CN114238020A - Multidimensional high-precision intelligent service monitoring method and system - Google Patents
Multidimensional high-precision intelligent service monitoring method and system Download PDFInfo
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- CN114238020A CN114238020A CN202111555715.XA CN202111555715A CN114238020A CN 114238020 A CN114238020 A CN 114238020A CN 202111555715 A CN202111555715 A CN 202111555715A CN 114238020 A CN114238020 A CN 114238020A
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Abstract
The invention discloses a multidimensional high-precision intelligent service monitoring method and a system, wherein the method comprises the following steps: setting a log template, wherein the content of the log template comprises basic information and associated dimension information; recording a monitoring log of the service according to a set log template; setting a monitoring index and a corresponding alarm condition; analyzing and calculating the monitoring log to obtain a set monitoring index; displaying a monitoring index in real time through a monitoring large disc; monitoring a monitoring index; and when the monitoring index exceeds the corresponding alarm condition, warning is carried out. The multidimensional high-precision intelligent service monitoring method and system can automatically deploy the monitoring large disk with clear service semantics, and can improve the efficiency of fault location and solution.
Description
Technical Field
The invention particularly relates to a multidimensional high-precision intelligent service monitoring method and system.
Background
The apm (application Performance monitoring) is the system that the IT department solves the usability problem of the network and IT infrastructure through the automatic monitoring means at first, and gradually develops from the network, infrastructure to the service application system monitoring, link monitoring and service monitoring with the complexity of the software system. The main practice of service monitoring in the industry at present is to reflect the health condition of current service operation by defining an access interface, combining a link and application data, and the general service monitoring mode has the following two main problems: 1) the current situation of the reaction service which cannot be easily understood needs to be translated to a service team by a technical team, and particularly, the cost is high when the fault processing is carried out by linking related departments together. 2) The granularity of service monitoring is coarse, only the success and failure of the interface can be reflected, and if the success and failure reasons need to be further subdivided, the time period is long.
Disclosure of Invention
The invention provides a multidimensional high-precision intelligent service monitoring method and a multidimensional high-precision intelligent service monitoring system, which solve the technical problems in the prior art and adopt the following technical scheme:
a multidimensional high-precision intelligent service monitoring method comprises the following steps:
setting a log template, wherein the content of the log template comprises basic information and associated dimension information;
recording a monitoring log of the service according to a set log template;
setting a monitoring index and a corresponding alarm condition;
analyzing and calculating the monitoring log to obtain a set monitoring index;
displaying a monitoring index in real time through a monitoring large disc;
monitoring a monitoring index;
and when the monitoring index exceeds the corresponding alarm condition, warning is carried out.
Further, after the monitoring log is calculated to obtain the set monitoring index, the multidimensional high-precision intelligent service monitoring method further comprises the following steps:
and storing the calculated monitoring index into a database.
Further, the multidimensional high-precision intelligent service monitoring method further comprises the following steps:
monitoring the associated dimension information;
analyzing the associated dimension information;
and alarming when the associated dimension information is abnormal.
Further, a specific method for analyzing the associated dimension information is as follows:
and analyzing the associated dimension information by a dimension drilling method.
Further, a specific method for analyzing the associated dimension information is as follows:
and analyzing the associated dimension information through an algorithm such as an Adtributor algorithm or a Monte Carlo search tree.
Further, the multidimensional high-precision intelligent service monitoring method further comprises the following steps:
and performing BI analysis modeling according to the associated dimension information.
A multidimensional high-precision intelligent service monitoring system comprises:
the system comprises a first setting module, a second setting module and a third setting module, wherein the first setting module is used for setting a log template, and the content of the log template comprises basic information and associated dimension information;
the log recording module is used for recording a monitoring log of the service according to the log template set by the first setting module;
the second setting module is used for setting monitoring indexes;
the third setting module is used for setting the alarm condition corresponding to the monitoring index;
the calculation module is used for analyzing and calculating the monitoring log to obtain a set monitoring index;
the monitoring large disk module is used for displaying monitoring indexes;
the first monitoring module is used for monitoring a monitoring index;
and the first warning module is used for warning when the monitoring index monitored by the detection module exceeds the corresponding warning condition.
Further, the multidimensional high-precision intelligent service monitoring system further comprises:
and the database is used for storing the monitoring indexes calculated by the calculation module.
