CN109408331A - Log alarming system based on user individual feature - Google Patents
Log alarming system based on user individual feature Download PDFInfo
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- CN109408331A CN109408331A CN201811198219.1A CN201811198219A CN109408331A CN 109408331 A CN109408331 A CN 109408331A CN 201811198219 A CN201811198219 A CN 201811198219A CN 109408331 A CN109408331 A CN 109408331A
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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
- G06F11/3065—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
Abstract
The problem of the present invention relates to log alarming technologies, and alarm rule cannot be automatically updated by solving existing log alarming system, and user experience is poor, and are easy to generate the redundant warning information unrelated with user demand, low efficiency of alarming.The technical solution adopted is that by acquisition user in real-time monitoring module to the enquiry frequency of the daily record data of various type of alarm, then alarm rule module is according to the corresponding relationship of preset enquiry frequency and statistical magnitude threshold value, obtain the statistical magnitude threshold value of the various type of alarm of user, and the statistical magnitude threshold value of the various type of alarm of user is updated into alarm rule warehouse in the corresponding alarm rule of the user, wherein enquiry frequency is higher, then the corresponding statistical magnitude threshold value of the enquiry frequency is smaller.Through the above technical solutions, system can be according to the alarm object adjust automatically alarm rule that user pays close attention to, so that user experience is good, it is not easy to generate the redundant warning information unrelated with user demand, alarm efficiency improves.
Description
Technical field
The present invention relates to log alarming technology, in particular to a kind of log alarming system based on user individual feature.
Background technique
Existing log alarming system is in terms of data storage and data processing real-time, and traditional relevant database is
It is unable to satisfy the demand of mass memory and magnanimity calculating, mostly uses NoSQL non-relational database and solr search engine at present
To overcome: acquired data storage to NoSQL database, using solr, quasi real time searching component inquires database；NoSQL database
Mass memory can preferably be solved and magnanimity calculates the application demand of aspect, solr is very fast to the search of historical data；But
Search efficiency can decline when solr establishes index, and real time indexing search efficiency is not high.
In terms of alarm rule building, user pre-defines early warning rule and its parameter or user by configuration file
Alarming logic is set according to self-demand by interactive interface, both modes all not can avoid artificial intervention, lead to user
Experience property is poor；And type of alarm is relatively fixed, can not dynamically change alarm rule according to the different needs of the user, causes to be easy
The redundant warning information unrelated with user's alarm demand is generated, and then influences alarm efficiency.
Summary of the invention
The invention solves existing log alarming systems cannot automatically update alarm rule, and user experience is poor, and holds
The technical issues of redundant warning information unrelated with user demand easily generated, low efficiency of alarming, provides a kind of based on user personality
Change the log alarming system of feature.
In order to solve the above technical problems, the technical solution adopted by the present invention is that: the log report based on user individual feature
Alert system, including log acquisition module, real-time monitoring module, alarm module and alarm rule module；
The log acquisition module arrives collected daily record data storage for the daily record data in acquisition server
The daily record data of storage is sent real-time monitoring module by database, database；
The real-time monitoring module daily record data that library is sent for receiving data, and daily record data inquiry is at least provided
Function, and timing updates each user to the enquiry frequency of the daily record data of every kind of type of alarm；
The alarm module is used to establish the alarm task of different user, and for the alarm task of each user, alarm is appointed
Business obtains the alarm rule of the user preset from preset alarm rule warehouse, and timing detects the corresponding alarm rule of the user
Whether there is update, the corresponding alarm rule of the updated user is obtained when there is update, alarm task poll monitors mould in real time
Whether the daily record data of the user in block meets alarm according to the daily record data that the judgement of the alarm rule of the user is currently read
Condition reads next daily record data if being unsatisfactory for alert if, if meeting alert if obtains the day currently read
The type of alarm of will data, and one is added to the statistical magnitude of the type of alarm of the user, then judge the alarm of the user
Whether the statistical magnitude of type reaches the statistical magnitude threshold value of the type of alarm set in the alarm rule of the user, if not reaching
The warning message of the daily record data currently read is then put into cache pool to threshold value, then proceedes to read next log number
According to, if reaching threshold value, by the warning message and cache pool of the daily record data currently read with the log that currently reads
After the warning message of the daily record data of the identical user of the type of alarm of data is integrated, it is sent to the alarm rule of the user
The terminal alarms equipment of the corresponding responsible person of the preset type of alarm in then, and by the statistical number of the type of alarm of the user
Amount is reset, while deleting the warning message of the daily record data of the type of alarm of the user in cache pool, is then read next
Daily record data；
The alarm rule module is used to obtain each user to the log number of every kind of type of alarm from real-time monitoring module
According to enquiry frequency, then according to each user to the enquiry frequency of the daily record data of every kind of type of alarm and preset inquiry frequency
The corresponding relationship of rate and statistical magnitude threshold value obtains the statistical magnitude threshold value of every kind of type of alarm of each user, then will be every
The statistical magnitude threshold value of every kind of type of alarm of a user is updated into alarm rule warehouse in the corresponding alarm rule of the user,
Wherein enquiry frequency is higher, then the corresponding statistical magnitude threshold value of the enquiry frequency is smaller.
