WO2020233077A1

WO2020233077A1 - System service monitoring method, device, and apparatus, and storage medium

Info

Publication number: WO2020233077A1
Application number: PCT/CN2019/122324
Authority: WO
Inventors: 韩亚洲
Original assignee: 深圳壹账通智能科技有限公司
Priority date: 2019-05-21
Filing date: 2019-12-02
Publication date: 2020-11-26
Also published as: CN110297738A

Abstract

A system service monitoring method, device, and apparatus, and a storage medium. The method comprises: receiving a system service access request, and extracting from the system service access request an identification number of a first system service being accessed (S10); determining whether or not the first system service is a system service to be monitored according to the identification number and a pre-established table of system services to be monitored (S20); if so, in response to the system service access request, collecting log information generated by the first system service when the first system service is being accessed (S30); and analyzing the log information, and storing an acquired real-time analysis result in a corresponding data management system (S40). The method resolves the technical issues in which system service monitoring cannot support the full storage of log information, development difficulty is high, and data analysis speed is slow.

Description

Monitoring method, device, equipment and storage medium of system service To

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office on May 21, 2019, the application number is 201910428277.7, and the invention title is "system service monitoring method, device, equipment and storage medium", the entire content of which is by reference Incorporated in this application.

Technical field

This application relates to the technical field of software monitoring, and in particular to a monitoring method, device, equipment, and storage medium for system services.

Background technique

With the rapid development of mobile Internet technology, there are more and more network applications suitable for smart terminal devices. In addition, in order to enable these network applications to provide better services to users, when the network application is launched, a monitoring program to monitor the network application will be launched. At present, the monitoring program for network applications when calling system services is usually based on Spring (an open source design-level framework), supplemented by Pinpoint (a java application performance management tool) and Dubbo (an open source distribution) Service framework).

Although, this monitoring solution can collect the log information generated by the system service when the network application accesses the corresponding system service, so that R&D personnel can locate the abnormality based on the collected log information when the network application is abnormal. Deal with abnormal problems. However, the monitoring solution based on the Spring framework cannot display all the log information, which results in the subsequent failure to accurately locate the abnormality, and because the Spring framework is large, it will take up more resources and cause the operation to be not smooth; while the Pinpoint framework is based on bytes The code injection method analyzes the performance of the system, which requires the operator to have high professional knowledge, and the operation is relatively complicated, which is not conducive to the realization; and the Dubbo framework cannot be used directly, so the realization process needs to be carried out on the basis of open source It can be used after modification and customization, so the access cost is relatively high.

Therefore, there is an urgent need to provide a monitoring method for system services that solves the above technical problems.

Summary of the invention

The main purpose of this application is to provide a monitoring method, device, equipment and storage medium for system services, aiming to solve the problem that the monitoring of system services in the prior art cannot support the storage of all log information, the difficulty of development, and the slow speed of data analysis Technical issues.

In order to achieve the above objective, this application provides a method for monitoring system services. The method includes the following steps:

Receiving a system service access request, and extracting the identification number of the accessed first system service from the system service access request;

Determine whether the first system service is a system service to be monitored according to the identification number and a pre-built system service table to be monitored;

If the first system service is the system service to be monitored, responding to the system service access request, collecting log information generated by the first system service during the process in which the first system service is accessed;

The log information is analyzed, and the real-time analysis result obtained is stored in the corresponding data management system.

In addition, in order to achieve the above objective, this application also proposes a system service monitoring device, which includes:

The extraction module is configured to receive a system service access request, and extract the identification number of the accessed first system service from the system service access request;

A determining module, configured to determine whether the first system service is a system service to be monitored according to the identification number and a pre-built system service table to be monitored;

The collection module is configured to respond to the system service access request when the first system service serves the system to be monitored, and collect the first system service generation during the process of the first system service being accessed Log information;

The analysis module is used to analyze the log information and store the real-time analysis results obtained in the corresponding data management system.

In addition, in order to achieve the above objective, this application also proposes a monitoring device for system services, the device including: a memory, a processor, and computer-readable instructions stored on the memory and executable by the processor, wherein When the computer-readable instructions are executed by the processor, the steps of the method for monitoring system services are as described above.

In addition, in order to achieve the above-mentioned object, this application also proposes a computer-readable storage medium with computer-readable instructions stored on the computer-readable storage medium. When the computer-readable instructions are executed by a processor, the implementation is as described above. The steps of the monitoring method of the system service.

The details of one or more embodiments of the application are set forth in the following drawings and description. Other features and advantages of this application will become apparent from the description, drawings and claims.

