CN107562603A - A kind of intelligent fault alignment system and method based on linux - Google Patents
A kind of intelligent fault alignment system and method based on linux Download PDFInfo
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Abstract
The invention discloses a kind of intelligent fault alignment system and method based on linux, including log processing module, for being analyzed and processed to the daily record in server；Fault knowledge center module, the daily record after log processing module processing is received, according to the daily record after the processing, build knowledge base；Accident analysis locating module, according to the content of knowledge base, the system failure is positioned；Troubleshooting scheme module, match for providing troubleshooting scheme, and by respective handling scheme and the system failure after being positioned by accident analysis locating module, finally match information is stored in result database.A kind of the intelligent fault alignment system and method based on linux of the present invention compared with prior art, when computer breaks down, is automatically performed fault location, accurate positioning is quick, so as to Upgrade Problem treatment effeciency, shortens maintenance time, it is practical, it is applied widely, it is easy to spread.
Description
Technical field
The present invention relates to computer server technical field, specifically a kind of intelligent fault positioning based on linux
System and method.
Background technology
In the prior art, technical staff typically can run into some problems, conventional place using the server product stage
Reason method is that technical staff checks that daily record solves problem, that is, by checking daily record, log information is analyzed, and finds phase
The fault message answered, solve the failure problems occurred.But this mode manual operation checked realizes that treatment effeciency is low, and
Due to artificial limitation, cause the situation for position inaccurate often occur.Based on this, need one kind badly and can automate and realize that failure is determined
The technology of position.
The content of the invention
The technical assignment of the present invention is to be directed to above weak point, there is provided a kind of intelligent fault positioning system based on linux
System and method.
A kind of intelligent fault alignment system based on linux, including,
Log processing module, for being analyzed and processed to the daily record in server；
Fault knowledge center module, the daily record after log processing module processing is received, according to the daily record after the processing, build knowledge
Storehouse；
Accident analysis locating module, according to the content of knowledge base, the system failure is positioned；
Troubleshooting scheme module, for providing troubleshooting scheme, and by respective handling scheme and by accident analysis positioning mould
The system failure after block positioning matches, and finally match information is stored in result database.
The log processing module is handled the information included in syslog file in different time sections, i.e. root
Daily record is resolved into different documents, physical fault existing for mark according to keyword match, the syslog file includes
System journal, RAID card daily record, BMC daily records, BIOS daily records, driving daily record under linux system, network interface card log information, it is described
Keyword includes temperature, processor, limiting temperature.
The fault knowledge center module to log content by excavating, analysis system failure, by the attribute of failure
Diagnosis rule is generalized into, the fault knowledge storehouse by diagnosis rule divide into several classes's failure is formed, so as to accident analysis positioning mould
Block carries out analyzing and positioning.
The detailed process of formation knowledge base is in the fault knowledge center module：It is first in fault knowledge center module
The document that first log processing module was marked is as training set；Then these training sets are trained again, training process is
Refer to the rule excavated and can effectively classified from these documents, generate grader, sum up diagnosis rule set；Further according to generation
Grader apply on the real time content of system journal, obtain the classification results of current failure, form fault knowledge storehouse.
Diagnosis rule in the knowledge base that the accident analysis locating module is built by fault knowledge center module is to being
System daily record is matched, and the failure in system journal is positioned, and pair that will be prestored with troubleshooting scheme module
Fault solution is answered to be stored in jointly in result database after matching.
The fault message being stored in result database includes the device name that breaks down or model, break down when
Between, fault category, trouble unit, failure rank, failure-description, daily record rank, daily record details, keyword, log path,
Processing scheme corresponding to failure.
Also include data security module, the data security module is used to add the data preserved in result database
It is close, i.e., database is encrypted using AES when result database creates, and decrypted and accessed by counterpart keys, protect
Demonstrate,prove the data safety in result database.
