Operation and maintenance monitoring method and device based on multiple data sources

Abstract

The present application discloses an operation and maintenance monitoring method and device based on multiple data sources, the method comprising: obtaining detection control configuration parameters, and generating detection task execution rules according to the detection control configuration parameters; determining whether the detection timing of the system to be detected meets the detection trigger conditions, and if so, obtaining detection data from multiple data sources of the system to be detected, wherein the data sources include Zabbix, Pinpoint, scripts, and data interfaces; judging in turn whether the detection data meets the accuracy conditions and compliance conditions, and if both are met, determining the warning level of the system to be detected according to the alarm rule engine, and issuing an alarm. The present application can intuitively reflect the operating status of the business system, accurately generate system portraits, provide a data basis for the value output of the business department, and help relevant staff to globally control all systems and business status, improve the quality of business systems, and improve the ability and level of social financial services.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an operation and maintenance monitoring method and device based on multiple data sources. Background Art

[0002] At present, many companies are extremely dependent on the normal operation of business systems, such as insurance business, financial business, etc. Some companies are involved in many types of businesses, and there are also many business systems deployed within the company, and each business system is usually independent. In order to ensure the normal operation of the business system, it is necessary to monitor all aspects of the business system during daily operation and maintenance.

[0003] As the number and complexity of systems in enterprises increase dramatically, and as different lines are responsible for different systems and different platforms, when staff receive push notifications for alarm information, they often receive alarms that are not from the systems they are responsible for. Therefore, the traditional model of discrete management of multiple data centers and multiple business systems using multiple monitoring tools can no longer meet existing operation and maintenance monitoring needs. Summary of the invention

[0004] To solve the above problems, an embodiment of the present application provides an operation and maintenance monitoring method and device based on multiple data sources.

[0005] In a first aspect, an operation and maintenance monitoring method based on multiple data sources is provided, including:

[0006] Acquire detection control configuration parameters, and generate detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions and compliance conditions;

[0007] Determine whether the detection timing of the system to be detected meets the detection trigger condition, and if so, obtain detection data from multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are used to collect detection data of databases, servers, middleware and applications respectively;

[0008] It is determined in turn whether the detection data meets the accuracy condition and the compliance condition. If both conditions are met, the warning level of the system to be detected is determined according to the alarm rule engine, and an alarm is issued.

[0009] Optionally, in the above method, the acquiring of the detection control configuration parameters and generating the detection task execution rules according to the detection control configuration parameters include:

[0010] Provide a front-end interface, the front-end interface includes multiple detection control configuration items, wherein the multiple detection control configuration items include: a configuration item of identity information of a system to be detected, a configuration item of enabling a detection task, a configuration item of enabling time of a detection task, a configuration item of a time period of a detection task, and a configuration item of dormancy of a detection task;

[0011] Responsive to configuration instructions in a plurality of detection control configuration items, acquiring detection control configuration parameters through the front-end interface;

[0012] The detection triggering condition is determined by combining multiple detection control configuration parameters, wherein the detection triggering condition includes: detection period of the detection task, detection task start timing, detection task sleep timing, and detection task start status.

[0013] Optionally, in the above method, determining whether the detection time of the system to be detected meets the detection trigger condition includes:

[0014] At the end of the detection cycle, the detection timing of the system to be detected is obtained, and the detection timing includes: the current time and the number of alarms within a preset historical time period;

[0015] Determine whether the current time meets the detection task start timing, and if so, determine whether the number of alarms within the preset historical duration meets the detection task sleep timing;

[0016] If not, it is determined whether the detection start execution state is enabled, and if so, it is determined that the detection timing of the system to be detected meets the detection trigger condition.

[0017] Optionally, in the above method, the plurality of detection control configuration items further include a data accuracy configuration item, and the data accuracy configuration item includes a plurality of first sub-configuration items;

[0018] The multiple first sub-configuration items include: a continuous interval configuration item, a continuous interval alarm number configuration item; an interval interval configuration item, an interval interval alarm number configuration item, and a proportion timeout threshold configuration item;

[0019] The acquiring of the detection control configuration parameters and generating the detection task execution rules according to the detection control configuration parameters also includes:

[0020] In response to configuration instructions for the plurality of first sub-configuration items, obtaining configuration parameters in the first sub-configuration items through the front-end interface;

[0021] The accurate condition is determined by combining configuration parameters in a plurality of first sub-configuration items.

[0022] Optionally, in the above method, the sequentially determining whether the detection data satisfies the accuracy condition and the compliance condition includes:

[0023] Determine within a continuous interval whether the number of historical alarms of the detection data reaches the number of alarms in the continuous interval, if so, determine that the detection data does not meet the accuracy condition, if not, determine that the detection data meets the accuracy condition;

[0024] or,

[0025] Determine within the interval whether the number of historical alarms of the detection data reaches the number of alarms within the interval, if so, determine that the detection data does not meet the accuracy condition, if not, determine that the detection data meets the accuracy condition;

[0026] or,

[0027] Determine the current transaction volume based on the detection data, and determine whether the current transaction volume is greater than the proportion timeout threshold. If so, determine that the detection data meets the accurate condition; if not, determine that the detection data does not meet the accurate condition.