Description of the drawings

FIG. 1 is a schematic structural diagram of a monitoring device for a system service of a hardware operating environment involved in a solution of an embodiment of the present application;

2 is a schematic flowchart of a first embodiment of a method for monitoring system services in this application;

3 is a schematic diagram of a specific implementation process of step S40 in the first embodiment of the method for monitoring system services of this application;

FIG. 4 is a schematic flowchart of a second embodiment of a method for monitoring system services in this application;

Figure 5 is a structural block diagram of a first embodiment of a monitoring device for system services in this application.

The realization, functional characteristics, and advantages of the purpose of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings.

Detailed ways

It should be understood that the specific embodiments described herein are only used to explain the application, and not used to limit the application.

Referring to FIG. 1, FIG. 1 is a schematic structural diagram of a monitoring device for a system service of a hardware operating environment involved in a solution of an embodiment of the application.

As shown in Figure 1, the monitoring equipment of the system service may include a processor 1001, such as a central processing unit (Central Processing Unit, CPU), communication bus 1002, user interface 1003, network interface 1004, memory 1005. Among them, the communication bus 1002 is used to implement connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WIreless-FIdelity, WI-FI) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) memory, can also be a stable non-volatile memory (Non-Volatile Memory, NVM), such as disk storage. Optionally, the memory 1005 may also be a storage device independent of the foregoing processor 1001.

Those skilled in the art can understand that the structure shown in FIG. 1 does not constitute a limitation on the monitoring equipment of the system service, and may include more or less components than shown in the figure, or a combination of certain components, or a different component arrangement .

As shown in FIG. 1, a memory 1005 as a computer-readable storage medium may include an operating system, a network communication module, a user interface module, and computer-readable instructions.

In the monitoring device of the system service shown in FIG. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with users; the processor 1001 in the monitoring device of the system service of this application The memory 1005 may be set in a monitoring device of a system service. The monitoring device of the system service uses the processor 1001 to call computer-readable instructions stored in the memory 1005 and execute the method for monitoring the system service provided in the embodiment of the present application.

An embodiment of the present application provides a method for monitoring system services. Referring to FIG. 2, FIG. 2 is a schematic flowchart of a first embodiment of a method for monitoring system services of this application.

In this embodiment, the monitoring method of the system service includes the following steps:

Step S10, receiving a system service access request, and extracting the identification number of the accessed first system service from the system service access request.

Specifically, the execution subject of this embodiment is a server on which the computer-readable instructions are deployed.

It should be understood that in practical applications, the server on which the computer-readable instructions are deployed can be a traditional physical server, that is, a server that occupies actual physical space, or a virtual cloud server. The specific selection method is based on the technology in the field. Personnel can set according to their needs, there is no restriction here.

Correspondingly, the received system service access request can be sent by any communication device, such as smart terminal devices for users, such as mobile phones, tablets, wearable devices, etc., or personal computers, servers and other devices. I will not list them one by one, and there will be no restrictions on this.

In addition, it should be understood that the above-mentioned identification number used to identify the first system service is specifically a unique identification number assigned to the developer when compiling the first system service. The service code, the specific format can be set by those skilled in the art as needed, and there is no limitation here. To

In addition, it is worth mentioning that in practical applications, in order to ensure the smooth progress of the subsequent step S20 operation, before performing the above step S10, it is necessary to construct the service table of the system to be monitored that needs to be used in step S20.

Specifically, in this embodiment, in order to reduce as much as possible the occupation of system resources of the server on which the computer-readable instructions are deployed, and at the same time increase the data transmission speed, when constructing the service table of the system to be monitored, the specific It is based on the Guice framework, not the Spring framework, Pinpoint framework and Dubbo framework.

The so-called Guice framework is a code compilation framework with generic and annotation features, small structure and fast. Therefore, the second system service compiled based on the Guice framework not only has a small amount of code, takes up less server resources, and has clear annotation information, which can greatly facilitate the reading of the staff during the monitoring of the entire system service, thereby reducing the follow-up The difficulty of maintenance.

The Spring framework due to its own code structure is large, so it will take up more resources, resulting in not smooth running, affecting the monitoring of system services; Pinpoint framework is based on bytecode injection method to analyze system performance, Therefore, in the implementation process, the operator needs to have high professional knowledge, and the operation is relatively complicated, which is not conducive to the implementation; the Dubbo framework cannot be used directly, so it needs to be modified and customized on the basis of open source during the implementation process. It can be used, so the access cost is relatively high.

