CN116340095A - Efficient and simple micro-service monitoring and alarming method and system - Google Patents

Efficient and simple micro-service monitoring and alarming method and system Download PDF

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CN116340095A
CN116340095A CN202310226642.2A CN202310226642A CN116340095A CN 116340095 A CN116340095 A CN 116340095A CN 202310226642 A CN202310226642 A CN 202310226642A CN 116340095 A CN116340095 A CN 116340095A
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service
monitoring
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alarm
log information
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彭莉婷
沈力
程为
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Shanghai Jinshida Software Technology Co 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
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
    • 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
    • G06F11/3068—Monitoring arrangements determined by the means or processing involved in reporting the monitored data where the reporting involves data format conversion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3089—Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents
    • G06F11/3093—Configuration details thereof, e.g. installation, enabling, spatial arrangement of the probes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
    • G06F11/323—Visualisation of programs or trace data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
    • G06F11/324—Display of status information
    • G06F11/327—Alarm or error message display
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G06F16/2272—Management thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2455—Query execution
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/258—Data format conversion from or to a database
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
    • G06F2201/80—Database-specific techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2201/00—Indexing scheme relating to error detection, to error correction, and to monitoring
    • G06F2201/865—Monitoring of software
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The invention discloses a high-efficiency and simple micro-service monitoring and alarming method and a system, which belong to the technical field of information, wherein the method comprises the following steps: the log information of each microservice in the system is uniformly output to an elastic search according to a preset format through the Logstar and stored; determining an associated target micro-service according to a service scene, and retrieving target data corresponding to the target micro-service from an elastic search; and respectively carrying out summarization analysis on the target data according to the monitoring rules and the alarm rules to generate monitoring content and alarm events. The invention takes the ES as a data source, which can well solve the problems of too many fields of the database, low query speed and no method for optimizing the index; the invention can effectively monitor the running and interface calling conditions of each micro service, improve the working efficiency of developers and operation and maintenance personnel, and support the calling details and exception analysis of the API and the performance analysis of the micro service.

