CN115914064A - Network system service performance evaluation method, device, computing equipment and storage medium - Google Patents
Network system service performance evaluation method, device, computing equipment and storage medium Download PDFInfo
- Publication number
- CN115914064A CN115914064A CN202110900142.3A CN202110900142A CN115914064A CN 115914064 A CN115914064 A CN 115914064A CN 202110900142 A CN202110900142 A CN 202110900142A CN 115914064 A CN115914064 A CN 115914064A
- Authority
- CN
- China
- Prior art keywords
- data
- data information
- information
- service
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The invention discloses a method and a device for evaluating service performance of a network system, computing equipment and a storage medium. According to the technical scheme provided by the invention, the flow data information in the service system is collected and stored in a database; the flow data information at least comprises a domain name, a URL (uniform resource locator), a state code and a timestamp; extracting flow data information generated in a target time period from a database, and analyzing the flow data information to obtain aggregate data and abnormal transaction data in the service system; generating and displaying a corresponding data chart according to the aggregated data; and sending alarm transaction information according to the abnormal transaction data. The invention can automatically acquire the flow data information in real time, and after analysis, the abnormal transaction data is displayed and the alarm information is sent out, thereby saving the labor cost, simultaneously conjecturing the possible system service performance deterioration result as early as possible and greatly reducing the negative effect of the result on the system service.
Description
Technical Field
The invention relates to the field of computer software, in particular to a network system service performance evaluation method, a network system service performance evaluation device, a computing device and a computer storage medium.
Background
With the gradual scale-up, load increase and traffic increase of the internet system, the use frequency of the WEB page, the client and the APP application is continuously increased, and then the generated data traffic is also continuously increased. HTTP traffic is necessary for all service data access usage, and therefore, the data can present real-time aspects of internet services. If the traffic data is not monitored in time, situations of pause, overtime, abnormity and the like of use may occur, so that the user experience of the IT application system is deteriorated, the communication cost is improved, the office efficiency of a salesman is reduced, the queuing time of a user is prolonged, and the complaint of customers is increased.
In the prior art, monitoring of network load equipment and a traffic trend graph are mainly used as data sources for judging traffic data. However, all received data traffic packets of the current system can be monitored through the network load device, so that traffic trends are reflected, but specific system service performance and application service conditions in specific service scenes cannot be judged; the performance of the current service system is judged according to the traffic trend graph, the traditional database table look-up calculation is needed, and the curve is drawn manually, so that the manual feedback system lags behind the current flow change of the system to cause errors, and a large amount of labor cost is consumed. Due to the lack of service performance embodiment conditions of the system of the service flow, continuous conditions after performance deterioration and first-time acquisition capability after recovery, the problems that service performance deterioration risks cannot be mastered in real time, and the data deposition accumulative aging is long and feedback cannot be performed quickly are caused. Specifically, the discovery of the performance deterioration phenomenon and the acquisition means in the development process are delayed, and the operation and maintenance personnel of the service maintenance party are required to have experience and autonomous judgment capability.
Disclosure of Invention
In view of the above problems, the present invention is proposed to provide a network system service performance evaluation method and a corresponding network system service performance evaluation apparatus, a computing device and a computer storage medium that overcome or at least partially solve the above problems.
According to an aspect of the present invention, there is provided a method for evaluating service performance of a network system, the method including:
collecting flow data information in a service system and storing the flow data information in a database; the flow data information at least comprises a domain name, a URL (uniform resource locator), a state code and a timestamp;
extracting flow data information generated in a target time period from a database, and analyzing the flow data information to obtain aggregate data and abnormal transaction data in the service system;
generating and displaying a corresponding data chart according to the aggregated data;
and sending alarm transaction information according to the abnormal transaction data.
In the above scheme, the acquiring and storing the traffic data information in the service system into the database further includes:
monitoring the flow of the service system;
collecting and analyzing the flow data information in a mirror flow mode;
wherein the database is a columnar storage data type-based database.