Further, the multidimensional high-precision intelligent service monitoring system further comprises:
the second monitoring module is used for monitoring the associated dimension information;
the analysis module is used for analyzing the associated dimension information;
and the second alarm module is used for giving an alarm when the associated dimension information is abnormal.
Further, the multidimensional high-precision intelligent service monitoring system further comprises:
and the BI modeling module is used for carrying out BI analysis modeling according to the associated dimension information.
The multidimensional high-precision intelligent service monitoring method and system provided by the invention have the beneficial effects that the large monitoring disc with clear service semantics can be automatically deployed, and the efficiency of fault location and solution can be improved.
The multidimensional high-precision intelligent service monitoring method and system have the advantages that when relevant services have faults, not only can the current monitoring index perform fault positioning, but also the current monitoring index supports monitoring and attribution analysis of dimensionality drilling, monitoring can be performed in each dimensionality, and monitoring granularity and effectiveness are greatly improved.
The multidimensional high-precision intelligent service monitoring method and system provided by the invention have the beneficial effects that the integration of monitoring and service analysis is realized, the cost of a technical team and a BI team is reduced, and the consistency and secondary multiplexing of data are realized.
Drawings
Fig. 1 is a schematic diagram of a multidimensional high-precision intelligent service monitoring method of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and the embodiments.
Fig. 1 shows a multidimensional high-precision intelligent service monitoring method according to the present application, which includes the following steps: s1: and setting a log template, wherein the content of the log template comprises basic information and associated dimension information. S2: and recording the monitoring log of the service according to the set log template. S3: and setting a monitoring index and a corresponding alarm condition. S4: and analyzing and calculating the monitoring log to obtain a set monitoring index. S5: and displaying the monitoring index in real time through the monitoring large disc. S6: and monitoring the monitoring index. S7: and when the monitoring index exceeds the corresponding alarm condition, warning is carried out. The above steps are specifically described below.
For step S1: and setting a log template.
Firstly, a log template of a monitoring log to be recorded needs to be set. Specifically, the content of the log template includes basic information and associated dimension information. Wherein the basic information includes: the product, the product action and the event information. The product to which the service is changed includes information such as a product name of the product. Product actions refer to specific operations on business changes that occur to the product. The event information refers to information such as time, interface, call parameter, response time and response interface when the service change occurs. The associated dimension information refers to the service information related to the current service monitoring, and includes but is not limited to information of participants, regions, mobile phone models, and the like. Taking a transaction log as an example, the participants refer to the users and merchants at the system level. A typical software system will use an internal ID to identify its identity. The territory refers to the place where the transaction occurred. When the position positioning information is opened at present, software can acquire the position positioning information. The mobile phone model is the mobile phone model of the current transaction. The associated dimension information is information related to the transaction that can be collected within the authorization scope of the user and the merchant.
For step S2: and recording the monitoring log of the service according to the set log template.
The monitoring log of the service is recorded according to the log template set in step S1.
For step S3: and setting a monitoring index and a corresponding alarm condition.
Corresponding monitoring indexes can be specifically set for different service types. The design of the monitoring index is to count the data of the current business products in unit time. Specifically, the monitoring index may be a transaction number per unit time, a payment number per unit time, or the like. The unit time may be set according to the amount of traffic of the company, such as by minute or by second.
And setting corresponding alarm conditions according to different monitoring indexes. For a monitoring indicator such as the number of strokes created for a transaction, an alarm threshold may be set in the range of 800 strokes/second to 1200 strokes/second. And when the speed is lower than 800 strokes/second or higher than 1200 strokes/second, an alarm is triggered. Or setting an index expected curve with a complex point, and triggering an alarm if the difference between the current value and the expected curve exceeds the alarm setting range.
The alarm condition can also be set correspondingly for the time period. That is, for the same monitoring index, the corresponding alarm conditions may be different at different time periods in a day. It will be appreciated that for some monitoring indicators, the range of reasonable values for different time periods in the day will be different due to the nature of the product. It is obviously not reasonable if monitoring is performed according to the same alarm condition.
For step S4: and analyzing and calculating the monitoring log to obtain a set monitoring index.
And analyzing and calculating the collected monitoring logs to obtain monitoring indexes to be monitored.
Preferably, after the monitoring log is calculated to obtain the set monitoring index, the multidimensional high-precision intelligent service monitoring method further includes: and storing the calculated monitoring index into a database.
