CN115292149A - Method and device for monitoring performance gradual-difference request based on ELK platform - Google Patents

Method and device for monitoring performance gradual-difference request based on ELK platform Download PDF

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CN115292149A
CN115292149A CN202210945790.5A CN202210945790A CN115292149A CN 115292149 A CN115292149 A CN 115292149A CN 202210945790 A CN202210945790 A CN 202210945790A CN 115292149 A CN115292149 A CN 115292149A
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request
count
difference value
sequence
monitoring
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张红侠
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Bank of China Ltd
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Bank of China Ltd
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    • 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
    • G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
    • G06F11/3072—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting
    • G06F11/3082—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data filtering, e.g. pattern matching, time or event triggered, adaptive or policy-based reporting the data filtering being achieved by aggregating or compressing the monitored data

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  • Theoretical Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Debugging And Monitoring (AREA)

Abstract

The invention provides a method and a device for monitoring a performance gradual-degradation request based on an ELK platform, which relate to the technical field of computers, and the method comprises the following steps: the method comprises the steps that IIS logs are used for collecting request text data of each request of a website server; sending the request text data to a LogStash and an ElasticSearch for analysis and retrieval to obtain request analysis data, wherein the request analysis data comprises request initiating time and request response time; analyzing data according to the request, and acquiring a cycle sequence difference value sequence of response time by using serial _ diff; and filtering out the requests with gradually poor performance according to the cycle sequence difference value sequence of the response time. The application can directly obtain the request of gradual performance deterioration along with time.