Description

Efficient and simple micro-service monitoring and alarming method and system
Technical Field
The invention relates to the technical field of information, in particular to a high-efficiency and simple micro-service monitoring and alarming method and system.
Background
In the development process of developers or when operation and maintenance staff develop operation and maintenance work, the operation and interface calling conditions of each micro service need to be monitored, and therefore a micro service monitoring and alarming system is needed to help the developers and the operation and maintenance staff to quickly locate the problems so as to improve the working efficiency.
At present, the same industry already has a monitoring alarm system, but most monitoring alarm systems are modified and checked based on the traditional database, so that when the number of micro services is large and the usage amount is large, the log record amount is generated in large quantity, and when the log data is large, the access frequency is relatively high, the database is overlarge in pressure and low in retrieval efficiency, so that the monitoring alarm system is blocked, and the working efficiency of developers and operation and maintenance staff is affected.
Disclosure of Invention
Aiming at the problem that the micro-service monitoring alarm system in the prior art is blocked when the log record quantity is large, the invention aims to provide an efficient and simple micro-service monitoring alarm method and system.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
in a first aspect, the present invention provides a highly efficient and compact micro-service monitoring and alarming method, comprising the following steps:
the log information of each microservice in the system is uniformly output to an elastic search according to a preset format through the Logstar and stored;
determining an associated target micro-service according to a service scene, and retrieving target data corresponding to the target micro-service from an elastic search;
and respectively carrying out summarization analysis on the target data according to the monitoring rules and the alarm rules to generate monitoring content and alarm events.
In a preferred embodiment, the log information includes application log information and access log information, and the application log information and the access log information are stored in an elastic search in different index marks, respectively.
In a preferred embodiment, the monitoring content and the alarm event are displayed through a Kibana display platform.
In a preferred embodiment, the log information includes a link ID, an application name, an interface name, a caller application name, a caller interface name, a timestamp, a remote call spending time period, a local call duration, and an interface call exception.
In a preferred embodiment, the monitoring content includes one or more of the following:
monitoring the total request number, the failure request number, the success rate, the average response time and the maximum response time of the target micro-service in a specified time range;
monitoring the inter-calling condition of the target micro-service in a specified time range;
monitoring the access times, failure rate, maximum response time and average response time of the key API in a specified time range;
monitoring M APIs with maximum response time within a specified time range, wherein M is more than or equal to 1;
and monitoring N APIs with the largest failure times within a specified time range, wherein N is more than or equal to 1.
In a preferred embodiment, the alarm event includes an alarm object, alarm content and alarm level; the alarm object is a micro service or interface; the alarm content comprises key API access times, key API failure rates, key API response times, key API average response times, micro-service failure rates and micro-service average response times; the alarm level comprises early warning, alarm and severity.
In a preferred embodiment, the key APIs are n APIs with the largest number of accesses within a specified time frame.
In a second aspect, the present invention further provides a highly efficient and compact micro-service monitoring and alarming system, including:
the information storage module is used for uniformly outputting the log information of each micro service in the system to the elastic search according to a preset format and storing the log information;
the query module is used for determining the associated target micro-service according to the service scene and retrieving target data corresponding to the target micro-service from the elastic search;
the monitoring module is used for generating monitoring content after summarizing and analyzing the target data according to the monitoring rule;
and the alarm module is used for generating an alarm event after summarizing and analyzing the target data according to the alarm rule.
In a third aspect, the invention also provides an electronic device comprising a memory storing executable program code and a processor coupled to the memory; wherein the processor invokes executable program code stored in the memory to perform the method as described above.
In a fourth aspect, the invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, performs a method as described above.
By adopting the technical scheme, the invention has the beneficial effects that: the invention uses ES as data source, which solves the problems of too many database fields, slow query speed and no method for optimizing index. The invention can effectively monitor the running and interface calling conditions of each micro service, improve the working efficiency of developers and operation and maintenance personnel, and support the calling details and exception analysis of the API and the performance analysis of the micro service.
Drawings
FIG. 1 is a flow chart of a method according to a first embodiment of the invention;
FIG. 2 is a diagram showing a log query architecture according to an embodiment of the present invention;
FIG. 3 is a diagram showing an API monitoring architecture in accordance with a first embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a second embodiment of the present invention;
fig. 5 is a schematic structural diagram of a third embodiment of the present invention.
Detailed Description
The following describes the embodiments of the present invention further with reference to the drawings. The description of these embodiments is provided to assist understanding of the present invention, but is not intended to limit the present invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
Example 1
An efficient and simple micro-service monitoring and alarming method, as shown in figure 1, comprises the following steps:
s1, uniformly outputting log information of each micro service in the system to an elastic search according to a preset format through the Logstar, and storing the log information.
The micro-service is Java application deployed in a scalable container mode, and is a functional implementation in a certain business field. In a financial system, each micro-service for supporting smooth service deployment is usually run in each server, and corresponding log information, such as application log information and access log information, is generated during the running process of each micro-service.
In this embodiment, log information of each micro service in the system is output to an elastic search in a unified manner according to a preset format through logstack and stored. The ES is a real-time data collection and retrieval platform, and one advantage of taking the ES as a data source is that the problems that the database has too many fields, the query speed is low and the index is not optimized can be well solved. The logstack is a powerful data processing tool, which can realize data transmission, format processing and format output, and has a powerful plug-in function, and is commonly used for log processing.