A kind of intelligent fault localization method based on linux, based on said system, its implementation process is to pass through day first
Will processing module will classify after all log file analysis under Linux system；By fault knowledge center module after classification
Journal file in analyze diagnosis rule, form the fault knowledge storehouse by diagnosis rule divide into several classes's failure；By failure
Analyzing and positioning module carries out the matching analysis positioning according to fault knowledge storehouse to the failure in daily record, eventually through troubleshooting scheme
Troubleshooting scheme corresponding to module matching, and troubleshooting scheme is stored in result database.
The specific forming process in the fault knowledge storehouse is：First using the document that log processing module marked as training
Collection；Then these training sets being trained again, training process refers to excavate the rule that can effectively classify from these documents,
Grader is generated, sums up diagnosis rule set；Apply on the real time content of system journal, obtain further according to the grader of generation
The classification results of current failure are taken, fault knowledge storehouse is formed, is preserved in the fault knowledge storehouse including operating system, failure classes
Not, trouble unit, daily record rank, daily record details, keyword, log path, the information of problem description.
Before troubleshooting scheme to be stored in result database, create result database when, include pass through data peace
The step of full module is encrypted：Data security module is entered when result database creates to result database using AES
Row encryption, and counterpart keys are configured, access is decrypted by key, ensures data safety in result database, the encryption is calculated
Method includes AES256 algorithms.
Compared to the prior art a kind of the intelligent fault alignment system and method based on linux of the present invention, has following
Beneficial effect：
A kind of the intelligent fault alignment system and method based on linux of the present invention, when computer breaks down, is automatically performed
Fault location, accurate positioning is quick, so as to Upgrade Problem treatment effeciency, shortens maintenance time, practical, applied widely
It is general, it is easy to spread.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
The embodiment of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing of offer obtains other accompanying drawings.
Accompanying drawing 1 is the specific implementation schematic diagram of intelligent fault alignment system.
Embodiment
In order that those skilled in the art more fully understand the solution of the present invention, with reference to embodiment to this
Invention is described in further detail.Obviously, described embodiment is only part of the embodiment of the present invention, rather than all
Embodiment.Based on the embodiment in the present invention, those of ordinary skill in the art institute under the premise of creative work is not made
The every other embodiment obtained, belongs to the scope of protection of the invention.
The purpose of the invention to be realized：
Build fault knowledge center.
Fault location.
Unified troubleshooting scheme description scheme, accurate troubleshooting scheme.
Based on above-mentioned purpose, as shown in Figure 1, the present invention provides a kind of intelligent fault alignment system based on linux, its
Structure includes,
Log processing module, for being analyzed and processed to the daily record in server；
Fault knowledge center module, the daily record after log processing module processing is received, according to the daily record after the processing, build knowledge
Storehouse；
Accident analysis locating module, according to the content of knowledge base, the system failure is positioned；
Troubleshooting scheme module, for providing troubleshooting scheme, and by respective handling scheme and by accident analysis positioning mould
The system failure after block positioning matches, and finally match information is stored in result database.
Log processing module is handled the various information included in syslog file in different time sections, for event
Barrier Knowledge Center structure is prepared, it is necessary to according to time series, and daily record is resolved into different documents simultaneously according to keyword match
It is labeled according to the situation of physical fault, prepares training set.The syslog file includes the system day under linux system
Will, RAID card daily record, BMC daily records, BIOS daily records, driving daily record, network interface card log information, the keyword include temperature
Temperature, going high, processor processor, limiting temperature Thermal Trip etc..
The fault knowledge center module to log content by excavating, analysis system failure, by the attribute of failure
Diagnosis rule is generalized into, the fault knowledge storehouse by diagnosis rule divide into several classes's failure is formed, so as to accident analysis positioning mould
Block carries out analyzing and positioning.
The detailed process of formation knowledge base is in the fault knowledge center module：It is first in fault knowledge center module
The document that first log processing module was marked is as training set；Then these training sets are trained again, training process is
Refer to the rule excavated and can effectively classified from these documents, generate grader, sum up diagnosis rule set；Further according to generation
Grader apply on the real time content of system journal, obtain the classification results of current failure, form fault knowledge storehouse.
Diagnosis rule in the knowledge base that the accident analysis locating module is built by fault knowledge center module is to being
System daily record is matched, and the failure in system journal is positioned, and pair that will be prestored with troubleshooting scheme module
Fault solution is answered to be stored in jointly in result database after matching.