[0028] Optionally, in the above method, the multiple detection control configuration items further include a data compliance configuration item, and the data compliance configuration item includes a plurality of second sub-configuration items;

[0029] Among them, the mandatory items of the multiple second sub-configuration items include IP compliance configuration item, system name compliance configuration item, alarm time compliance configuration item, and alarm content compliance configuration item;

[0030] The acquiring of the detection control configuration parameters and generating the detection task execution rules according to the detection control configuration parameters also includes:

[0031] In response to configuration instructions for the plurality of second sub-configuration items, obtaining configuration parameters in the second sub-configuration items through the front-end interface;

[0032] Combining configuration parameters in a plurality of second sub-configuration items to determine the compliance condition;

[0033] The determining in sequence whether the detection data satisfies the accuracy condition and the compliance condition further includes:

[0034] It is determined whether the acquired detection data includes mandatory items of the plurality of second sub-configuration items and meets the configuration compliance requirements of each second sub-configuration item. If so, it is determined that the detection data meets the compliance condition.

[0035] Optionally, in the above method, determining the warning level of the system to be detected according to the alarm rule engine and issuing an alarm includes:

[0036] Based on the detection data of the system to be detected, running the alarm rule engine to determine the warning level of the system to be detected;

[0037] If the detection data is within the first-level warning level threshold, it is determined that the system to be detected is at the first-level warning level, and an alarm is issued to the first target in the form of information;

[0038] If the detection data is within the second-level warning level threshold, it is determined that the system to be detected is at the second-level warning level, and an alarm is issued to the first target and the second target in the form of information;

[0039] If the detection data is within the third-level warning level threshold, it is determined that the system to be detected is at the third-level warning level, and an alarm is issued to the first target, the second target, and the third target in the form of information.

[0040] In a second aspect, an operation and maintenance monitoring device based on multiple data sources is provided, the device comprising:

[0041] An acquisition unit, configured to acquire detection control configuration parameters, and generate detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions and compliance conditions;

[0042] A judgment unit, used to determine whether the detection timing of the system to be detected meets the detection trigger condition, and if so, obtain detection data from multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are used to collect detection data of databases, servers, middleware and applications respectively;

[0043] The alarm unit is used to determine whether the detection data meets the accuracy condition and the compliance condition in turn. If both are met, the warning level of the system to be detected is determined according to the alarm rule engine, and an alarm is issued.

[0044] In a third aspect, an embodiment of the present application further provides an electronic device, comprising: a processor and a memory arranged to store computer executable instructions, wherein the executable instructions, when executed, cause the processor to perform any of the above methods.

[0045] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores one or more programs, and when the one or more programs are executed by an electronic device including multiple applications, the electronic device executes any of the above methods.

[0046] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0047] In order to adapt to the development of business systems and meet the requirements of large-scale, large number and high-performance monitoring systems, the present application obtains detection control configuration parameters and generates detection task execution rules based on the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions and compliance conditions; determining whether the detection conditions of the system to be detected meet the detection trigger conditions, and if so, obtaining detection data from multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are respectively used to collect detection data from databases, servers, middleware and applications; judging in turn whether the detection data meets the accuracy conditions and the compliance conditions, and if both are met, determining the warning level of the system to be detected according to the alarm rule engine, and issuing an alarm. A comprehensive monitoring method has been built that integrates business monitoring of servers, databases, middleware, applications, etc., to conduct centralized and unified monitoring, display and alarm, support extensive data access and rapid adaptation capabilities at the platform level, and can proactively and timely discover whether there are problems with application status and performance, forming a new situation of proactive IT operation and maintenance services, which can quickly locate faults, assist in quickly resolving faults, and better support and ensure the stable operation of various system businesses; establish industry service channels for various industries, promote transparent and convenient services, and achieve a stable situation in which business system supervision can be controlled. At the same time, it also builds an information fortress for the realization of industry "linked operation and maintenance" and provides a foundation for the formation of the most important tool in the field of application operation and maintenance. This application realizes the transformation of operation and maintenance personnel from passive solution to active discovery of problems, and can quickly locate and resolve faults. In addition, the integrated and configured management of multiple data sources can enable the linkage and collaboration of multiple operation and maintenance tools, and the closed-loop guarantee of the orderly operation of the IT operation and maintenance ecosystem, which to a certain extent lays a solid foundation for the goal of "reducing costs and increasing efficiency"; and this application can intuitively reflect the operating status of the business system, accurately generate system portraits, and provide a data basis for the value output of the business department, which will help relevant staff to have a global control of all systems and business status, improve the quality of business systems, and improve the ability and level of social financial services. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0049] Figure 1 A schematic diagram showing a flow chart of an operation and maintenance monitoring method based on multiple data sources according to an embodiment of the present application is shown;

[0050] Figure 2 A schematic diagram showing a flow chart of an operation and maintenance monitoring method based on multiple data sources according to another embodiment of the present application is shown;

[0051] Figure 3 A schematic diagram showing the structure of an operation and maintenance monitoring device based on multiple data sources according to an embodiment of the present application is shown;

[0052] Figure 4 This is a schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0054] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0055] The idea of ​​this application is to adapt to the development of business systems and meet the requirements of large-scale, large-scale and high-performance monitoring systems. This application starts from the pain points of operation and maintenance monitoring, takes business system monitoring as the main line, and forms a comprehensive monitoring method that integrates server, database, middleware, application and other monitoring.

[0056] Figure 1 A flow chart of an operation and maintenance monitoring method based on multiple data sources according to an embodiment of the present application is shown. Figure 1 It can be seen that the present application at least includes steps S110 to S130:

[0057] Step S110: Acquire detection control configuration parameters, and generate detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions and compliance conditions.

[0058] Users have different requirements for the operation and maintenance detection of business systems. In this regard, this application supports users to configure the detection of business systems based on the system operation and maintenance status.