As advanced optimizing, the log acquisition module passes through in the shipper component acquisition server of logstash
Daily record data and monitoring server log storage catalogue variation, and by collected daily record data be output to redis caching,
Daily record data is acquired from redis by the indexer component of logstash and is stored, and is connected by the broker component of logstash
Shipper component and indexer component are connect, the daily record data of storage is sent kafka message-oriented middleware by indexer component,
By kafka message-oriented middleware by daily record data storage to kafka database, daily record data is sent reality by kafka database
When monitoring module.Kafka message-oriented middleware is as the bridge between the processing of data acquisition and storage, at coordination data acquisition and storage
Manage the inconsistent of speed.
As advanced optimizing, the real-time monitoring module receives the log number that database is sent by logstash
According to, and daily record data is carried out according to preset configuration file to send elasticsearch for daily record data after cleaning filtering
In, elasticsearch is added to daily record data according to default rule template and is indexed and stored, and is passed through
The search API that elasticsearch is provided inquires daily record data, and is carried out the daily record data of inquiry by kibana
It shows.The daily record data that elasticsearch is obtained as real-time search engine, analysis by logstash filtering, constructs phase
It should index quickly by a large amount of log filing storage to elasticsearch, building does not influence search efficiency when indexing.
Beneficial effect is: the enquiry frequency of the daily record data for the various type of alarm that the present invention is inquired according to user and
The corresponding relationship of preset enquiry frequency and statistical magnitude threshold value, the statistical number of corresponding type of alarm in adjust automatically alarm rule
Threshold value is measured, if the enquiry frequency of the daily record data of a certain type of alarm is higher, illustrates that user more pays close attention to the type of alarm, and the report
The corresponding statistical magnitude threshold value of police's type is again smaller, and then opposite can accelerate the alarm of the type of alarm and increase alarm number
Amount, otherwise similarly, the individual demand adjust automatically alarm rule according to user is realized, user experience is good, it is not easy to raw
At the redundant warning information unrelated with user demand, efficiency of alarming is improved.
Specific embodiment
Below with reference to embodiment, technical solution of the present invention is further illustrated.