From the above description, it is not difficult to find that when compiling the second system service in this embodiment, the Guice framework is used instead of the Spring framework, Pinpoint framework, and Dubbo framework, which not only simplifies the process, reduces the compilation difficulty, and more importantly, The usage and working methods of the compiled second system service are completely different from those of the existing system service. It is based on this difference that the monitoring process of the entire system service greatly facilitates the reading of the staff and reduces The difficulty of subsequent maintenance.

For ease of understanding, the following describes the operation of constructing the service table of the system to be monitored based on the Guice framework. The specific implementation steps are roughly as follows:

(1) According to business needs, compile at least one second system service based on the Guice framework.

It should be understood that the business needs mentioned here are specifically determined in advance by the technical personnel responsible for system service monitoring in actual applications according to the network application to be monitored.

For example, when a certain network application launches a new function, in order to count the user's usage, it may be specified in advance that the second system service that needs to be monitored by the system service needs to include the system service for monitoring the new function.

That is to say, in the above step (1), the system architecture of any second system service obtained by compiling is based on the lightweight Guice framework, that is, the log information generated in the process of accessing the second system service is clear and clear Comment information.

At the same time, the second system service meets the business requirements specified by the technical personnel, that is, a specified function or business.

(2) Determine the system service to be monitored according to the business requirements and the attributes of the second system service.

Specifically, the operation of determining the system service to be monitored according to the business requirements and the attributes of the second system service mentioned in the above step (2) can be roughly as follows:

First, according to the business requirements and the attributes of the second system service, it is determined whether the second system service needs to be monitored.

It should be understood that, since a certain network application program supports a large number of functions when it is released, that is to say, there may be multiple second system services compiled, for example, one function corresponds to one second system service. However, in actual applications, not every function needs to be monitored. Therefore, not all of the compiled second system services need to be monitored. At this time, it needs to be based on the business requirements given by the technicians and the second system services. Attributes to determine the first system services obtained by compiling, which ones need to be monitored.

Correspondingly, if the second system service needs to be monitored, the second system service is marked as a system service to be monitored.

In order to facilitate understanding, the following description is combined with examples:

For example, during the use of a certain network application, the five second system services A, B, C, D, and E are involved. According to business requirements, the second system service A, the second system service B, and the second system service The second system service D needs to be monitored during the access process, and the second system service C and the second system service E are not needed, then the determined system services to be monitored are the second system service A, the second system service B, and the second system Service D.

(3) Obtain the identification number of the system service to be monitored, and construct the service table of the system to be monitored according to the identification number of the system service to be monitored.

Still taking the above case to explain, for example, the identification number of the second system service A is A100, the identification number of the second system service B is B100, and the identification number of the second system service D is D100, then the system service to be monitored is being constructed When making a list, specifically, a note document or note table is created, and the identification numbers A100, B100, and D100 are sequentially entered into the created note document or note table to obtain the service table of the system to be monitored.

It should be understood that the above is only a specific implementation manner, and does not constitute any limitation to the technical solution of the present application. In actual applications, those skilled in the art can make settings as needed, and there is no limitation here. .

In addition, in this embodiment, the “first” in the “first system service” mentioned above is only used to distinguish the system service from other system services, and does not limit the system service itself, and the first system The service may be any one of the at least one second system service compiled based on the Guice framework.

Correspondingly, the "second" in the "second system service" is only used to distinguish the system service from other system services, and does not limit the system service itself, and is based on at least one pre-compiled first system service based on the Guice framework. Among the two system services, at least one second system service is the first system service.

Step S20: Determine whether the first system service is a system service to be monitored according to the identification number and a pre-built system service table to be monitored.

Specifically, in order to facilitate the understanding of the operations performed in step S20, a specific implementation manner is given below, which is roughly as follows:

First, the service table of the system to be monitored is traversed, that is, the identification numbers of the service of the system to be monitored are read in order from the service table of the system to be monitored.

Then, the identification number is compared with the traversed identification number of the current system service to be monitored.

Specifically, if it is determined by comparison that the identification number of the first system service matches the identification number of the traversed current system service to be monitored, it is determined that the first system service is the system service to be monitored, and the step is entered S30: If, by comparison, it is determined that the identification number of the first system service does not match the identification number of any of the traversed system services to be monitored, only respond to the system access request, and there is no need to Collecting log information generated by the first system service during the process of accessing the system service.

Step S30, if the first system service is the system service to be monitored, respond to the system service access request, and collect log information generated by the first system service during the process in which the first system service is accessed .

Specifically, the log information collected in this embodiment mainly includes traceId, spanId, and annotation.

It should be noted that the traceId is used to identify a certain system service. When a certain system service is accessed, the corresponding specific system access request ID, here refers to the identification number that carries the first system service The ID of the system access request.

