CN107517131A - A kind of analysis and early warning method based on log collection - Google Patents
A kind of analysis and early warning method based on log collection Download PDFInfo
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- CN107517131A CN107517131A CN201710771927.9A CN201710771927A CN107517131A CN 107517131 A CN107517131 A CN 107517131A CN 201710771927 A CN201710771927 A CN 201710771927A CN 107517131 A CN107517131 A CN 107517131A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/069—Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/18—File system types
- G06F16/1805—Append-only file systems, e.g. using logs or journals to store data
- G06F16/1815—Journaling file systems
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/147—Network analysis or design for predicting network behaviour
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
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Abstract
The invention belongs to computer operating system technical field, it discloses a kind of analysis and early warning method based on log collection, solve the problems, such as in conventional art can not real-time analysis and early warning, while realize and customize early warning scheme.The present invention obtains the running log of whole system using log collection software, is analyzed daily record by real-time big data analytical technology, accurately obtains the information in daily record；The log content inquired about using distributed type assemblies after processing in real time, the early warning task reached the standard grade is monitored in real time simultaneously, when the result of inquiry meets the early warning rule of early warning task, being specifically responsible for people and sending mail for the task is obtained, completes the accurate distributed quasi real time inquiry early warning task of whole system.
Description
Technical field
The invention belongs to computer operating system technical field, and in particular to a kind of analysis and early warning side based on log collection
Method.
Background technology
With developing rapidly for enterprise's IT business system, network size expands rapidly, main frame, the network equipment, application software
Quantity is on the increase, and service resources access, operational ton is continuously increased, and provides business on a large amount of lines, because accusing of the measure inside is ineffective
Caused by safety problem happen occasionally.The journal function for relying on equipment itself in each communication network, service network and each support system enters
Row monitoring way can not meet enterprise at present and Future Services Development requirement.Daily record monitoring and early warning platform relies on greatly
Data platform, it is possible to achieve the daily record to each cluster of enterprise and business is managed collectively and monitored, and is adopted by daily record
The mechanism such as collection, daily record cleaning, blog search, log statistic, daily record early warning, can not only monitor online service, and can pass through
Daily record carries out data analysis and data sheet, more fully grasps the overall condition of product, while keyword can be utilized real-time
Inquiry log information, so as to so that business personnel's fast positioning daily record, improves the ability pinpointed the problems with process problem.
Daily record (log) this term actually refers to the set of the log information for showing some event overall pictures, and one
Inside bar log information the day of web page request resource is accessed containing many useful data, such as web server record user
Will.Simple log analysis function can be completed as the log collection analysis framework increased income using ELK in the prior art, but
It is that it does not have real-time, therefore application system orientation problem postpones, and triggers a series of chain problem；One can not be met
Monitored while application system different functional module, the exploitation of customization can not be realized.
The content of the invention
The technical problems to be solved by the invention are：A kind of analysis and early warning method based on log collection is proposed, solves to pass
In system technology can not real-time analysis and early warning the problem of, while realize customize early warning scheme.
The technical solution adopted by the present invention is as follows：
A kind of analysis and early warning method based on log collection, comprises the following steps：
A. analyze the running of goal systems and carry out daily record output；
B. self-defined flume source, the real-time collection to Log Directory and file is realized；Self-defined flume sink,
The event events of collection are sent to kafka；
C. the log information in kafka is analyzed, using kafka as storm's as real-time analytic unit using Storm
Spout data sources read data, the effective information in daily record are extracted according to business demand, then by structuring and non-structured
Daily record is respectively stored into different mongo databases；
D. in the newly-built daily record early warning rule in front end, establish early warning task and mission requirements is set；
E. early warning task requests are submitted, data are arrived into task specific configuration information storage after keeper's examination ＆ verification passes through
In storehouse；
F. each early warning task is monitored in real time.
As further optimization, step f is specifically included：
F1. early warning task controller reads the storage location of early warning task, obtains the relevant information of the task；
F2. after early warning controller confirms that the task has been reached the standard grade, call query interface to the data of mongo databases according to rope
Introduce row inquiry；
F3. early warning controller matches according to early warning rule to the inquiry data of acquisition, if matching result, and
The result number has reached the number for sending mail, then sends mail, preserves the time for sending mail；
F4. after mail is sent, program is run again according to the monitoring frequency of setting, and wanting for mail is sent if arriving again at
Ask, then check that last time sends the time of mail, if time interval not up to sends mail compartment every not sending twice；If surpass
Time interval is crossed, then is sent again；
F5. f1~f4 steps are repeated, realize the real-time of early warning.