The technical scheme is that the log alarming system based on user individual feature, including log acquisition module,
Real-time monitoring module, alarm module and alarm rule module；
The log acquisition module arrives collected daily record data storage for the daily record data in acquisition server
The daily record data of storage is sent real-time monitoring module by database, database；
The real-time monitoring module daily record data that library is sent for receiving data, and daily record data inquiry is at least provided
Function, and timing updates each user to the enquiry frequency of the daily record data of every kind of type of alarm；
The alarm module is used to establish the alarm task of different user, and for the alarm task of each user, alarm is appointed
Business obtains the alarm rule of the user preset from preset alarm rule warehouse, and timing detects the corresponding alarm rule of the user
Whether there is update, the corresponding alarm rule of the updated user is obtained when there is update, alarm task poll monitors mould in real time
Whether the daily record data of the user in block meets alarm according to the daily record data that the judgement of the alarm rule of the user is currently read
Condition reads next daily record data if being unsatisfactory for alert if, if meeting alert if obtains the day currently read
The type of alarm of will data, and one is added to the statistical magnitude of the type of alarm of the user, then judge the alarm of the user
Whether the statistical magnitude of type reaches the statistical magnitude threshold value of the type of alarm set in the alarm rule of the user, if not reaching
The warning message of the daily record data currently read is then put into cache pool to threshold value, then proceedes to read next log number
According to, if reaching threshold value, by the warning message and cache pool of the daily record data currently read with the log that currently reads
After the warning message of the daily record data of the identical user of the type of alarm of data is integrated, it is sent to the alarm rule of the user
The terminal alarms equipment of the corresponding responsible person of the preset type of alarm in then, and by the statistical number of the type of alarm of the user
Amount is reset, while deleting the warning message of the daily record data of the type of alarm of the user in cache pool, is then read next
Daily record data；
The alarm rule module is used to obtain each user to the log number of every kind of type of alarm from real-time monitoring module
According to enquiry frequency, then according to each user to the enquiry frequency of the daily record data of every kind of type of alarm and preset inquiry frequency
The corresponding relationship of rate and statistical magnitude threshold value obtains the statistical magnitude threshold value of every kind of type of alarm of each user, then will be every
The statistical magnitude threshold value of every kind of type of alarm of a user is updated into alarm rule warehouse in the corresponding alarm rule of the user,
Wherein enquiry frequency is higher, then the corresponding statistical magnitude threshold value of the enquiry frequency is smaller.
The enquiry frequency of the daily record data for the various type of alarm that the present invention is inquired according to user and preset inquiry
The corresponding relationship of frequency and statistical magnitude threshold value, the statistical magnitude threshold value of corresponding type of alarm in adjust automatically alarm rule, if
The enquiry frequency of the daily record data of a certain type of alarm is higher, illustrates that user more pays close attention to the type of alarm, and the type of alarm pair
The statistical magnitude threshold value answered is again smaller, and then opposite can accelerate the alarm of the type of alarm and increase alarm quantity, on the contrary
Similarly, the individual demand adjust automatically alarm rule according to user is realized, user experience is good, it is not easy to generation and user
The unrelated redundant warning information of demand, alarm efficiency improve, and close wherein preset enquiry frequency is corresponding with statistical magnitude threshold value
System, can be the corresponding relationship of specific enquiry frequency value and statistical magnitude threshold value, be also possible to enquiry frequency value range and system
The corresponding relationship of count number threshold value.
Above-mentioned steps are advanced optimized, specifically may is that based on ELK (elasticsearch, logstash and
Kibana) log handles frame in real time, and log acquisition module can be by the shipper component acquisition server of logstash
Daily record data and monitoring server log storage catalogue variation, and by collected daily record data be output to redis caching,
Daily record data is acquired from redis by the indexer component of logstash and is stored, and is connected by the broker component of logstash
Shipper component and indexer component are connect, the daily record data of storage is sent kafka message-oriented middleware by indexer component,
By kafka message-oriented middleware by daily record data storage to kafka database, daily record data is sent reality by kafka database
When monitoring module.Kafka message-oriented middleware is as the bridge between the processing of data acquisition and storage, at coordination data acquisition and storage
Manage the inconsistent of speed.The daily record data that real-time monitoring module can be sent by logstash reception database, and according to
Preset configuration file send daily record data in elasticsearch after cleaning filtering to daily record data,
Elasticsearch is added to daily record data according to default rule template and is indexed and stored, and passes through elasticsearch
The search API of offer inquires daily record data, and is shown the daily record data of inquiry by kibana.
The daily record data that elasticsearch is obtained as real-time search engine, analysis by logstash filtering, constructs respective index
Elasticsearch quickly is arrived into a large amount of log filing storage, building does not influence search efficiency when indexing.
Embodiment
Below with reference to embodiment, the technical solution that the present invention will be described in detail.