To facilitate understanding, the traceId is briefly described below.

Specifically, the traceId is used in a remote procedure call (Remote Procedure Call, RPC) interface is generated when the first layer of the network is called, and the traceId is globally unique, and will be continuously passed back with the RPC calls of each layer, so that the first system service is collected by collecting The traceId generated during the access process can connect the path called by a user request in the system in series, so as to know what operations have been performed in this request, and then facilitate the location of subsequent abnormal problems.

In addition, the spanId mentioned above is used to identify the position of an RPC call in a distributed request.

For example, when the user's system access request enters the system and is in the first layer A of the RPC calling network, the initial value of spanId can be 0. When entering the next layer of RPC calling B, the spanId is 0.1, continue to enter When the next layer of RPC calls C, spanId is 0.1.1; and when the RPC at the same layer as B calls E, spanId can be 0.2. In this way, the spanId can be used to locate the position of a certain RPC request in the system call and who its upstream and downstream dependencies are.

In addition, the above-mentioned annotation refers to the embedded point data customized by the R&D personnel in the code corresponding to the system service. The embedded point data can be data that is of business interest and wants to be uploaded to the backend, such as a user requesting once Identity Information.

Through the above description, it is not difficult to find that in practical applications, according to the collected traceId, it is possible to concatenate the information of all the paths that a request traverses in the system. According to the spanId, it is possible to distinguish the sequence of calls between different services of the system, according to the annotation Any data can be obtained according to business needs.

The traceId and spanId in the above log information are automatically obtained when the system service access request is triggered after the development of the Guice framework.

Annotation is to embed the point in the code corresponding to the system service through preview, so that after the system service access request is triggered, in the process of accessing the system service, when the accessed system service executes the code that sets the embedment point, RPC will be called automatically, and the buried point data will be sent to the next link through RPC.

The implementation principle of the embedding point is very simple. Specifically, when the user operates the network application or interface initialization, the software development kit of the third-party data analysis service provider (Software Development Kit, SDK), and then call the corresponding data sending interface in the SDK to send data when an event occurs. For example, if we want to count the number of clicks on a certain button in a web application, when the button is clicked, we can click the corresponding button The OnClick function calls the data sending interface provided by the SDK to send data.

It should be understood that the above is only an example for illustration, and does not constitute any limitation to the technical solution of the present application. In practical applications, those skilled in the art can make settings as needed, and there is no limitation here.

Step S40: Analyze the log information, and store the obtained real-time analysis result in the corresponding data management system.

Specifically, when analyzing the log information, multiple types of analysis results can be obtained. In order to facilitate subsequent queries, the data management system used to store the analysis results will also be different.

In this embodiment, the data management system can be roughly divided into the following three subsystems: a relational database management subsystem, a distributed storage management subsystem, and a distributed file management subsystem.

Correspondingly, the step of analyzing the log information and storing the obtained real-time analysis result in the corresponding data management system can be detailed into two sub-steps shown in FIG. 3, which are specifically as follows:

Sub-step S401, using big data analysis technology to analyze the log information to obtain model information corresponding to the log information and threshold information for judging the log information.

Specifically, in actual applications, in order to facilitate the analysis of the log information, a big data analysis technology and machine learning algorithm can be used to construct an analysis model in advance.

Correspondingly, when analyzing the log information, directly inputting the log information to the analysis model can quickly and accurately output the model information corresponding to the log information and use it to perform analysis on the log information. Judgment threshold information.

Regarding the construction of the analysis model, it may specifically be:

First, build a training model based on the training data stored in each big data platform.

Then, based on the selected machine learning algorithm, the training model is trained until a certain log information is input, and the model information corresponding to the log information and the threshold information position for judging the log information can be obtained. The training of the training model can be completed.

Correspondingly, the training model at this moment is the analysis model.

Sub-step S402, adding the model information to the distributed storage management subsystem, adding the threshold information to the relational database management subsystem, and adding the log information to the distributed file management sub-system system.

Specifically, regarding the above-mentioned relational database management subsystem, Mysql database can be selected in practical applications; the above-mentioned distributed storage management subsystem can be selected with high reliability, high performance, column-oriented, and Scalable Hadoop Database (usually referred to as HBase); for the distributed file management subsystem mentioned above, Hadoop Distributed File can be used System (commonly known as HDFS).

From the above description, it is not difficult to find that after the log information is analyzed and processed, the real-time analysis results obtained are stored in different data management subsystems, such as storing various models derived from real-time analysis in Hbase, and real-time analysis The obtained control data with a small amount of data such as switches and thresholds are stored in Mysql, and the complete original log information is stored in HDFS, so that the subsequent location of abnormal problems can be quickly searched for different data management subsystems as needed, thereby Speed up processing.

