CN112100047A - Service performance monitoring and analyzing method and device - Google Patents
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Abstract
The embodiment of the application discloses a service performance monitoring and analyzing method and a service performance monitoring and analyzing device, which are used for providing data basis for problem location of service performance, service performance monitoring, service performance optimization and business rule optimization. The method comprises the following steps: data slicing is carried out on the service logic of the open service, and a log function is called at the slicing position, so that the open service generates a performance log in the running process; collecting performance logs at regular time, and sorting the performance logs into log analysis files according to time, name and dimension of log category, wherein the log analysis files comprise performance files and business process files; taking the log analysis file as a data source, carrying out multi-dimensional analysis on the data source, and obtaining performance data, wherein the performance data comprises a service process tree of an Application Programming Interface (API), the overall performance condition of the API, the service performance condition of the API, the time-consuming interval distribution condition of the API, the abnormal transaction detail condition of the API and the time-consuming condition of a single flow service process of the API.
Description
Technical Field
The embodiment of the application relates to the field of data analysis, in particular to a service performance monitoring and analyzing method and device.
Background
In the mobile internet era, the life and working modes of people are changing, and as the applications of internet, cloud computing and mobile become more and more popular, more and more Application services are packaged into a series of Application Programming Interfaces (APIs) and issued to users. The aggregation and the opening of the API capability are necessary measures for integrating an industrial chain, and the opened API service becomes an important way for enterprises to open own business and merge and develop with partners and users, so that the difference of the application interface data service performance directly relates to the business operation quality.
The good customer experience after the API capability is opened depends on the high efficiency and high availability of the API, the performance is always an important index for measuring a software system, the use experience of a user is directly influenced, only the macroscopic backlog condition of the API can be analyzed in the rough management mode of the current API, and the total efficiency, the business process and the efficiency of each business process of the API cannot be obtained.
Disclosure of Invention
The embodiment of the application provides a service performance monitoring and analyzing method and device. The performance data is obtained by performing multi-dimensional analysis on the performance log, and data basis is provided for problem location of service performance, service performance monitoring, optimization of service performance and optimization of service rules.
In order to achieve the above object, a first aspect of the embodiments of the present application provides a service performance monitoring analysis method, including:
data slicing is carried out on the service logic of the open service, and a log function is called at the slicing position, so that a performance log is generated by the open service in the running process;
collecting the performance logs at regular time, and sorting the performance logs into different log analysis files according to the dimensions of time, name and log category, wherein the log analysis files comprise performance files and business process files;
and taking the log analysis file as a data source, carrying out multi-dimensional analysis on the data source, and acquiring performance data, wherein the performance data comprises a service process tree of an Application Programming Interface (API), the total performance condition of the API, the service performance condition of the API, the time consumption interval distribution condition of the API, the abnormal transaction detail condition of the API and the time consumption condition of a single flow service process of the API.
Optionally, the performing multidimensional analysis on the data source includes:
analyzing the overall performance condition of the API, the service performance condition of the API, the time-consuming interval distribution condition of the API performance and the abnormal transaction detail condition of the API according to the performance file;
and analyzing the service process tree of the API and the time consumption situation of the single flow service process of the API according to the service process file.
Optionally, the analyzing the overall performance condition of the API includes:
traffic volume, maximum time consumption, and average time consumption of the API are analyzed.
Optionally, the time-consuming situation of the single-stroke pipeline business process of the API analysis includes:
performing tree display on the time consumption situation of the single flow business process according to the business process number, wherein the time consumption situation comprises the business process name, the starting timestamp, the time consumption and the time consumption ratio of the single flow business process;
marking the single-stroke pipeline business process ranked 5 top in time consumption by using different ground colors;
and flashing and warning the single-stroke pipeline business process which takes more than 500 milliseconds.
Optionally, the collecting the performance log at regular time includes:
and periodically collecting the performance logs generated by the API deployed on all the middleware through a log storage service.
A second aspect of the embodiments of the present application provides a service performance monitoring and analyzing apparatus, including:
the logic processing unit is used for carrying out data slicing on the service logic of the open service and calling a log function at the slicing position so that the open service generates a performance log in the running process;
the log collection unit is used for collecting the performance logs at regular time and sorting the performance logs into log analysis files according to the time, the name and the dimension of the log category, wherein the log analysis files comprise a performance file and a service process file;
and the performance analysis unit is used for taking the log analysis file as a data source, carrying out multi-dimensional analysis on the data source and obtaining performance data, wherein the performance data comprises a service process tree of an Application Programming Interface (API), the overall performance condition of the API, the service performance condition of the API, the time-consuming interval distribution condition of the API, the abnormal transaction detail condition of the API and the time-consuming condition of a single flow service process of the API.
Optionally, the performance analysis unit includes:
the business process tree analysis module is used for analyzing a business process tree of an Application Programming Interface (API) according to the business process file;
the overall performance analysis module is used for analyzing the overall performance condition of the API according to the performance file;
the service performance analysis module is used for analyzing the service performance condition of the API according to the performance file;
the performance time-consuming analysis module is used for analyzing the performance time-consuming interval distribution condition of the API according to the performance file;
the abnormal transaction flow detail analysis module is used for analyzing the abnormal transaction flow detail condition of the API according to the performance file;
and the single-stroke flow business process analysis module is used for analyzing the time consumption situation of the single-stroke flow business process of the API according to the business process file.
Optionally, the overall performance condition of the API includes a traffic volume, a maximum consumed time, and an average consumed time of the API, and the overall performance analysis module is configured to analyze the traffic volume, the maximum consumed time, and the average consumed time of the API.
Optionally, the time consumption condition of the single pipeline business process of the API includes a business process name, a start timestamp, time consumption and a time consumption ratio of the single pipeline business process, the single pipeline business process analysis module is configured to display the time consumption condition of the single pipeline business process through a tree diagram, mark the single pipeline business process with different ground colors 5 before the time consumption ranking, and flash and warn the single pipeline business process with the time consumption greater than 500 milliseconds.
Optionally, the log collection unit is configured to collect, at regular time, performance logs generated by APIs deployed on all the middleware through a log storage service.
A third aspect of the embodiments of the present application provides a service performance monitoring and analyzing apparatus, including:
the device comprises a processor, a memory, an input and output unit and a bus;
the processor is connected with the memory, the input and output unit and the bus;
the processor specifically performs the following operations:
data slicing is carried out on the service logic of the open service, and a log function is called at the slicing position, so that a performance log is generated by the open service in the running process;
collecting the performance logs at regular time, and sorting the performance logs into different log analysis files according to the dimensions of time, name and log category, wherein the log analysis files comprise performance files and business process files;
and taking the log analysis file as a data source, carrying out multi-dimensional analysis on the data source, and acquiring performance data, wherein the performance data comprises a service process tree of an Application Programming Interface (API), the total performance condition of the API, the service performance condition of the API, the time consumption interval distribution condition of the API, the abnormal transaction detail condition of the API and the time consumption condition of a single flow service process of the API.
Optionally, the processor is further configured to perform the method of the first aspect and the alternatives of the first aspect.
The fourth aspect of the embodiment of the present application further provides a computer-readable storage medium, where a program is stored on the computer-readable storage medium, and after the program runs, the program controls the processor to execute the foregoing service performance monitoring and analyzing method.
In the technical scheme, the performance of the API is analyzed through different dimensions such as the service process tree of the API, the overall performance condition of the API, the service performance condition of the API, the time-consuming interval distribution condition of the API, the abnormal transaction detail condition of the API, the time-consuming condition of the single pipeline service process of the API and the like, the running condition of the API is obtained, and a data basis is provided for the performance optimization of the capability opening service.
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Fig. 1 is a schematic flow chart illustrating an embodiment of a service performance monitoring and analyzing method according to the present application;
fig. 2 is a schematic flow chart illustrating another embodiment of a service performance monitoring and analyzing method according to the present application;
fig. 3 is a schematic structural diagram of an embodiment of a service performance monitoring and analyzing apparatus according to the present application;
fig. 4 is a schematic structural diagram of another embodiment of a service performance monitoring and analyzing apparatus in the present application.
Detailed Description
The embodiment of the application provides a service performance monitoring and analyzing method and device. The performance data is obtained by performing multi-dimensional analysis on the performance log, and data basis is provided for problem location of service performance, service performance monitoring, optimization of service performance and optimization of service rules.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. The following describes a method and an apparatus for implementing performance monitoring of a mobile terminal specifically:
referring to fig. 1, an embodiment of a service performance monitoring and analyzing method in the present application includes:
101. data slicing is carried out on the service logic of the open service, and a log function is called at the slicing position, so that a performance log is generated by the open service in the running process;
it should be noted that the service opening management and control capability of the open service supports the developer to invoke the opened data service and also supports the developer to open the data service developed by the developer to others to invoke through the platform, thereby implementing the co-construction and sharing of the large data service opening.
Specifically, each API request corresponds to an access record, and the contents include the caller IP, the URL of the request, the response delay, the return status code, the number of bytes requested and responded, and other important information, which can facilitate the user to know the operating status of the service. Based on the calling relationship among the API components of the open service, the data segmentation is carried out on the business logic codes of the related open service, and the packaged log function is called at the slicing position, so that the position of the program with problems is conveniently and accurately positioned. The parameters of the log function include API identification of the API interface, so that the open service records and generates a performance log reflecting the relevant system performance information at runtime, for example, cpu occupancy, transaction response time, physical memory usage, throughput, etc., and records in the form of numerical values.
102. Collecting the performance logs at regular time, and sorting the performance logs into log analysis files according to the time, the name and the dimension of the log category, wherein the log analysis files comprise a performance file and a service process file;
specifically, all performance logs generated during the operation of the open service deployed on the middleware are collected at regular time, and the performance logs are sorted into a performance file and a business process file according to the time, the name and the dimension of the log category.
103. And taking the log analysis file as a data source, carrying out multi-dimensional analysis on the data source, and acquiring performance data.
Since the analysis of the information in the log analysis file is obtained by comparing the log analysis file with the script file and counting the related or similar information, the preliminarily obtained log analysis file needs to be converted into a log analysis file with a uniform format. And analyzing the log analysis file to obtain performance data, wherein the performance data comprises a service process tree of the API, the overall performance condition of the API, the service performance condition of the API, the performance time-consuming interval distribution condition of the API, the abnormal transaction detail condition of the API and the time-consuming condition of the single flow service process of the API.
Referring to fig. 2, another embodiment of a service performance monitoring and analyzing method in the present application includes:
201. data slicing is carried out on the service logic of the open service, and a log function is called at the slicing position, so that a performance log is generated by the open service in the running process;
step 201 in this embodiment is similar to step 101 in the previous embodiment, and is not described herein again.
202. The method comprises the steps that performance logs issued by APIs deployed on all middleware are collected at regular time through log storage service, and the performance logs are sorted into log analysis files according to time, names and dimensions of log categories, wherein the log analysis files comprise performance files and business process files;
specifically, all performance logs generated during the operation of the open service deployed on the middleware are collected at regular time through a log file storage service, and the performance logs are sorted into a performance file and a business process file according to the time, the name and the dimension of the log category through a log file management service.
203. Taking the log analysis file as a data source, and analyzing a business process tree of the API according to the business process file;
specifically, according to the business process file, the whole process information in an API access request is analyzed, and a function interface called in the process is represented by a tree diagram.
204. Analyzing the service volume, the maximum time consumption and the average time consumption of the API according to the performance file;
specifically, for a service, the traffic is to analyze the number of its user concurrencies, record the time consumed from the time when the user sends an access request to the time when the user receives a response, and calculate the maximum time consumption and the average time consumption, so as to know the basic response time of the service.
205. Analyzing the service performance condition of the API according to the performance file;
specifically, the service time consumption ratio is analyzed according to the service number, the service name, the time consumption ratio and the average time consumption.
206. Analyzing the performance time-consuming interval distribution condition of the API according to the performance file;
specifically, the performance time consumption situation of the service is divided according to the interval range, and the time consumption ratio of the service performance in each interval range is analyzed.
207. Analyzing the abnormal transaction flow detail condition of the API according to the performance file;
specifically, for abnormal transaction business, the starting time, the ending time, the total consumed time, the called middleware name and the middleware user of each service processing abnormal transaction are recorded.
208. Analyzing the time consumption situation of the single-stroke flow business process of the API according to the business process file;
specifically, according to the business process file, the business process number, the start timestamp, the time consumption and the time consumption ratio of the single stream business process are recorded, and the business process number, the start timestamp, the time consumption and the time consumption ratio can be displayed through a tree diagram. Sequencing the time consumed by the business processes in the service process from at least one time, marking and prompting the business processes with the time consumed ranking in the top five by using different ground colors, and flashing and warning the business processes with the time consumed more than 500 milliseconds.
Referring to fig. 3, an embodiment of a service performance monitoring and analyzing apparatus in the present application includes:
a logic processing unit 301, configured to perform data slicing on a service logic of an open service, and call a log function at the slice, so that a performance log is generated in an operating process of the open service;
the log collection unit 302 is configured to collect the performance logs at regular time, and sort the performance logs into different log analysis files according to the time, the name, and the dimension of the log category, where the log analysis files include a performance file and a service process file;
and the performance analysis unit 303 is configured to perform multidimensional analysis on the data source by using the log analysis file as a data source, and obtain performance data, where the performance data includes a service process tree of an application programming interface API, a total performance condition of the API, a service performance condition of the API, a performance time-consuming interval distribution condition of the API, an abnormal transaction detail condition of the API, and a time-consuming condition of a single flow service process of the API.
The performance analysis unit 303 includes:
a business process tree analysis module 3031, configured to analyze a business process tree of the API according to the business process file;
the overall performance analysis module 3032 is used for analyzing the overall performance condition of the API according to the performance file;
a service performance analysis module 3033, configured to analyze a service performance condition of the API according to the performance file;
a performance time-consuming analysis module 3034, configured to analyze a performance time-consuming interval distribution condition of the API according to the performance file;
an abnormal transaction flow detail analysis module 3035, configured to analyze an abnormal transaction flow detail condition of the API according to the performance file;
and the single-stroke pipeline business process analysis module 3036 is configured to analyze a time consumption situation of the single-stroke pipeline business process of the API according to the business process file.
The overall performance condition of the API includes a traffic volume, a maximum time consumption, and an average time consumption of the API, and the overall performance analysis module 3032 is configured to analyze the traffic volume, the maximum time consumption, and the average time consumption of the API.
The time consumption situation of the single pipeline business process of the API includes a business process name, a start timestamp, time consumption and a time consumption ratio of the single pipeline business process, the single pipeline business process analysis module 3036 is configured to display the time consumption situation of the single pipeline business process through a tree diagram, label the single pipeline business process 5 before the time consumption ranking with different ground colors, and perform a flash warning on the single pipeline business process with the time consumption more than 500 milliseconds.
The log collection unit 302 is configured to collect, at regular time, performance logs generated by APIs deployed on all middleware through a log storage service.
In this embodiment, the functions of each unit and each module correspond to the steps in the embodiment shown in fig. 2, and are not described herein again.
Referring to fig. 4, an embodiment of the present application provides a service performance monitoring and analyzing apparatus, including:
a processor 401, a memory 402, an input-output unit 403, a bus 404;
the processor 401 is connected to the memory 402, the input/output unit 403 and the bus 404;
the processor 401 specifically executes the following operations:
data slicing is carried out on the service logic of the open service, and a log function is called at the slicing position, so that a performance log is generated by the open service in the running process;
collecting the performance logs at regular time, and sorting the performance logs into log analysis files according to the time, the name and the dimension of the log category, wherein the log analysis files comprise performance files and business process files;
and taking the log analysis file as a data source, carrying out multi-dimensional analysis on the data source, and acquiring performance data, wherein the performance data comprises a service process tree of an Application Programming Interface (API), the total performance condition of the API, the service performance condition of the API, the time consumption interval distribution condition of the API, the abnormal transaction detail condition of the API and the time consumption condition of a single flow service process of the API.
In this embodiment, the functions of the processor 401 correspond to the steps in the embodiments shown in fig. 1 to fig. 2, and are not described herein again.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like.
Claims (10)
1. A method for monitoring and analyzing service performance, the method comprising:
data slicing is carried out on the service logic of the open service, and a log function is called at the slicing position, so that a performance log is generated by the open service in the running process;
collecting the performance logs at regular time, and sorting the performance logs into log analysis files according to the time, the name and the dimension of the log category, wherein the log analysis files comprise performance files and business process files;
and taking the log analysis file as a data source, carrying out multi-dimensional analysis on the data source, and acquiring performance data, wherein the performance data comprises a service process tree of an Application Programming Interface (API), the total performance condition of the API, the service performance condition of the API, the time consumption interval distribution condition of the API, the abnormal transaction detail condition of the API and the time consumption condition of a single flow service process of the API.
2. The service performance monitoring analysis method of claim 1, wherein the performing multidimensional analysis on the data source comprises:
analyzing the overall performance condition of the API, the service performance condition of the API, the time-consuming interval distribution condition of the API performance and the abnormal transaction detail condition of the API according to the performance file;
and analyzing the service process tree of the API and the time consumption situation of the single flow service process of the API according to the service process file.
3. The service performance monitoring analysis method of claim 2, wherein analyzing the overall performance of the API comprises:
traffic volume, maximum time consumption, and average time consumption of the API are analyzed.
4. The service performance monitoring analysis method of claim 2, wherein analyzing the time-consuming behavior of the single-stroke pipeline business process of the API comprises:
performing tree display on the time consumption situation of the single flow business process according to the business process number, wherein the time consumption situation comprises the business process name, the starting timestamp, the time consumption and the time consumption ratio of the single flow business process;
marking the single-stroke pipeline business process ranked 5 top in time consumption by using different ground colors;
and flashing and warning the single-stroke pipeline business process which takes more than 500 milliseconds.
5. The service performance monitoring analysis method of any of claims 1 to 4, wherein the periodically collecting the performance logs comprises:
and periodically collecting the performance logs generated by the API deployed on all the middleware through a log storage service.
6. A service performance monitoring and analysis apparatus, the apparatus comprising:
the logic processing unit is used for carrying out data slicing on the service logic of the open service and calling a log function at the slicing position so that the open service generates a performance log in the running process;
the log collection unit is used for collecting the performance logs at regular time and sorting the performance logs into log analysis files according to the time, the name and the dimension of the log category, wherein the log analysis files comprise a performance file and a service process file;
and the performance analysis unit is used for taking the log analysis file as a data source, carrying out multi-dimensional analysis on the data source and obtaining performance data, wherein the performance data comprises a service process tree of an Application Programming Interface (API), the overall performance condition of the API, the service performance condition of the API, the time-consuming interval distribution condition of the API, the abnormal transaction detail condition of the API and the time-consuming condition of a single flow service process of the API.
7. The service performance monitoring and analyzing apparatus of claim 6, wherein the performance analyzing unit comprises:
the business process tree analysis module is used for analyzing a business process tree of an Application Programming Interface (API) according to the business process file;
the overall performance analysis module is used for analyzing the overall performance condition of the API according to the performance file;
the service performance analysis module is used for analyzing the service performance condition of the API according to the performance file;
the performance time-consuming analysis module is used for analyzing the performance time-consuming interval distribution condition of the API according to the performance file;
the abnormal transaction flow detail analysis module is used for analyzing the abnormal transaction flow detail condition of the API according to the performance file;
and the single-stroke flow business process analysis module is used for analyzing the time consumption situation of the single-stroke flow business process of the API according to the business process file.
8. The service performance monitoring and analyzing apparatus of claim 7, wherein the overall performance of the API includes a traffic volume, a maximum consumed time, and an average consumed time of the API, and the overall performance analyzing module is configured to analyze the traffic volume, the maximum consumed time, and the average consumed time of the API.
9. The service performance monitoring and analyzing apparatus according to claim 7, wherein the time consumption status of the single pipeline business process of the API includes a business process name, a start timestamp, a time consumption and a time consumption ratio of the single pipeline business process, the single pipeline business process analyzing module is configured to display the time consumption status of the single pipeline business process through a tree diagram, label the single pipeline business process ranked 5 before the time consumption with different ground colors, and flash and warn the single pipeline business process with the time consumption more than 500 milliseconds.
10. The service performance monitoring and analyzing apparatus according to any one of claims 6 to 9, wherein the log collection unit is configured to collect, at regular time, the performance logs generated by APIs deployed on all the middleware through a log storage service.
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| CN107168844A (en) * | 2016-03-07 | 2017-09-15 | 中国移动通信集团河南有限公司 | A kind of method and device of performance monitoring |
| CN109756364A (en) * | 2018-12-07 | 2019-05-14 | 成都四方伟业软件股份有限公司 | A kind of micro services performance optimization system and analysis method based on log analysis |
| CN111221702A (en) * | 2019-11-18 | 2020-06-02 | 上海维谛信息科技有限公司 | Exception handling method, system, terminal and medium based on log analysis |
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| CN116643909A (en) * | 2023-07-27 | 2023-08-25 | 北京仁科互动网络技术有限公司 | Business performance analysis method and device based on SaaS mode CRM system |
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