reduction, etc.) to obtain cluster operating indicators, and then the cluster operating indicators are uploaded to the OPS cluster management to realize the monitoring of the cluster operating indicators of the monitored system through the OPS cluster management.

[0025] S102: Monitor cluster operation indicators of the system to be monitored through OPS cluster management to determine whether there are any abnormalities in the cluster operation indicators.

[0026] In some embodiments of the present application, after uploading cluster operation indicators to OPS cluster management, an indicator trend prediction model is constructed using an LSTM neural network based on historical cluster operation indicator data. The cluster operation indicators of the monitored system are then predicted based on the indicator trend prediction model to obtain the indicator prediction value. When the indicator prediction value exceeds the preset indicator threshold, an early warning message is sent to the client. For example, if the model predicts that the number of connections of a database instance will exceed the threshold in 4 hours, the system will automatically send a "resource pre-occupancy warning" to prompt early expansion.

[0027] Trend-predictive early warning solves the problem of delayed response after a fault occurs, and advances fault handling to the budding stage.

[0028] Furthermore, based on a preset business-technology correlation table, the business and technical indicators in the cluster's operational indicators are correlated to generate business-technology correlation indicators. For example, during the payroll calculation period on the 5th of each month, the database CPU usage is automatically correlated with the SQL time consumed by the payroll module. Another example is during peak attendance clocking periods, where the correlation between application server memory usage and clocking interface response time is analyzed. The business-technology correlation indicators are then monitored through OPS cluster management. Only when both the correlated business and technical indicators exceed the preset thresholds is an indicator identified as abnormal.

[0029] It breaks through the limitation of existing monitoring that only focuses on technical indicators, deeply integrates business scenarios with infrastructure monitoring, makes business problems traceable, and provides a basis for resource optimization, solving the pain point of the disconnect between technology and business in existing solutions.

[0030] S103: When the cluster operation indicator is abnormal, an alarm message is sent to the client.

[0031] In some embodiments of the present application, the cluster operation indicators of the system are continuously monitored. When there are abnormalities in the cluster operation indicators, alarm information is sent to the client through the communication enhancement architecture (such as sending a code request or voice prompt, alarm light prompt, etc.), and a visual alarm view is generated according to the preset alarm level (such as application no response is a high alarm level, and application failure to submit SQL is a low alarm level).

[0032] S104: When the alarm information is confirmed, the OPS performs abnormal repair processing on the application corresponding to the cluster abnormality indicator.

[0033] In some embodiments of the present application, when the alarm information sent to the client is confirmed, if the alarm information indicates that the application corresponding to the abnormal indicator is unresponsive, then the unresponsive application is restarted according to the preset grayscale restart strategy; if the alarm information indicates that the memory usage of the application corresponding to the abnormal indicator exceeds the threshold, data migration is performed on the application whose memory usage exceeds the threshold; if the alarm information indicates that the application corresponding to the abnormal indicator has not submitted SQL, a kill statement is generated and sent to the client.

[0034] Furthermore, after the abnormality prompted by the alarm information is processed, the alarm information will be hashed and stored on the blockchain, and a distributed alarm record ledger will be built through multi-node consensus; at the same time, a blockchain transaction certificate will be generated for the abnormality repair process to achieve traceability of the operation.

[0035] This application introduces blockchain technology into the monitoring system to solve the problems of insufficient credibility of monitoring data and difficulty in operation traceability in existing system monitoring solutions, and meet the data compliance needs of financial-level enterprises.

[0036] It should be noted that although the embodiments of this application are based on Figure 1 Steps S101 to S104 are described in sequence, but this does not mean that steps S101 to S104 must be performed in a strict order. Figure 1 The order shown in FIG1 is to introduce and explain step S101 to step S104 in order to facilitate those skilled in the art to understand the technical solution of the embodiment of the present application. In other words, in the embodiment of the present application, the order between step S101 to step S104 can be appropriately adjusted according to actual needs.

[0037] pass Figure 1 This method deploys only a lightweight operating system-level indicator collection service on the application server and directly uses the application service to collect relevant alarm information for reporting. This reduces the communication costs of system alarm processing and monitoring platform managers. It also reduces the repeated deployment of multiple agents on multiple monitoring platforms, greatly relieves the pressure on the application server, improves the processing time of system failures, and effectively reduces the system failure rate. The system can also collect various resource monitoring indicators related to the business.

[0038] Figure 2 A monitoring operation flow chart of an OPS-based system monitoring method provided in an embodiment of the present application.

[0039] exist Figure 2 In the figure, it is shown how the system of the present application is monitored and how the monitoring end is deployed.