[0059] First, the user's configuration parameters for detection control are obtained, and whether and when detection is performed are controlled according to the detection control parameters.

[0060] In the configuration parameters, various parameters of the detection process can be configured, including but not limited to the detection cycle, detection time, whether the detection is started, etc. Based on these detection control configuration parameters, detection task execution rules will be generated, which include but are not limited to detection trigger conditions, accuracy conditions and compliance conditions.

[0061] The detection trigger condition is the user's definition of whether to conduct detection and when to conduct detection. The accuracy condition and compliance condition are the conditions used to verify the data in the subsequent detection process.

[0062] Step S120: Determine whether the detection timing of the system to be detected meets the detection trigger condition. If so, obtain the detection data of multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are used to collect detection data of databases, servers, middleware and applications respectively.

[0063] The monitoring of the business system in this application is multi-faceted and as comprehensive as possible. To this end, this application is designed to obtain detection data from multiple data sources and make judgments during detection. These data sources include but are not limited to: databases, servers, middleware, applications, etc.

[0064] The monitoring items for the database include but are not limited to: whether the database port is normal, whether the database connectivity is good, whether the number of database connections is too many, etc.

[0065] The monitoring items of the server include but are not limited to: application server disk space usage, application server disk space usage, database archive log server disk space usage, database archive log server disk space usage, remaining disk index nodes, whether the processor load is too high, whether the available memory is too low, whether the free swap space is too low, whether the CPU usage is too high, whether the number of processes is too many, whether the number of running processes is too many, whether the agent is abnormal, etc.

[0066] The monitoring items of middleware (including but not limited to WebLogic) include but are not limited to: whether the middleware process is abnormal, middleware status monitoring, middleware open sockets, the number of data source connections opened by the middleware and other general monitoring items. It can also include KAFKA (a distributed publish-subscribe message system, there is no unified Chinese name in the industry), redis (a cache database, there is no unified Chinese name in the industry), MQ (Message Queue, a message queue, there is no unified Chinese name in the industry), ActiveMQ (a code message middleware, there is no unified Chinese name in the industry) and other related monitoring items. For example, the monitoring items of KAFKA include but are not limited to the number of files opened by the kafka server, whether the kafka process is abnormal, whether the zookeeper process is abnormal, and whether its port is abnormal; for example, the monitoring items of redis include but are not limited to whether the redis port is abnormal, the redis hit rate, etc., and the MQ message queue depth, and the ActiveMQ queue depth, etc.

[0067] The monitoring items of the application include but are not limited to: application layer monitoring items, log monitoring items, application interface monitoring items, and link-related monitoring items, among which application layer monitoring items include but are not limited to whether the application port is abnormal, whether the application address is abnormal, whether the application load address is abnormal, etc.; log monitoring items include but are not limited to monitoring the error type log content, the appearance of specified keywords in the log, whether the log file exists, and whether the monitoring log is updated within N minutes (the N value is configurable); application interface monitoring items include but are not limited to application interface status monitoring, application interface keyword monitoring, application interface message interaction, and application interface response timeout, etc.; link-related monitoring items include but are not limited to response timeout data volume, response timeout data volume ratio, abnormal alarm information, etc. In the prior art, for the detection of business systems, for the above-mentioned detection items, different monitoring tools or software are usually used to manage the business system in a discrete manner. However, this application is different from being limited to technology. It has built a comprehensive monitoring tool that integrates server, database, middleware, application and other business monitoring to conduct centralized and unified monitoring, display and alarm.

[0068] Before detecting the system to be detected, certain logical judgments need to be made to determine whether to detect. For the detection triggering time, users can limit the detection control configuration parameters, such as whether to detect and the detection time. For example, if the detection cycle is set to 5 minutes, detection can be performed every 5 minutes; specific detection times can also be set, such as setting a detection at 7:00 every night. It is also possible to set whether to detect. For example, during the upgrade of the business system, the detection process is best to be terminated. At this time, the startup item of the detection task can be turned off to terminate the detection.

[0069] The detection trigger conditions are not limited to the simple logical judgment mentioned above, but can also save calculation amount, reduce alarm redundancy, etc. by setting parameters.

[0070] For example, if the current moment is used as the benchmark, for a monitoring item, if an alarm has occurred within a certain period of time in history, no alarm will be given, etc. For the detection trigger conditions, there is no restriction without application, and users can set them according to the detection accuracy and actual working conditions.

[0071] Only when it is determined that detection is to be carried out, data collection or acquisition is carried out, which can greatly reduce the amount of calculation. When "obtaining" detection data from multiple data sources of the system to be detected, due to the diversity of data sources, a combination of multiple means and methods can be used to obtain these data. For example, based on the Zabbix (there is no unified Chinese name in the industry) component, the detection data of the database, the detection data of the middleware, and the infrastructure layer data of the server are obtained; based on the Pinpoint component, the log data of the server is obtained; based on a self-built script, the detection data of the application is obtained; and the detection data from multiple data sources obtained are temporarily stored in a time series database for use.

[0072] Taking Zabbix as an example, Zabbix is ​​an enterprise-level open source solution based on a WEB interface that provides distributed system monitoring and network monitoring functions. Zabbix can monitor various network parameters to ensure the safe operation of the server system; and provide a flexible notification mechanism to allow system administrators to quickly locate / solve various existing problems. Zabbix consists of two parts, Zabbix server and the optional component Zabbix agent. Zabbix server can provide remote server / network status monitoring, data collection and other functions through SNMP, Zabbixagent, ping, port monitoring and other methods. It can run on Linux, Solaris, HP-UX, AIX, Free BSD, Open BSD, OSX and other platforms.

