CN113254312B - Front-end abnormality monitoring and analyzing method, device, equipment and storage medium - Google Patents
Front-end abnormality monitoring and analyzing method, device, equipment and storage medium Download PDFInfo
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- CN113254312B CN113254312B CN202110607807.1A CN202110607807A CN113254312B CN 113254312 B CN113254312 B CN 113254312B CN 202110607807 A CN202110607807 A CN 202110607807A CN 113254312 B CN113254312 B CN 113254312B
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Abstract
The invention relates to the field of research and development process optimization, and discloses a front-end abnormity monitoring and analyzing method, device, equipment and storage medium, which are used for improving the monitoring efficiency of a front-end abnormity monitoring system. The front-end anomaly monitoring and analyzing method comprises the following steps: acquiring monitoring information data of a front-end HTML5 page in real time; when the front end HTML5 page is abnormal, extracting abnormal information data in the monitoring information data, capturing behavior information data of the front end HTML5 page, and analyzing the monitoring information data to obtain environment information data of the front end HTML5 page; encrypting the abnormal information data, the behavior information data and the environment information data by using an encryption algorithm, and integrating the encrypted information data to obtain detection information data; formatting the detection information data to generate an information display set, and analyzing the information display set to obtain an abnormal data analysis result of the front-end HTML5 page. The invention also relates to a blockchain technology, and the monitoring information data can be stored in the blockchain.
Description
Technical Field
The present invention relates to the field of optimization of research and development processes, and in particular, to a method, an apparatus, a device, and a storage medium for monitoring and analyzing front-end anomalies.
Background
With the vigorous development of mobile internet, more and more enterprises utilize the internet to conduct business propaganda display, when utilizing the internet to conduct business propaganda display, front end HTML5 pages can be utilized to display business contents needing propaganda display, and therefore, in order to optimize the effect of business propaganda display, the enterprises need to monitor the front end HTML5 pages. The current front-end monitoring platforms, such as sentry, ARMS, fundebug, frontJS, need to implement different conventions when in use, so it is important to adopt a reasonable and appropriate front-end anomaly monitoring system.
The existing front-end monitoring abnormal system can capture abnormal information data in project operation, but the obtained abnormal information data is single and coarse in content and insufficient for analyzing the abnormal information data, so that the monitoring efficiency of the front-end monitoring abnormal system is low.
Disclosure of Invention
The invention provides a front-end abnormity monitoring and analyzing method, device, equipment and storage medium, which are used for improving the monitoring efficiency of a front-end abnormity monitoring system.
The first aspect of the present invention provides a method for monitoring and analyzing front-end anomalies, including: monitoring information data generated by a front-end HTML5 page by using a preset monitoring system, and acquiring the monitored information data of the front-end HTML5 page in real time; when the front end HTML5 page is abnormal, extracting abnormal information data in the monitoring information data, capturing behavior information data of the front end HTML5 page, and analyzing the monitoring information data to obtain environment information data of the front end HTML5 page; encrypting the abnormal information data, the behavior information data and the environment information data by using an encryption algorithm, and integrating the encrypted information data to obtain detection information data; and formatting the detection information data to generate an information display set, analyzing the information display set to obtain an abnormal data analysis result of the front-end HTML5 page, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data.
Optionally, in a first implementation manner of the first aspect of the present invention, when the front end HTML5 page is abnormal, extracting abnormal information data in the monitored information data, capturing behavior information data of the front end HTML5 page, and analyzing the monitored information data to obtain environment information data of the front end HTML5 page includes: when the front end HTML5 page is abnormal, an error monitoring function is screened out from the monitoring information data through a preset monitoring system, and the error monitoring function is determined to be abnormal information data; capturing user behavior data and application side behavior data of the front-end HTML5 page, and integrating the user behavior data and the application side behavior data to obtain behavior information data; and analyzing the monitoring information data to obtain the environment information data of the front-end HTML5 page.
Optionally, in a second implementation manner of the first aspect of the present invention, the parsing the listening information data to obtain the environmental information data of the front-end HTML5 page includes: acquiring user agent data of the front end HTML5 page in the monitoring information data, and determining abnormal system version data and system type data in the user agent data; acquiring an application program interface of the front end HTML5 page in the monitoring information data, and determining a network data type when an abnormality occurs based on the application program interface; and integrating the system version data, the system type data and the network data type to obtain environment information data.