In the foregoing scheme, the extracting traffic data information generated in a target time period from a database, and analyzing the traffic data information to obtain aggregated data and abnormal transaction data in the service system further includes:
classifying the traffic data information according to a preset rule to obtain classified traffic data information;
analyzing the classified flow data information according to a preset analysis dimension to obtain a data analysis result corresponding to the preset analysis dimension;
aggregating and merging data analysis results corresponding to preset analysis dimensions by using a data model to obtain aggregated data;
and obtaining abnormal data in the service system according to the aggregated data and the abnormal judgment condition.
In the above scheme, the preset analysis dimension includes at least one of: access traffic, response success rate, request call response duration.
In the above solution, the data chart includes at least one of: access traffic histogram, response request time consumption ratio line graph, area distribution pie graph.
In the foregoing solution, the sending alarm transaction information according to the abnormal transaction data further includes:
and sending alarm transaction information to the service maintenance end through page notification or short messages according to the abnormal transaction data so as to inform the service maintenance end of the service performance state of the service system.
According to another aspect of the present invention, there is provided a network system service performance evaluation apparatus, including: the device comprises an acquisition module, a data analysis module, a generation module and an information sending module; wherein the content of the first and second substances,
the acquisition module is used for acquiring flow data information in the service system and storing the flow data information in the database; the flow data information at least comprises a domain name, a URL (uniform resource locator), a state code and a timestamp;
the data analysis module is used for extracting flow data information generated in a target time period from a database, and analyzing the flow data information to obtain aggregate data and abnormal transaction data in the service system;
the generating module is used for generating and displaying a corresponding data chart according to the aggregated data;
and the information sending module is used for sending alarm transaction information according to the abnormal transaction data.
In the foregoing solution, the data analysis module further includes: the device comprises a classification module, an analysis and aggregation module and a determination module; wherein, the first and the second end of the pipe are connected with each other,
the classification module is used for classifying the traffic data information according to a preset rule to obtain classified traffic data information;
the analysis aggregation module is used for analyzing the classified flow data information according to a preset analysis dimension to obtain a data analysis result corresponding to the preset analysis dimension; aggregating and merging data analysis results corresponding to preset analysis dimensions by using a data model to obtain aggregated data;
and the determining module is used for obtaining abnormal transaction data in the service system according to the aggregation data and the transaction judging conditions.
According to yet another aspect of the present invention, there is provided a computing device comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface are communicated with each other through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the network system service performance evaluation method.
According to still another aspect of the present invention, a computer storage medium is provided, where at least one executable instruction is stored in the storage medium, and the executable instruction causes a processor to perform operations corresponding to the network system service performance evaluation method as described above.
According to the technical scheme provided by the invention, the flow data information in the service system is collected and stored in a database; the flow data information at least comprises a domain name, a URL (uniform resource locator), a state code and a timestamp; extracting flow data information generated in a target time period from a database, and analyzing the flow data information to obtain aggregate data and abnormal transaction data in the service system; generating and displaying a corresponding data chart according to the aggregated data; and sending alarm transaction information according to the abnormal transaction data. Therefore, the problems that in the prior art, the manual feedback system lags behind the current flow change of the system to cause errors and consume a large amount of labor cost are solved. According to the technical scheme provided by the invention, the flow data information is collected and analyzed, and after the aggregation data and the abnormal transaction data in the service system are obtained, the data chart is finally generated and the alarm transaction information is sent. The flow data information automatically acquired in real time is analyzed, the service performance deterioration trend can be found in time, the warning information can be sent out as early as possible, the monitoring and feedback speed of the service performance of the business is greatly improved, and the labor cost is greatly reduced.