The fault message being stored in result database includes the device name that breaks down or model, break down when
Between, fault category, trouble unit, failure rank, failure-description, daily record rank, daily record details, keyword, log path,
Processing scheme corresponding to failure.
Also include data security module, the data security module is used to add the data preserved in result database
It is close, i.e., database is encrypted using AES when result database creates, and decrypted and accessed by counterpart keys, protect
Demonstrate,prove the data safety in result database.
A kind of intelligent fault localization method based on linux, the intelligent fault mainly carried out to the daily record in server are determined
Position, the matching analysis positioning failure is carried out to daily record according to the knowledge base at fault knowledge center, most troubleshooting scheme stores at last
In database.
This method is based on said system, and its implementation process is, first by log processing module by the institute under Linux system
Classify after having log file analysis；Diagnosis rule is analyzed from sorted journal file by fault knowledge center module,
Form the fault knowledge storehouse by diagnosis rule divide into several classes's failure；By accident analysis locating module according to fault knowledge storehouse pair
Failure in daily record carries out the matching analysis positioning, eventually through troubleshooting scheme corresponding to the matching of troubleshooting scheme module,
And troubleshooting scheme is stored in result database.
The specific forming process in the fault knowledge storehouse is：First using the document that log processing module marked as training
Collection；Then these training sets being trained again, training process refers to excavate the rule that can effectively classify from these documents,
Grader is generated, sums up diagnosis rule set；Apply on the real time content of system journal, obtain further according to the grader of generation
The classification results of current failure are taken, fault knowledge storehouse is formed, is preserved in the fault knowledge storehouse including operating system, failure classes
Not, trouble unit, daily record rank, daily record details, keyword, log path, the information of problem description.
From above procedure, the renewal of fault knowledge consolidated storage no longer needs expert to be participated in, it is only necessary to artificial addition
New log information renewal training set just can generate new grader（The set of diagnosis rule）.The knowledge base mainly combs allusion quotation
Type failure, the important attribute of failure is generalized into diagnosis rule, lifts knowledge accumulation.
Before troubleshooting scheme to be stored in result database, create result database when, include pass through data peace
The step of full module is encrypted：Data security module is entered when result database creates to result database using AES
Row encryption, and counterpart keys are configured, access is decrypted by key, ensures data safety in result database, the encryption is calculated
Method includes AES256 algorithms.
The present invention contrasts keyword, directly obtains fault solution, solve technical staff according to the knowledge base of structure
Check that log processing problem efficiency is low, the problem of position inaccurate.
By embodiment above, the those skilled in the art can readily realize the present invention.Herein
Apply specific case to be set forth the principle and embodiment of the present invention, the explanation of above example is only intended to help
Understand the method and its core concept of the present invention.It should be pointed out that for those skilled in the art, do not taking off
On the premise of from the principle of the invention, some improvement and modification can also be carried out to the present invention, these are improved and modification also falls into this
In invention scope of the claims.
Claims (10)
- A kind of 1. intelligent fault alignment system based on linux, it is characterised in that including,Log processing module, for being analyzed and processed to the daily record in server；Fault knowledge center module, the daily record after log processing module processing is received, according to the daily record after the processing, build knowledge Storehouse；Accident analysis locating module, according to the content of knowledge base, the system failure is positioned；Troubleshooting scheme module, for providing troubleshooting scheme, and by respective handling scheme and by accident analysis positioning mould The system failure after block positioning matches, and finally match information is stored in result database.
- A kind of 2. intelligent fault alignment system based on linux according to claim 1, it is characterised in that the daily record Processing module is handled the information included in syslog file in different time sections, i.e., according to keyword match by day Will resolves into different documents, physical fault existing for mark, and the syslog file includes the system day under linux system Will, RAID card daily record, BMC daily records, BIOS daily records, driving daily record, network interface card log information, the keyword include temperature, processing Device, limiting temperature.