Optionally, in a third implementation manner of the first aspect of the present invention, the encrypting the abnormal information data, the behavior information data and the environment information data by using an encryption algorithm, and integrating the encrypted information data to obtain the detection information data includes: extracting an abnormal data type, an abnormal data item and an abnormal information error stack in the abnormal information data, and encrypting the abnormal information data based on the abnormal data type, the abnormal data item, the abnormal error information and an encryption algorithm to obtain first encrypted information data; extracting behavior initiator information, behavior initiation address, behavior agent information, behavior data type, behavior information content and behavior occurrence time from the behavior information data, and encrypting the behavior information data based on the behavior initiator information, the behavior initiation address, the behavior agent information, the behavior data type, the behavior information content, the behavior occurrence time and the encryption algorithm to obtain second encrypted information data; extracting an environment system version and an environment system type from the environment information data, and encrypting the environment information data based on the environment system version, the environment system type and the encryption algorithm to obtain third encrypted information data; and integrating the first encryption information data, the second encryption information data and the third encryption information data to obtain detection information data.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the extracting an abnormal data type, an abnormal data item, and an abnormal information error stack in the abnormal information data, encrypting the abnormal information data based on the abnormal data type, the abnormal data item, the abnormal error information, and an encryption algorithm, and obtaining first encrypted information data includes: respectively extracting an abnormal data type, an abnormal data item and an abnormal information error stack in the abnormal information data according to the sequence from front to back, respectively extracting a preset number of data characters from the abnormal data type, the abnormal data item and the abnormal information error, and integrating each data character according to the extraction sequence to obtain a first abnormal data character; adding a supplementary character at the tail of the first abnormal data character to obtain a second abnormal data character, wherein the character length of the second abnormal data character is k, k=n×512+448, and n is a natural number; adding a counting character at the end of the second abnormal data character to obtain a third abnormal data character, wherein the counting character is used for recording the number of the first abnormal data character, and the character length of the counting character is the standard character length; and performing cyclic operation on the third abnormal data character by using the standard magic number to obtain first encrypted information data.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the formatting processing is performed on the detected information data to generate an information display set, and the information display set is analyzed to obtain an abnormal data analysis result of the front end HTML5 page, where the information display set includes an abnormal information data display table, an environmental information data display table, and a behavior information data display table that are generated based on the detected information data, and the information display set includes: formatting the detection information data to generate an information display set, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data; calculating an abnormal data generation trend by using the abnormal information data display table; determining a network environment condition when an abnormality occurs based on the environment information data display table, determining a geographic position of the abnormality occurrence through an internet protocol address of the front-end HTML5 page, and determining a network processing strategy through the geographic position of the abnormality occurrence and the corresponding network environment condition; determining the distribution of abnormal behavior information data through the behavior information data display table; and integrating the abnormal data generation trend, the network processing strategy and the distribution of the abnormal behavior information data to obtain an abnormal data analysis result of the front-end HTML5 page.
Optionally, in a sixth implementation manner of the first aspect of the present invention, before the monitoring information data generated by the front-end HTML5 page by using the preset monitoring system, the front-end anomaly monitoring and analyzing method further includes: and initializing the preset monitoring system by using an initialization function.
The second aspect of the present invention provides a front-end abnormality monitoring and analyzing apparatus, comprising: the monitoring module is used for monitoring information data generated by the front-end HTML5 page by using a preset monitoring system, and acquiring the monitoring information data of the front-end HTML5 page in real time; the processing module is used for extracting abnormal information data in the monitoring information data when the front-end HTML5 page is abnormal, capturing behavior information data of the front-end HTML5 page, and analyzing the monitoring information data to obtain environment information data of the front-end HTML5 page; the encryption module is used for encrypting the abnormal information data, the behavior information data and the environment information data respectively by utilizing an encryption algorithm, and integrating the encrypted information data to obtain detection information data; the analysis module is used for carrying out formatting processing on the detection information data to generate an information display set, analyzing the information display set to obtain an abnormal data analysis result of the front end HTML5 page, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data.
Optionally, in a first implementation manner of the second aspect of the present invention, the processing module includes: the screening unit is used for screening out an error monitoring function from the monitoring information data through a preset monitoring system when the front-end HTML5 page is abnormal, and determining the error monitoring function as abnormal information data; the capturing unit is used for capturing the user behavior data and the application side behavior data of the front-end HTML5 page, and integrating the user behavior data and the application side behavior data to obtain behavior information data; and the analysis unit is used for analyzing the monitoring information data to obtain the environment information data of the front-end HTML5 page.
Optionally, in a second implementation manner of the second aspect of the present invention, the parsing unit is specifically configured to: acquiring user agent data of the front end HTML5 page in the monitoring information data, and determining abnormal system version data and system type data in the user agent data; acquiring an application program interface of the front end HTML5 page in the monitoring information data, and determining a network data type when an abnormality occurs based on the application program interface; and integrating the system version data, the system type data and the network data type to obtain environment information data.
Optionally, in a third implementation manner of the second aspect of the present invention, the encryption module includes: the first encryption unit is used for extracting an abnormal data type, an abnormal data item and an abnormal information error stack in the abnormal information data, and encrypting the abnormal information data based on the abnormal data type, the abnormal data item, the abnormal error information and an encryption algorithm to obtain first encrypted information data; the second encryption unit is used for extracting behavior initiator information, behavior initiation address, behavior agent information, behavior data type, behavior information content and behavior occurrence time from the behavior information data, and encrypting the behavior information data based on the behavior initiator information, the behavior initiation address, the behavior agent information, the behavior data type, the behavior information content, the behavior occurrence time and the encryption algorithm to obtain second encrypted information data; the third encryption unit is used for extracting an environment system version and an environment system type from the environment information data, encrypting the environment information data based on the environment system version, the environment system type and the encryption algorithm, and obtaining third encrypted information data; and the integration unit is used for integrating the first encryption information data, the second encryption information data and the third encryption information data to obtain detection information data.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the first encryption unit is specifically configured to: respectively extracting an abnormal data type, an abnormal data item and an abnormal information error stack in the abnormal information data according to the sequence from front to back, respectively extracting a preset number of data characters from the abnormal data type, the abnormal data item and the abnormal information error, and integrating each data character according to the extraction sequence to obtain a first abnormal data character; adding a supplementary character at the tail of the first abnormal data character to obtain a second abnormal data character, wherein the character length of the second abnormal data character is k, k=n×512+448, and n is a natural number; adding a counting character at the end of the second abnormal data character to obtain a third abnormal data character, wherein the counting character is used for recording the number of the first abnormal data character, and the character length of the counting character is the standard character length; and performing cyclic operation on the third abnormal data character by using the standard magic number to obtain first encrypted information data.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the analysis module is specifically configured to: formatting the detection information data to generate an information display set, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data; calculating an abnormal data generation trend by using the abnormal information data display table; determining a network environment condition when an abnormality occurs based on the environment information data display table, determining a geographic position of the abnormality occurrence through an internet protocol address of the front-end HTML5 page, and determining a network processing strategy through the geographic position of the abnormality occurrence and the corresponding network environment condition; determining the distribution of abnormal behavior information data through the behavior information data display table; and integrating the abnormal data generation trend, the network processing strategy and the distribution of the abnormal behavior information data to obtain an abnormal data analysis result of the front-end HTML5 page.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the front end anomaly monitoring and analysis device further includes: and the initialization module is used for initializing the preset monitoring system by using an initialization function.