For step S5: and displaying the monitoring index in real time through the monitoring large disc.
And after the monitoring indexes are calculated, the monitoring indexes are displayed by the dashboards through the large monitoring discs.
For step S6: and monitoring the monitoring index.
For step S7: and when the monitoring index exceeds the corresponding alarm condition, warning is carried out.
These monitoring indexes are monitored according to the alarm conditions set in step S3, and when the monitoring indexes exceed their corresponding alarm conditions, an alarm is given. Further, alarm reason positioning can be carried out aiming at the alarm.
As a preferred embodiment, the multidimensional high-precision intelligent service monitoring method further includes:
and monitoring the associated dimension information.
And analyzing the associated dimension information.
And alarming when the associated dimension information is abnormal.
It can be understood that for some monitoring indexes, alarm conditions are set from the whole situation to monitor the monitoring indexes, and problems cannot be found in time under certain conditions. For example, the magnitude of commodity transaction information for a total station is around 10 ten thousand/s, and the alarm condition set for it may be 8w/s to 12 w/s. When the commodity transaction information of the total station is normal within 8w/s to 12w/s, no alarm occurs. However, for merchandise transaction information that is relevant to a particular city, a 500/s fluctuation may be present indicating an anomaly. However, the fluctuation of 500/s cannot be reflected in the overall station index level, so that the problem cannot be found in time.
In the application, the associated dimension information document of the transaction is modeled algorithmically and monitored.
The service dimensions associated with one log may be very many, and in the present application, a specific method for analyzing the associated dimension information is as follows: and analyzing the associated dimension information by adopting a dimension drilling method.
As an optional implementation, the specific method for analyzing the associated dimension information may further be: and analyzing the associated dimension information through an algorithm such as an Adtributor algorithm or a Monte Carlo search tree.
As a preferred embodiment, the multidimensional high-precision intelligent service monitoring method further includes: and performing BI analysis modeling according to the associated dimension information.
The specific method for performing BI analysis modeling according to the associated dimension information comprises the following steps:
and performing BI analysis modeling comprehensively according to the associated dimension information and the external service data associated with the associated dimension information, so that integration of data monitoring and service analysis can be realized. Specifically, the external business data refers to data with analysis value associated with currently monitored associated dimension information. For example, the monitoring data monitors the transaction and provides the user id and merchant id of the parties to the transaction. If BI needs to analyze user age distribution, region distribution and preference distribution of business participated in yesterday, the uid and external uid portrait data association capability is provided at the monitoring system level, namely, the association dimension information is connected with external business data. And then, carrying out aggregation statistics on a plurality of windows according to the level of minutes, hours and days, thereby realizing the BI analysis capability on the user service distribution condition in different time windows. Other business scenarios are similar to the description scenario, namely, the integration of monitoring and business analysis is realized.
The application also discloses a multidimensional high-precision intelligent service monitoring system, which comprises: the device comprises a first setting module, a log recording module, a second setting module, a third setting module, a calculating module, a monitoring large disk module, a first monitoring module and a first warning module.
Specifically, the first setting module is used for setting a log template, and the content of the log template comprises basic information and associated dimension information. The log recording module is used for recording the monitoring log of the service according to the log template set by the first setting module. The second setting module is used for setting the monitoring index. The third setting module is used for setting the alarm condition corresponding to the monitoring index. The calculation module is used for analyzing and calculating the monitoring log to obtain a set monitoring index. The monitoring large disk module is used for displaying monitoring indexes. The first monitoring module is used for monitoring the monitoring index. The first warning module is used for warning when the monitoring index monitored by the detection module exceeds the corresponding warning condition.
As a preferred embodiment, the multidimensional high-precision intelligent service monitoring system further comprises: a database. The database is used for storing the monitoring indexes calculated by the calculation module.
As a preferred embodiment, the multidimensional high-precision intelligent service monitoring system further comprises: the system comprises a second monitoring module, an analysis module and a second alarm module. The second monitoring module is used for monitoring the associated dimension information. The analysis module is used for analyzing the associated dimension information. The second alarm module is used for giving an alarm when the associated dimension information is abnormal.
As a preferred embodiment, the multidimensional high-precision intelligent service monitoring system further comprises: a BI modeling module.