- A kind of 3. intelligent fault alignment system based on linux according to claim 2, it is characterised in that the failure Knowledge Center's module to log content by excavating, analysis system failure, by the attribute induction of failure into diagnosis rule, shape Into the fault knowledge storehouse by diagnosis rule divide into several classes's failure, so that accident analysis locating module carries out analyzing and positioning.
- A kind of 4. intelligent fault alignment system based on linux according to claim 3, it is characterised in that the failure The detailed process of formation knowledge base is in Knowledge Center's module：In fault knowledge center module, first by log processing module The document marked is as training set；Then these training sets are trained again, training process refers to dig from these documents The rule that can effectively classify is excavated, grader is generated, sums up diagnosis rule set；Apply further according to the grader of generation and be Unite on the real time content of daily record, obtain the classification results of current failure, form fault knowledge storehouse.
- 5. according to a kind of any described intelligent fault alignment systems based on linux of claim 1-4, it is characterised in that institute The diagnosis rule stated in the knowledge base that accident analysis locating module is built by fault knowledge center module is carried out to system journal Matching, the failure in system journal is positioned, and solves the corresponding failure prestored with troubleshooting scheme module Scheme is stored in result database jointly after matching.
- 6. a kind of intelligent fault alignment system based on linux according to claim 5, it is characterised in that be stored in knot Fault message in fruit database includes the device name or model, the time broken down, fault category, failure to break down Processing side corresponding to part, failure rank, failure-description, daily record rank, daily record details, keyword, log path, failure Case.
- 7. a kind of intelligent fault alignment system based on linux according to claim 5, it is characterised in that also include number According to security module, the data security module is used to the data preserved in result database be encrypted, i.e., in result database Database is encrypted using AES during establishment, and is decrypted and accessed by counterpart keys, is ensured in result database Data safety.
- A kind of 8. intelligent fault localization method based on linux, it is characterised in that based on the system described in claim 1-7, its Implementation process is that will be classified first by log processing module after all log file analysis under Linux system；Pass through failure Knowledge Center's module analyzes diagnosis rule from sorted journal file, and formation passes through diagnosis rule divide into several classes's failure Fault knowledge storehouse；The matching analysis positioning is carried out to the failure in daily record according to fault knowledge storehouse by accident analysis locating module, Eventually through troubleshooting scheme corresponding to the matching of troubleshooting scheme module, and troubleshooting scheme is stored in result data In storehouse.
- A kind of 9. intelligent fault localization method based on linux according to claim 8, it is characterised in that the failure The specific forming process of knowledge base is：The document that log processing module was marked first is as training set；Then again to these Training set is trained, and training process refers to excavate the rule that can effectively classify from these documents, generates grader, is summarized Be out of order regular collection；Applied further according to the grader of generation on the real time content of system journal, obtain point of current failure Class result, fault knowledge storehouse is formed, is preserved in the fault knowledge storehouse including operating system, fault category, trouble unit, daily record Rank, daily record details, keyword, log path, the information of problem description.