The above description is only an overview of the technical solutions of the present invention, and the present invention can be implemented in accordance with the content of the description so as to make the technical means of the present invention more clearly understood, and the above and other objects, features, and advantages of the present invention will be more clearly understood.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow diagram illustrating a method for evaluating service performance of a network system according to one embodiment of the invention;
FIG. 2 is a flow diagram illustrating a method of analyzing traffic data information according to one embodiment of the invention;
fig. 3 is a block diagram showing the construction of a network system service performance evaluation apparatus according to an embodiment of the present invention;
FIG. 4 shows a schematic structural diagram of a computing device according to an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Fig. 1 is a flowchart illustrating a method for evaluating service performance of a network system according to an embodiment of the present invention, where the method includes the following steps as shown in fig. 1:
step S101, collecting flow data information in a service system and storing the flow data information in a database; the traffic data information at least comprises a domain name, a URL (uniform resource locator), a status code and a timestamp.
Specifically, the collecting and storing the traffic data information in the service system into the database further includes:
monitoring the traffic of the service system;
collecting and analyzing the flow data information in a mirror flow mode;
wherein the database is a column-based database of stored data types.
Further, the traffic monitoring is performed on the service system, all domain name URL data packets (i.e., the traffic data information) of the service system are collected in a mirror traffic capture mode, and after the collection, a plurality of fields are split, wherein the fields at least include the contents of domain names, detailed URLs, status codes, timestamps, and the like. The collected flow data information is then stored in a columnar store data type based database (CLICKHOUSE).
The mirror image flow capturing mode is to capture and copy the flow data information of the service system, and analyze the copied flow data information without influencing the original flow data information. Meanwhile, the flow data information is stored into a CLICKHOUSE database, and the CLICKHOUSE database has great performance advantage in data index flow analysis.
And step S102, extracting the flow data information generated in the target time period from the database, and analyzing the flow data information to obtain the aggregation data and the abnormal transaction data in the service system.
Specifically, the extracting traffic data information generated in a target time period from a database, analyzing the traffic data information, and obtaining aggregation data and abnormal transaction data in the service system further includes:
classifying the traffic data information according to a preset rule to obtain classified traffic data information;
analyzing the classified flow data information according to a preset analysis dimension to obtain a data analysis result corresponding to the preset analysis dimension;
aggregating and merging data analysis results corresponding to preset analysis dimensions by using a data model to obtain aggregated data;
and obtaining abnormal transaction data in the service system according to the aggregated data and the transaction judgment condition.
Wherein the preset analysis dimension comprises at least one of: access traffic, response success rate, request invocation response duration.
And step S103, generating and displaying a corresponding data chart according to the aggregated data.
The resulting aggregated data provides data support for automatically charting data. Specifically, the data chart includes at least one of:
access traffic histogram, response request time consumption ratio line graph, area distribution pie graph.
The aggregated data obtained by aggregating and merging the data analysis results corresponding to the preset analysis dimensions can embody the deterioration judgment result of the system service performance corresponding to the domain name, the possibility of service performance trend change and the system range of influence. Therefore, the corresponding data graph drawn based on the aggregated data can embody the above results from different dimensions more intuitively.
Step S104: and sending alarm transaction information according to the abnormal transaction data.
Specifically, the sending alarm transaction information according to the abnormal transaction data further includes:
and sending alarm transaction information to the service maintenance end through page notification or short messages according to the abnormal transaction data so as to inform the service maintenance end of the service performance state of the service system. Setting the hazard level to normal, for example, when the response exceeds 1 s; when the response exceeds 2s, the hazard level is set to medium; when the response exceeds 3s, the risk level is set high.
According to the method for evaluating the service performance of the network system, the flow data information in the service system is collected and stored in a database; the flow data information at least comprises a domain name, a URL (uniform resource locator), a state code and a timestamp; extracting flow data information generated in a target time period from a database, and analyzing the flow data information to obtain aggregate data and abnormal transaction data in the service system; generating and displaying a corresponding data chart according to the aggregated data; and sending alarm transaction information according to the abnormal transaction data. The scheme effectively solves the problems that in the prior art, the manual feedback system lags behind the current flow change of the system to cause errors and consumes a large amount of labor cost. By means of the method, the flow data information is collected and analyzed, and after aggregation data and abnormal data in a service system are obtained, a data chart is finally generated and alarm abnormal information is sent. The method can automatically acquire and analyze the flow data information in real time, excessive manual communication cost is not needed, and the larger the data volume is, the better the noise reduction effect is; specific scene analysis can be performed based on the statistical characteristics, so that the final evaluation can be more targeted and adaptive; the data can be processed through the calibration value during data analysis, so that the result is more accurate. Therefore, the monitoring and feedback precision and speed of the business service performance are greatly improved, and the labor cost is greatly reduced.
