CN115277361A - Intelligent information system performance analysis method based on big data - Google Patents
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Abstract
The invention discloses an intelligent analysis method for information system performance based on big data, which comprises the following steps: s1, monitoring user perception by utilizing big data; s2, determining an application logic topology; s3, end-to-end monitoring and transaction tracking; s4, monitoring deep application components; s5, monitoring and analyzing network quality; s6, fault diagnosis; s7, generating a data report: and generating a data report according to the requirement. The analysis method has the advantages that authenticity, rapidness, diversity and multiple quantity of big data are fully utilized, intelligent analysis on system performance is achieved, fault probability is reduced, problem processing is shortened, user complaints are reduced, and application performance is improved.
Description
Technical Field
The invention relates to the technical field of information system analysis, in particular to an intelligent information system performance analysis method based on big data.
Background
With the rapid development of the IT technology, large-scale enterprises are increasingly expanded in informatization construction, the informatization degree and continuity requirements of related services are gradually improved, the operation and maintenance requirements of the IT system are higher and higher, the time window of the operation and maintenance of the system is smaller and smaller, and even key services present zero tolerance to major faults.
The application of large-scale domestic enterprises to enterprise informatization data analysis technology focuses more on research and exploration on business development, and the application in the aspect of system operation and maintenance is less. At present, most enterprises adopt a relatively-solidified information operation and maintenance strategy, an original operation and maintenance system based on personnel monitoring and manual processing is difficult to deal with dynamic changes of actual business of the enterprises on the aspects of accuracy and efficiency of judgment of system operation states due to the fact that the personal levels of operation and maintenance personnel are different and the intensity of monitoring different systems is lack of reasonable standard specifications, the problem of operation and maintenance resource waste exists due to high dependence on personnel, and meanwhile, no scientific and effective method is provided for early warning of system operation faults.
With the advent of the "big data" era, people's mining and application of massive data, which indicates the growth of new wave productivity and the arrival of surplus wave of consumers. The big data is used as a still large and subversive technical revolution in the IT industry after cloud computing and the Internet of things, and can be fully applied to various industries.
Disclosure of Invention
The invention aims to provide an intelligent information system performance analysis method based on big data, so as to achieve the purposes of reducing failure probability, shortening problem processing, reducing user complaints and improving application performance.
The invention achieves the above purpose through the following technical scheme:
an intelligent analysis method for performance of an information system based on big data comprises the following steps:
s1, user perception monitoring: monitoring the availability and performance state of the system in real time from the big data, and mastering the real perception of each regional user accessing the service system in real time;
s2, determining the application logic topology: determining the logic relationship among the application components, and automatically generating a service logic topological graph of each service system;
s3, end-to-end monitoring and transaction tracking: tracking end-to-end business transactions across application components and code level transactions;
s4, monitoring application components in a deep level: acquiring KPI indexes inside a big data server through an application probe, wherein a monitoring point comprises the execution efficiency of each code, and analyzing an application state;
s5, monitoring and analyzing network quality: monitoring each event occurring in the network in real time, and providing tracking and visualization functions;
s6, fault diagnosis: storing and indexing important fault field data, positioning the real reason of the fault, and informing operation and maintenance personnel;
s7, generating a data report: and generating a data report according to the requirement.
The further improvement is that the user perception monitoring comprises the monitoring client of the network part, the TCP connection establishment time of the big data server, the Payload data transmission time, the data packet retransmission time, and the application service response time of the monitoring application part.
In a further refinement, the applying a logical topology determination refers to: and collecting application data flow in a production environment by utilizing monitoring equipment, and automatically generating an application topology so as to discover the mutual access relation between the application hosts.
A further improvement is that tracking end-to-end business transactions across application components refers to: and monitoring the access state of the Web-AP-DB full-service flow based on the service logic architecture of the application, and monitoring the application response and the network communication state among all application components end to end.
A further improvement is that tracking code level transactions refers to: identifying specific method calls causing performance problems, and visualizing the running states of JSP, JDBC and servlet of business transactions; and performing memory analysis and real-time memory leak detection to identify the code level root cause of the memory leak.
In a further refinement, the application component monitoring further refers to: and monitoring and analyzing users in different channels and accessing performance states of different services through a plurality of angles.
The system is further improved in that during fault diagnosis, the monitoring equipment automatically discovers and identifies all URLs in the application from network flow, can carry out deep analysis on an HTTP protocol, and can monitor the running states of different URLs in real time, wherein the running states comprise the access times of pages, the response time of the pages, HTTP return codes, the number of slow pages and the information of browser statistics used by users.
The further improvement is that the self-customization range of the data report comprises an interface, a data source and a report format.
The invention has the beneficial effects that:
(1) Based on a big data technology, the performance change condition of the application is monitored from an application flow level, and the application performance problem which cannot be discovered by the traditional tool is discovered, so that an administrator can discover the potential performance hazard in the early stage of system performance reduction and deal with the problem in advance.
(2) By means of the fault alarm, fault tracing and fault analysis functions of the system, regression analysis can be performed on the found performance events, the root cause of the problem is judged by using flow data at the fault point, the fault point of the problem is defined, and favorable guarantee and evidence are provided for thoroughly solving the problem.
(3) By applying the flow topology analysis function, managers can know the flow relation and the port opening condition among a single complex system and a plurality of systems, so that the managers can master a service operation state table which is the same as the actual application operation environment, and effective data support is provided for daily management and problem positioning work.
(4) The application performance management system is utilized to find various performance problems and help managers to provide effective tool support in the work aspects of application daily monitoring, information system data acquisition, daily performance tuning, information system on-line detection and the like.
Drawings
FIG. 1 is a flow chart of the present invention.
FIG. 2 is a diagram of a typical deployment of the application components of the present invention.
Fig. 3 is a schematic diagram of a two-level general deployment system.
FIG. 4 is a schematic diagram of the present invention deployed with respect to the architecture of FIG. 3.
Detailed Description
The present application will now be described in further detail with reference to the drawings, it should be noted that the following detailed description is given for illustrative purposes only and is not to be construed as limiting the scope of the present application, as those skilled in the art will be able to make numerous insubstantial modifications and adaptations to the present application based on the above disclosure.
The invention relates to an Application Performance Management (APM) solution adopting a soft and hard integrated technical means, which focuses on deep comprehensive analysis and management of the application performance of an information system, quickly searches and positions the root cause of the problem, shortens the time consumption for problem processing, assists an enterprise information operation and maintenance department to master the operation state of the information system, solves various performance problems which are difficult to process in the work, and is divided into two steps:
first, the real needs of the application level user need to be known: the method can monitor the true satisfaction degree of users on each layer and each area, the business transaction state of each area, and the performance of various application systems, can quickly lock fault points influencing the business, and can provide report data based on the business transaction state.
Secondly, it is necessary to solve the application level user problem:
a. user perception monitoring: monitoring the real experience of each area user (such as whether the system is available or not and the response time of a business operating system);
b. monitoring business transaction: the method comprises the steps of penetrating into a Web application code layer, monitoring and counting the execution condition of the service of each application system in each area;
and (3) fault quick positioning: monitoring a complete service link, and quickly positioning fault points influencing the service in an end-to-end monitoring mode;
and (3) mastering the system state: through technical analysis such as structural analysis, flow analysis, connection analysis, code analysis and the like, the user is helped to comprehensively master the working state of the system.
The intelligent analysis method is described in detail below:
as shown in fig. 1, an intelligent analysis method for information system performance based on big data includes the steps:
s1, user perception monitoring: monitoring the availability and performance state of the system in real time from big data through the visual angle of a user, and mastering the real perception of the user accessing the service system in each area in real time;
s2, determining the application logic topology: determining the logic relationship among the application components, and automatically generating a service logic topological graph of each service system;
s3, end-to-end monitoring and transaction tracking: tracking end-to-end business transactions and code-level transactions of the cross-application component to realize historical data playback;
s4, monitoring application components in a deep level: acquiring KPI indexes inside a big data server through an application probe, wherein a monitoring point comprises the execution efficiency of each code, and analyzing an application state;
s5, monitoring and analyzing network quality: monitoring each event occurring in the network in real time, and providing tracking and visualization functions;
s6, fault diagnosis: storing and indexing important fault field data, positioning the real reason of the fault, and informing operation and maintenance personnel;
s7, generating a data report: and generating a data report according to the requirement.
The user perception monitoring comprises the TCP connection establishment time, payload data transmission time and data packet retransmission time of a monitoring client side and a big data server side of a network part, and also comprises the application service response time of a monitoring application part.
The application logic topology determination refers to: the monitoring equipment is utilized to collect the application data flow in the production environment, and the application topology is automatically generated, so that the application operation and maintenance personnel can be helped to quickly find the mutual access relation between the application hosts.
Tracking end-to-end business transactions across application components refers to: and monitoring the access state of the Web-AP-DB full-service flow based on the service logic architecture of the application, and monitoring the application response and the network communication state among all application components end to end.
Tracking transactions at the code level refers to: executing and tracking the application code, identifying specific method calls causing performance problems, and visualizing the running states of JSP, JDBC and servlet of business transaction; and performing memory analysis and real-time memory leak detection to identify the code level root cause of the memory leak.
The application component monitoring further refers to: and monitoring and analyzing users in different channels and accessing performance states of different services through a plurality of angles.
In network quality monitoring and analysis: the network quality state can be monitored in real time, specifically, the total network quality and the corresponding network bandwidth occupation condition, the network communication quality of each branch mechanism and the corresponding network delay condition are monitored, abnormal events are found in time, tracking and visualization functions are provided, and fault influence is reduced.
During fault diagnosis, the monitoring equipment automatically discovers and identifies all URLs in application from network flow, can carry out deep analysis on an HTTP (hyper text transport protocol), and monitors the running states of different URLs in real time, wherein the running states comprise the access times of pages, the response time of the pages, HTTP return codes, the number of slow pages and the information counted by browsers used by users; analyzing the fault source, namely penetrating into a single web page or trading and diagnosing the problem source; after the fault source is confirmed, the fault evidence is downloaded, the fault site is reserved, and operation and maintenance personnel are informed immediately.
The invention has the self-customizing capability of the data report, so that the report can be customized according to the service requirement, and the self-customizing range of the data report comprises an interface, a data source and a report format.
The application components formed by the scheme of the invention and the main application thereof are described as follows:
the user experience, network monitoring and analysis component adopts software and hardware integrated equipment for acquiring, storing and analyzing flow data;
the transaction performance analysis and prediction component adopts a software component and is used for deep unpacking analysis of the traffic data;
the centralized data collection monitoring component adopts software and hardware integrated equipment and is used for uniformly collecting and storing multi-node statistical data;
the system flow, the report and the display component adopt software components and are used for customizing reports, display interfaces and generating flow topology;
the flow aggregation component adopts software and hardware integrated equipment and is used for collecting, forwarding and filtering multi-source flow;
the application program monitoring and analyzing component adopts a software component for code performance analysis, code quality analysis and database execution quality analysis.
Example 1:
as shown in fig. 2: in a typical deployment, network traffic is mirrored-the communication quality of the network is monitored, analyzed; f5-based front-end flow monitoring and user real perception degree analysis; applying internal end-to-end flow-monitoring analysis and applying response between links and applying internal probes-method level code monitoring; therefore, the method can monitor the real satisfaction of each layer (each channel), each area user, each area business transaction state and the performance of each application system, can quickly lock fault points influencing the business, and can provide report data based on the business transaction state.
Example 2:
as shown in fig. 3: a user can not accurately judge where a fault point is located when accessing the secondary deployment system and the performance problem occurs; on the contrary, the performance problem occurs when the user accesses the first-level deployment system, the fault point is not in the headquarter server area, and the link from the branch organization to the headquarter has a problem, so that the judgment cannot be carried out.
As shown in fig. 4: on the basis of each application component in fig. 3, the system realizes refined end-to-end application performance monitoring above basic functions through a multi-level deployment architecture, solves the problem of incomplete application performance monitoring caused by single node deployment, simultaneously solves the performance monitoring problem of the multi-level deployment application system, and realizes deep-level application monitoring problems such as service deep-level component monitoring and code quality monitoring through code data acquisition plug-ins.
In summary, the present invention is an Application Performance Management (APM) solution using a soft and hard integration technique, which focuses on deep comprehensive analysis and management of the application performance of the information system, quickly finds and locates the root cause of the problem, shortens the time consumption for problem processing, assists the enterprise information operation and maintenance department in mastering the operation state of the information system, and solves various performance problems difficult to process in the work, and the application effects of the present invention are as follows:
in the aspect of monitoring the application performance of the information system, the performance change condition of the application is monitored from the application flow level, and the application performance problem which cannot be found by the traditional tool is found, so that an administrator can find the potential performance hazard in the early stage of the reduction of the system performance and deal with the problem in advance.
In the aspect of application performance analysis, by means of the functions of fault alarming, fault tracing and fault analysis of the system, regression analysis can be performed on the found performance events, the root cause of the problem is judged by using flow data at the fault point, the fault point of the problem is defined, and favorable guarantee and evidence are provided for thoroughly solving the problem.
In the aspect of data management of an information system, by applying a flow topology analysis function, a manager can know the flow relation and the port opening condition among a single complex system and a plurality of systems, so that the manager can master a service operation state table which is the same as the actual application operation environment, and effective data support is provided for daily management and problem location work.
In the process of schedule work matching, the application performance management system is utilized to find various performance problems, and management personnel are helped to provide effective tool support in the aspects of work such as application daily monitoring, information system data acquisition, daily performance tuning, information system on-line detection and the like.
The invention can help operation and maintenance personnel know and solve the following problems: quality of service of each application; real user experience in each area; whether the failure is caused by a web application or a client; which Java method has the longest response time during the failure; whether the network has abnormity (packet loss, time delay and retransmission); which parameters changed significantly during peak periods; what kind of association a servlet slowly associates with a database; which EJB method results in the most database activity; how the structure of the system is, whether the deployment is in accordance with the design and the like. Therefore, the effects of reducing the failure probability, shortening problem processing, reducing user complaints and improving application performance are achieved.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.
Claims (8)
1. An intelligent analysis method for information system performance based on big data is characterized in that: the method comprises the following steps:
s1, user perception monitoring: monitoring the availability and performance state of the system in real time from the big data, and mastering the real perception of each regional user accessing the service system in real time;
s2, determining the application logic topology: determining the logic relationship among the application components, and automatically generating a service logic topological graph of each service system;
s3, end-to-end monitoring and transaction tracking: tracking end-to-end business transactions across application components and code level transactions;
s4, monitoring application components in a deep level: acquiring KPI indexes inside a big data server through an application probe, wherein a monitoring point comprises the execution efficiency of each code, and analyzing an application state;
s5, monitoring and analyzing network quality: monitoring each event occurring in the network in real time, and providing tracking and visualization functions;
s6, fault diagnosis: storing and indexing important fault field data, positioning the real reason of the fault, and informing operation and maintenance personnel;
s7, generating a data report: and generating a data report according to the requirement.
2. The intelligent big data-based information system performance analysis method according to claim 1, wherein: the user perception monitoring comprises TCP connection establishment time, payload data transmission time and data packet retransmission time of a monitoring client side and a big data server side of a network part; also included is monitoring an application service response time of the application portion.
3. The intelligent big data-based information system performance analysis method according to claim 1, wherein: the application logic topology determination refers to: and collecting application data traffic in a production environment by using monitoring equipment, and automatically generating an application topology to discover the mutual access relation between the application hosts.
4. The intelligent big data-based information system performance analysis method according to claim 1, wherein: tracking end-to-end business transactions across application components refers to: and monitoring the access state of the Web-AP-DB full-service flow based on the service logic architecture of the application, and monitoring the application response and the network communication state among all application components end to end.
5. The intelligent big data-based information system performance analysis method according to claim 1, wherein: tracking transactions at the code level refers to: identifying specific method calls causing performance problems, and visualizing the running states of JSP, JDBC and servlet of business transactions; and performing memory analysis and real-time memory leak detection to identify the code level root cause of the memory leak.
6. The intelligent big data-based information system performance analysis method according to claim 1, wherein: the application component monitoring further refers to: and monitoring and analyzing users in different channels and accessing performance states of different services through a plurality of angles.
7. The intelligent big data-based information system performance analysis method according to claim 1, wherein: during fault diagnosis, the monitoring equipment automatically discovers and identifies all URLs in the application from network flow, can carry out deep analysis on the HTTP protocol, and monitors the running states of different URLs in real time, wherein the running states comprise the access times of pages, the response time of the pages, HTTP return codes, the number of slow pages and the information of browser statistics used by users.
8. The intelligent big data-based information system performance analysis method according to claim 1, wherein: the self-customization range of the data report comprises an interface, a data source and a report format.
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