[0073] The Pinpoint component is also an open source distributed application performance management tool, and like the Zabbix component, it is open source. In some embodiments of the present application, the above methods can be used in combination according to the detection requirements, such as using Zabbix, Pinpoint and scripts to collect data. The Zabbix component can be used to obtain database detection data, middleware detection data, and server infrastructure layer data, including but not limited to memory, disk, CPU, port, process, web address, etc.; for the data collected by Zabbix, the required data can be extracted and sorted for easy display and data push.

[0074] For example, the Pinpoint component is mainly used for link monitoring. Each time a call is made between systems, the number of calls and the duration of the call are recorded. Pinpoint can collect and organize the number of calls and the duration of each call into data of less than or equal to 1S, greater than 1S and less than 3S, greater than 3S and less than or equal to 5S, and greater than 5S. The data of each time interval is compared with the total transaction volume to obtain the percentage. These data can be stored in the log data of the server.

[0075] Not only can pinpoint collect log data, but self-built scripts, such as Xshell scripts, can also be used to collect logs. Self-built scripts can also be used to obtain detection data related to the application, etc., which will not be listed one by one.

[0076] After obtaining the detection data of the system to be detected, necessary processing is performed and then proceed to the next step.

[0077] Step S130: determine whether the detection data meets the accuracy condition and the compliance condition in turn. If both conditions are met, determine the warning level of the system to be detected according to the alarm rule engine and issue an alarm.

[0078] When it is confirmed whether the detection timing of the system to be detected meets the detection triggering conditions, the detection task is started, and an alarm calculation is performed based on the detection data from the multiple data sources obtained as above.

[0079] Before performing an alarm calculation, it is necessary to confirm whether the detection data meets the accuracy conditions and compliance conditions of the data. In some embodiments of the present application, in order to save computing power and improve computing efficiency, the accuracy conditions and compliance conditions are judged in sequence. The judgment rules for the accuracy and compliance of data are different for different collection methods. According to the accuracy conditions and compliance conditions, the accuracy and compliance of the data can be greatly improved to avoid data misreporting.

[0080] Users can also set accuracy conditions and compliance conditions for detection data. When it is determined that the detection data meets the accuracy conditions and compliance conditions, the alarm calculation phase is entered, that is, the warning level of the system to be detected is determined according to the alarm rule engine, and an alarm is issued.

[0081] The alarm rules and alarm thresholds in the alarm rule engine can be preset in advance. For example, if the server memory usage is set to no more than 85%, through calculation, when it is determined that the server memory usage is greater than or equal to 85%, an alarm will be issued for this monitoring item; if the server memory usage is less than 85%, no alarm will be issued.

[0082] In the prior art, since each line is responsible for different systems and each system belongs to a different platform, when WeChat pushes alarm information, the received alarm may not be for the system that the corresponding worker is responsible for. In order to avoid too much alarm information, which causes the staff to be unable to view the alarm of the system they are responsible for in real time, and to ensure the accuracy of the alarm system received by each line, this application sets up hierarchical alarms. Based on the detection data of the system to be detected, the alarm rule engine is run to determine the warning level of the system to be detected; if the detection data is at the first-level warning level threshold, it is determined that the system to be detected is at the first-level warning level, and an alarm is issued to the first target in the form of information; if the detection data is at the second-level warning level threshold, it is determined that the system to be detected is at the second-level warning level, and an alarm is issued to the first target and the second target in the form of information; if the detection data is at the third-level warning level threshold, it is determined that the system to be detected is at the third-level warning level, and an alarm is issued to the first target, the second target and the third target in the form of information.

[0083] For example, when the detection data reaches the first-level warning level, the business system is running normally at this time, and the front-line operation and maintenance colleagues will be notified by WeChat to be informed and handle it; when the detection data reaches the second-level warning level, a certain node of the business system is no longer available, and the system access has been transplanted to other nodes for access. At this time, the front-line operation and maintenance colleagues and the leaders responsible for this system will be informed by WeChat, and the person in charge of the system will urge to resolve the problem; when the detection data reaches the third-level warning level, the business system is paralyzed and cannot provide access. At this time, WeChat notifications and text messages will be notified to the front-line operation and maintenance colleagues, the leaders responsible for this system, and department leaders, and the department leaders will urge to resolve the problem.

[0084] have Figure 1It can be seen from the method shown that in order to adapt to the development of business systems and meet the requirements of large-scale, large number and high performance of their monitoring systems, the present application obtains the detection control configuration parameters and generates detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger rules, accurate conditions and compliance conditions; determining whether the detection conditions of the system to be detected meet the detection trigger rules, and if so, obtaining detection data from multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are respectively used to collect detection data from databases, servers, middleware and applications; judging in turn whether the detection data meets the accurate conditions and the compliance conditions, if both are met, determining the warning level of the system to be detected according to the alarm rule engine, and issuing an alarm. A comprehensive monitoring method has been built that integrates business monitoring of servers, databases, middleware, applications, etc., to conduct centralized and unified monitoring, display and alarm, support extensive data access and rapid adaptation capabilities at the platform level, and can proactively and timely discover whether there are problems with application status and performance, forming a new situation of proactive IT operation and maintenance services, which can quickly locate faults, assist in quickly resolving faults, and better support and ensure the stable operation of various system businesses; establish industry service channels for various industries, promote transparent and convenient services, and achieve a stable situation in which business system supervision can be controlled. At the same time, it also builds an information fortress for the realization of industry "linked operation and maintenance" and provides a foundation for the formation of the most important tool in the field of application operation and maintenance. This application realizes the transformation of operation and maintenance personnel from passive solution to active discovery of problems, and can quickly locate and resolve faults. In addition, the integrated and configured management of multiple data sources can enable the linkage and collaboration of multiple operation and maintenance tools, and the closed-loop guarantee of the orderly operation of the IT operation and maintenance ecosystem, which to a certain extent lays a solid foundation for the goal of "reducing costs and increasing efficiency"; and this application can intuitively reflect the operating status of the business system, accurately generate system portraits, and provide a data basis for the value output of the business department, which will help relevant staff to have a global control of all systems and business status, improve the quality of business systems, and improve the ability and level of social financial services.