Fig. 2 is a schematic flow chart of analyzing traffic data information according to an embodiment of the present invention, and as shown in fig. 2, the method includes the following steps:
step S201: and classifying the traffic data information according to a preset rule to obtain the classified traffic data information.
Specifically, based on contents such as a domain name, a detailed URL, a status code, and a timestamp included in the traffic data information, reusability of field indexes after URL splitting is subdivided, three types of granularity indexes of an interface are distinguished by access traffic, access success rate, and request call response time, are applied within a plurality of time intervals, and are distinguished as common or common, high frequency, or high frequency for a domain name URL.
Step S202: and analyzing the classified flow data information according to the preset analysis dimension to obtain a data analysis result corresponding to the preset analysis dimension.
Wherein the preset analysis dimensions comprise at least one of:
access traffic, response success rate, request call response duration.
Specifically, data analysis results corresponding to dimensions such as access traffic, response success rate, request call response duration, or system influence number and system success rate ratio are analyzed according to the dimension of the minute level.
Step S203: and aggregating and merging the data analysis results corresponding to the preset analysis dimensionality by using the data model to obtain aggregated data.
Specifically, SQL (Structured Query Language) is used for querying on the CLICKHOUSE database, real-time data sorting output is met through a timer, the overall growth trend of data is fitted through a model, data aggregation calculation is performed according to a minute-scale dimension, and the aggregated data is obtained by analyzing the ring ratio and the homonymy data of three types of granularity indexes and merging according to a main domain dimension and serves as a judgment result of system service performance deterioration. The effect of reflecting the service efficiency of the system with gradient trend can be obtained by using the combination of SQL according to the aimed purpose and one or more columns of conditions according to a fixed time interval.
Preferably, the fluctuation data of the ring ratio and the same ratio of the three types of granularity indexes exceeding 25% is analyzed and merged according to the dimension of the main domain name.
Step S204: and obtaining abnormal transaction data in the service system according to the aggregated data and the transaction judgment condition.
Specifically, the transaction determination condition is a service performance deterioration change rule summarized according to historical precipitation data, and the determination result can be optimized by inputting time interval and traffic parameter value data to remove unusable abnormal data. Therefore, more accurate abnormal and abnormal data in the service system can be obtained through the aggregated data and the abnormal and abnormal judgment condition. And (3) deducing abnormal change judgment conditions (such as value range intervals) through historical precipitation data statistics, realizing system service performance deterioration analysis and calculation, and finally outputting a system service performance problem with a large influence surface as early as possible through a result of statistical speculation.
For example, to obtain the latest response service condition of a domain name, the domain name searched in real time in the latest 6 hours meets the condition that the response start minus the request start is more than 3s under the same request content under the condition that the character string response start is more than the request start, and then the response service condition of the domain name can be obtained. Where the condition that the response start is greater than the request start is to remove erroneous data, 3s is a value that can be customized. An example of SQL is as follows:
select toString(toDateTime(floor(req_timestamp/1000/60)*60))time,count(*)cnt,sum(if(res_start_time-req_timestamp>＝3000,1,0))/cnt hits3_per from sm_https WHERE req_timestamp>＝toUnixTimestamp(now())*1000-60*60*1000*6AND req_timestamp<＝toUnixTimestamp(now())*1000and request_host＝'XXX'and res_start_time>＝req_timestamp group by time order by time
select toString(toDateTime(floor(req_timestamp/1000/60)*60))time,count(*)cnt,sum(if(res_start_time-req_timestamp>＝3000,1,0))/cnt hits3_per from sm_https WHERE req_timestamp>＝toUnixTimestamp(now())*1000-60*60*1000*6AND req_timestamp<＝toUnixTimestamp(now())*1000and request_host＝'XXX'and res_start_time>＝req_timestamp group by time order by time
in an example, the larger the custom number is, the larger the proportion of aggregated data is, the more serious the system is blocked, the less timely the response is, and the worse the system service performance is.