[0040] Figure 3A schematic diagram of the structure of an OPS-based system monitoring device provided in an embodiment of the present application includes: at least one processor; and, a memory communicatively connected to at least one processor; wherein, The memory stores instructions that can be executed by at least one processor. The instructions are executed by the at least one processor so that the at least one processor can execute any one of the above-mentioned OPS-based system monitoring methods.

[0041] Some embodiments of the present application provide an OPS-based system monitoring non-volatile computer storage medium storing computer-executable instructions capable of executing any one of the above-mentioned OPS-based system monitoring methods.

[0042] The various embodiments in this application are described in a progressive manner. Similar portions between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device and medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simple. For relevant portions, refer to the descriptions of the method embodiments.

[0043] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0044] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0045] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0046] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0047] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0048] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0049] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM), and non-volatile memory such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0050] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0051] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0052] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the technical principles of the present application should fall within the scope of protection of the present application.

Claims

1. A system monitoring method based on OPS, characterized in that: The method comprises: Obtain the config information, token value, and encrypted string of the system to be monitored to establish a data connection between the OPS and the system to be monitored; Monitor the cluster operation indicators of the monitored system through OPS cluster management to determine whether there are any abnormalities in the cluster operation indicators; the cluster operation indicators include server operation indicators, database transaction indicators, application survival indicators and log information; When there is an abnormality in the cluster operation indicator, an alarm message is sent to the client; When the alarm information is confirmed, the OPS performs abnormal repair processing on the application corresponding to the cluster abnormality indicator.

2. The method according to claim 1, characterized in that Before monitoring the cluster operation indicators of the monitored system through the OPS cluster management and determining whether the cluster operation indicators are abnormal, the method further includes: Based on historical cluster operation indicator data, an indicator trend prediction model is constructed through the LSTM neural network; Predicting the cluster operation indicators of the system to be monitored based on the indicator trend prediction model to obtain indicator prediction values; When the predicted indicator value is greater than the preset indicator threshold, an early warning message is sent to the client.

3. The method according to claim 1, characterized in that When the alarm information is confirmed, the OPS performs abnormal repair processing on the application corresponding to the cluster abnormality indicator, specifically including: If the application corresponding to the abnormal indicator is unresponsive, restart the unresponsive application according to the preset grayscale restart strategy; If the memory usage of the application corresponding to the abnormal indicator exceeds the threshold, data migration is performed on the application with excessive memory usage. If the application corresponding to the abnormal indicator does not submit SQL, a kill statement is generated and sent to the client.

4. The method according to claim 1, wherein When the alarm information is confirmed, after performing abnormal repair processing on the application corresponding to the cluster abnormality indicator through the OPS, the method further includes: The alarm information is stored in a blockchain hash and a distributed alarm record book is built through multi-node consensus. Generate blockchain transaction vouchers for abnormal repair processing.

5. The method according to claim 1, wherein The OPS cluster management monitors the cluster operation indicators of the monitored system and determines whether there are any abnormalities in the cluster operation indicators, specifically including: According to the preset business-technology correlation table, the business indicators and technical indicators in the cluster operation indicators are correlated to generate business-technology correlation indicators; The business-technology related indicators are monitored through OPS cluster management, and only when the related business indicators and technical indicators are both greater than the preset indicator thresholds, it is determined that the indicators are abnormal.

6. The method according to claim 1, characterized in that After obtaining the config information, token value, and encrypted string of the system to be monitored to establish a data connection between the OPS and the system to be monitored, the method further includes: Use Python monitoring scripts to collect basic operating indicators of the system cluster to be monitored; Deploy OPS monitoring components for the monitored system through containerized deployment to implement the monitoring function of OPS cluster management.

7. The method according to claim 6, characterized in that After deploying the OPS monitoring component for the system to be monitored through containerized deployment, the method further includes: Through the edge computing nodes, the basic operating indicators of the monitoring system cluster are preprocessed to obtain the cluster operating indicators; Upload the cluster operation indicators to OPS cluster management.

8. The method according to claim 1, characterized in that When the cluster operation indicator is abnormal, an alarm message is sent to the client, specifically including: The alarm information is sent to the client through the communication enhancement architecture, and a visual alarm view is generated according to the preset alarm level.

9. A system monitoring device based on OPS, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the OPS-based system monitoring method according to any one of claims 1 to 8.

10. An OPS-based system monitoring storage medium storing computer-executable instructions, characterized in that: The computer executable instructions can execute the OPS-based system monitoring method described in any one of claims 1 to 8.

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