The link log information typically includes a link ID, a user name, an application name, an interface name, a caller application name, a caller interface name, a timestamp, a remote call spent duration, a local call duration, an interface call exception. As shown in table 1, the link log information is stored in the ES in the structure:
TABLE 1 Log information storage Structure details in ES
Figure BDA0004118734960000031
Wherein the application log information and the access log information are to be stored in the ES in different index marks (index), respectively, as shown in table 2.
Table 2-log information of different categories is stored in ES
Figure BDA0004118734960000032
S2, determining the associated target micro-service according to the service scene, and retrieving target data corresponding to the target micro-service from the elastic search.
In this embodiment, after the service scenario is determined, the target micro service associated with the service scenario can also be determined, and based on the determined target micro service, that is, the ELK-based solution, target data corresponding to the target micro service is retrieved from the elastic search, as shown in fig. 2, where log is used as an input source of log, ES is used as an output target of log, that is, ES is used as a data source, and the problem that when log data is large, the database pressure is too high and the retrieval efficiency is low due to the high access frequency is solved well, and there is no concern that the database fields are large, the data volume is large, and the database index is not optimized.
In this embodiment, the storage format of the application log information in the ES is as follows:
"％t％h％m\"％r\"％s％b％a
\"％q\"％{originalIpAddress}r％{isInnerRequest}r％{traceId}r％{userName}r％{applicationNa me}r％{apiName}r％{originalApplicationName}r％{originalMethod}r％{originalApiName}r％D％{remoteTimeTaken}r％{localTimeTaken}r％{success}r"
as shown in table 3, which is a detailed description of a storage format of application log information in the ES.
Table 3-detailed description of storage format of application log information in ES
Expression type Description of the invention
％{originalIpAddress}r Requesting ip addresses
％{isInnerRequest}r Whether or not it is an internal request
％{traceId}r Link ID
％{userName}r User name
％{applicationName}r Application name
％{apiName}r Interface name
％{originalApplicationName}r Caller application name
％{originalMethod}r Calling party method
％{originalApiName}r Calling party interface name
％{remoteTimeTaken}r Remote invocation of spent duration
％{localTimeTaken}r Local call duration
％{success}r Interface call exception
And S3, respectively carrying out summarization analysis on the target data according to the monitoring rules and the alarm rules to generate monitoring content and alarm events.
The monitoring rules and the alarm rules can be defined manually and preset, and the corresponding generated monitoring content and alarm event are displayed through the Kibana display platform.
Kibana is an open source analysis and visualization platform for elastomer search to search and view data interactively stored in elastomer search index. Using Kibana, advanced data analysis and presentation can be performed through various charts.
As shown in fig. 3, an architecture diagram of the method provided in the present invention in the aspect of API monitoring is shown, where the monitoring content includes one or more of the following, and is shown by a Kibana showing platform:
1. monitoring the total request number, the failure request number, the success rate, the average response time and the maximum response time of all the target micro-services in a specified time range;
2. monitoring failure conditions of all target micro-services within a specified time range, displaying the failure conditions in a bee-shaped graph, and displaying different colors according to the numerical value of failure times;
3. monitoring and displaying the mutual calling condition of each target micro-service in a specified time range;
4. monitoring a line graph and/or a bar graph of the number of requests, average response time, maximum response time, success rate of all target micro-services over a period of time (counted at fixed time intervals);
5. monitoring and displaying a pie chart of total request number and failure number of each target micro-service in a specified time range;
6. monitoring and displaying a histogram of average response times and maximum response times of each target microservice over a specified time range (counted at fixed time intervals);
7. monitoring and displaying the access times, failure rate, maximum response time and average response time of the key APIs in a specified time range, wherein the key APIs are n APIs with the largest access times in the specified time range, and n is more than or equal to 1;
8. monitoring and displaying M APIs with maximum response time in a specified time range, wherein M is more than or equal to 1;
9. n APIs with the largest number of failures in the specified time range are monitored and displayed, wherein N is more than or equal to 1, preferably 10.
In terms of alarms, it can be appreciated that the generation of alarm events is based on the judgment of the monitored content (based on alarm rules), for example, when the monitored result is greater than a preset value (set by alarm rules), then the alarm event is generated. The embodiment can generate corresponding alarm events aiming at each target micro-service, and display the bee-shaped graph of the alarm events of each target micro-service and all the alarm events which are not ended currently.
In this embodiment, the alarm event specifically includes three dimensions of an alarm object, alarm content, and alarm level. Wherein the alert object is a microservice or interface. The alert content includes a number of key API accesses (e.g., greater than or equal to a set point, the same applies below), a number of key API failures, a key API failure rate, a key API response time, a key API average response time, a number of micro-service failures, a micro-service failure rate, a micro-service average response time. The alarm level comprises early warning, alarm and severity.
Therefore, the method provided by the invention can effectively monitor the running and interface calling conditions of each micro-service, thereby improving the working efficiency of developers and operation and maintenance personnel, and in addition, supporting the calling details and exception analysis of the API and the performance analysis of the micro-service.
Example two
An efficient and compact micro-service monitoring and alarming system, as shown in fig. 4, comprises:
the acquisition module is used for uniformly outputting the log information of each micro-service in the system to the elastic search according to a preset format and storing the log information;
the query module is used for determining the associated target micro-service according to the service scene and retrieving target data corresponding to the target micro-service from the elastic search;
the monitoring module is used for generating monitoring content after summarizing and analyzing the target data according to the monitoring rule and displaying the monitoring content through the Kibana display platform;
and the alarm module is used for generating alarm events after summarizing and analyzing the target data according to alarm rules and displaying the alarm events through the Kibana display platform.
Example III
An electronic device, as shown in fig. 5, includes a memory storing executable program code and a processor coupled to the memory; wherein the processor invokes executable program code stored in the memory to perform the method steps disclosed in the above embodiments.
Example IV
A computer storage medium having a computer program stored therein, which when executed by a processor performs the method steps disclosed in the above embodiments.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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 embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. It will be apparent to those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, and yet fall within the scope of the invention.