In addition to the above example, the corresponding result may be obtained by aggregating the fields cut out by the URL in the traffic data information such as the success/failure status code, the region, the job number, and the like.
Fig. 3 is a block diagram illustrating a structure of a network system service performance evaluation apparatus according to an embodiment of the present invention, and as shown in fig. 3, the apparatus includes: the system comprises an acquisition module 301, a data analysis module 302, a generation module 303 and an information sending module 304; wherein the content of the first and second substances,
the acquisition module 301 is configured to: collecting flow data information in a service system and storing the flow data information in a database; the traffic data information at least comprises a domain name, a URL (uniform resource locator), a status code and a timestamp.
Specifically, the collecting and storing the traffic data information in the service system into the database further includes: monitoring the traffic of the service system; collecting and analyzing the flow data information in a mirror flow mode; wherein the database is a column-based database of stored data types.
The data analysis module 302 is configured to: and extracting the flow data information generated in the target time period from the database, and analyzing the flow data information to obtain the aggregation data and the abnormal transaction data in the service system.
Specifically, the data analysis module 302 further includes: a classification module 305, an analysis aggregation module 306, and a determination module 307; wherein the content of the first and second substances,
the classification module 305 is configured to classify the traffic data information according to a preset rule, so as to obtain classified traffic data information;
the analysis aggregation module 306 is configured to analyze the classified flow data information according to a preset analysis dimension, so as to obtain a data analysis result corresponding to the preset analysis dimension; aggregating and merging data analysis results corresponding to preset analysis dimensions by using a data model to obtain aggregated data;
the determining module 307 is configured to obtain abnormal transaction data in the service system according to the aggregation data and the transaction determining condition;
the preset analysis dimension comprises at least one of: access traffic, response success rate, request call response duration.
The generating module 303 is configured to: and generating and displaying a corresponding data chart according to the aggregated data.
Specifically, the data chart includes at least one of: access traffic histogram, response request time consumption ratio line graph, area distribution pie graph.
The information sending module 304 is configured to: and sending alarm transaction information according to the abnormal transaction data.
Specifically, the sending alarm transaction information according to the abnormal transaction data further includes: and sending alarm transaction information to the service maintenance end through page notification or short messages according to the abnormal transaction data so as to inform the service maintenance end of the service performance state of the service system.
According to the network system service performance evaluation device provided by the embodiment, the flow data information in the service system is collected and stored in the database; the flow data information at least comprises a domain name, a URL (uniform resource locator), a state code and a timestamp; extracting flow data information generated in a target time period from a database, and analyzing the flow data information to obtain aggregate data and abnormal transaction data in the service system; generating and displaying a corresponding data chart according to the aggregated data; and sending alarm transaction information according to the abnormal transaction data. The device effectively solves the problems that in the prior art, the manual feedback system lags behind the current flow change of the system to cause errors and consumes a large amount of labor cost. By the device in the embodiment of the application, the flow data information is collected and analyzed, and after aggregation data and abnormal data in a service system are obtained, a data chart is finally generated and alarm abnormal information is sent. The method can automatically acquire and analyze the flow data information in real time, excessive manual communication cost is not needed, and the larger the data volume is, the better the noise reduction effect is; specific scene analysis can be performed based on the statistical characteristics, so that the final evaluation can be more targeted and adaptive; the data can be processed through the calibration value during data analysis, so that the result is more accurate. Therefore, the monitoring and feedback precision and speed of the business service performance are greatly improved, and the labor cost is greatly reduced.