Description

Method and device for monitoring performance gradual-difference request based on ELK platform
Technical Field
The invention relates to the technical field of computers, can be used in the financial field, and particularly relates to a method and a device for monitoring a performance gradual-degradation request based on an ELK platform.
Background
When the operation and maintenance monitoring is performed on the service system, besides the resources of the system, such as a Central Processing Unit (CPU), a memory, an access amount, and the like, need to be monitored, the response time of the request is also monitored to observe whether the request response speed is abnormal. The conventional request response time monitoring is generally all request monitoring or monitoring by filtering out requests according to request keywords. Such monitoring cannot filter out requests whose performance gradually deteriorates over time, and in actual use, such requests often need to be specially monitored, so that the prior art can only manually reprocess various requests, which increases the cost, is complicated in process, and is easy to miss and make mistakes.
Disclosure of Invention
In view of the above, the present invention provides a method and an apparatus for monitoring a performance degradation request based on an ELK platform, so as to solve at least one of the above-mentioned problems.
In order to achieve the purpose, the invention adopts the following scheme:
according to a first aspect of the present invention, there is provided a method for monitoring a performance degradation request based on an ELK platform, the method comprising: acquiring request text data of each request of a website server by using an Internet Information Service (IIS) log; sending the request text data to a LogStash plug-in and an ElasticSearch plug-in for analysis and retrieval to obtain request analysis data, wherein the request analysis data comprises request initiating time and request response time; analyzing data according to the request, and acquiring a cycle sequence difference value sequence of response time by using serial _ diff; and filtering out the requests with gradually poor performance according to the cycle sequence difference value sequence of the response time.
According to a second aspect of the present invention, there is provided an ELK platform based performance degradation request monitoring apparatus, the apparatus comprising: the system comprises a text acquisition unit, a data processing unit and a data processing unit, wherein the text acquisition unit is used for acquiring request text data of each request of a website server by using an IIS log; the analysis retrieval unit is used for sending the request text data to a LogStash plug-in and an ElasticSearch plug-in for analysis retrieval to obtain request analysis data, and the request analysis data comprises request initiating time and request response time; a sequence obtaining unit, configured to analyze data according to the request, and obtain a cycle sequence difference sequence of response time by using serial _ diff; and the request filtering unit is used for filtering out the requests with gradually poor performance according to the cycle sequence difference value sequence of the response time.
According to a third aspect of the present invention, there is provided an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the above method when executing the computer program.
According to a fourth aspect of the invention, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
According to a fifth aspect of the invention, there is provided a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the above method.
According to the technical scheme, the IIS log is analyzed and retrieved through the ELK platform, the request that the performance gradually becomes worse along with the time is filtered out through the obtained periodic sequence difference sequence of the response time, and therefore the problem that the request that the performance gradually becomes worse along with the time cannot be directly obtained in the prior art is solved.
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 embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts. In the drawings:
fig. 1 is a schematic flowchart of a monitoring method for performance degradation requests based on an ELK platform according to an embodiment of the present disclosure;
FIG. 2 is a schematic flowchart illustrating a monitoring method for performance degradation request based on ELK platform according to another embodiment of the present application;
fig. 3 is a schematic flowchart illustrating a process of using a Kibana plug-in to perform a graphical display request for parsing data according to an embodiment of the present application;
FIG. 4 is a schematic illustration of a graphical display of the Kibana plug-in without increasing word aggregation;
FIG. 5 is a schematic diagram of the graphical display of the Kibana plug-in when adding word aggregation;
FIG. 6 is a block diagram illustrating a monitoring system based on an ELK platform performance degradation request provided herein;
fig. 7 is a schematic structural diagram of a monitoring apparatus based on an ELK platform performance degradation request according to an embodiment of the present disclosure;
FIG. 8 is a schematic structural diagram of a monitoring apparatus for performance degradation request based on an ELK platform according to another embodiment of the present application;
fig. 9 is a schematic diagram of an electronic device provided in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
The following first presents some technical terms related to the present application in a simplified form:
the term "ELK platform": ELK is an abbreviation for three open source software, representing: elasticsearch, logstack, kibana, all of which are open source software. The Elasticissearch is an open source distributed search engine and provides three functions of collecting, analyzing and storing data. The Logstash is mainly used for collecting, analyzing and filtering logs and supports a large number of data acquisition modes. Kibana is also an open source and free tool, and Kibana can provide a log analysis friendly Web interface for Logstash and ElasticSearch to help summarize, analyze and search important data logs.
Fig. 1 is a schematic flow chart of a monitoring method for performance degradation request based on an ELK platform according to an embodiment of the present disclosure, where the method includes the following steps:
step S101: and acquiring request text data of each request of the website server by using the IIS log.
Since the service system also monitors the request during operation and maintenance monitoring, the IIS log of the website server also records detailed data of the request, such as a Uniform Resource Locator (URL) address of the request, request response time, request initiation time, request processing result, and the like. These data exist in the IIS log in the form of text.
Step S102: and sending the request text data to a LogStash plug-in and an ElasticSearch plug-in for analysis and retrieval to obtain request analysis data, wherein the request analysis data comprises request initiating time and request response time.
In this embodiment, through parsing and searching of the logstack plug-in and the ElasticSearch plug-in, the requested text data may be converted into request parsing data, where the request parsing data is a data type that can be analyzed in a subsequent step, and may be stored in a database. The request for parsing the content of the data at least needs to include: the request initiation time and the request response time may also include other requested data for comprehensiveness of subsequent monitoring, which is not limited in this embodiment.