And the BI modeling module is used for carrying out BI analysis modeling according to the associated dimension information.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It should be understood by those skilled in the art that the above embodiments do not limit the present invention in any way, and all technical solutions obtained by using equivalent alternatives or equivalent variations fall within the scope of the present invention.
Claims (10)
1. A multidimensional high-precision intelligent service monitoring method is characterized by comprising the following steps:
setting a log template, wherein the content of the log template comprises basic information and associated dimension information;
recording a monitoring log of the service according to the set log template;
setting a monitoring index and a corresponding alarm condition;
analyzing and calculating the monitoring log to obtain a set monitoring index;
displaying the monitoring index in real time through a monitoring large disc;
monitoring the monitoring index;
and when the monitoring index exceeds the corresponding alarm condition, warning is carried out.
2. The multidimensional high-precision intelligent traffic monitoring method according to claim 1,
after the monitoring log is calculated to obtain the set monitoring index, the multidimensional high-precision intelligent service monitoring method further comprises the following steps:
and storing the calculated monitoring index into a database.
3. The multidimensional high-precision intelligent traffic monitoring method according to claim 1,
the multidimensional high-precision intelligent service monitoring method further comprises the following steps:
monitoring the associated dimension information;
analyzing the associated dimension information;
and alarming when the associated dimension information is abnormal.
4. The multidimensional high-precision intelligent traffic monitoring method according to claim 3,
the specific method for analyzing the associated dimension information comprises the following steps:
and analyzing the associated dimension information by a dimension drilling method.
5. The multidimensional high-precision intelligent traffic monitoring method according to claim 3,
the specific method for analyzing the associated dimension information comprises the following steps:
and analyzing the associated dimension information through an algorithm such as an Adtributor algorithm or a Monte Carlo search tree.
6. The multidimensional high-precision intelligent traffic monitoring method according to claim 3,
the multidimensional high-precision intelligent service monitoring method further comprises the following steps:
and performing BI analysis modeling according to the associated dimension information.
7. A multidimensional high-precision intelligent service monitoring system is characterized by comprising:
the system comprises a first setting module, a second setting module and a third setting module, wherein the first setting module is used for setting a log template, and the content of the log template comprises basic information and associated dimension information;
the log recording module is used for recording a monitoring log of the service according to the log template set by the first setting module;
the second setting module is used for setting monitoring indexes;
the third setting module is used for setting the alarm condition corresponding to the monitoring index;
the calculation module is used for analyzing and calculating the monitoring log to obtain the set monitoring index;
the monitoring large disk module is used for displaying the monitoring index;
the first monitoring module is used for monitoring the monitoring index;
and the first warning module is used for warning when the detection module monitors that the monitoring index exceeds the corresponding warning condition.
8. The multidimensional high-precision intelligent traffic monitoring system of claim 7,
the multi-dimensional high-precision intelligent service monitoring system further comprises:
and the database is used for storing the monitoring index calculated by the calculation module.
9. The multidimensional high-precision intelligent traffic monitoring system of claim 7,
the multi-dimensional high-precision intelligent service monitoring system further comprises:
the second monitoring module is used for monitoring the associated dimension information;
the analysis module is used for analyzing the associated dimension information;
and the second alarm module is used for giving an alarm when the associated dimension information is abnormal.
10. The multidimensional high-precision intelligent traffic monitoring system of claim 9,
the multi-dimensional high-precision intelligent service monitoring system further comprises:
and the BI modeling module is used for carrying out BI analysis modeling according to the associated dimension information.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114531338A (en) * | 2022-04-24 | 2022-05-24 | 中邮消费金融有限公司 | Monitoring alarm and tracing method and system based on call chain data |
| CN116401127A (en) * | 2023-06-02 | 2023-07-07 | 梅州客商银行股份有限公司 | Information system health state monitoring method and device and electronic equipment |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114531338A (en) * | 2022-04-24 | 2022-05-24 | 中邮消费金融有限公司 | Monitoring alarm and tracing method and system based on call chain data |
| CN116401127A (en) * | 2023-06-02 | 2023-07-07 | 梅州客商银行股份有限公司 | Information system health state monitoring method and device and electronic equipment |
| CN116401127B (en) * | 2023-06-02 | 2023-10-31 | 梅州客商银行股份有限公司 | Information system health state monitoring method and device and electronic equipment |
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