The invention also provides a nonvolatile computer storage medium, which stores at least one executable instruction, wherein the executable instruction can execute the network system service performance evaluation method in any method embodiment.
Fig. 4 is a schematic structural diagram of a computing device according to an embodiment of the present invention, and the specific embodiment of the present invention does not limit the specific implementation of the computing device.
As shown in fig. 4, the computing device may include: a processor (processor) 402, a communication Interface 404, a memory 406, and a communication bus 408.
Wherein:
the processor 402, communication interface 404, and memory 406 communicate with each other via a communication bus 408.
A communication interface 404 for communicating with network elements of other devices, such as clients or other servers.
The processor 402 is configured to execute the program 410, and may specifically execute the relevant steps in the network system service performance evaluation embodiment described above.
In particular, program 410 may include program code comprising computer operating instructions.
The processor 402 may be a central processing unit CPU, or an Application Specific Integrated Circuit ASIC (Application Specific Integrated Circuit), or one or more Integrated circuits configured to implement an embodiment of the present invention. The computing device includes one or more processors, which may be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
A memory 406 for storing a program 410. Memory 406 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 410 may be specifically configured to cause the processor 402 to execute the network system service performance evaluation method in any of the above-described method embodiments. For specific implementation of each step in the program 410, reference may be made to corresponding steps and corresponding descriptions in units in the foregoing network system service performance evaluation method embodiment, which are not described herein again. It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described devices and modules may refer to the corresponding process descriptions in the foregoing method embodiments, and are not described herein again.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system is apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: rather, the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the devices in an embodiment may be adaptively changed and arranged in one or more devices different from the embodiment. The modules or units or components in the embodiments may be combined into one module or unit or component, and furthermore, may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Moreover, those skilled in the art will appreciate that although some embodiments described herein include some features included in other embodiments, not others, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components in accordance with embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on a computer readable medium or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Claims (10)
1. A network system service performance evaluation method comprises the following steps:
collecting flow data information in a service system and storing the flow data information in a database; the flow data information at least comprises a domain name, a URL (uniform resource locator), a state code and a timestamp;
extracting flow data information generated in a target time period from a database, and analyzing the flow data information to obtain aggregate data and abnormal transaction data in the service system;
generating and displaying a corresponding data chart according to the aggregated data;
and sending alarm transaction information according to the abnormal transaction data.
2. The method of claim 1, wherein the collecting and storing traffic data information in a business system into a database further comprises:
monitoring the traffic of the service system;
collecting and analyzing the flow data information in a mirror flow mode;
wherein the database is a columnar storage data type-based database.
3. The method of claim 1, wherein the extracting traffic data information generated in a target time period from a database, analyzing the traffic data information, and obtaining aggregate data and abnormal transaction data in the service system further comprises:
classifying the traffic data information according to a preset rule to obtain classified traffic data information;
analyzing the classified flow data information according to a preset analysis dimension to obtain a data analysis result corresponding to the preset analysis dimension;
aggregating and merging data analysis results corresponding to preset analysis dimensions by using a data model to obtain aggregated data;
and obtaining abnormal data in the service system according to the aggregated data and the abnormal judgment condition.
4. The method of claim 3, wherein the preset analysis dimensions comprise at least one of: access traffic, response success rate, request invocation response duration.
5. The method of claim 1, wherein the data graph comprises at least one of: access traffic histogram, response request time consumption ratio line graph, area distribution pie graph.
6. The method of claim 1, wherein said sending alarm transaction information based on said abnormal transaction data further comprises:
and sending alarm transaction information to the service maintenance end through page notification or short messages according to the abnormal transaction data so as to inform the service maintenance end of the service performance state of the service system.