A third aspect of the present invention provides a front-end anomaly monitoring and analyzing apparatus, comprising: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the front-end anomaly monitoring and analysis device to perform the front-end anomaly monitoring and analysis method described above.
A fourth aspect of the present invention provides a computer-readable storage medium having instructions stored therein that, when executed on a computer, cause the computer to perform the front-end anomaly monitoring and analysis method described above.
According to the technical scheme provided by the invention, a preset monitoring system is utilized to monitor information data generated by a front-end HTML5 page, and the monitored information data of the front-end HTML5 page is obtained in real time; when the front end HTML5 page is abnormal, extracting abnormal information data in the monitoring information data, capturing behavior information data of the front end HTML5 page, and analyzing the monitoring information data to obtain environment information data of the front end HTML5 page; encrypting the abnormal information data, the behavior information data and the environment information data by using an encryption algorithm, and integrating the encrypted information data to obtain detection information data; and formatting the detection information data to generate an information display set, analyzing the information display set to obtain an abnormal data analysis result of the front-end HTML5 page, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data. In the embodiment of the invention, a preset monitoring system is used for monitoring the front end HTML5 page, when an abnormality occurs, abnormal information data, capturing behavior information data and analyzing environment information data in monitoring information data are extracted, the information is encrypted by utilizing an encryption algorithm to obtain detection information data, and finally the detection information data is formatted to generate an information display set, and the information display set is further analyzed to obtain an abnormal data analysis result of the front end HTML5 page. The monitoring efficiency of the front-end monitoring abnormal system is improved.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a front-end anomaly monitoring and analysis method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of another embodiment of a front-end anomaly monitoring and analysis method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an embodiment of a front-end anomaly monitoring and analysis device according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of another embodiment of a front-end anomaly monitoring and analysis device according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an embodiment of a front-end anomaly monitoring and analysis device according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a front-end abnormity monitoring and analyzing method, device, equipment and storage medium, which are used for improving the monitoring efficiency of a front-end abnormity monitoring system.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For ease of understanding, a specific flow of an embodiment of the present application is described below, referring to fig. 1, and an embodiment of a front-end anomaly monitoring and analyzing method in an embodiment of the present application includes:
101. monitoring information data generated by the front-end HTML5 page by using a preset monitoring system, and acquiring the monitored information data of the front-end HTML5 page in real time;
it can be understood that the execution body of the present application may be a front-end anomaly monitoring and analyzing device, and may also be a terminal or a server, which is not limited herein. The embodiment of the application is described by taking a server as an execution main body as an example.
Before judging whether the front end HTML5 page is abnormal or not, a software development kit of the preset monitoring system needs to be introduced into a corresponding front end project, wherein the software development kit utilized in the application is a JS software development kit, and specifically, the type of the software development kit of the preset monitoring system can be determined according to actual conditions, and the type of the software development kit of the preset monitoring system is not limited in the application.
After initializing a software development kit of the preset monitoring system, the preset monitoring system can monitor information data generated in the running process of the corresponding front-end HTML5 page, and acquire the monitoring information data of the front-end HTML5 page in real time. The listening information data here includes: error-aware data: sensing errors generated when the front-end page runs, wherein the errors comprise multiple dimensions, and different system monitoring degrees are different; time-consuming statistics: and data for monitoring the opening speed and various response speeds of the front-end webpage when the front-end webpage is opened.
It should be emphasized that, to further ensure the privacy and security of the above-mentioned snoop information data, the above-mentioned snoop information data may also be stored in a node of a blockchain.
102. When the front end HTML5 page is abnormal, extracting abnormal information data in the monitoring information data, capturing behavior information data of the front end HTML5 page, and analyzing the monitoring information data to obtain environment information data of the front end HTML5 page;
when the front end HTML5 page is abnormal, the abnormal information data needs to be extracted from the monitored information data monitored by the preset monitoring system, and it needs to be explained that, when the front end HTML5 page is abnormal, the front end program is in the corresponding browser, and the program execution error is caused by the factors of environment, network and the like, so that the correct front end HTML5 page cannot be displayed, for example: clicking a button option in the front-end HTML5 page, wherein the front-end HTML5 page cannot display a corresponding feedback result, and the data generated in the process is abnormal information data.
After the abnormal information data is extracted, in order to accurately analyze the abnormal occurrence reason of the front end HTML5 page, the behavior information data of the front end HTML5 page needs to be further captured, the monitoring information data is analyzed to obtain the environment information data of the front end HTML5 page, and the three information data are analyzed to obtain a final front end abnormal monitoring result.
103. Encrypting the abnormal information data, the behavior information data and the environment information data by using an encryption algorithm, and integrating the encrypted information data to obtain detection information data;
after obtaining the abnormal information data, the behavior information data and the environment information data of the front-end HTML5 page, in order to ensure the safety of the information data, the information data is encrypted and transmitted by using an encryption algorithm. The application utilizes the MD5 encryption algorithm to encrypt the information data, and the MD5 encryption algorithm has the following functions:
1. inputting information with any length, processing, and outputting 128-bit information (digital fingerprint);
2. different inputs result in different results (uniqueness);
3. it is impossible to reverse-extrapolate the input information (irreversible) from the 128-bit output result.