The method for monitoring system services provided in this embodiment constructs a list of system services to be monitored in advance, and adds the system services to be monitored that need to be monitored in the list of system services to be monitored, so that when a system service access request is received, After the identification number of the accessed first system service is extracted from the system service access request, it can be directly determined whether the first system service is the system service to be monitored based on the identification number and the pre-built system service table to be monitored. The first system service responds only when the first system service is a system service to be monitored, and at the same time, the log information generated by the first system service is collected while the first system service is being accessed. In this way, it is realized that only the first system service that needs to be monitored is monitored, thereby ensuring that the collected log information is only the log information of the first system service that needs to be monitored, greatly reducing the log information that needs to be analyzed later The quantity makes subsequent analysis more targeted and fast.

In addition, because the collected log information is only the log information of the first system service that needs to be monitored, under the premise that the amount of log information is controllable, the analysis can be obtained without increasing the development cost and difficulty. All real-time analysis results are stored, thereby realizing the storage of all log information of the first system service, which greatly facilitates the subsequent R&D personnel to locate the abnormal problem of the first system service.

Further, in order to be able to monitor system services more intuitively, in practical applications, the real-time analysis results can also be displayed according to a preset display style for R&D personnel to view, such as graphics in different styles, or Charts of different dimensions are displayed.

Referring to FIG. 4, FIG. 4 is a schematic flowchart of a second embodiment of a method for monitoring system services according to this application.

Based on the above-mentioned first embodiment, before the sub-step S402, the method for monitoring system services in this embodiment further includes:

Sub-step S403, performing a preprocessing operation on the log information according to preset processing rules to obtain log information from which interference information is removed;

Specifically, in actual applications, the log information generated in the process of accessing the first system service often contains some information that is useless for subsequent analysis abnormalities and locating problems. Therefore, in order to ensure the collected log information To be as effective as possible to avoid increasing analysis burden and affecting analysis results, it is necessary to perform a series of preprocessing operations on the collected log information before performing the step of analyzing the log information using big data analysis technology.

For example, if the preset processing rule is to perform a data cleaning operation on the data in the log information, the log information obtained after the data cleaning operation is performed on the log information according to the processing rule is to remove the interference information. It is the log information that removes duplicate information and corrects the existing errors, so that it can ensure that the analysis results obtained during the subsequent log analysis process are more accurate.

Further, in practical applications, the preprocessing operation may also be set to group the log information according to business needs.

It should be understood that the above are only examples and do not constitute any limitation to the technical solution of the present application. In specific applications, those skilled in the art can make settings as needed, and the present application does not limit this.

Sub-step S404, adding the log information for removing interference information to a pre-built distributed publish-subscribe message queue.

Specifically, in this embodiment, the above-mentioned distributed publish-subscribe message queue is essentially a commonly-called Kafka message queue.

Because Kafka has the characteristics of persistence, stability, high-pass throughput, support for server and consumer clusters to partition messages, and support for parallel data loading of distributed systems, Kafka message queues are selected to cache the log information that removes interference information, which can It is possible to avoid a large amount of log information from accumulating on the log analysis node, thereby preventing thread blocking and ensuring the processing speed of log analysis.

In addition, Kafka is an open source stream processing platform developed by the Apache Software Foundation, and its use is relatively mature. Those skilled in the art can find relevant documents and implement them by themselves in specific implementations. I will not repeat them here. .

Correspondingly, the operation performed in the atomic step S401 adaptively becomes the operation of the sub-step S401' in FIG. 4: for the first time, the log information for removing interference information is sequentially read from the distributed publish-subscribe message queue; Then, the big data analysis technology is used to analyze the log information of the interference removal information.

It should be understood that the above is only a specific implementation manner, and does not constitute any limitation to the technical solution of the present application. In specific applications, those skilled in the art can make settings as required, for example, in the log information In the case of small quantity and fast analysis and processing speed, after preprocessing the collected log information, the log information that removes interference information can be added to the Kafka message queue, but directly transmitted to the analysis node Perform log analysis.

From the above description, it is not difficult to find that the monitoring method of the system service provided in this embodiment uses the big data analysis technology to analyze the log information by pre-processing the log information according to preset processing rules. Processing operations to obtain log information for removing interference information, and adding the log information for removing interference information to a pre-built distributed publish-and-subscribe message queue for caching, so as to effectively prevent a large amount of log information from being accumulated in log analysis at the same time The node solves the problem of thread blocking, which greatly improves the processing speed.