The log alarming system based on user individual feature of this example handles frame based on ELK log in real time and carries out structure
It builds, including log acquisition module, real-time monitoring module, alarm module and alarm rule module；
The log acquisition module of this example is using the daily record data and prison in the shipper component acquisition server of logstash
The variation of server log storage catalogue is controlled, and collected daily record data is output to redis caching, passes through logstash's
Indexer component acquires daily record data from redis and stores, and connects shipper component by the broker component of logstash
With indexer component, the daily record data of storage is sent kafka message-oriented middleware by indexer component, passes through kafka message
Middleware sends real-time monitoring module for daily record data for daily record data storage to kafka database, kafka database.
Real-time monitoring module can receive the daily record data that database is sent by logstash, and be matched according to preset
It sets file and daily record data send daily record data in elasticsearch after cleaning filtering, elasticsearch root
It is added according to default rule template to daily record data and indexes and stored, API pairs of search provided by elasticsearch
Daily record data is inquired, and is shown the daily record data of inquiry by kibana, such as user one passes through real time monitoring
Module polls type of alarm is the daily record data of mistake 401, then sees that is shown in a manner of multi-dimensional report, icon etc. looks into
It askes as a result, real-time monitoring module will record the inquiry operation that user's a pair of type of alarm is the daily record data of mistake 401, and timing
Calculate the enquiry frequency for updating that user's a pair of type of alarm is the daily record data of mistake 401.
Alarm module establishes the alarm task of different user using the real-time analytic unit of storm, such as establishes user's one
Alarm task, and the preset alarm rule of user one is obtained from preset alarm rule warehouse, and timing detects user one and corresponds to
Alarm rule whether have update, the corresponding alarm rule of updated user one, the alarm of user one are obtained when there is update
Task uses the daily record data of user one in elastAlert real-time early warning component poll real-time monitoring module, according to user's one
Whether the daily record data that alarm rule judgement is currently read meets alert if, reads if being unsatisfactory for alert if next
Daily record data obtains the type of alarm of the daily record data currently read if meeting alert if, such as type of alarm is wrong
Accidentally 401, and one is added to the statistical magnitude of the mistake 401 of user one, then judge the mistake 401 of user one statistical magnitude whether
The statistical magnitude threshold value for reaching the mistake 401 set in the alarm rule of user one will currently be read if not up to threshold value
The warning message of daily record data be put into cache pool, then proceed to read next daily record data, will be current if reaching threshold value
The warning message of the daily record data of the mistake 401 of user one carries out whole in the warning message and cache pool of the daily record data read
After conjunction, it is sent to the terminal alarms equipment of preset wrong 401 corresponding responsible person in the alarm rule of user one, and by user
The statistical magnitude of one mistake 401 is reset, while deleting the alarm signal of the daily record data of the mistake 401 of user one in cache pool
Breath, then reads next daily record data；
Alarm rule module obtains the daily record data that user's a pair of type of alarm is mistake 401 from real-time monitoring module and looks into
Frequency is ask, is then the enquiry frequency and preset enquiry frequency of the daily record data of mistake 401 according to user's a pair of type of alarm
With the corresponding relationship of statistical magnitude threshold value, the statistical magnitude threshold value of the mistake 401 of user one is obtained, then by the mistake of user one
401 statistical magnitude threshold value is updated into alarm rule warehouse in the corresponding alarm rule of user one, and wherein user's a pair is alarmed
Type is that the enquiry frequency of the daily record data of mistake 401 is higher, then the statistical magnitude threshold value of the mistake 401 obtained is with regard to smaller.When
As soon as user pay close attention to type of alarm be mistake 401 daily record data when, to its enquiry frequency in real-time monitoring module
It will increase, therefore the statistical magnitude threshold value of mistake 401 will reduce after the alarm rule update of user one, the effect of generation is exactly
401 alarm velocity of mistake of user one is opposite to be accelerated, alarm times relative increase, otherwise when user one no longer pays close attention to alarm
Type be mistake 401 daily record data when, with it is above-mentioned similarly, the effect of generation is exactly the 401 alarm velocity phase of mistake of user one
To delaying, alarm times are opposite to be reduced.