7. A network system service performance evaluation apparatus, comprising: the device comprises an acquisition module, a data analysis module, a generation module and an information sending module; wherein, the first and the second end of the pipe are connected with each other,
the acquisition module is used for acquiring flow data information in the service system and storing the flow data information in the database; the flow data information at least comprises a domain name, a URL (uniform resource locator), a state code and a timestamp;
the data analysis module is used for extracting flow data information generated in a target time period from a database, and analyzing the flow data information to obtain aggregate data and abnormal transaction data in the service system;
the generating module is used for generating and displaying a corresponding data chart according to the aggregated data;
and the information sending module is used for sending alarm transaction information according to the abnormal transaction data.
8. The apparatus of claim 7, the data analysis module further comprising: the system comprises a classification module, an analysis and aggregation module and a determination module; wherein, the first and the second end of the pipe are connected with each other,
the classification module is used for classifying the traffic data information according to a preset rule to obtain classified traffic data information;
the analysis aggregation module is used for analyzing the classified flow data information according to a preset analysis dimension to obtain a data analysis result corresponding to the preset analysis dimension; aggregating and merging data analysis results corresponding to preset analysis dimensions by using a data model to obtain aggregated data;
and the determining module is used for obtaining abnormal data in the service system according to the aggregation data and the abnormal judgment condition.
9. A computing device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the network system service performance evaluation method according to any one of claims 1-7.
10. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the network system service performance assessment method of any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110900142.3A CN115914064A (en) | 2021-08-06 | 2021-08-06 | Network system service performance evaluation method, device, computing equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110900142.3A CN115914064A (en) | 2021-08-06 | 2021-08-06 | Network system service performance evaluation method, device, computing equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115914064A true CN115914064A (en) | 2023-04-04 |
Family
ID=86478222
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110900142.3A Pending CN115914064A (en) | 2021-08-06 | 2021-08-06 | Network system service performance evaluation method, device, computing equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115914064A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117896284A (en) * | 2024-01-17 | 2024-04-16 | 北京奇虎科技有限公司 | Performance fluctuation positioning method, device, equipment and storage medium |
-
2021
- 2021-08-06 CN CN202110900142.3A patent/CN115914064A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117896284A (en) * | 2024-01-17 | 2024-04-16 | 北京奇虎科技有限公司 | Performance fluctuation positioning method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10977147B2 (en) | System for continuous monitoring of data quality in a dynamic feed environment | |
| CN111049705B (en) | Method and device for monitoring distributed storage system | |
| US10904112B2 (en) | Automatic capture of detailed analysis information based on remote server analysis | |
| US11042525B2 (en) | Extracting and labeling custom information from log messages | |
| CN109471783B (en) | Method and device for predicting task operation parameters | |
| US8135666B2 (en) | Systems and methods for policy based execution of time critical data warehouse triggers | |
| CN112307057A (en) | Data processing method and device, electronic equipment and computer storage medium | |
| CN108492150B (en) | Method and system for determining entity heat degree | |
| CN114091704B (en) | Alarm suppression method and device | |
| CN114223189A (en) | Duration statistical method and device, electronic equipment and computer readable medium | |
| CN105471938B (en) | Server load management method and device | |
| CN106951360B (en) | Data statistical integrity calculation method and system | |
| CN115914064A (en) | Network system service performance evaluation method, device, computing equipment and storage medium | |
| CN113347201B (en) | Abnormality detection method, abnormality detection system and computing device | |
| CN112256548B (en) | Abnormal data monitoring method and device, server and storage medium | |
| CN112948223A (en) | Method and device for monitoring operation condition | |
| CN106557483B (en) | Data processing method, data query method, data processing equipment and data query equipment | |
| US20120054181A1 (en) | Online management of historical data for efficient reporting and analytics | |
| CN113342625A (en) | Data monitoring method and system | |
| CN110677271B (en) | Big data alarm method, device, equipment and storage medium based on ELK | |
| CN110633165B (en) | Fault processing method, device, system server and computer readable storage medium | |
| CN110795239A (en) | Application memory leakage detection method and device | |
| CN107357703B (en) | Terminal application power consumption detection method and server | |
| US11758021B2 (en) | System for processing coherent data | |
| CN109388546B (en) | Method, device and system for processing faults of application program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |