CN113407430A - Single index parameter acquisition method and device based on application performance monitoring - Google Patents
Single index parameter acquisition method and device based on application performance monitoring Download PDFInfo
- Publication number
- CN113407430A CN113407430A CN202110740513.6A CN202110740513A CN113407430A CN 113407430 A CN113407430 A CN 113407430A CN 202110740513 A CN202110740513 A CN 202110740513A CN 113407430 A CN113407430 A CN 113407430A
- Authority
- CN
- China
- Prior art keywords
- performance monitoring
- single index
- index parameter
- index
- middleware
- 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
- 238000012544 monitoring process Methods 0.000 title claims abstract description 168
- 238000000034 method Methods 0.000 title claims abstract description 51
- 230000002776 aggregation Effects 0.000 claims abstract description 62
- 238000004220 aggregation Methods 0.000 claims abstract description 62
- 238000004364 calculation method Methods 0.000 claims abstract description 52
- 238000004590 computer program Methods 0.000 claims description 12
- 230000005540 biological transmission Effects 0.000 claims description 2
- 238000004458 analytical method Methods 0.000 abstract description 13
- 230000009286 beneficial effect Effects 0.000 abstract description 5
- 238000004891 communication Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 238000013499 data model Methods 0.000 description 5
- 238000012935 Averaging Methods 0.000 description 4
- 230000008878 coupling Effects 0.000 description 4
- 238000010168 coupling process Methods 0.000 description 4
- 238000005859 coupling reaction Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000000750 progressive effect Effects 0.000 description 2
- 108010001267 Protein Subunits Proteins 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3466—Performance evaluation by tracing or monitoring
- G06F11/3476—Data logging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3051—Monitoring arrangements for monitoring the configuration of the computing system or of the computing system component, e.g. monitoring the presence of processing resources, peripherals, I/O links, software programs
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- General Physics & Mathematics (AREA)
- Computing Systems (AREA)
- Computer Hardware Design (AREA)
- Mathematical Physics (AREA)
- Debugging And Monitoring (AREA)
Abstract
The invention belongs to the technical field of big data, and provides a single index parameter acquisition method and a single index parameter acquisition device based on application performance monitoring, wherein the single index parameter acquisition method based on application performance monitoring comprises the following steps: acquiring performance monitoring single index parameters in a longitudinal acquisition mode; sending the performance monitoring single index parameter to a middleware; and performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware. The invention has the following beneficial effects: higher monitoring timeliness. The acquisition end reports certain indexes immediately without waiting for other indexes, real-time monitoring is realized, and monitoring timeliness is improved. And (4) flexible configuration. The acquisition frequency of different indexes of the acquisition end can be flexibly configured. And resources are saved. The analysis of the monitoring data is completely placed at the server side, only data acquisition logic exists in the application program, and the occupation of application program resources is reduced to the minimum.
Description
Technical Field
The application can be used in the technical field of big data, and particularly relates to a single index parameter acquisition method and device based on application performance monitoring.
Background
In the prior art, for the acquisition of monitoring data, a point-burying mode is usually adopted to weave the acquisition logic into an application program. For example, at the point of receipt and response of the transaction, the time consumed by the transaction can be obtained by subtracting the timestamp of receipt from the timestamp of response. For another example, the operation index is usually obtained at regular time, for example, key indexes (such as CPU, memory, IO condition, and the like of the system) for measuring the health condition of the operating system are collected every minute, and then the indexes are reported uniformly. After receiving the monitoring data, the monitoring system can process, aggregate and analyze the data, and then store the analysis result into a database for troubleshooting of operation and maintenance personnel.
The technical defects of the monitoring data acquisition method in the prior art are as follows: the acquisition of monitoring data is easily coupled. For example, for a transaction, it is usually necessary to wait until the transaction is finished before calculating the transaction elapsed time. And aiming at the index monitoring of the operating system, timing triggering is needed, one-time collection is completed and then the data set is assembled, and the data set is reported to a server side of the monitoring system for analysis. This presents several problems:
1. monitoring data coupling problems of different monitoring frequencies. For example, in the collection and reporting of various indexes of the operating system, once the data model of the reporting interface is well defined, the collection end can report the collected monitoring data. However, a flexible manner is sometimes required, for example, if the IO of the operating system network rarely goes wrong, the conventional scheme cannot be achieved by properly turning down the acquisition frequency.
2. The data aggregation analysis capability of the monitoring system is not utilized to the maximum extent. Monitoring data is reported uniformly, that is, the server of the monitoring system can process the data only when all the data are collected completely, which does not make the most use of the data aggregation analysis capability of the server (the data analysis capability of the monitoring system is usually very strong in the face of massive monitoring data). For example, the transaction time consumption does not need to be calculated at the acquisition end when the acquisition end waits for a response, and the transaction time consumption can be reported when the transaction starts and ends, and the server end calculates the transaction time consumption by using strong calculation power.
3. Wasting application resources. As described above, the monitoring data collection logic (i.e., the client) is usually embedded in the application program, and shares resources such as CPU and memory with the application process, and the batch report data occupies a certain resource. Such as the transaction time consuming calculations described above or some other pre-aggregation, would take up CPU computing resources if placed on the client. For example, the operation system indexes are collected at regular time, and the collected operation system indexes can only be temporarily stored in a memory because of the requirement of collecting and reporting, so that the storage resources of the application are occupied, and the more reasonable scheme has the better influence on the operation of the application program.
Disclosure of Invention
The invention can be used in the technical field of big data, and the application field of the single index parameter acquisition method and the single index parameter acquisition device based on application performance monitoring disclosed by the invention is not limited. The invention not only has the aggregation analysis capability in the prior art, but also can independently collect, report and analyze each index without depending on other indexes, and is very flexible.
In order to solve the technical problems, the invention provides the following technical scheme:
in a first aspect, the present invention provides a single index parameter acquisition method based on application performance monitoring, including:
acquiring performance monitoring single index parameters in a longitudinal acquisition mode;
sending the performance monitoring single index parameter to a middleware;
and performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
In an embodiment, the middleware is kafka middleware, and the sending the performance monitoring single index parameter to the middleware includes:
and sending the performance monitoring single index parameter to a topic table of the kafka middleware.
In an embodiment, the performing aggregation calculation on the performance monitoring single indicator parameter forwarded by the middleware includes:
subscribing the performance monitoring single index parameter from the topic table;
storing the performance monitoring single index parameter into a corresponding drive database according to the index type and the timestamp of the performance monitoring single index;
and performing aggregation calculation on the performance monitoring single index parameters by using the Druid database.
In an embodiment, the performing, by using the Druid database, aggregation calculation on the performance monitoring single index parameter includes:
and performing aggregation calculation on the performance monitoring single index parameters by using the Druid database according to the index name, the index type, the index acquisition frequency, the class of the index, the application of the index, the link ID of the index and the acquisition time.
In a second aspect, the present invention provides a single index parameter collecting device based on application performance monitoring, the device comprising:
the single index parameter acquisition module is used for acquiring performance monitoring single index parameters in a longitudinal acquisition mode;
the single index parameter sending module is used for sending the performance monitoring single index parameter to the middleware;
and the single index parameter aggregation calculation module is used for performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
In one embodiment, the single index parameter sending module includes:
and the single index parameter sending unit is used for sending the performance monitoring single index parameter to a topic table of the kafka middleware.
In one embodiment, the single index parameter aggregation calculation module includes:
a single index parameter subscription unit, configured to subscribe the performance monitoring single index parameter from the topic table;
the single index parameter storage unit is used for storing the performance monitoring single index parameters into a corresponding drive database according to the index types and the timestamps of the performance monitoring single indexes;
and the single index parameter aggregation calculation unit is used for performing aggregation calculation on the performance monitoring single index parameters by using the Druid database.
In one embodiment, the single index parameter aggregation calculation unit includes:
and the single index parameter aggregation operator unit is used for performing aggregation calculation on the performance monitoring single index parameters by using the Druid database according to the index name, the index type, the index acquisition frequency, the category to which the index belongs, the application to which the index belongs, the link ID to which the index belongs and the acquisition time.
In a third aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the single index parameter acquisition method based on application performance monitoring when executing the program.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of a single index parameter acquisition method based on application performance monitoring.
As can be seen from the above description, the embodiment of the present invention provides a single-index parameter acquisition method and apparatus based on application performance monitoring, where first, a performance monitoring single-index parameter is acquired in a longitudinal acquisition manner; then, sending the performance monitoring single index parameter to the middleware; and finally, performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware. Specifically, the invention has the following beneficial effects:
1. higher monitoring timeliness. The acquisition end reports certain indexes immediately without waiting for other indexes, real-time monitoring is realized, and monitoring timeliness is improved.
2. And (4) flexible configuration. The acquisition frequency of different indexes of the acquisition end can be flexibly configured.
3. And resources are saved. The analysis of the monitoring data is completely placed at the server side, only data acquisition logic exists in the application program, and the occupation of application program resources is reduced to the minimum.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a single index parameter acquisition method based on application performance monitoring according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating step 200 according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating step 300 according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating step 103 according to an embodiment of the present invention;
FIG. 5 is a schematic flow chart of a single-index parameter acquisition method based on application performance monitoring according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating a single index parameter collection method based on application performance monitoring in accordance with an embodiment of the present invention;
FIG. 7 is a block diagram of a single index parameter acquisition device based on application performance monitoring in an embodiment of the present invention;
FIG. 8 is a block diagram of a single index parameter sending module 20 according to an embodiment of the present invention;
FIG. 9 is a block diagram of a single index parameter aggregation calculation module 30 according to an embodiment of the present invention;
FIG. 10 is a block diagram of a single index parameter aggregation calculation unit 303 according to an embodiment of the present invention;
fig. 11 is a schematic structural diagram of an electronic device in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
It should be noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of this application and the above-described drawings, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
The embodiment of the invention provides a specific implementation mode of a single index parameter acquisition method based on application performance monitoring, and referring to fig. 1, the method specifically comprises the following contents:
step 100: and acquiring performance monitoring single index parameters in a longitudinal acquisition mode.
Specifically, the horizontal reporting in the prior art is changed into the longitudinal reporting. For example, jvm (Java virtual machine) monitoring, a conventional method needs a regular thread to collect jvm memory and gc conditions at intervals, and report them uniformly. In this mode, the data model of the report interface is a collection of various collected indexes, such as content usage of different generations (young generation, old generation, and permanent generation) in the heap memory, and the GC of different generations consumes time and GC times. Pictorially, these metrics are tiled horizontally across the interface, each metric being equal. Each index is reported independently, and is reported immediately as long as the index is collected, and the index is not paved in a certain interface for one-time reporting. Therefore, the data models of different indexes are consistent, including the index name, the index type, the index acquisition frequency, the class to which the index belongs, the application to which the index belongs, the link ID to which the index belongs, and the acquisition time.
Step 200: and sending the performance monitoring single index parameter to the middleware.
It is understood that middleware is a kind of software between application systems and system software, and it uses the basic service (function) provided by system software to connect different parts of application systems or different applications on the network, so as to achieve the purpose of resource sharing and function sharing. Currently, it is not strictly defined, but the definition of IDC is generally accepted: middleware is a separate system software service by which distributed application software shares resources between different technologies, resides on the operating system of the client server, manages computing resources and network communications. In this sense, middleware can be represented by an equation: middleware is platform + communication, which defines that middleware can only be called in a distributed system, and also distinguishes the middleware from supporting software and utility software.
Middleware is a type of computer software that connects software components and applications, and includes a set of services. Such that multiple pieces of software running on one or more machines interact over a network. The interoperability provided by this technology has driven the evolution of a consistent distributed architecture that is typically used to support and simplify those complex distributed applications, including web servers, transaction monitors, and message queue software. Middleware (middleware) is a large class of underlying software, and belongs to the field of reusable software. As the name implies, middleware is in the middle of the operating system software and the user's application software.
The middleware is arranged on an operating system, a network and a database and on the lower layer of the application software, and is generally used for providing an operation and development environment for the application software on the upper layer of the middleware, and helping a user to flexibly and efficiently develop and integrate the complex application software. Among the many definitions of middleware, the IDC expression is more commonly accepted: middleware is a separate system software or service by which distributed application software shares resources between different technologies, resides on the operating system of the client server, manages computing resources and network communications.
In recent years, more and more fields in human life have become irreconcilable with computers, network technologies, and communication technologies. And with the rapid development of computer technology, more application software is required to operate on many different network protocols, different hardware manufacturers, and different network platforms and environments. This results in the need for software developers to face data dispersion, operational difficulties, low system matching, and the need to develop multiple applications for operational purposes. Therefore, the generation of the middleware technology greatly reduces the burden of developers, so that the operation of the network is more efficient.
Step 300: and performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
An aggregation operation refers to calculating a value from a set of values (performing a custom aggregation operation on the values of the set). For example: merging, averaging, maximum and minimum
As can be seen from the above description, the embodiment of the present invention provides a single-index parameter acquisition method based on application performance monitoring, which first acquires a performance monitoring single-index parameter in a longitudinal acquisition manner; then, sending the performance monitoring single index parameter to the middleware; and finally, performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware. Specifically, the invention has the following beneficial effects:
1. higher monitoring timeliness. The acquisition end reports certain indexes immediately without waiting for other indexes, real-time monitoring is realized, and monitoring timeliness is improved.
2. And (4) flexible configuration. The acquisition frequency of different indexes of the acquisition end can be flexibly configured.
3. And resources are saved. The analysis of the monitoring data is completely placed at the server side, only data acquisition logic exists in the application program, and the occupation of application program resources is reduced to the minimum.
In one embodiment, the middleware is kafka middleware, and further, referring to fig. 2, step 200 includes:
step 201: and sending the performance monitoring single index parameter to a topic table of the kafka middleware.
The kafka message middleware is a high-throughput distributed publish-subscribe message system and is a distributed, partitioned and reliable distributed log storage service. The advantages are that: and a real-time stream data pipeline is constructed, and data between the system and the application program is reliably acquired. And constructing an application program of the real-time stream, and converting or reacting the data stream.
In one embodiment, referring to FIG. 3, step 300 comprises:
step 301: subscribing the performance monitoring single index parameter from the topic table;
step 302: storing the performance monitoring single index parameter into a corresponding drive database according to the index type and the timestamp of the performance monitoring single index;
step 303: and performing aggregation calculation on the performance monitoring single index parameters by using the Druid database.
In steps 301 to 303, specifically, the server receives the independently reported data through the message middleware, and stores the index into the corresponding database table according to the information such as the index type and the like for aggregation calculation. The Druid database is adopted, and is a high-performance aggregation analysis product, and aggregation calculation (such as summation, averaging, maximization and the like) can be realized by directly configuring in a table structure.
In one embodiment, referring to fig. 4, step 303 further comprises:
step 3031: and performing aggregation calculation on the performance monitoring single index parameters by using the Druid database according to the index name, the index type, the index acquisition frequency, the class of the index, the application of the index, the link ID of the index and the acquisition time.
It is understood that in the embodiment of the present invention, the message middleware may not use kafka, which is only an example, and other message middleware products may be used. The aggregated database may also be used without a Druid, such as fluxdb, clickhouse.
In a specific embodiment, the invention further takes jvm (Java virtual machine) monitoring as an example, and provides a specific embodiment of a single index parameter collection method based on application performance monitoring, specifically referring to fig. 5 and 6.
Description of terms:
monitoring application performance: the purpose of mastering the health condition of the system in real time is achieved by collecting, reporting and analyzing the applied performance monitoring data.
Step S1: acquiring performance monitoring single index parameters in a longitudinal acquisition mode;
the single-index reporting is adopted, and the aggregation calculation is carried out at the server side by using the drive database, so that the problem is solved technically by changing the original horizontal reporting into longitudinal reporting. For example, for monitoring jvm (Java virtual machine), a conventional method needs a timed thread to collect jvm memory and gc conditions at intervals, and report them uniformly. In this mode, the data model of the report interface is a collection of various collected indexes, such as content usage of different generations (young generation, old generation, and permanent generation) in the heap memory, and the GC of different generations consumes time and GC times. Pictorially, these metrics are tiled horizontally across the interface, each metric being equal.
In the specific implementation manner of the present invention, the collected single-index parameters for monitoring the application performance are changed to be reported longitudinally, that is, each index is reported independently, and is reported immediately as long as the index is collected, and is not spread in a certain interface for reporting once. Therefore, the data models of different indexes are consistent, including the index name, the index type, the index acquisition frequency, the class to which the index belongs, the application to which the index belongs, the link ID to which the index belongs, and the acquisition time.
Step S2: sending the performance monitoring single index parameter to a middleware;
the server side receives the independently reported data through the message middleware, and stores the indexes into the corresponding database table for aggregation calculation according to the information such as the index types. The Druid database is adopted, and is a high-performance aggregation analysis product, and aggregation calculation (such as summation, averaging, maximization and the like) can be realized by directly configuring in a table structure.
Step S3: and performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
For example, in the above example, the server confirms that a memory size index of a young generation in the heap memory is received according to the index type (the server needs to maintain a correspondence between an index and a database expression by an operation and maintenance worker), and then stores the index into the JVM memory information minute table according to the timestamp, where the table is a minute table (one minute automatic aggregation) in which an averaging operator is configured for the memory size column. Then the average memory size of the younger generation in one minute can be looked up directly from the Druid when the one minute is over. Therefore, the original aggregation analysis capability is provided, each index can be independently collected, reported and analyzed without depending on other indexes, and the method is very flexible.
As can be seen from the above description, the embodiment of the present invention provides a single-index parameter acquisition method based on application performance monitoring, which first acquires a performance monitoring single-index parameter in a longitudinal acquisition manner; then, sending the performance monitoring single index parameter to the middleware; and finally, performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware. Specifically, the invention has the following beneficial effects:
1. higher monitoring timeliness. The acquisition end reports certain indexes immediately without waiting for other indexes, real-time monitoring is realized, and monitoring timeliness is improved.
2. And (4) flexible configuration. The acquisition frequency of different indexes of the acquisition end can be flexibly configured.
3. And resources are saved. The analysis of the monitoring data is completely placed at the server side, only data acquisition logic exists in the application program, and the occupation of application program resources is reduced to the minimum.
Based on the same inventive concept, the embodiment of the present application further provides a single index parameter acquisition device based on application performance monitoring, which can be used to implement the method described in the above embodiment, such as the following embodiments. The principle of solving the problems of the single-index parameter acquisition device based on application performance monitoring is similar to that of the single-index parameter acquisition method based on application performance monitoring, so the implementation of the single-index parameter acquisition device based on application performance monitoring can refer to the implementation of the single-index parameter acquisition method based on application performance monitoring, and repeated parts are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. While the system described in the embodiments below is preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.
The embodiment of the present invention provides a specific implementation manner of a single index parameter acquisition device based on application performance monitoring, which is capable of implementing a single index parameter acquisition method based on application performance monitoring, and referring to fig. 7, the single index parameter acquisition device based on application performance monitoring specifically includes the following contents:
the single index parameter acquisition module 10 is used for acquiring performance monitoring single index parameters in a longitudinal acquisition mode;
a single index parameter sending module 20, configured to send the performance monitoring single index parameter to the middleware;
and a single index parameter aggregation calculation module 30, configured to perform aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
In one embodiment, referring to fig. 8, the single index parameter sending module 20 includes:
and the single index parameter sending unit 201 is configured to send the performance monitoring single index parameter to a topic table of the kafka middleware.
In one embodiment, referring to fig. 9, the single-index parameter aggregation calculation module 30 includes:
a single index parameter subscribing unit 301, configured to subscribe the performance monitoring single index parameter from the topic table;
a single index parameter storage unit 302, configured to store the performance monitoring single index parameter into a corresponding Druid database according to the index type and the timestamp of the performance monitoring single index;
and a single index parameter aggregation calculation unit 303, configured to perform aggregation calculation on the performance monitoring single index parameter by using the Druid database.
In an embodiment, referring to fig. 10, the single index parameter aggregation calculation unit 303 includes:
and a single index parameter aggregation calculation subunit 3031, configured to perform aggregation calculation on the performance monitoring single index parameter according to the index name, the index type, the index acquisition frequency, the category to which the index belongs, the application to which the index belongs, the link ID to which the index belongs, and the acquisition time, by using the draid database.
As can be seen from the above description, the embodiment of the present invention provides a single-index parameter acquisition device based on application performance monitoring, which first acquires a performance monitoring single-index parameter in a longitudinal acquisition manner; then, sending the performance monitoring single index parameter to the middleware; and finally, performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware. Specifically, the invention has the following beneficial effects:
1. higher monitoring timeliness. The acquisition end reports certain indexes immediately without waiting for other indexes, real-time monitoring is realized, and monitoring timeliness is improved.
2. And (4) flexible configuration. The acquisition frequency of different indexes of the acquisition end can be flexibly configured.
3. And resources are saved. The analysis of the monitoring data is completely placed at the server side, only data acquisition logic exists in the application program, and the occupation of application program resources is reduced to the minimum.
An embodiment of the present application further provides a specific implementation manner of an electronic device, which is capable of implementing all steps in the single index parameter acquisition method based on application performance monitoring in the foregoing embodiment, and referring to fig. 11, the electronic device specifically includes the following contents:
a processor (processor)1201, a memory (memory)1202, a communication Interface 1203, and a bus 1204;
the processor 1201, the memory 1202 and the communication interface 1203 complete communication with each other through the bus 1204; the communication interface 1203 is used for implementing information transmission between related devices such as server-side devices and client-side devices;
the processor 1201 is configured to invoke a computer program in the memory 1202, and when the processor executes the computer program, all steps in the single index parameter acquisition method based on application performance monitoring in the foregoing embodiment are implemented, for example, when the processor executes the computer program, the following steps are implemented:
step 100: acquiring performance monitoring single index parameters in a longitudinal acquisition mode;
step 200: sending the performance monitoring single index parameter to a middleware;
step 300: and performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
An embodiment of the present application further provides a computer-readable storage medium capable of implementing all steps in the single index parameter acquisition method based on application performance monitoring in the foregoing embodiment, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, implements all steps of the single index parameter acquisition method based on application performance monitoring in the foregoing embodiment, for example, when the processor executes the computer program, the following steps are implemented:
step 100: acquiring performance monitoring single index parameters in a longitudinal acquisition mode;
step 200: sending the performance monitoring single index parameter to a middleware;
step 300: and performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to the partial description of the method embodiment.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Although the present application provides method steps as in an embodiment or a flowchart, more or fewer steps may be included based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or client product executes, it may execute sequentially or in parallel (e.g., in the context of parallel processors or multi-threaded processing) according to the embodiments or methods shown in the figures.
For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the embodiments of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, and the like. The above-described embodiments of the apparatus 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.
Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may therefore be considered as a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
The embodiments of this specification may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The described embodiments may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
The above description is only an example of the embodiments of the present disclosure, and is not intended to limit the embodiments of the present disclosure. Various modifications and variations to the embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification should be included in the scope of the claims of the embodiments of the present specification.
Claims (10)
1. A single index parameter acquisition method based on application performance monitoring is characterized by comprising the following steps:
acquiring performance monitoring single index parameters in a longitudinal acquisition mode;
sending the performance monitoring single index parameter to a middleware;
and performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
2. The single index parameter collection method based on application performance monitoring of claim 1, wherein the middleware is kafka middleware, and the sending the performance monitoring single index parameter to the middleware comprises:
and sending the performance monitoring single index parameter to a topic table of the kafka middleware.
3. The single index parameter collection method based on application performance monitoring according to claim 2, wherein the performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware comprises:
subscribing the performance monitoring single index parameter from the topic table;
storing the performance monitoring single index parameter into a corresponding drive database according to the index type and the timestamp of the performance monitoring single index;
and performing aggregation calculation on the performance monitoring single index parameters by using the Druid database.
4. The method for single-index parameter collection based on application performance monitoring of claim 3, wherein the performing the aggregation calculation on the performance monitoring single-index parameters by using the Druid database comprises:
and performing aggregation calculation on the performance monitoring single index parameters by using the Druid database according to the index name, the index type, the index acquisition frequency, the class of the index, the application of the index, the link ID of the index and the acquisition time.
5. The utility model provides a single index parameter acquisition device based on application performance monitoring which characterized in that includes:
the single index parameter acquisition module is used for acquiring performance monitoring single index parameters in a longitudinal acquisition mode;
the single index parameter sending module is used for sending the performance monitoring single index parameter to the middleware;
and the single index parameter aggregation calculation module is used for performing aggregation calculation on the performance monitoring single index parameters forwarded by the middleware.
6. The single index parameter acquisition device based on application performance monitoring of claim 5, wherein the single index parameter transmission module comprises:
and the single index parameter sending unit is used for sending the performance monitoring single index parameter to a topic table of the kafka middleware.
7. The single index parameter collection device based on application performance monitoring of claim 6, wherein the single index parameter aggregation calculation module comprises:
a single index parameter subscription unit, configured to subscribe the performance monitoring single index parameter from the topic table;
the single index parameter storage unit is used for storing the performance monitoring single index parameters into a corresponding drive database according to the index types and the timestamps of the performance monitoring single indexes;
and the single index parameter aggregation calculation unit is used for performing aggregation calculation on the performance monitoring single index parameters by using the Druid database.
8. The single index parameter collection device based on application performance monitoring of claim 7, wherein the single index parameter aggregation calculation unit comprises:
and the single index parameter aggregation operator unit is used for performing aggregation calculation on the performance monitoring single index parameters by using the Druid database according to the index name, the index type, the index acquisition frequency, the category to which the index belongs, the application to which the index belongs, the link ID to which the index belongs and the acquisition time.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the single-index parameter collection method based on application performance monitoring of any one of claims 1 to 4 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for single-index parameter acquisition based on application performance monitoring of any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110740513.6A CN113407430A (en) | 2021-06-30 | 2021-06-30 | Single index parameter acquisition method and device based on application performance monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110740513.6A CN113407430A (en) | 2021-06-30 | 2021-06-30 | Single index parameter acquisition method and device based on application performance monitoring |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113407430A true CN113407430A (en) | 2021-09-17 |
Family
ID=77680756
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110740513.6A Pending CN113407430A (en) | 2021-06-30 | 2021-06-30 | Single index parameter acquisition method and device based on application performance monitoring |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113407430A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115914033A (en) * | 2022-11-24 | 2023-04-04 | 中兴系统技术有限公司 | Method and device for monitoring equipment information, electronic equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112433909A (en) * | 2020-11-03 | 2021-03-02 | 中国南方电网有限责任公司 | Processing method of real-time monitoring data based on kafka |
| CN112835765A (en) * | 2021-02-02 | 2021-05-25 | 中国工商银行股份有限公司 | Java program memory use condition monitoring method and device |
-
2021
- 2021-06-30 CN CN202110740513.6A patent/CN113407430A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112433909A (en) * | 2020-11-03 | 2021-03-02 | 中国南方电网有限责任公司 | Processing method of real-time monitoring data based on kafka |
| CN112835765A (en) * | 2021-02-02 | 2021-05-25 | 中国工商银行股份有限公司 | Java program memory use condition monitoring method and device |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115914033A (en) * | 2022-11-24 | 2023-04-04 | 中兴系统技术有限公司 | Method and device for monitoring equipment information, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102880503B (en) | Data analysis system and data analysis method | |
| CN1321368C (en) | Automatic data interpretation and implementation using performance capacity management framework over many servers | |
| US10116534B2 (en) | Systems and methods for WebSphere MQ performance metrics analysis | |
| EP2503733B1 (en) | Data collecting method, data collecting apparatus and network management device | |
| CN108733464B (en) | Method and device for determining scheduling scheme of computing task | |
| CN111026602A (en) | Health inspection scheduling management method and device of cloud platform and electronic equipment | |
| CN110147327B (en) | Multi-granularity-based web automatic test management method | |
| CN114090366A (en) | Method, device and system for monitoring data | |
| CN113806191A (en) | Data processing method, device, equipment and storage medium | |
| CN112000548A (en) | Big data component monitoring method and device and electronic equipment | |
| CN113407430A (en) | Single index parameter acquisition method and device based on application performance monitoring | |
| CN115080373A (en) | Performance detection method, device, equipment and medium of power distribution terminal operating system | |
| CN112883253A (en) | Data processing method, device, equipment and readable storage medium | |
| CN110928663A (en) | Cross-platform multithreading monitoring method and device | |
| CN110928750B (en) | Data processing method, device and equipment | |
| CN115712572A (en) | Task testing method and device, storage medium and electronic device | |
| Vogel et al. | High-level Stream Processing: A Complementary Analysis of Fault Recovery | |
| CN110928938B (en) | Interface middleware system | |
| CN114138720A (en) | Log processing method, log processing device, electronic device and storage medium | |
| Wang et al. | Model Construction and Data Management of Running Log in Supporting SaaS Software Performance Analysis. | |
| CN112363774A (en) | Storm real-time task configuration method and device | |
| CN102238022A (en) | Network management system and data acquisition method | |
| CN111556098A (en) | Artificial intelligence based analysis system and analysis method for internet of things data | |
| CN111159004A (en) | Hadoop cluster simulation test method and device and storage medium | |
| CN115203292B (en) | Data processing method, device and equipment for industrial equipment |
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 |