It should be noted that, here, the encryption is performed on different types of information data, rather than the encryption performed after the integration of the anomaly information data, the behavior information data and the environment information data, so that the security in transmitting the information data is greatly improved.
104. And formatting the detection information data to generate an information display set, and analyzing the information display set to obtain an abnormal data analysis result of the front-end HTML5 page, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data.
After the detection information data of the front end are obtained, the information data are required to be displayed and analyzed, the server performs formatting processing on the detection information data and correspondingly generates an information display set of the detection information data, wherein the information display set at least comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated by taking the detection information data as the detection information data. Information data of the front end HTML5 page is displayed through multiple angles, and abnormality of the information data can be observed more intuitively and specifically.
In the embodiment of the invention, a preset monitoring system is used for monitoring the front end HTML5 page, when an abnormality occurs, abnormal information data, capturing behavior information data and analyzing environment information data in monitoring information data are extracted, the information is encrypted by utilizing an encryption algorithm to obtain detection information data, and finally the detection information data is formatted to generate an information display set, and the information display set is further analyzed to obtain an abnormal data analysis result of the front end HTML5 page. The monitoring efficiency of the front-end monitoring abnormal system is improved.
Referring to fig. 2, another embodiment of a method for monitoring and analyzing front-end anomalies according to an embodiment of the present invention includes:
201. Initializing a preset monitoring system by using an initialization function;
the server initializes the preset monitoring system by using an initialization function, and is used for initializing data objects or variables in the preset monitoring system, setting the control to be in a default state, and generally, after the initialized initial values of the variables are located at the data positions of the executable file code segments, occupying a certain storage space, thereby being beneficial to reducing the occurrence of system errors.
202. Monitoring information data generated by the front-end HTML5 page by using a preset monitoring system, and acquiring the monitored information data of the front-end HTML5 page in real time;
before judging whether the front end HTML5 page is abnormal or not, a software development kit of the preset monitoring system needs to be introduced into a corresponding front end project, wherein the software development kit utilized in the application is a JS software development kit, and specifically, the type of the software development kit of the preset monitoring system can be determined according to actual conditions, and the type of the software development kit of the preset monitoring system is not limited in the application.
After initializing a software development kit of the preset monitoring system, the preset monitoring system can monitor information data generated in the running process of the corresponding front-end HTML5 page, and acquire the monitoring information data of the front-end HTML5 page in real time. The listening information data here includes: error-aware data: sensing errors generated when the front-end page runs, wherein the errors comprise multiple dimensions, and different system monitoring degrees are different; time-consuming statistics: and data for monitoring the opening speed and various response speeds of the front-end webpage when the front-end webpage is opened.
It should be emphasized that, to further ensure the privacy and security of the above-mentioned snoop information data, the above-mentioned snoop information data may also be stored in a node of a blockchain.
203. When the front end HTML5 page is abnormal, extracting abnormal information data in the monitoring information data, capturing behavior information data of the front end HTML5 page, and analyzing the monitoring information data to obtain environment information data of the front end HTML5 page;
specifically, when the front end HTML5 page is abnormal, the server screens out an error monitoring function from the monitored information data through a preset monitoring system, and determines the error monitoring function as abnormal information data; the server captures user behavior data and application side behavior data of a front-end HTML5 page, and integrates the user behavior data and the application side behavior data to obtain behavior information data; and the server analyzes the monitoring information data to obtain the environment information data of the front-end HTML5 page.
When the front end HTML5 page is abnormal, the server needs to further acquire the following data:
1. anomaly information data
The abnormal information data are screened out from the monitored information data of a preset monitoring system, and error monitoring functions are screened out from the monitored information data, wherein at least one error monitoring function is selected.
2. Behavior information data
The behavior information data herein includes user behavior data and application side behavior data, where the user behavior data refers to data generated by a user operating on a front-end HTML5 page, such as: sliding data, clicking data, page skip data, keyboard input data, audio and video play pause data and the like; application-side behavior data refers to data generated by a developer operating on a front-end HTML5 page, such as: the log information data is automatically printed.
3. Environmental information data
The environmental information data is analyzed by monitoring the information data.
When acquiring the environmental information data, the method specifically comprises the following steps: the server acquires user agent data of a front end HTML5 page in the monitoring information data, and determines abnormal system version data and system type data in the user agent data; the server acquires an application program interface of a front end HTML5 page in the monitoring information data, and determines the type of network data when abnormality occurs based on the application program interface; and the server integrates the system version data, the system type data and the network data type to obtain environment information data.
The environmental information data here includes at least:
1. User agent data
The user agent data refers to userAgents, which are components of header in the Http protocol, and are also abbreviated as UA. The browser is a special character string head, and is an identifier for providing information such as browser type and version, operating system and version, browser kernel and the like used by a user for accessing a website. With this identification, the website visited by the user can display different typesetting to provide better experience or information statistics for the user.
2. Application program interface
The application program interface (application programming interface, API) refers to an application program interface carried by the browser itself, through which the corresponding network data type and network data condition can be queried when an anomaly occurs.