Step S103: and analyzing data according to the request, and acquiring a cycle sequence difference value sequence of response time by using serial _ diff.
Step S104: and filtering out the requests with gradually poor performance according to the cycle sequence difference value sequence of the response time.
In the present embodiment, it is assumed that the same request is made in a period of days, the average response time of the day is d (t), the period sequence difference is d (t) -d (t-1), and the sequence formed by the period sequence difference has a physical meaning that the response time is longer or shorter every day compared with the previous day, a positive value indicates that today is longer than yesterday, and a negative value indicates that today is shorter than yesterday.
Preferably, the step may specifically include: and obtaining the number of elements, namely the Large _ Count with the difference value larger than 0 and the number of elements, namely the Less _ Count with the difference value smaller than or equal to 0 in the periodic sequence difference value sequence by using the Count, and filtering out the requests of the Large _ Count > the Less _ Count. In this embodiment, the response in which the performance is gradually deteriorated with time is determined based on the fact that the number of Large _ counts is larger than that of small _ counts.
Preferably, the step may further include: obtaining the number of elements, large _ Count, with the difference value larger than 0 and the number of elements, less _ Count, with the difference value smaller than or equal to 0 in the periodic sequence difference value sequence by using Count, calculating the difference value quantity between the Large _ Count and the Less _ Count, and filtering out the request with the difference value quantity larger than a preset threshold value. In this embodiment, it is not only determined the size between Large _ count and Less _ count, but also further determined whether the difference between them is greater than a preset threshold, that is, the criterion for determining the response of gradually deteriorating the performance with time is more strict than the determination rule in the above embodiment.
According to the technical scheme, the IIS log is analyzed and retrieved through the ELK platform, the request that the performance gradually becomes worse along with the time is filtered out through the obtained periodic sequence difference sequence of the response time, and therefore the problem that the request that the performance gradually becomes worse along with the time cannot be directly obtained in the prior art is solved.
Fig. 2 is a schematic flow chart of a monitoring method for performance degradation request based on an ELK platform according to another embodiment of the present disclosure, where the method includes the following steps:
step S201: and acquiring request text data of each request of the website server by using the IIS log.
Step S202: and sending the request text data to a LogStash plug-in and an ElasticSearch plug-in for analysis and retrieval to obtain request analysis data, wherein the request analysis data comprises request initiating time and request response time.
The general working mode of the Logstash is a c/s architecture, a client end is installed on a host of logs needing to be collected, and a server end is responsible for filtering, modifying and the like the received logs of all nodes and then sending the logs to an elasticsearch. The Elasticissearch is an open source distributed search engine and provides three functions of collecting, analyzing and storing data. The analysis and retrieval of the Logstash are based on text content, and the processing comprises the conversion, replacement, filtration and the like of data types; analytic search of the Elasticsearch is based on analysis of a usage scenario, such as query based on conditions, after data output by logstack is stored in the Elasticsearch.
Step S203: and carrying out graphical monitoring on the request analysis data by utilizing a Kibana plug-in.
Fig. 3 is a schematic flow chart illustrating a process of graphically displaying request parsing data by using a Kibana plug-in according to an embodiment of the present application, where the process includes the following steps:
s2031: the ordinate is set to show the average of the response times of the single cycles.
S2032: the abscissa is set to show the aggregation of the requested times.
S2033: and adding word aggregation according to the request name for graphical display.
The graphical display is represented by a curve in the first quadrant, after the ordinate and the abscissa are set according to steps S2031 and S2032, word aggregation according to the request name is required, if word aggregation is not added, only one curve is provided, as shown in fig. 4, the curve is an aggregated display of requests for all different services, as shown in fig. 5, a plurality of curves are provided, and a request for the same service is aggregated for display, and a request for the same service can be represented as one curve in the graph, so that service requests with gradually poor performance can be conveniently found.
Fig. 6 is a structural diagram of a monitoring system based on an ELK platform performance degradation request provided by the present application, and it can be seen from the diagram that an IIS log respectively enters a logstack plug-in and an elastic search plug-in, and then is graphically displayed by a Kibana plug-in.
Step S204: analyzing data according to the request, and acquiring a cycle sequence difference value sequence of response time by utilizing serial _ diff
Step S205: and obtaining the number of elements, large _ Count, with the difference larger than 0 and the number of elements, less _ Count, with the difference smaller than or equal to 0 in the period sequence difference value sequence by using the Count, and filtering out the request of the Large _ Count > Less _ Count.
Step S206: the filtered requests are displayed graphically using a Kibana plug-in.
According to the technical scheme, the IIS log is analyzed and retrieved through the ELK platform, the obtained periodic sequence difference value sequence of the response time is compared with the number of elements with the difference value larger than 0 and the difference value smaller than or equal to 0, and the requests of the Large _ count > Less _ count, namely the requests of the gradual performance degradation, are filtered out, so that the problem that the requests of the gradual performance degradation cannot be directly obtained in the prior art is solved. In addition, the Kibana plug-in is used for displaying the filtered request in an imaging mode, and the request can be displayed more intuitively.
Fig. 7 is a schematic structural diagram of a monitoring apparatus based on an ELK platform performance degradation request according to an embodiment of the present application, where the apparatus includes: the text collection unit 710, the parsing retrieval unit 720, the sequence acquisition unit 730 and the request filtering unit 740 are connected in sequence.
The text collection unit 710 is configured to collect request text data of each request of the web server by using the IIS log.
The parsing and retrieving unit 720 is configured to send the request text data to the logstack plug-in and the ElasticSearch plug-in for parsing and retrieving to obtain request parsing data, where the request parsing data includes request initiation time and request response time.
The sequence acquiring unit 730 is configured to analyze data according to the request, and acquire a cycle sequence difference sequence of response time by using serial _ diff.
The request filtering unit 740 is configured to filter out requests with gradually degraded performance according to the sequence of the cycle order difference values of the response time.