In addition, the embodiments of the present application also provide a computer-readable storage medium, and the computer-readable storage medium may be a non-volatile readable storage medium.

The computer-readable storage medium of the present application stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the method for monitoring system services as described above are realized.

For the method implemented when the computer-readable instruction is executed, reference may be made to the various embodiments of the monitoring method of the system service of this application, which will not be repeated here.

Referring to Fig. 5, Fig. 5 is a structural block diagram of a first embodiment of a monitoring device serviced by the system of this application.

As shown in Figure 5, the system service monitoring device proposed in the embodiment of the present application includes:

The extraction module 5001 is used to receive a system service access request and extract the identification number of the first system service to be accessed from the system service access request; the determination module 5002 is used to determine the identification number and the pre-built system to be monitored based on the identification number The service table determines whether the first system service is the service of the system to be monitored; the collection module 5003 is used to respond to the system service access request when the first system service is the service of the system to be monitored. The log information generated by the first system service is collected during the process when the first system service is accessed; the analysis module 5004 is configured to analyze the log information and store the real-time analysis result obtained in the corresponding data management system.

Among them, each virtual function module of the monitoring device of the above system service is stored in the memory 1005 of the monitoring device of the system service shown in FIG. 1, and is used to realize all the functions of computer-readable instructions; when each module is executed by the processor 1001, it can be Complete the entire process of monitoring system services.

Further, the monitoring device of the system service further includes:

The service table construction module of the system to be monitored is used to construct the service table of the system to be monitored;

Wherein, the step of constructing the service table of the system to be monitored includes: compiling at least one second system service based on the Guice framework according to business requirements; determining the service according to the business requirements and the attributes of the second system service Whether the second system service needs to be monitored; if the second system service needs to be monitored, mark the second system service as a system service to be monitored; obtain the identification number of the system service to be monitored, and The identification number of the monitoring system service constructs the service table of the system to be monitored.

Further, in practical applications, the operation of determining whether the first system service is the system service to be monitored based on the identification number and the pre-built system service table to be monitored may be as follows:

Traverse the service table of the system to be monitored, and compare the identification number with the traversed identification number of the service of the system to be monitored;

If the identification number matches the traversed identification number of the current system service to be monitored, it is determined that the first system service is the system service to be monitored.

Further, in practical applications, the data management system may include a relational database management subsystem, a distributed storage management subsystem, and a distributed file management subsystem;

Correspondingly, the analysis module includes:

The big data analysis unit is configured to use big data analysis technology to analyze the log information to obtain model information corresponding to the log information and threshold information for judging the log information;

An information adding unit, configured to add the model information to the distributed storage management subsystem, add the threshold information to the relational database management subsystem, and add the log information to the distributed file Management subsystem.

Further, the monitoring device of the system service further includes:

The preprocessing module is configured to perform preprocessing operations on the log information according to preset processing rules to obtain log information that removes interference information;

Wherein, the step of using big data analysis technology to analyze the log information includes:

The big data analysis technology is used to analyze the log information for removing interference information.

Further, the monitoring device of the system service further includes:

A log information adding module, configured to add the log information for removing interference information to a pre-built distributed publish-subscribe message queue;

Correspondingly, the step of using big data analysis technology to analyze the log information for removing interference information includes:

Sequentially reading the log information for removing interference information from the distributed publish-subscribe message queue;

Further, the monitoring device of the system service further includes:

The display module is used to display the real-time analysis result according to the preset display style.

Among them, the function realization of each module in the monitoring device of the above system service corresponds to each step in the embodiment of the monitoring method of the above system service, and the function and realization process are not repeated here.

In addition, it should be noted that in this article, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those Elements, but also include other elements that are not explicitly listed, or elements inherent to this process, method, article, or system. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, article or system that includes the element.

The serial numbers of the foregoing embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand the above The method of the embodiment can be implemented by means of software plus a necessary general hardware platform, of course, it can also be implemented by hardware, but the former is a better implementation in many cases. Based on this understanding, the application’s The essence of the technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as Read Only Memory). Memory, ROM)/RAM, disk, optical The disk) includes several instructions to make a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) execute the method described in each embodiment of the present application.

The above are only preferred embodiments of this application, and do not limit the scope of this application. Any equivalent structure or equivalent process transformation made using the content of the description and drawings of this application, or directly or indirectly used in other related technical fields , The same reason is included in the scope of patent protection of this application.