Optimize as further, in step f1, the relevant information of the task includes：Upper down status, rule, monitoring frequency
Rate, mail sender's information.
As further optimization, in step c, Kafka is as message-oriented middleware solving gathered data speed and processing
The nonsynchronous situation of speed.
Optimize as further, in step d, the mission requirements includes early warning monitoring frequency, corresponding early warning task is born
Blame people.
The beneficial effects of the invention are as follows：The running log of whole system is obtained using log collection software, by big in real time
Data analysis technique is analyzed daily record, accurately obtains the information in daily record；Processing in real time is inquired about using distributed type assemblies
Log content afterwards, while the early warning task to having reached the standard grade is monitored in real time, when the result of inquiry meets early warning task
During early warning rule, being specifically responsible for people and sending mail for the task is obtained, the accurate distribution for completing whole system is quasi real time looked into
Ask early warning task；The early warning that the present invention can freely be efficiently completed complexity in log collection stage and daily record early warning stage is appointed
Business, system development and maintenance process are fitted entirely into, improve in development process and repair abnormal efficiency, reduce the work of attendant
Measure, reduce the waste of resource in development process.
Brief description of the drawings
Fig. 1 is the flume+kafka log collection frameworks in the present invention；
Fig. 2 is that the storm log analysis in the present invention handles framework；
Fig. 3 is the daily record early warning framework in the present invention；
Fig. 4 is daily record early warning flow chart.
Embodiment
The present invention is directed to propose a kind of analysis and early warning method based on log collection, solves in real time to divide in conventional art
The problem of analysing early warning, while realize and customize early warning scheme.
The present invention can provide daily record based on the Real-Time Components such as Storm+kafka+solr in the case of near real-time
Early warning, the adaptability and maintainability of system are improved, help enterprise to enter the real-time monitoring of business, service exception on line fixed in time
The functions such as position, business datum trend analysis, server security analysis and database performance index analysis.
In specific implementation, the analysis and early warning method based on log collection in the present invention comprises the following steps：
A) running of goal systems is analyzed, daily record output, structuring or unstructured are carried out in main technology point
Daily record.
B) system journal is acquired and analyzed in real time, using flume+kafka+storm frameworks, by collection
Daily record is stored in mongo databases.
C) self-defined flume source, the real-time collection to Log Directory and file is realized；Self-defined flume sink,
The event events of collection are sent to kafka.
D) because the speed of flume gathered datas and the speed of data processing are not necessarily synchronous, message-oriented middleware is configured
Kafka does the buffering of message.Distributed kafka clusters are configured, the daily record of flume collections is completely reliable to be sent to kafka.
E) using Storm as real-time analytic unit, the log information in kafka is analyzed, by structuring and unstructured
Daily record be respectively stored into different mongo databases.Complete whole log collection analysis process.
F) in the newly-built daily record early warning rule in front end, such as the rule using keyword " 504 " as early warning, early warning task is established,
The mission requirements such as early warning monitoring frequency and corresponding early warning task leader is set.Submit early warning task requests, keeper's inspection
Make a thorough investigation of and ask, confirm after having no problem by the request.If the early warning task by clicking on by by that can be reached the standard grade to run this
Task, can also be offline by operating task.
Early warning task start, main processing step are as follows:
F1. customized early warning task controller reads the storage location of task, obtains upper down status, the rule of the task
Then, the information such as monitoring frequency, mail sender.
F2. after early warning controller confirms that the task has been reached the standard grade, query interface will be called, the data of mongo databases is pressed
According to search index.