[0085] In some embodiments of the present application, detection control configuration parameters are obtained, and detection task execution rules are generated according to the detection control configuration parameters, including: providing a front-end interface, the front-end interface including multiple detection control configuration items, wherein the multiple detection control configuration items include: a system identity information configuration item to be detected, a detection task activation configuration item, a detection task activation time configuration item, a detection task time period configuration item, and a detection task sleep configuration item; in response to configuration instructions in the multiple detection control configuration items, the detection control configuration parameters are obtained through the front-end interface; and the detection trigger conditions are determined by combining the multiple detection control configuration parameters, wherein the detection trigger conditions include: a detection period of the detection task, a detection task start timing, a detection task sleep timing, and a detection task start status.

[0086] To facilitate user use, a front-end interface can be provided on the user terminal. Users can set the detection control configuration parameters by selecting or filling in the front-end interface. This application does not limit the specific detection control configuration items. All parameters required for detecting the business system can be configured, including but not limited to the identity information parameters of the system to be detected, detection task activation parameters, detection task activation time parameters, detection task time cycle parameters, detection task sleep parameters, etc.

[0087] After obtaining the above parameters, multiple detection control configuration parameters are combined to determine the detection trigger conditions, where the detection trigger conditions include but are not limited to: detection task detection cycle, detection task start time, detection task sleep time, detection task start status, etc.

[0088] In addition to the trigger-related parameters of the detection task, it can also include data accuracy condition parameters, compliance condition parameters, and information parameters of the alarm object, etc.

[0089] It should be noted that these parameters need to be filled in by the user only when the detection is performed for the first time. Each subsequent detection can use the parameters of the previous round of detection or the default parameters when there is no need to change the parameters. In some embodiments of the present application, a method for determining the detection triggering timing is recommended. Specifically, in the above method, the determination of whether the detection time of the system to be detected meets the detection triggering condition includes: at the end of the detection cycle, obtaining the detection timing of the system to be detected, and the detection timing includes: the current time and the number of alarms within the preset historical time length; judging whether the current time meets the detection task start timing, if so, judging whether the number of alarms within the preset historical time length meets the detection task sleep timing; if not, judging whether the detection start execution state is enabled, and if so, determining that the detection timing of the system to be detected meets the detection triggering condition.

[0090] That is to say, first determine whether the current time reaches the detection cycle. If not, wait. If reached, determine whether the number of alarms within the preset historical time length meets the detection task sleep timing. For example, the detection task sleep timing specifies that, based on the current time, within 10 minutes of history, the number of alarms reaches the alarm number threshold in the detection task sleep timing. Assuming the number of alarms is 5 times and the alarm number threshold is 3 times, it is determined that the number of alarms within the preset historical time length meets the detection task sleep timing. At this time, no detection is performed and the process ends. Assuming the number of alarms is 2 times and the alarm number threshold is 3 times, it is determined that the number of alarms within the preset historical time length does not meet the detection task sleep timing. At this time, it can be determined that the detection timing of the system to be detected meets the detection trigger condition, that is, the detection task is started.

[0091] In some other embodiments of the present application, it is possible to continue to determine whether the detection start execution state is enabled. If so, it is determined that the detection timing of the system to be detected meets the detection trigger condition, and the detection task is started to enter the subsequent process. This step can be configured in the configuration interface. The main purpose is to use this method to directly suspend the detection task when the system is urgently upgraded and there is no time to set the non-detection time for the specified system.

[0092] In some embodiments of the present application, the multiple detection control configuration items also include a data accuracy configuration item, and the data accuracy configuration item includes multiple first sub-configuration items; the multiple first sub-configuration items include: a continuous interval configuration item, a continuous interval alarm number configuration item; an interval interval configuration item, an interval interval alarm number configuration item, and a proportion timeout threshold configuration item. The acquisition of detection control configuration parameters and the generation of detection task execution rules based on the detection control configuration parameters also include: in response to configuration instructions for multiple first sub-configuration items, acquiring configuration parameters in the first sub-configuration items through the front-end interface; and combining the configuration parameters in multiple first sub-configuration items to determine the accuracy condition.

[0093] The sequentially judging whether the detection data satisfies the accurate condition and the compliance condition includes: determining within a continuous interval whether the number of historical alarms of the detection data reaches the number of alarms in the continuous interval, if so, determining that the detection data does not meet the accurate condition, if not, determining that the detection data meets the accurate condition; or, determining within an interval interval whether the number of historical alarms of the detection data reaches the number of alarms in the interval interval, if so, determining that the detection data does not meet the accurate condition, if not, determining that the detection data meets the accurate condition; or, determining the current transaction volume based on the detection data, and determining whether the current transaction volume is greater than the proportion timeout threshold, if so, determining that the detection data meets the accurate condition, if not, determining that the detection data does not meet the accurate condition.

[0094] When judging the accuracy of the data, it is sufficient to set the above-mentioned accuracy conditions reasonably. This application does not limit this. In some embodiments of this application, the above-mentioned method can be adopted as long as the detection data meets one or more of the above-mentioned conditions.

[0095] In some embodiments of the present application, if N alarms appear continuously in a continuous interval (N value is configurable) according to different collection time intervals and set conditions; or A alarms appear at an interval of M time (M value is configurable); or the data collected by Zabbix and Pinpoint both appear the same alarm or related alarm of the same monitoring item; or the collected data has a specified abnormality, it is determined that the detection data does not meet the accurate conditions. For example, Zabbix mainly monitors hardware resources, Pinpoint monitors business, and the self-built script monitors the deep status of the log middleware. The data from the three sources are integrated. When an alarm appears in the resource monitoring data, the current transaction volume is synchronously detected to see if the proportion timeout exceeds the threshold. The current script detection data also exceeds the threshold. If it exceeds, a combined alarm is issued.

[0096] On the premise that the detection data meets the accuracy requirements, compliance judgment is entered, and the multiple detection control configuration items also include data compliance configuration items, and the data compliance configuration items include multiple second sub-configuration items; wherein the required items of the multiple second sub-configuration items include IP compliance configuration items, system name compliance configuration items, alarm time compliance configuration items, and alarm content compliance configuration items; the acquisition of detection control configuration parameters and the generation of detection task execution rules based on the detection control configuration parameters also include: in response to configuration instructions for multiple second sub-configuration items, obtaining the configuration parameters in the second sub-configuration items through the front-end interface; combining the configuration parameters in multiple second sub-configuration items to determine the compliance conditions.

[0097] The step of successively judging whether the detection data satisfies the accuracy condition and the compliance condition further includes: judging whether the acquired detection data contains the required items of the multiple second sub-configuration items and meets the configuration compliance requirements of each second sub-configuration item; if so, determining that the detection data satisfies the compliance condition.

[0098] After the accuracy of the data is judged, the compliance is judged. When judging the compliance, the detection data needs to meet multiple conditions, such as IP, system name, alarm time, alarm content and other information. If one of the information is missing or one of the information does not meet the regulatory requirements, the detection data is considered to be non-compliant and will not be transferred to the next link.

[0099] Figure 2 A flow chart of an operation and maintenance monitoring method based on multiple data sources according to another embodiment of the present application is shown. Figure 2 It can be seen that this embodiment includes:

[0100] Determine whether there is alarm information within the specified time. If so, do not perform detection and end the process. If not, determine whether the current time is within the execution time. If so, do not perform detection and end the process. If so, determine whether the detection task execution status is execution. If so, obtain detection data from multiple data sources of the system to be detected, and determine whether they all meet the accuracy conditions and compliance conditions in turn. If they are met, run the warning rule engine, determine the warning level of the system to be detected, and issue an alarm.

[0101] Figure 3 An operation and maintenance monitoring device based on multiple data sources according to an embodiment of the present application is shown. Figure 3 It can be seen that the device 300 comprises:

[0102] The acquisition unit 310 is used to acquire the detection control configuration parameters and generate the detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions and compliance conditions;

[0103] The judgment unit 320 is used to determine whether the detection timing of the system to be detected meets the detection trigger condition. If so, the detection data of multiple data sources of the system to be detected are obtained, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are used to collect detection data of databases, servers, middleware and applications respectively;

[0104] The alarm unit 330 is used to determine whether the detection data meets the accuracy condition and the compliance condition in turn. If both are met, the warning level of the system to be detected is determined according to the alarm rule engine, and an alarm is issued.

[0105] In some embodiments of the present application, in the above-mentioned device, the acquisition unit 310 is used to provide a front-end interface, and the front-end interface includes multiple detection control configuration items, wherein the multiple detection control configuration items include: a system identity information configuration item to be detected, a detection task activation configuration item, a detection task activation time configuration item, a detection task time period configuration item, and a detection task sleep configuration item; in response to the configuration instructions in the multiple detection control configuration items, the detection control configuration parameters are acquired through the front-end interface; and the detection trigger conditions are determined in combination with the multiple detection control configuration parameters, wherein the detection trigger conditions include: a detection period of the detection task, a detection task start timing, a detection task sleep timing, and a detection task start status.

[0106] In some embodiments of the present application, in the above-mentioned device, the judgment unit 320 is used to obtain the detection timing of the system to be detected at the end of the detection cycle, and the detection timing includes: the current time and the number of alarms within a preset historical time length; judge whether the current time meets the detection task start timing, if so, judge whether the number of alarms within the preset historical time length meets the detection task sleep timing; if not, judge whether the detection start execution status is enabled, and if so, determine that the detection timing of the system to be detected meets the detection trigger condition.

[0107] In some embodiments of the present application, in the above-mentioned device, the multiple detection control configuration items also include a data accuracy configuration item, and the data accuracy configuration item includes a plurality of first sub-configuration items; the plurality of first sub-configuration items include: a continuous interval configuration item, a continuous interval alarm number configuration item; an interval interval configuration item, an interval interval alarm number configuration item, and a proportion timeout threshold configuration item; the acquisition unit 310 is also used to respond to configuration instructions for the plurality of first sub-configuration items, and obtain the configuration parameters in the first sub-configuration item through the front-end interface; and determine the accurate condition by combining the configuration parameters in the plurality of first sub-configuration items.

[0108] In some embodiments of the present application, in the above-mentioned device, the alarm unit 330 is used to determine whether the historical alarm number of the detection data reaches the continuous interval alarm number within a continuous interval. If so, it is determined that the detection data does not meet the accurate condition; if not, it is determined that the detection data meets the accurate condition; or, determine whether the historical alarm number of the detection data reaches the interval alarm number within an interval. If so, it is determined that the detection data does not meet the accurate condition; if not, it is determined that the detection data meets the accurate condition; or, determine the current transaction volume according to the detection data, and determine whether the current transaction volume is greater than the proportion timeout threshold. If so, it is determined that the detection data meets the accurate condition; if not, it is determined that the detection data does not meet the accurate condition.

[0109] In some embodiments of the present application, in the above-mentioned device, the multiple detection control configuration items also include data compliance configuration items, and the data compliance configuration items include multiple second sub-configuration items; wherein the required items of the multiple second sub-configuration items include IP compliance configuration items, system name compliance configuration items, alarm time compliance configuration items, and alarm content compliance configuration items; the acquisition unit 310 is also used to respond to configuration instructions for multiple second sub-configuration items, and obtain configuration parameters in the second sub-configuration items through the front-end interface; and determine the compliance conditions by combining the configuration parameters in multiple second sub-configuration items.

[0110] In some embodiments of the present application, in the above-mentioned device, the alarm unit 330 is used to determine whether the acquired detection data contains the required items of the multiple second sub-configuration items and meets the configuration compliance requirements of each second sub-configuration item. If so, it is determined that the detection data meets the compliance condition. In some embodiments of the present application, in the above-mentioned device, the alarm unit 330 is used to run the alarm rule engine based on the detection data of the system to be detected to determine the warning level of the system to be detected; if the detection data is at the first-level warning level threshold, it is determined that the system to be detected is at the first-level warning level, and an alarm is issued to the first target in the form of information; if the detection data is at the second-level warning level threshold, it is determined that the system to be detected is at the second-level warning level, and an alarm is issued to the first target and the second target in the form of information; if the detection data is at the third-level warning level threshold, it is determined that the system to be detected is at the third-level warning level, and an alarm is issued to the first target, the second target, and the third target in the form of information.

[0111] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. Figure 4At the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory. The memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. Of course, the electronic device may also include hardware required for other services.

[0112] The processor, network interface and memory can be interconnected through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0113] The memory is used to store the program. Specifically, the program may include a program code, and the program code includes a computer operation instruction. The memory may include a memory and a non-volatile memory, and provides instructions and data to the processor.

[0114] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming an operation and maintenance monitoring device based on multiple data sources at the logical level. The processor executes the program stored in the memory and is specifically used to perform the following operations:

[0115] Acquire detection control configuration parameters, and generate detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions and compliance conditions;

[0116] Determine whether the detection timing of the system to be detected meets the detection trigger condition, and if so, obtain detection data from multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are used to collect detection data of databases, servers, middleware and applications respectively;

[0117] It is determined in turn whether the detection data meets the accuracy condition and the compliance condition. If both conditions are met, the warning level of the system to be detected is determined according to the alarm rule engine, and an alarm is issued.

[0118] The above application Figure 3 The method performed by the operation and maintenance monitoring device based on multiple data sources disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0119] The electronic device may also perform Figure 3 The method is implemented in the operation and maintenance monitoring device based on multiple data sources, and the operation and maintenance monitoring device based on multiple data sources is implemented in Figure 3 The functions of the illustrated embodiment will not be described in detail in the embodiments of the present application.

[0120] The present application also provides a computer-readable storage medium, which stores one or more programs, wherein the one or more programs include instructions, which, when executed by an electronic device including multiple application programs, enable the electronic device to execute Figure 3 The method performed by the operation and maintenance monitoring device based on multiple data sources in the illustrated embodiment is specifically used to perform:

[0121] Acquire detection control configuration parameters, and generate detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions and compliance conditions;

[0122] Determine whether the detection timing of the system to be detected meets the detection trigger condition, and if so, obtain detection data from multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are used to collect detection data of databases, servers, middleware and applications respectively;

[0123] It is determined in turn whether the detection data meets the accuracy condition and the compliance condition. If both conditions are met, the warning level of the system to be detected is determined according to the alarm rule engine, and an alarm is issued.

[0124] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0125] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, 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 generate 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 flowchart and / or block diagram. 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.

[0126] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0127] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0128] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0129] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0130] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by 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 memory (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 technology, compact disk read-only memory (CD-ROM), digital versatile disk (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 temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0131] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0132] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0133] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. An operation and maintenance monitoring method based on multiple data sources, characterized in that: include: Acquire detection control configuration parameters, and generate detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions and compliance conditions; Determine whether the detection timing of the system to be detected meets the detection trigger condition, and if so, obtain detection data from multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are used to collect detection data of databases, servers, middleware and applications respectively; Determine in sequence whether the detection data meets the accuracy condition and the compliance condition. If both conditions are met, determine the warning level of the system to be detected according to the alarm rule engine and issue an alarm; The step of sequentially determining whether the detection data satisfies the accuracy condition and the compliance condition includes: Determine whether the number of historical alarms of the detection data reaches the number of alarms in the continuous interval within the continuous interval, if so, determine that the detection data does not meet the accuracy condition, if not, determine that the detection data meets the accuracy condition; or, Determine whether the number of historical alarms of the detection data reaches the number of alarms of the interval within the interval, if so, determine that the detection data does not meet the accuracy condition, if not, determine that the detection data meets the accuracy condition; or, Determine the current transaction volume according to the detection data, determine whether the current transaction volume is greater than the proportion timeout threshold, if so, determine that the detection data meets the accuracy condition, if not, determine that the detection data does not meet the accuracy condition; Wherein, the step of sequentially determining whether the detection data satisfies the accuracy condition and the compliance condition further includes: Determine whether the detection data contains information of corresponding IP compliance configuration items, system name compliance configuration items, alarm time compliance configuration items, and alarm content compliance configuration items, and meets the configuration compliance requirements of each configuration item. If so, determine that the detection data meets the compliance conditions; if one of the information is missing or one of the information does not meet the configuration compliance requirements, determine that the detection data does not meet the compliance conditions.