Claims

A method for monitoring system services, wherein the method includes the following steps:

Receiving a system service access request, and extracting the identification number of the accessed first system service from the system service access request;

Determine whether the first system service is a system service to be monitored according to the identification number and a pre-built system service table to be monitored;

If the first system service is the system service to be monitored, responding to the system service access request, collecting log information generated by the first system service during the process in which the first system service is accessed;

The log information is analyzed, and the real-time analysis result obtained is stored in the corresponding data management system.
The method according to claim 1, wherein before the step of receiving a system service access request, the method further comprises the following steps:

Construct the service table of the system to be monitored;

Wherein, the step of constructing the service table of the system to be monitored includes:

Compile at least one second system service based on the Guice framework according to business requirements;

Determine whether the second system service needs to be monitored according to the business requirements and the attributes of the second system service;

If the second system service needs to be monitored, mark the second system service as a system service to be monitored;

The identification number of the system service to be monitored is acquired, and the system service table to be monitored is constructed according to the identification number of the system service to be monitored.
3. The method according to claim 2, wherein the step of determining whether the first system service is a system service to be monitored according to the identification number and a pre-built system service table to be monitored comprises:

Traverse the service table of the system to be monitored, and compare the identification number with the traversed identification number of the service of the system to be monitored;

If the identification number matches the traversed identification number of the current system service to be monitored, it is determined that the first system service is the system service to be monitored.
3. The method of claim 1, wherein the data management system comprises a relational database management subsystem, a distributed storage management subsystem, and a distributed file management subsystem;

The step of analyzing the log information and storing the obtained real-time analysis result in the corresponding data management system includes:

Using big data analysis technology to analyze the log information to obtain model information corresponding to the log information and threshold information for judging the log information;

The model information is added to the distributed storage management subsystem, the threshold information is added to the relational database management subsystem, and the log information is added to the distributed file management subsystem.
The method according to claim 4, wherein, before the step of analyzing the log information by using big data analysis technology, the method further comprises the following steps:

Perform preprocessing operations on the log information according to preset processing rules to obtain log information that removes interference information;

Wherein, the step of using big data analysis technology to analyze the log information includes:

The big data analysis technology is used to analyze the log information for removing interference information.
The method according to claim 5, wherein, before the step of analyzing the log information from the interference information removal by using big data analysis technology, the method further comprises:

Adding the log information for removing interference information to a pre-built distributed publish-subscribe message queue;

Wherein, the step of using big data analysis technology to analyze the log information for removing interference information includes:

Sequentially reading the log information for removing interference information from the distributed publish-subscribe message queue;

The big data analysis technology is used to analyze the log information for removing interference information.
The method according to any one of claims 1 to 3, wherein after the step of analyzing the log information and storing the obtained real-time analysis result in the corresponding data management system, the method further comprises the following steps :

According to the preset display style, the real-time analysis result is displayed.
A monitoring device for system services, wherein the device includes:

The extraction module is configured to receive a system service access request, and extract the identification number of the accessed first system service from the system service access request;

A determining module, configured to determine whether the first system service is a system service to be monitored according to the identification number and a pre-built system service table to be monitored;

The collection module is configured to respond to the system service access request when the first system service serves the system to be monitored, and collect the first system service generation during the process of the first system service being accessed Log information;

The analysis module is used to analyze the log information and store the real-time analysis results obtained in the corresponding data management system.
8. The monitoring device for system services according to claim 8, wherein the monitoring device for system services further comprises:

The service table construction module of the system to be monitored is used to construct the service table of the system to be monitored;

Wherein, the step of constructing the service table of the system to be monitored includes:

Compile at least one second system service based on the Guice framework according to business requirements;

Determine whether the second system service needs to be monitored according to the business requirements and the attributes of the second system service;

If the second system service needs to be monitored, mark the second system service as a system service to be monitored;

The identification number of the system service to be monitored is acquired, and the system service table to be monitored is constructed according to the identification number of the system service to be monitored.
8. The monitoring device for system services according to claim 8, wherein the data management system includes a relational database management subsystem, a distributed storage management subsystem, and a distributed file management subsystem; the analysis module includes:

The big data analysis unit is configured to use big data analysis technology to analyze the log information to obtain model information corresponding to the log information and threshold information for judging the log information;

An information adding unit, configured to add the model information to the distributed storage management subsystem, add the threshold information to the relational database management subsystem, and add the log information to the distributed file Management subsystem.
10. The monitoring device for system services according to claim 10, wherein the monitoring device for system services further comprises:

The preprocessing module is configured to perform preprocessing operations on the log information according to preset processing rules to obtain log information that removes interference information;

Wherein, the step of using big data analysis technology to analyze the log information includes:

The big data analysis technology is used to analyze the log information for removing interference information.
The monitoring device for system services according to claim 11, wherein the monitoring device for system services further comprises:

A log information adding module, configured to add the log information for removing interference information to a pre-built distributed publish-subscribe message queue;

Wherein, the step of using big data analysis technology to analyze the log information for removing interference information includes:

Sequentially reading the log information for removing interference information from the distributed publish-subscribe message queue;

The big data analysis technology is used to analyze the log information for removing interference information.
A monitoring device for system services, wherein the device includes: a memory, a processor, and computer-readable instructions stored on the memory and executable by the processor, wherein the computer-readable instructions are When the processor executes, the following steps are implemented:

Receiving a system service access request, and extracting the identification number of the accessed first system service from the system service access request;

Determine whether the first system service is a system service to be monitored according to the identification number and a pre-built system service table to be monitored;

If the first system service is the system service to be monitored, responding to the system service access request, collecting log information generated by the first system service during the process in which the first system service is accessed;

The log information is analyzed, and the real-time analysis result obtained is stored in the corresponding data management system.
The monitoring device for system services according to claim 13, wherein, before the step of receiving the system service access request, the method further comprises the following steps:

Construct the service table of the system to be monitored;

Wherein, the step of constructing the service table of the system to be monitored includes:

Compile at least one second system service based on the Guice framework according to business requirements;

Determine whether the second system service needs to be monitored according to the business requirements and the attributes of the second system service;

If the second system service needs to be monitored, mark the second system service as a system service to be monitored;

The identification number of the system service to be monitored is acquired, and the system service table to be monitored is constructed according to the identification number of the system service to be monitored.
The monitoring device for system services according to claim 13, wherein the data management system includes a relational database management subsystem, a distributed storage management subsystem, and a distributed file management subsystem;

The step of analyzing the log information and storing the obtained real-time analysis result in the corresponding data management system includes:

Using big data analysis technology to analyze the log information to obtain model information corresponding to the log information and threshold information for judging the log information;

The model information is added to the distributed storage management subsystem, the threshold information is added to the relational database management subsystem, and the log information is added to the distributed file management subsystem.
The monitoring device for system services according to claim 15, wherein, before the step of analyzing the log information by using big data analysis technology, the method further comprises the following steps:

Perform preprocessing operations on the log information according to preset processing rules to obtain log information that removes interference information;

Wherein, the step of using big data analysis technology to analyze the log information includes:

The big data analysis technology is used to analyze the log information for removing interference information.
The monitoring device for system services according to claim 16, wherein, before the step of analyzing the log information of the interference removal information by using big data analysis technology, the method further comprises:

Adding the log information for removing interference information to a pre-built distributed publish-subscribe message queue;

Wherein, the step of using big data analysis technology to analyze the log information for removing interference information includes:

Sequentially reading the log information for removing interference information from the distributed publish-subscribe message queue;

The big data analysis technology is used to analyze the log information for removing interference information.
A computer-readable storage medium, wherein computer-readable instructions are stored on the computer-readable storage medium, and when the computer-readable instructions are executed by a processor, the following steps are implemented:

Receiving a system service access request, and extracting the identification number of the accessed first system service from the system service access request;

Determine whether the first system service is a system service to be monitored according to the identification number and a pre-built system service table to be monitored;

If the first system service is the system service to be monitored, responding to the system service access request, collecting log information generated by the first system service during the process in which the first system service is accessed;

The log information is analyzed, and the real-time analysis result obtained is stored in the corresponding data management system.
18. The computer-readable storage medium of claim 18, wherein, before the step of receiving a system service access request, the method further comprises the following steps:

Construct the service table of the system to be monitored;

Wherein, the step of constructing the service table of the system to be monitored includes:

Compile at least one second system service based on the Guice framework according to business requirements;

Determine whether the second system service needs to be monitored according to the business requirements and the attributes of the second system service;

If the second system service needs to be monitored, mark the second system service as a system service to be monitored;

The identification number of the system service to be monitored is acquired, and the system service table to be monitored is constructed according to the identification number of the system service to be monitored.
18. The computer-readable storage medium of claim 18, wherein the data management system includes a relational database management subsystem, a distributed storage management subsystem, and a distributed file management subsystem;

The step of analyzing the log information and storing the obtained real-time analysis result in the corresponding data management system includes:

Using big data analysis technology to analyze the log information to obtain model information corresponding to the log information and threshold information for judging the log information;

The model information is added to the distributed storage management subsystem, the threshold information is added to the relational database management subsystem, and the log information is added to the distributed file management subsystem. To