- 10. a kind of intelligent fault localization method based on linux according to claim 8 or claim 9, it is characterised in that inciting somebody to action Troubleshooting scheme be stored in result database before, when creating result database, in addition to added by data security module Close step：Result database is encrypted using AES when result database creates for data security module, and is matched somebody with somebody Counterpart keys are put, access is decrypted by key, ensures data safety in result database, the AES includes AES256 Algorithm.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108897666A (en) * | 2018-06-29 | 2018-11-27 | 郑州云海信息技术有限公司 | Server failure log generation method and relevant device |
| CN108897665A (en) * | 2018-06-29 | 2018-11-27 | 平安科技（深圳）有限公司 | Blog management method, device, computer equipment and storage medium |
| CN109445978A (en) * | 2018-11-13 | 2019-03-08 | 郑州云海信息技术有限公司 | A kind of server failure processing method and device |
| CN109542661A (en) * | 2018-11-23 | 2019-03-29 | 北京北纬通信科技股份有限公司 | Log analysis prompt system and method based on content characteristic |
| CN110716843A (en) * | 2019-09-09 | 2020-01-21 | 深圳壹账通智能科技有限公司 | System fault analysis processing method and device, storage medium and electronic equipment |
| CN112068981A (en) * | 2020-09-24 | 2020-12-11 | 中国人民解放军国防科技大学 | Knowledge base-based fault scanning recovery method and system in Linux operating system |
| CN112988537A (en) * | 2021-03-11 | 2021-06-18 | 山东英信计算机技术有限公司 | Server fault diagnosis method and device and related equipment |
| CN115730020A (en) * | 2022-11-22 | 2023-03-03 | 哈尔滨工程大学 | Automatic driving data monitoring method and system based on MySQL database log analysis |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101833497A (en) * | 2010-03-30 | 2010-09-15 | 山东高效能服务器和存储研究院 | Computer fault management system based on expert system method |
| CN102662788A (en) * | 2012-04-28 | 2012-09-12 | 浪潮电子信息产业股份有限公司 | Computer system fault diagnosis decision and processing method |
| CN103871003A (en) * | 2014-03-31 | 2014-06-18 | 国家电网公司 | Power distribution network fault diagnosis method utilizing historical fault data |
| CN106897193A (en) * | 2017-02-28 | 2017-06-27 | 郑州云海信息技术有限公司 | A kind of monitoring and operation managing system of the cloud data center based on ITIL |
-
2017
- 2017-09-25 CN CN201710887066.0A patent/CN107562603A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101833497A (en) * | 2010-03-30 | 2010-09-15 | 山东高效能服务器和存储研究院 | Computer fault management system based on expert system method |
| CN102662788A (en) * | 2012-04-28 | 2012-09-12 | 浪潮电子信息产业股份有限公司 | Computer system fault diagnosis decision and processing method |
| CN103871003A (en) * | 2014-03-31 | 2014-06-18 | 国家电网公司 | Power distribution network fault diagnosis method utilizing historical fault data |
| CN106897193A (en) * | 2017-02-28 | 2017-06-27 | 郑州云海信息技术有限公司 | A kind of monitoring and operation managing system of the cloud data center based on ITIL |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108897666A (en) * | 2018-06-29 | 2018-11-27 | 郑州云海信息技术有限公司 | Server failure log generation method and relevant device |
| CN108897665A (en) * | 2018-06-29 | 2018-11-27 | 平安科技（深圳）有限公司 | Blog management method, device, computer equipment and storage medium |
| CN108897665B (en) * | 2018-06-29 | 2021-06-15 | 平安科技（深圳）有限公司 | Log management method and device, computer equipment and storage medium |
| CN109445978A (en) * | 2018-11-13 | 2019-03-08 | 郑州云海信息技术有限公司 | A kind of server failure processing method and device |
| CN109542661A (en) * | 2018-11-23 | 2019-03-29 | 北京北纬通信科技股份有限公司 | Log analysis prompt system and method based on content characteristic |
| CN110716843A (en) * | 2019-09-09 | 2020-01-21 | 深圳壹账通智能科技有限公司 | System fault analysis processing method and device, storage medium and electronic equipment |
| CN110716843B (en) * | 2019-09-09 | 2022-11-22 | 深圳壹账通智能科技有限公司 | System fault analysis processing method and device, storage medium and electronic equipment |
| CN112068981A (en) * | 2020-09-24 | 2020-12-11 | 中国人民解放军国防科技大学 | Knowledge base-based fault scanning recovery method and system in Linux operating system |
| CN112068981B (en) * | 2020-09-24 | 2022-06-21 | 中国人民解放军国防科技大学 | Knowledge base-based fault scanning recovery method and system in Linux operating system |
| CN112988537A (en) * | 2021-03-11 | 2021-06-18 | 山东英信计算机技术有限公司 | Server fault diagnosis method and device and related equipment |
| CN115730020A (en) * | 2022-11-22 | 2023-03-03 | 哈尔滨工程大学 | Automatic driving data monitoring method and system based on MySQL database log analysis |
| CN115730020B (en) * | 2022-11-22 | 2023-10-10 | 哈尔滨工程大学 | Automatic driving data monitoring method and monitoring system based on MySQL database log analysis |
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