F3. early warning controller matches according to early warning rule to the inquiry of acquisition, if matching result, and the knot
Fruit number has reached the number for sending mail, then sends mail, preserves the time for sending mail.
F4. after mail is sent, program is run again according to the monitoring frequency of setting, and wanting for mail is sent if arriving again at
Ask, then check that last time sends the time of mail, if time interval not up to sends mail compartment every not sending twice；If surpass
Cross, then send again.
F5. f1~f4 steps are repeated, realize the real-time of early warning system.
Invention is further illustrated below in conjunction with the accompanying drawings：
As shown in figure 1, this figure is flume+kafka log collection frameworks：Flume log collections framework using source,
Tri- components of channel, sink complete the circulation of whole data flow, source collection log informations, are passed by channel
To pass, pass to sink and be further processed or store, the system uses sink components of the kafka sink as flume,
Purpose is that coordination flume source components and sink components are coordinated in the collection of data and the inconsistent of processing, kafka
As reliable message queue, it can ensure that every message is all fully processed, and speed is quickly, can handle completely very big
Data flow.The source components of Flume collection daily records can use the component carried, can also Custom component.Only need to inherit
AbstractSource simultaneously realizes EventDrivenSource and Configurable, and self-defined source components can be very
The cofree acquisition daily record of big degree, and the useless daily record in part can be rejected.Kafka Message Queuing systems are by flume's
Sink produces component Producer as message, by Zookeeper coordination, sends a message to kafka clusters
Brokers, the present invention is in order to meet the requirement of processing daily record in real time, not using traditional Hadoop clusters, but uses real
When computing Storm frameworks, complete the further processing of whole log stream.
As shown in Fig. 2 this figure is the logging process after Storm processing collections.The specific component of Storm processing procedures is
Spout and Bolt, Spout are responsible for external message stream being sent to inside storm, the source as storm processing message；Bolt groups
Part is specifically responsible for the log analysis process of each step, and final result storage to Mongo or MySql etc. is locally stored,
It can also be stored in distributed data base hive.Storm can realize laterally expansion as streaming computing framework in each component,
Increase computing capability, improve arithmetic speed.Storm receives the daily record in kafka in the present invention, by series of computation by structure
Change and different processing is done in unstructured daily record, extract useful information, and add the attribute such as daily record storage time of response
Deng completing the analyzing and processing process of daily record, final result be stored in the databases such as mongo, inquired about for early warning system.
Fig. 3 is daily record early warning framework, and early warning framework configures the page by front-end task and back end task handles two parts and formed.
The front-end configuration page configures early warning task, stores mission bit stream after examination ＆ verification according to developer and operation maintenance personnel requirement
To database, used for early warning controller.
Fig. 4 is the carry out early warning process chart of early warning system, specific as follows：
1. early warning system starts, run as background task.
2. early warning system and log collection analysis system combine, searched for the result log of Log Analysis System as early warning
Data source.
3. early warning task configuration center configures early warning task, audited by keeper and after by the task concrete configuration
Database is arrived in information storage
4. control centre of the early warning system controller as whole system, it is responsible for the operation of whole system, according to second level
Design real-time retrieval assignment database, the log-on data search engine if new task is obtained, according to the regular right of task configuration
Database is scanned for operating, and search engine is inquired about according to index, can realize data retrieval service quasi real time, specifically
Search engine be solrcloud clusters, configuration process is not explained in detail again
5. search engine is according to Mission Rules Guidelines searching database, return Query Result, if the Query Result is not sky,
Statistical query result number, and be compared with early warning task configuration parameter, mail condition is sent if reached, returns to mark
To controller, controller obtains the mark, sends mail to related personnel, and records this and send the mail time
6. database search engine continues search for database according to setting retrieval interval, and repeats search service and send postal
Part service, it is to prevent because some period result is excessively intensive to set retrieval interval, causes mail to repeat asking for transmission
Topic.
7. early warning system continuous service, High Availabitity, high practical service are provided for goal systems.