Claims (3)
1. the log alarming system based on user individual feature, including log acquisition module, real-time monitoring module and alarm mould
Block, it is characterised in that: further include alarm rule module；
The log acquisition module is stored for the daily record data in acquisition server, and by collected daily record data to data
The daily record data of storage is sent real-time monitoring module by library, database；
The real-time monitoring module daily record data that library is sent for receiving data, and daily record data is at least provided and inquires function
Can, and timing updates each user to the enquiry frequency of the daily record data of every kind of type of alarm；
The alarm module is used to establish the alarm task of different user, for the alarm task of each user, task of alarming from
Preset alarm rule warehouse obtains the alarm rule of the user preset, and whether timing detects the corresponding alarm rule of the user
There is update, the corresponding alarm rule of the updated user is obtained when there is update, in task poll real-time monitoring module of alarming
Whether the daily record data of the user meets alarm bar according to the daily record data that the judgement of the alarm rule of the user is currently read
Part reads next daily record data if being unsatisfactory for alert if, if meeting alert if obtains the log currently read
The type of alarm of data, and one is added to the statistical magnitude of the type of alarm of the user, then judge the alarm class of the user
Whether the statistical magnitude of type reaches the statistical magnitude threshold value of the type of alarm set in the alarm rule of the user, if not up to
The warning message of the daily record data currently read is then put into cache pool by threshold value, then proceedes to read next daily record data,
If reaching threshold value, by the warning message and cache pool of the daily record data currently read with the daily record data that currently reads
The identical user of type of alarm daily record data warning message integrate after, be sent in the alarm rule of the user
The terminal alarms equipment of the corresponding responsible person of the preset type of alarm, and the statistical magnitude of the type of alarm of the user is clear
Zero, while the warning message of the daily record data of the type of alarm of the user in cache pool is deleted, then read next log
Data；
The alarm rule module is used to obtain each user from real-time monitoring module to the daily record data of every kind of type of alarm
Enquiry frequency, then according to each user to the enquiry frequency of the daily record data of every kind of type of alarm and preset enquiry frequency with
The corresponding relationship of statistical magnitude threshold value obtains the statistical magnitude threshold value of every kind of type of alarm of each user, then by each use
The statistical magnitude threshold value of every kind of type of alarm at family is updated into alarm rule warehouse in the corresponding alarm rule of the user, wherein
Enquiry frequency is higher, then the corresponding statistical magnitude threshold value of the enquiry frequency is smaller.
2. as described in claim 1 based on the log alarming system of user individual feature, it is characterised in that: the log is adopted
Collect the daily record data and monitoring server log storage catalogue in the shipper component acquisition server that module passes through logstash
Variation, and by collected daily record data be output to redis caching, adopted by the indexer component of logstash from redis
Collection daily record data simultaneously stores, and connects shipper component and indexer component, indexer by the broker component of logstash
The daily record data of storage is sent kafka message-oriented middleware by component, is arrived daily record data storage by kafka message-oriented middleware
Daily record data is sent real-time monitoring module by kafka database, kafka database.
3. as described in claim 1 based on the log alarming system of user individual feature, it is characterised in that: the real-time prison
Control module by the daily record data that sends of logstash reception database, and according to preset configuration file to daily record data into
It sends daily record data in elasticsearch after row cleaning filtering, elasticsearch gives according to default rule template
Daily record data addition is indexed and is stored, and is inquired by the search API that elasticsearch is provided daily record data,
And the daily record data of inquiry is shown by kibana.
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| CN110399405A (en) * | 2019-07-26 | 2019-11-01 | 广州虎牙科技有限公司 | Log alarming method, apparatus, system and storage medium |
| CN110825592A (en) * | 2019-11-06 | 2020-02-21 | 北京皮尔布莱尼软件有限公司 | Method and computing device for generating alarm content |
| CN111984845A (en) * | 2020-08-17 | 2020-11-24 | 江苏百达智慧网络科技有限公司 | Website wrongly-written character recognition method and system |
| CN112152823A (en) * | 2019-06-26 | 2020-12-29 | 北京易真学思教育科技有限公司 | Website operation error monitoring method and device and computer storage medium |
| CN113515433A (en) * | 2021-07-28 | 2021-10-19 | 中移（杭州）信息技术有限公司 | Alarm log processing method, device, equipment and storage medium |
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Application publication date: 20190301 |