2. The method according to claim 1, characterized in that The acquiring of the detection control configuration parameters and generating the detection task execution rules according to the detection control configuration parameters includes: Provide a front-end interface, the front-end interface includes multiple detection control configuration items, wherein the multiple detection control configuration items include: a configuration item of identity information of a system to be detected, a configuration item of enabling a detection task, a configuration item of enabling time of a detection task, a configuration item of a time period of a detection task, and a configuration item of dormancy of a detection task; Responsive to configuration instructions for a plurality of detection control configuration items, acquiring detection control configuration parameters through the front-end interface; The detection triggering condition is determined by combining multiple detection control configuration parameters, wherein the detection triggering condition includes: detection period of the detection task, detection task start timing, detection task sleep timing, and detection task start status.

3. The method according to claim 2, characterized in that The determining whether the detection timing of the system to be detected meets the detection triggering condition includes: At the end of the detection cycle, the detection timing of the system to be detected is obtained, and the detection timing includes: the current time and the number of alarms within a preset historical time period; Determine whether the current time meets the detection task start time, and if so, determine whether the number of alarms within the preset historical time period meets the detection task sleep time; If not, it is determined whether the detection task startup state is enabled, and if so, it is determined that the detection timing of the system to be detected meets the detection trigger condition.

4. The method according to claim 2, characterized in that: The plurality of detection control configuration items further include a data accuracy configuration item, and the data accuracy configuration item includes a plurality of first sub-configuration items; The multiple first sub-configuration items include: a continuous interval configuration item, a continuous interval alarm number configuration item; an interval interval configuration item, an interval interval alarm number configuration item, and a proportion timeout threshold configuration item; The acquiring of the detection control configuration parameters and generating the detection task execution rules according to the detection control configuration parameters further includes: In response to configuration instructions for the plurality of first sub-configuration items, obtaining configuration parameters in the first sub-configuration items through the front-end interface; The accurate condition is determined by combining configuration parameters in a plurality of first sub-configuration items.

5. The method according to claim 2, characterized in that: The plurality of detection control configuration items further include a data compliance configuration item, and the data compliance configuration item includes a plurality of second sub-configuration items; Among them, the mandatory items of the multiple second sub-configuration items include IP compliance configuration item, system name compliance configuration item, alarm time compliance configuration item, and alarm content compliance configuration item; The acquiring of the detection control configuration parameters and generating the detection task execution rules according to the detection control configuration parameters further includes: In response to configuration instructions for the plurality of second sub-configuration items, obtaining configuration parameters in the second sub-configuration items through the front-end interface; The compliance condition is determined by combining configuration parameters in a plurality of second sub-configuration items.

6. An operation and maintenance monitoring device based on multiple data sources, characterized in that: The device comprises: An acquisition unit, configured to acquire detection control configuration parameters, and generate detection task execution rules according to the detection control configuration parameters, wherein the detection task execution rules include: detection trigger conditions, accuracy conditions, and compliance conditions; A judgment unit, used to determine whether the detection timing of the system to be detected meets the detection trigger condition, and if so, obtain detection data from multiple data sources of the system to be detected, wherein the multiple data sources include Zabbix, Pinpoint, scripts and data interfaces, wherein the Zabbix, Pinpoint, scripts and data interfaces are used to collect detection data of databases, servers, middleware and applications respectively; An alarm unit is used to determine whether the detection data meets the accuracy condition and the compliance condition in turn. If both conditions are met, the alarm rule engine is used to determine the warning level of the system to be detected and issue an alarm. The alarm unit is further used to determine whether the number of historical alarms of the detection data reaches the number of alarms in the continuous interval within a continuous interval, and if so, determine that the detection data does not meet the accuracy condition, and if not, determine that the detection data meets the accuracy condition; or, Determine whether the number of historical alarms of the detection data reaches the number of alarms of the interval within the interval, if so, determine that the detection data does not meet the accuracy condition, if not, determine that the detection data meets the accuracy condition; or, Determine the current transaction volume according to the detection data, determine whether the current transaction volume is greater than the proportion timeout threshold, if so, determine that the detection data meets the accuracy condition, if not, determine that the detection data does not meet the accuracy condition; The alarm unit is also used to determine whether the detection data contains information of corresponding IP compliance configuration items, system name compliance configuration items, alarm time compliance configuration items, and alarm content compliance configuration items, and meets the configuration compliance requirements of each configuration item. If so, it is determined that the detection data meets the compliance conditions; if one of the information is missing or one of the information does not meet the configuration compliance requirements, it is determined that the detection data does not meet the compliance conditions.

7. An electronic device comprising: A processor and a memory arranged to store computer executable instructions, which when executed cause the processor to perform the method of any one of claims 1 to 5. 8 . A computer-readable storage medium storing one or more programs, which, when executed by an electronic device including a plurality of application programs, causes the electronic device to execute the method according to claim 1 .

Images