Claims (5)
- A kind of 1. analysis and early warning method based on log collection, it is characterised in that comprise the following steps：A. analyze the running of goal systems and carry out daily record output；B. self-defined flume source, the real-time collection to Log Directory and file is realized；Self-defined flume sink, will be adopted The event events of collection are sent to kafka；C. the log information in kafka, the spout using kafka as storm are analyzed as real-time analytic unit using Storm Data source reads data, the effective information in daily record is extracted according to business demand, then by structuring and non-structured daily record It is respectively stored into different mongo databases；D. in the newly-built daily record early warning rule in front end, establish early warning task and mission requirements is set；E. early warning task requests are submitted, database is arrived into task specific configuration information storage after keeper's examination ＆ verification passes through In；F. each early warning task is monitored in real time.
- A kind of 2. analysis and early warning method based on log collection as claimed in claim 1, it is characterised in thatStep f is specifically included：F1. early warning task controller reads the storage location of early warning task, obtains the relevant information of the task；F2. after early warning controller confirms that the task has been reached the standard grade, call query interface to the data of mongo databases according to index into Row inquiry；F3. early warning controller matches according to early warning rule to the inquiry data of acquisition, if matching result, and the knot Fruit number has reached the number for sending mail, then sends mail, preserves the time for sending mail；F4. after mail is sent, program is run again according to the monitoring frequency of setting, if arriving again at the requirement for sending mail, Then check that last time sends the time of mail, if time interval not up to sends mail compartment every not sending twice；If exceed Between be spaced, then send again；F5. f1~f4 steps are repeated, realize the real-time of early warning.
- A kind of 3. analysis and early warning method based on log collection as claimed in claim 2, it is characterised in that in step f1, institute Stating the relevant information of task includes：Upper down status, rule, monitoring frequency, mail sender's information.
- A kind of 4. analysis and early warning method based on log collection as claimed in claim 1, it is characterised in that in step c, Kafka is as message-oriented middleware solving gathered data speed and the nonsynchronous situation of processing speed.
- 5. a kind of analysis and early warning method based on log collection as claimed in claim 1, it is characterised in that described in step d Mission requirements includes early warning monitoring frequency, corresponding early warning task leader.
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Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107729214A (en) * | 2017-10-13 | 2018-02-23 | 福建富士通信息软件有限公司 | A kind of visual distributed system monitors O＆M method and device in real time |
| CN108259269A (en) * | 2017-12-30 | 2018-07-06 | 上海陆家嘴国际金融资产交易市场股份有限公司 | The monitoring method and system of the network equipment |
| CN108306980A (en) * | 2018-03-06 | 2018-07-20 | 北京工业大学 | A kind of engineering flight support big data Log Analysis System |
| CN109032824A (en) * | 2018-05-31 | 2018-12-18 | 康键信息技术（深圳）有限公司 | Database method of calibration, device, computer equipment and storage medium |
| CN109144817A (en) * | 2018-08-03 | 2019-01-04 | 江苏满运软件科技有限公司 | A kind of daily record data monitoring system and method |
| CN109274540A (en) * | 2018-11-16 | 2019-01-25 | 四川长虹电器股份有限公司 | A kind of web access log processing method based on storm |
| CN109656792A (en) * | 2018-11-02 | 2019-04-19 | 深圳市快付通金融网络科技服务有限公司 | Applied performance analysis method, apparatus, computer equipment and storage medium based on network call log |