For detailed description of the above units, reference may be made to the description of the embodiment corresponding to fig. 1, and details are not repeated herein.
According to the technical scheme, the monitoring device for the performance gradual-degradation request based on the ELK platform analyzes and retrieves the IIS log through the ELK platform, and the request of the performance gradual-degradation along with the time is filtered out by using the acquired cycle sequence difference sequence of the response time, so that the problem that the request of the performance gradual-degradation along with the time cannot be directly acquired in the prior art is solved. Fig. 8 is a schematic structural diagram of a monitoring apparatus for performance degradation request based on an ELK platform according to an embodiment of the present disclosure, where the apparatus includes: a text collection unit 810, an analysis retrieval unit 820, a sequence acquisition unit 830, a request filtering unit 840 and a graph monitoring unit 850, wherein: the text collection unit 810, the analysis retrieval unit 820, the sequence acquisition unit 830 and the request filter unit 840 are connected in sequence, and the graphic monitoring unit 850 is connected with the analysis retrieval unit 820 and the request filter unit 840 respectively.
The text collection unit 810 is configured to collect request text data of each request of the website server by using the IIS log.
The parsing and retrieving unit 820 is configured to send the request text data to the logstack plug-in and the ElasticSearch plug-in for parsing and retrieving to obtain request parsing data, where the request parsing data includes request initiation time and request response time.
The sequence obtaining unit 830 is configured to analyze data according to the request, and obtain a sequence of cycle sequence difference values of the response time by using serial _ diff.
The request filtering unit 840 is configured to obtain, by using the Count, the number of elements Large _ Count whose difference is greater than 0 and the number of elements Less _ Count whose difference is Less than or equal to 0 in the periodic sequence difference sequence, and filter out a request that Large _ Count > Less _ Count.
Preferably, the request filtering unit 840 may be further configured to obtain, by using Count, the number of elements Large _ Count whose difference is greater than 0 and the number of elements Less _ Count whose difference is Less than or equal to 0 in the periodic sequence difference sequence, calculate the difference between Large _ Count and Less _ Count, and filter out the request whose difference is greater than the preset threshold.
The graphic monitoring unit 850 is configured to perform graphic monitoring on the request parsing data by using a Kibana plug-in.
Preferably, the graphic monitoring unit 850 is specifically configured to: setting the average value of the response time of the vertical coordinate display single period; setting an aggregation of abscissa display request times; and adding word aggregation according to the request name for graphical display. It can display all requests graphically, or can display filtered requests that have degraded performance over time graphically.
According to the technical scheme, the monitoring device for the performance gradual-degradation request based on the ELK platform analyzes and retrieves the IIS log through the ELK platform, compares the number of elements with the difference value larger than 0 and the difference value smaller than or equal to 0 in the obtained periodic sequence difference value sequence of the response time, and filters out the request with the Large _ count > Less _ count, namely the request with the performance gradually degraded along with the time, so that the problem that the request with the performance gradually degraded along with the time cannot be directly obtained in the prior art is solved. In addition, the Kibana plug-in is used for displaying the filtered request in an imaging mode, and the request can be displayed more intuitively.
Fig. 9 is a schematic diagram of an electronic device provided in an embodiment of the present invention. The electronic device shown in fig. 9 is a general-purpose data processing apparatus comprising a general-purpose computer hardware structure including at least a processor 501 and a memory 502. The processor 501 and the memory 502 are connected by a bus 503. Memory 502 is adapted to store one or more instructions or programs that are executable by processor 501. The one or more instructions or programs are executed by the processor 501 to implement the steps in the above-described monitoring method based on an ELK platform performance degradation request.
The processor 501 may be an independent microprocessor or a set of one or more microprocessors. Thus, processor 501 implements the processing of data and the control of other devices by executing commands stored in memory 502 to thereby execute the method flows of embodiments of the present invention as described above. The bus 503 connects the above components together, and also connects the above components to a display controller 504 and a display device and an input/output (I/O) device 505. Input/output (I/O) device 505 may be a mouse, keyboard, modem, network interface, touch input device, motion sensitive input device, printer, and other devices known in the art. Typically, input/output (I/O) devices 505 are connected to the system through an input/output (I/O) controller 506.
The memory 502 may store, among other things, software components such as an operating system, communication modules, interaction modules, and application programs. Each of the modules and applications described above corresponds to a set of executable program instructions that perform one or more functions and methods described in embodiments of the invention.
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the steps of the monitoring method based on the performance degradation request of the ELK platform.
An embodiment of the present invention further provides a computer program product, which includes a computer program/instruction, and when the computer program/instruction is executed by a processor, the steps of the monitoring method based on the performance degradation request of the ELK platform are implemented.
In summary, the method and apparatus for monitoring a performance gradual-degradation request based on an ELK platform according to the embodiments of the present invention analyze and retrieve the IIS log through the ELK platform, and filter out the request of which the performance gradually degrades over time by using the obtained cycle sequence difference sequence of the response time, thereby solving the problem in the prior art that the request of which the performance gradually degrades over time cannot be directly obtained. In addition, the Kibana plug-in is used for displaying the filtered request in an imaging mode, and the request can be displayed more intuitively.
The preferred embodiments of the present invention have been described above with reference to the accompanying drawings. The many features and advantages of the embodiments are apparent from the detailed specification, and thus, it is intended by the appended claims to cover all such features and advantages of the embodiments which fall within the true spirit and scope thereof. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the embodiments of the invention to the exact construction and operation illustrated and described, and accordingly, all suitable modifications and equivalents may be resorted to, falling within the scope thereof.
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.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (13)