Claims (10)

1. A high-efficiency and simple micro-service monitoring and alarming method is characterized in that: the method comprises the following steps:
the log information of each microservice in the system is uniformly output to an elastic search according to a preset format through the Logstar and stored;
determining an associated target micro-service according to a service scene, and retrieving target data corresponding to the target micro-service from an elastic search;
and respectively carrying out summarization analysis on the target data according to the monitoring rules and the alarm rules to generate monitoring content and alarm events.
2. The method according to claim 1, characterized in that: the log information includes application log information and access log information, which are stored in an elastic search with different index marks, respectively.
3. The method according to claim 1, characterized in that: and displaying the monitoring content and the alarm event through a Kibana display platform.
4. The method according to claim 1, characterized in that: the log information comprises a link ID, an application name, an interface name, a caller application name, a caller interface name, a timestamp, a remote call spending time length, a local call time length and an interface call abnormal condition.
5. The method according to claim 1, characterized in that: the monitoring content comprises one or more of the following:
monitoring the total request number, the failure request number, the success rate, the average response time and the maximum response time of the target micro-service in a specified time range;
monitoring the inter-calling condition of the target micro-service in a specified time range;
monitoring the access times, failure rate, maximum response time and average response time of the key API in a specified time range;
monitoring M APIs with maximum response time within a specified time range, wherein M is more than or equal to 1;
and monitoring N APIs with the largest failure times within a specified time range, wherein N is more than or equal to 1.
6. The method according to claim 5, wherein: the alarm event comprises an alarm object, alarm content and alarm level; the alarm object is a micro service or interface; the alarm content comprises key API access times, key API failure rates, key API response times, key API average response times, micro-service failure rates and micro-service average response times; the alarm level comprises early warning, alarm and severity.
7. The method according to claim 5 or 6, characterized in that: and the key APIs are n APIs with the largest access times in the appointed time range.
8. A high-efficient succinct microservice monitoring alarm system which characterized in that: comprising the following steps:
the information storage module is used for uniformly outputting the log information of each micro service in the system to the elastic search according to a preset format and storing the log information;
the query module is used for determining the associated target micro-service according to the service scene and retrieving target data corresponding to the target micro-service from the elastic search;
the monitoring module is used for generating monitoring content after summarizing and analyzing the target data according to the monitoring rule;
and the alarm module is used for generating an alarm event after summarizing and analyzing the target data according to the alarm rule.
9. An electronic device, characterized in that: comprising a memory storing executable program code and a processor coupled to the memory; wherein the processor invokes executable program code stored in the memory to perform the method of any of claims 1-7.
10. A computer-readable storage medium storing a computer program, characterized in that: the computer program, when executed by a processor, performs the method of any of claims 1-7.
CN202310226642.2A 2023-03-08 2023-03-08 Efficient and simple micro-service monitoring and alarming method and system Pending CN116340095A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118093329A (en) * 2024-04-28 2024-05-28 成都乐超人科技有限公司 Event-driven-based micro-service monitoring and alarming method and system

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118093329A (en) * 2024-04-28 2024-05-28 成都乐超人科技有限公司 Event-driven-based micro-service monitoring and alarming method and system

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