| CN110245120A (en) * | 2019-06-19 | 2019-09-17 | 北京百度网讯科技有限公司 | The daily record data processing method of streaming computing system and streaming computing system |
| CN110309150A (en) * | 2019-06-14 | 2019-10-08 | 杭州迪普科技股份有限公司 | A kind of log storage, querying method and device |
| CN110569178A (en) * | 2019-09-12 | 2019-12-13 | 成都中科大旗软件股份有限公司 | interface early warning method and system based on big data platform |
| CN111078496A (en) * | 2019-11-29 | 2020-04-28 | 联想(北京)有限公司 | Data monitoring method, platform and storage medium |
| CN111652616A (en) * | 2020-07-07 | 2020-09-11 | 中国银行股份有限公司 | Transaction data real-time monitoring method and device |
| CN113612816A (en) * | 2021-07-06 | 2021-11-05 | 深圳市酷开网络科技股份有限公司 | Data acquisition method, system, terminal and computer readable storage medium |
| CN113810475A (en) * | 2021-08-30 | 2021-12-17 | 中国电子科技集团公司第五十四研究所 | Wifi probe equipment management and control system based on big data architecture |
| CN114143166A (en) * | 2021-11-12 | 2022-03-04 | 锐捷网络股份有限公司 | Electronic equipment copy-down test monitoring method and device, electronic equipment and storage medium |
| CN114489598A (en) * | 2022-01-18 | 2022-05-13 | 徐工汉云技术股份有限公司 | Storm task management and scheduling method |
| CN114584457A (en) * | 2022-03-22 | 2022-06-03 | 北京结慧科技有限公司 | Log analysis alarm method and platform for system |
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| CN107729214B (en) * | 2017-10-13 | 2021-03-09 | 中电福富信息科技有限公司 | Visual distributed system real-time monitoring operation and maintenance method and device |
| CN107729214A (en) * | 2017-10-13 | 2018-02-23 | 福建富士通信息软件有限公司 | A kind of visual distributed system monitors O＆M method and device in real time |
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| CN108306980A (en) * | 2018-03-06 | 2018-07-20 | 北京工业大学 | A kind of engineering flight support big data Log Analysis System |
| CN109032824A (en) * | 2018-05-31 | 2018-12-18 | 康键信息技术（深圳）有限公司 | Database method of calibration, device, computer equipment and storage medium |
| CN109144817A (en) * | 2018-08-03 | 2019-01-04 | 江苏满运软件科技有限公司 | A kind of daily record data monitoring system and method |
| CN109656792A (en) * | 2018-11-02 | 2019-04-19 | 深圳市快付通金融网络科技服务有限公司 | Applied performance analysis method, apparatus, computer equipment and storage medium based on network call log |
| CN109274540A (en) * | 2018-11-16 | 2019-01-25 | 四川长虹电器股份有限公司 | A kind of web access log processing method based on storm |
| CN110309150A (en) * | 2019-06-14 | 2019-10-08 | 杭州迪普科技股份有限公司 | A kind of log storage, querying method and device |
| CN110245120A (en) * | 2019-06-19 | 2019-09-17 | 北京百度网讯科技有限公司 | The daily record data processing method of streaming computing system and streaming computing system |
| CN110569178A (en) * | 2019-09-12 | 2019-12-13 | 成都中科大旗软件股份有限公司 | interface early warning method and system based on big data platform |
| CN111078496A (en) * | 2019-11-29 | 2020-04-28 | 联想(北京)有限公司 | Data monitoring method, platform and storage medium |
| CN111652616A (en) * | 2020-07-07 | 2020-09-11 | 中国银行股份有限公司 | Transaction data real-time monitoring method and device |
| CN111652616B (en) * | 2020-07-07 | 2023-11-21 | 中国银行股份有限公司 | Transaction data real-time monitoring method and device |
| CN113612816A (en) * | 2021-07-06 | 2021-11-05 | 深圳市酷开网络科技股份有限公司 | Data acquisition method, system, terminal and computer readable storage medium |
| CN113810475A (en) * | 2021-08-30 | 2021-12-17 | 中国电子科技集团公司第五十四研究所 | Wifi probe equipment management and control system based on big data architecture |
| CN114143166A (en) * | 2021-11-12 | 2022-03-04 | 锐捷网络股份有限公司 | Electronic equipment copy-down test monitoring method and device, electronic equipment and storage medium |
| CN114489598A (en) * | 2022-01-18 | 2022-05-13 | 徐工汉云技术股份有限公司 | Storm task management and scheduling method |
| CN114584457A (en) * | 2022-03-22 | 2022-06-03 | 北京结慧科技有限公司 | Log analysis alarm method and platform for system |
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Application publication date: 20171226 |