1. A monitoring method for performance degradation requests based on an ELK platform is characterized by comprising the following steps:
the method comprises the steps that IIS logs are used for collecting request text data of each request of a website server;
sending the request text data to a LogStash plug-in and an ElasticSearch plug-in for analysis and retrieval to obtain request analysis data, wherein the request analysis data comprises request initiating time and request response time;
analyzing data according to the request, and acquiring a cycle sequence difference value sequence of response time by using serial _ diff;
and filtering out the requests with gradually poor performance according to the cycle sequence difference value sequence of the response time.
2. The method for monitoring performance degradation requests based on an ELK platform as claimed in claim 1, wherein said filtering out the performance degradation requests according to the periodic sequence difference sequence of the response time comprises:
and obtaining the number of elements, namely the Large _ Count with the difference value larger than 0 and the number of elements, namely the Less _ Count with the difference value smaller than or equal to 0 in the periodic sequence difference value sequence by using the Count, and filtering out the requests of the Large _ Count > the Less _ Count.
3. The method for monitoring performance degradation requests based on an ELK platform as claimed in claim 1, wherein said filtering out the performance degradation requests according to the periodic sequence difference sequence of the response time comprises:
obtaining the number of elements, large _ Count, with the difference value larger than 0 and the number of elements, less _ Count, with the difference value smaller than or equal to 0 in the periodic sequence difference value sequence by using Count, calculating the difference value quantity between the Large _ Count and the Less _ Count, and filtering out the request with the difference value quantity larger than a preset threshold value.
4. The method of claim 1, wherein the method of monitoring for performance degradation requests based on an ELK platform further comprises: and carrying out graphical monitoring on the request analysis data by utilizing a Kibana plug-in.
5. The method for monitoring requests for performance degradation based on ELK platform as claimed in claim 4, wherein said graphically monitoring said request resolution data using Kibana plug-in includes:
setting the average value of the response time of the vertical coordinate display single period;
setting an aggregation of abscissa display request times;
and adding word aggregation according to the request name for graphical display.
6. An ELK platform-based performance degradation request monitoring apparatus, the apparatus comprising:
the system comprises a text acquisition unit, a data processing unit and a data processing unit, wherein the text acquisition unit is used for acquiring request text data of each request of a website server by using an IIS log;
the analysis retrieval unit is used for sending the request text data to a LogStash plug-in and an ElasticSearch plug-in for analysis retrieval to obtain request analysis data, and the request analysis data comprises request initiating time and request response time;
a sequence obtaining unit, configured to analyze data according to the request, and obtain a cycle sequence difference sequence of response time by using serial _ diff;
and the request filtering unit is used for filtering out the requests with gradually poor performance according to the cycle sequence difference value sequence of the response time.
7. The ELK platform-based performance degradation request monitoring apparatus of claim 6, wherein the request filtering unit is specifically configured to: and obtaining the number of elements, namely the Large _ Count with the difference value larger than 0 and the number of elements, namely the Less _ Count with the difference value smaller than or equal to 0 in the periodic sequence difference value sequence by using the Count, and filtering out the requests of the Large _ Count > the Less _ Count.
8. The ELK platform-based performance degradation request monitoring apparatus of claim 6, wherein the request filtering unit is specifically configured to: obtaining the number of elements, large _ Count, with the difference value larger than 0 and the number of elements, less _ Count, with the difference value smaller than or equal to 0 in the periodic sequence difference value sequence by using Count, calculating the difference value quantity between the Large _ Count and the Less _ Count, and filtering out the request with the difference value quantity larger than a preset threshold value.
9. The ELK platform-based performance degradation request monitoring apparatus of claim 6, further comprising: and the graphic monitoring unit is used for carrying out graphic monitoring on the request analysis data by utilizing the Kibana plug-in.
10. The ELK platform-based performance degradation request monitoring apparatus of claim 9, wherein the graphics monitoring unit is specifically configured to:
setting the average value of the response time of the vertical coordinate display single period;
setting an aggregation of abscissa display request times;
and adding word aggregation according to the request name for graphical display.
11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any one of claims 1 to 5 when executing the computer program.
12. 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 according to any one of claims 1 to 5.
13. A computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the steps of the method of any of claims 1 to 5.
CN202210945790.5A 2022-08-08 2022-08-08 Method and device for monitoring performance gradual-difference request based on ELK platform Pending CN115292149A (en)

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