204. Encrypting the abnormal information data, the behavior information data and the environment information data by using an encryption algorithm, and integrating the encrypted information data to obtain detection information data;
specifically, the server extracts an abnormal data type, an abnormal data item and an abnormal information error stack in the abnormal information data, encrypts the abnormal information data based on the abnormal data type, the abnormal data item, the abnormal error information and an encryption algorithm, and obtains first encrypted information data; the server extracts behavior initiator information, behavior initiation address, behavior agent information, behavior data type, behavior information content and behavior occurrence time in the behavior information data, encrypts the behavior information data based on the behavior initiator information, the behavior initiation address, the behavior agent information, the behavior data type, the behavior information content, the behavior occurrence time and an encryption algorithm to obtain second encrypted information data; the server extracts an environment system version and an environment system type in the environment information data, encrypts the environment information data based on the environment system version, the environment system type and an encryption algorithm, and obtains third encrypted information data; the server integrates the first encrypted information data, the second encrypted information data and the third encrypted information data to obtain detection information data.
The server needs to confirm the input information of each information data before encrypting the abnormal information data, the behavior information data and the environment information data by utilizing an encryption algorithm, wherein the input information of the abnormal information data is the combination of the abnormal data type, the abnormal data item and the abnormal information error stack in the abnormal information data and is based on the combination of the first 30 characters of the abnormal data type, the abnormal data item and the abnormal information error; the input information of the behavior information data is behavior initiator information, behavior initiation address, behavior agent information, behavior data type, behavior information content and behavior occurrence time in the behavior information data, and the combination of the first 30 characters of the behavior initiator information, the behavior initiation address, the behavior agent information, the behavior data type, the behavior information content and the behavior occurrence time is based on the behavior initiator information; the input information of the environment information data is a combination of the environment system version and the first 30 characters of the environment system type in the environment information data. After confirming the input information of each information data, each information data may be separately subjected to encryption processing.
To encrypt the anomaly information data for illustration:
1. Determining input information of anomaly information data
The method comprises the steps of extracting an abnormal data type, an abnormal data item and an abnormal information error stack in abnormal information data according to a sequence from front to back, extracting a preset number of data characters in the abnormal data type, the abnormal data item and the abnormal information error, namely, combining the 30 characters based on the first 30 characters of the abnormal data type, the abnormal data item and the abnormal information error, and obtaining a first abnormal data character which is encrypted input information. It should be noted that, here, the preset number of data characters is set to the first 30 characters, and specifically, the preset number of data characters is set according to the actual situation.
2. Adding supplemental characters
And adding a supplementary character at the end of the first abnormal data character to obtain a second abnormal data character, wherein the character length of the second abnormal data character is k, k=n×512+448, n is a natural number, and the supplementary character is in the form of one 1 and m 0, wherein m is the natural number.
3. Adding counting characters
And adding a counting character at the end of the second abnormal data character to obtain a third abnormal data character, wherein the character length of the third abnormal data character is q multiplied by 512, q is a natural number, the character length of the counting character is a standard character length 64, and the counting character is used for recording the number of the first abnormal data character.
4. Loop operation
Four-round linear calculation of the third abnormal data character using a standard magic number, where a= (01234567) is a, to obtain the final first encrypted information data 16 ，B＝(89ABCDEF) 16 ，C＝(FEDCBA98) 16 ，D＝(76543210) 16 。
It is understood that the encryption of the behavior information data and the environment information data by the encryption algorithm is the same as the encryption of the abnormal information data.
205. And formatting the detection information data to generate an information display set, and analyzing the information display set to obtain an abnormal data analysis result of the front-end HTML5 page, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data.
Specifically, the server performs formatting processing on the detection information data to generate an information display set, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data; the server calculates abnormal data generation trend by using the abnormal information data display table; the server determines the network environment condition when the abnormality occurs based on the environment information data display table, determines the geographic position of the abnormality occurrence through the internet protocol address of the front-end HTML5 page, and determines the network processing strategy through the geographic position of the abnormality occurrence and the corresponding network environment condition; the server determines the distribution of abnormal behavior information data through a behavior information data display table; the server integrates the abnormal data generation trend, the network processing strategy and the distribution of abnormal behavior information data to obtain an abnormal data analysis result of the front-end HTML5 page.
The server can further analyze the abnormal data of the front-end HTML5 page, and the specific analysis process at least comprises the following aspects:
1. the abnormal data generation trend can be calculated through the abnormal information data display table, and whether the abnormal data volume changes caused by data change before and after application release can be rapidly identified through the abnormal data generation trend.
2. The basic information and the program source of the error can be clarified through the error stack of the abnormal information in the abnormal information data display table.
3. The network environment condition when the abnormality occurs can be determined based on the environment information data display table, the geographic position of the abnormality occurs is determined through the internet protocol address of the front end HTML5 page, and the network processing strategy is determined through the network environment condition corresponding to the geographic position of the abnormality, for example: the number of times of front-end abnormality occurrence in a certain area is very large, whether the area has network fluctuation problems is judged, and if the network fluctuation problems exist, the corresponding network processing strategy is what.
4. The distribution of the abnormal behavior information data can be determined through the behavior information data display list behavior data, and the user operation information can be conveniently searched through the behavior information list.
5. The system type and system version in which an abnormality occurs may be determined based on the environmental information data presentation table, such as "the system type is more problematic than ios" the speculatively compatibility problem, "the client version is abnormally significantly increased in the case of 70000" the speculatively app version compatibility problem ".
In addition, a custom application program interface is added in the preset monitoring system, through which a user can upload abnormal information data, behavior information data, and error information intercepted by error handling (componentDidCATch) for a reaction application, etc. independently. The accuracy of the abnormal information data is improved.
In the embodiment of the invention, a preset monitoring system is used for monitoring the front end HTML5 page, when an abnormality occurs, abnormal information data, capturing behavior information data and analyzing environment information data in monitoring information data are extracted, the information is encrypted by utilizing an encryption algorithm to obtain detection information data, and finally the detection information data is formatted to generate an information display set, and the information display set is further analyzed to obtain an abnormal data analysis result of the front end HTML5 page. The monitoring efficiency of the front-end monitoring abnormal system is improved.
The front-end anomaly monitoring and analyzing method in the embodiment of the present invention is described above, and the front-end anomaly monitoring and analyzing apparatus in the embodiment of the present invention is described below, referring to fig. 3, an embodiment of the front-end anomaly monitoring and analyzing apparatus in the embodiment of the present invention includes:
the monitoring module 301 is configured to monitor information data generated by a front-end HTML5 page by using a preset monitoring system, and acquire monitoring information data of the front-end HTML5 page in real time;
the processing module 302 is configured to extract abnormal information data from the monitoring information data when the front-end HTML5 page is abnormal, capture behavior information data of the front-end HTML5 page, and parse the monitoring information data to obtain environmental information data of the front-end HTML5 page;
an encryption module 303, configured to encrypt the abnormal information data, the behavior information data, and the environmental information data by using an encryption algorithm, and integrate the encrypted information data to obtain detection information data;
the analysis module 304 is configured to perform formatting processing on the detected information data, generate an information display set, and analyze the information display set to obtain an abnormal data analysis result of the front end HTML5 page, where the information display set includes an abnormal information data display table, an environmental information data display table, and a behavior information data display table that are generated based on the detected information data.
In the embodiment of the invention, a preset monitoring system is used for monitoring the front end HTML5 page, when an abnormality occurs, abnormal information data, capturing behavior information data and analyzing environment information data in monitoring information data are extracted, the information is encrypted by utilizing an encryption algorithm to obtain detection information data, and finally the detection information data is formatted to generate an information display set, and the information display set is further analyzed to obtain an abnormal data analysis result of the front end HTML5 page. The monitoring efficiency of the front-end monitoring abnormal system is improved.
Referring to fig. 4, another embodiment of the front-end anomaly monitoring and analyzing apparatus according to the present invention includes:
the monitoring module 301 is configured to monitor information data generated by a front-end HTML5 page by using a preset monitoring system, and acquire monitoring information data of the front-end HTML5 page in real time;
the processing module 302 is configured to extract abnormal information data from the monitoring information data when the front-end HTML5 page is abnormal, capture behavior information data of the front-end HTML5 page, and parse the monitoring information data to obtain environmental information data of the front-end HTML5 page;
An encryption module 303, configured to encrypt the abnormal information data, the behavior information data, and the environmental information data by using an encryption algorithm, and integrate the encrypted information data to obtain detection information data;
the analysis module 304 is configured to perform formatting processing on the detected information data, generate an information display set, and analyze the information display set to obtain an abnormal data analysis result of the front end HTML5 page, where the information display set includes an abnormal information data display table, an environmental information data display table, and a behavior information data display table that are generated based on the detected information data.
Optionally, the processing module 302 includes:
a screening unit 3021, configured to screen an error monitoring function from the monitoring information data by means of a preset monitoring system when the front-end HTML5 page is abnormal, and determine the error monitoring function as abnormal information data;
the capturing unit 3022 is configured to capture user behavior data and application behavior data of the front-end HTML5 page, and integrate the user behavior data and the application behavior data to obtain behavior information data;
And the parsing unit 3023 is configured to parse the listening information data to obtain the environmental information data of the front-end HTML5 page.
Optionally, the parsing unit 3023 is specifically configured to:
acquiring user agent data of the front end HTML5 page in the monitoring information data, and determining abnormal system version data and system type data in the user agent data;
acquiring an application program interface of the front end HTML5 page in the monitoring information data, and determining a network data type when an abnormality occurs based on the application program interface;
and integrating the system version data, the system type data and the network data type to obtain environment information data.
Optionally, the encryption module 303 includes:
a first encryption unit 3031, configured to extract an abnormal data type, an abnormal data item, and an abnormal information error stack in the abnormal information data, encrypt the abnormal information data based on the abnormal data type, the abnormal data item, the abnormal error information, and an encryption algorithm, and obtain first encrypted information data;
a second encryption unit 3032, configured to extract behavior initiator information, a behavior initiation address, behavior agent information, a behavior data type, behavior information content, and behavior occurrence time in the behavior information data, and encrypt the behavior information data based on the behavior initiator information, the behavior initiation address, the behavior agent information, the behavior data type, the behavior information content, the behavior occurrence time, and the encryption algorithm to obtain second encrypted information data;
A third encrypting unit 3033, configured to extract an environmental system version and an environmental system type in the environmental information data, and encrypt the environmental information data based on the environmental system version, the environmental system type and the encryption algorithm to obtain third encrypted information data;
an integrating unit 3034, configured to integrate the first encrypted information data, the second encrypted information data, and the third encrypted information data to obtain detection information data.
Optionally, the first encrypting unit 3031 is specifically configured to:
respectively extracting an abnormal data type, an abnormal data item and an abnormal information error stack in the abnormal information data according to the sequence from front to back, respectively extracting a preset number of data characters from the abnormal data type, the abnormal data item and the abnormal information error, and integrating each data character according to the extraction sequence to obtain a first abnormal data character;
adding a supplementary character at the tail of the first abnormal data character to obtain a second abnormal data character, wherein the character length of the second abnormal data character is k, k=n×512+448, and n is a natural number;
adding a counting character at the end of the second abnormal data character to obtain a third abnormal data character, wherein the counting character is used for recording the number of the first abnormal data character, and the character length of the counting character is the standard character length;
And performing cyclic operation on the third abnormal data character by using the standard magic number to obtain first encrypted information data.
Optionally, the analysis module 304 is specifically configured to:
formatting the detection information data to generate an information display set, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data;
calculating an abnormal data generation trend by using the abnormal information data display table;
determining a network environment condition when an abnormality occurs based on the environment information data display table, determining a geographic position of the abnormality occurrence through an internet protocol address of the front-end HTML5 page, and determining a network processing strategy through the geographic position of the abnormality occurrence and the corresponding network environment condition;
determining the distribution of abnormal behavior information data through the behavior information data display table;
and integrating the abnormal data generation trend, the network processing strategy and the distribution of the abnormal behavior information data to obtain an abnormal data analysis result of the front-end HTML5 page.
Optionally, the front-end anomaly monitoring and analyzing device further includes:
An initialization module 305 is configured to initialize the preset listening system by using an initialization function.
In the embodiment of the invention, a preset monitoring system is used for monitoring the front end HTML5 page, when an abnormality occurs, abnormal information data, capturing behavior information data and analyzing environment information data in monitoring information data are extracted, the information is encrypted by utilizing an encryption algorithm to obtain detection information data, and finally the detection information data is formatted to generate an information display set, and the information display set is further analyzed to obtain an abnormal data analysis result of the front end HTML5 page. The monitoring efficiency of the front-end monitoring abnormal system is improved.
The front-end abnormality monitoring and analyzing apparatus in the embodiment of the present invention is described in detail from the point of view of the modularized functional entity in fig. 3 and 4 above, and the front-end abnormality monitoring and analyzing device in the embodiment of the present invention is described in detail from the point of view of hardware processing below.
Fig. 5 is a schematic structural diagram of a front-end anomaly monitoring and analysis device 500 according to an embodiment of the present invention, where the front-end anomaly monitoring and analysis device 500 may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (e.g., one or more processors) and a memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) storing application programs 533 or data 532. Wherein memory 520 and storage medium 530 may be transitory or persistent storage. The program stored in the storage medium 530 may include one or more modules (not shown), each of which may include a series of instruction operations in the front-end anomaly monitoring and analysis device 500. Still further, the processor 510 may be configured to communicate with the storage medium 530 and execute a series of instruction operations in the storage medium 530 on the front-end anomaly monitoring and analysis device 500.
The front-end anomaly monitoring and analysis device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input/output interfaces 560, and/or one or more operating systems 531, such as Windows Server, mac OS X, unix, linux, freeBSD, and the like. It will be appreciated by those skilled in the art that the front-end anomaly monitoring and analysis device structure shown in FIG. 5 is not limiting of the front-end anomaly monitoring and analysis device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
The invention also provides front-end anomaly monitoring and analyzing equipment, which comprises a memory and a processor, wherein the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the front-end anomaly monitoring and analyzing method in the above embodiments.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, or may be a volatile computer readable storage medium, where instructions are stored in the computer readable storage medium, when the instructions are executed on a computer, cause the computer to perform the steps of the front-end anomaly monitoring and analysis method.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The front-end anomaly monitoring and analyzing method is characterized by comprising the following steps of:
monitoring information data generated by a front-end HTML5 page by using a preset monitoring system, and acquiring the monitored information data of the front-end HTML5 page in real time;
when the front end HTML5 page is abnormal, extracting abnormal information data in the monitoring information data, capturing behavior information data of the front end HTML5 page, and analyzing the monitoring information data to obtain environment information data of the front end HTML5 page;
encrypting the abnormal information data, the behavior information data and the environment information data by using an encryption algorithm, and integrating the encrypted information data to obtain detection information data;
And formatting the detection information data to generate an information display set, analyzing the information display set to obtain an abnormal data analysis result of the front-end HTML5 page, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data.
2. The method for monitoring and analyzing front-end anomalies according to claim 1, wherein when the front-end HTML5 page is anomalous, extracting anomaly information data from the monitored information data, capturing behavior information data of the front-end HTML5 page, and analyzing the monitored information data to obtain environmental information data of the front-end HTML5 page comprises:
when the front end HTML5 page is abnormal, an error monitoring function is screened out from the monitoring information data through a preset monitoring system, and the error monitoring function is determined to be abnormal information data;
capturing user behavior data and application side behavior data of the front-end HTML5 page, and integrating the user behavior data and the application side behavior data to obtain behavior information data;
And analyzing the monitoring information data to obtain the environment information data of the front-end HTML5 page.
3. The method for monitoring and analyzing front-end anomalies according to claim 2, wherein the parsing the listening information data to obtain environmental information data of the front-end HTML5 page includes:
acquiring user agent data of the front end HTML5 page in the monitoring information data, and determining abnormal system version data and system type data in the user agent data;
acquiring an application program interface of the front end HTML5 page in the monitoring information data, and determining a network data type when an abnormality occurs based on the application program interface;
and integrating the system version data, the system type data and the network data type to obtain environment information data.
4. The front-end anomaly monitoring and analysis method according to claim 1, wherein the encrypting the anomaly information data, the behavior information data, and the environmental information data by using an encryption algorithm, respectively, and integrating the encrypted information data to obtain detection information data includes:
extracting an abnormal data type, an abnormal data item and an abnormal information error stack in the abnormal information data, and encrypting the abnormal information data based on the abnormal data type, the abnormal data item, the abnormal information error stack and an encryption algorithm to obtain first encrypted information data;
Extracting behavior initiator information, behavior initiation address, behavior agent information, behavior data type, behavior information content and behavior occurrence time from the behavior information data, and encrypting the behavior information data based on the behavior initiator information, the behavior initiation address, the behavior agent information, the behavior data type, the behavior information content, the behavior occurrence time and the encryption algorithm to obtain second encrypted information data;
extracting an environment system version and an environment system type from the environment information data, and encrypting the environment information data based on the environment system version, the environment system type and the encryption algorithm to obtain third encrypted information data;
and integrating the first encryption information data, the second encryption information data and the third encryption information data to obtain detection information data.
5. The method of front-end anomaly monitoring and analysis of claim 4, wherein the extracting the anomaly data type, the anomaly data item, and the anomaly information error stack from the anomaly information data, encrypting the anomaly information data based on the anomaly data type, the anomaly data item, the anomaly information error stack, and an encryption algorithm, the obtaining the first encrypted information data comprises:
Respectively extracting an abnormal data type, an abnormal data item and an abnormal information error stack in the abnormal information data according to the sequence from front to back, respectively extracting a preset number of data characters from the abnormal data type, the abnormal data item and the abnormal information error stack, and integrating each data character according to the extraction sequence to obtain a first abnormal data character;
adding a supplementary character at the tail of the first abnormal data character to obtain a second abnormal data character, wherein the character length of the second abnormal data character is as follows，/>Wherein->Is a natural number;
adding a counting character at the end of the second abnormal data character to obtain a third abnormal data character, wherein the counting character is used for recording the number of the first abnormal data character, and the character length of the counting character is the standard character length;
and performing cyclic operation on the third abnormal data character by using the standard magic number to obtain first encrypted information data.
6. The front-end anomaly monitoring and analyzing method according to claim 1, wherein the formatting the detected information data to generate an information display set, and analyzing the information display set to obtain an anomaly data analysis result of the front-end HTML5 page, the information display set including an anomaly information data display table, an environmental information data display table, and a behavior information data display table generated based on the detected information data includes:
Formatting the detection information data to generate an information display set, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data;
calculating an abnormal data generation trend by using the abnormal information data display table;
determining a network environment condition when an abnormality occurs based on the environment information data display table, determining a geographic position of the abnormality occurrence through an internet protocol address of the front-end HTML5 page, and determining a network processing strategy through the geographic position of the abnormality occurrence and the corresponding network environment condition;
determining the distribution of abnormal behavior information data through the behavior information data display table;
and integrating the abnormal data generation trend, the network processing strategy and the distribution of the abnormal behavior information data to obtain an abnormal data analysis result of the front-end HTML5 page.
7. The front-end anomaly monitoring and analysis method according to any one of claims 1 to 6, wherein before the monitoring of the information data generated by the front-end HTML5 page by the preset monitoring system, the front-end anomaly monitoring and analysis method further comprises:
And initializing the preset monitoring system by using an initialization function.
8. A front-end anomaly monitoring and analysis device, the front-end anomaly monitoring and analysis device comprising:
the monitoring module is used for monitoring information data generated by the front-end HTML5 page by using a preset monitoring system, and acquiring the monitoring information data of the front-end HTML5 page in real time;
the processing module is used for extracting abnormal information data in the monitoring information data when the front-end HTML5 page is abnormal, capturing behavior information data of the front-end HTML5 page, and analyzing the monitoring information data to obtain environment information data of the front-end HTML5 page;
the encryption module is used for encrypting the abnormal information data, the behavior information data and the environment information data respectively by utilizing an encryption algorithm, and integrating the encrypted information data to obtain detection information data;
the analysis module is used for carrying out formatting processing on the detection information data to generate an information display set, analyzing the information display set to obtain an abnormal data analysis result of the front end HTML5 page, wherein the information display set comprises an abnormal information data display table, an environment information data display table and a behavior information data display table which are generated based on the detection information data.
9. A front-end anomaly monitoring and analysis device, the front-end anomaly monitoring and analysis device comprising: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invoking the instructions in the memory to cause the front-end anomaly monitoring and analysis device to perform the front-end anomaly monitoring and analysis method of any one of claims 1-7.
10. A computer readable storage medium having instructions stored thereon, which when executed by a processor implement the front-end anomaly monitoring and analysis method of any one of claims 1-7.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140304399A1 (en) * | 2013-04-06 | 2014-10-09 | Citrix Systems, Inc. | Systems and methods for providing monitoring in a cluster system |
| US20170126709A1 (en) * | 2015-10-30 | 2017-05-04 | Citrix Systems, Inc. | Feature engineering for web-based anomaly detection |
| CN107566200A (en) * | 2016-06-30 | 2018-01-09 | 阿里巴巴集团控股有限公司 | A kind of monitoring method, apparatus and system |
| CN110347524A (en) * | 2019-05-28 | 2019-10-18 | 平安普惠企业管理有限公司 | A kind of feedback method and device, storage medium, electronic equipment of exception information |
-
2021
- 2021-06-01 CN CN202110607807.1A patent/CN113254312B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140304399A1 (en) * | 2013-04-06 | 2014-10-09 | Citrix Systems, Inc. | Systems and methods for providing monitoring in a cluster system |
| US20170126709A1 (en) * | 2015-10-30 | 2017-05-04 | Citrix Systems, Inc. | Feature engineering for web-based anomaly detection |
| CN107566200A (en) * | 2016-06-30 | 2018-01-09 | 阿里巴巴集团控股有限公司 | A kind of monitoring method, apparatus and system |
| CN110347524A (en) * | 2019-05-28 | 2019-10-18 | 平安普惠企业管理有限公司 | A kind of feedback method and device, storage medium, electronic equipment of exception information |
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