CN104378262A - Intelligent monitoring analyzing method and system under cloud computing - Google Patents
Intelligent monitoring analyzing method and system under cloud computing Download PDFInfo
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- CN104378262A CN104378262A CN201410664711.9A CN201410664711A CN104378262A CN 104378262 A CN104378262 A CN 104378262A CN 201410664711 A CN201410664711 A CN 201410664711A CN 104378262 A CN104378262 A CN 104378262A
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Abstract
The invention provides an intelligent monitoring analyzing method and system under cloud computing. The intelligent monitoring analyzing method and system are applied to the field of intelligent monitoring. The method includes the following steps that a monitoring strategy maintaining module issues a monitoring strategy to an information collecting module; the information collecting module conducts data monitoring and sends a monitoring result to a resource allocation module, an alarming module and a trend prediction module according to the monitoring strategy; the resource allocation module, the alarming module and the trend prediction module analyze the monitoring result and conduct control processing. According to the intelligent monitoring analyzing method and system, collected data can be analyzed, and therefore the problems, which may exist, of resources under a cloud computing platform can be prevented in advance; alarming can be conducted automatically in time at the moment a fault happens.
Description
Technical field
The present invention relates to field of intelligent monitoring, particularly relate to intelligent monitoring analytical method and system under a kind of cloud computing.
Background technology
Present stage, cloud computing has had many cases to enter operation stage, the IT giants such as external Amazon, Google successful implementation cloud computing all, and earns abundant income; The telecom operators such as domestic China Telecom, China Mobile, the Internet enterprises such as Sina, Alibaba, Tengxun, Baidu are also all implementing cloud computing in varying degrees, various places government also constantly sets up cloud computing platform, to promote cloud computing in wider application, and drive the development of local economy.
Although cloud computing platform solution is numerous, but great majority face identical intelligent monitoring problem, a conduct monitoring at all levels and trend prediction can not be carried out to the platform of current operation, even if the Amazon cloud platform AWS that business model is extremely successful, deficiency in this respect is also clearly, this platform is Service supportive monitoring and trend prediction not, and as other Open Source Platform cloud openstack, cloudstack, Eucalyptus etc. also all in various degree at intelligent monitoring Shortcomings in this.
Existing typical cloud computing platform there is subject matter and deficiency is summarized as follows:
Part also will be monitored the resource under platform by third-party monitoring solution, adds the difficulty of butt-joint; Partial flats does not provide alarm mechanism, does not arrange threshold values to monitored item (cpu busy percentage, memory usage), note abnormalities or fault time can auto-alarming; Not to the data analysis monitored, to predicting by Problems existing; From the angle of service, condition monitoring is not carried out to service, automatically to adjust the resource use amount of service, ensure robustness and the accessibility of the application service of user.
Summary of the invention
The invention provides intelligent monitoring analytical method and system under a kind of cloud computing, to solve the problem.
The invention provides intelligent monitoring analytical method under a kind of cloud computing.Said method comprises the following steps:
Monitoring strategies maintenance module issues monitoring strategies to information acquisition module;
Information acquisition module, according to described monitoring strategies, carries out data monitoring and monitored results is sent to resource allocation module, alarm module, trend prediction module;
Monitored results described in resource allocation module, alarm module, trend prediction module analysis, carries out control treatment.
The present invention also provides intelligent monitoring analytical system under a kind of cloud computing, comprising: monitoring strategies maintenance module, information acquisition module, resource allocation module, alarm module, trend prediction module; Monitoring strategies maintenance module is connected with information acquisition module; Information acquisition module is connected with resource allocation module, alarm module, trend prediction module respectively;
Monitoring strategies maintenance module, for issuing monitoring strategies to information acquisition module;
Information acquisition module, for according to described monitoring strategies, carries out data monitoring and monitored results is sent to resource allocation module, alarm module, trend prediction module;
Resource allocation module, the monitor data for the collection to the information acquisition module feedback received carries out analyzing and according to the adjustable strategies preset, by control command module, carries out resource adjustment;
Alarm module, for analyzing the monitor data of collection of the information acquisition module feedback received, when the keystone resources under cloud platform exceed or lower than the threshold values arranged time, automatic trigger alerts;
Trend prediction module, the monitor data for the collection to the information acquisition module feedback received carries out periodic analysis and according to analysis result, formulates countermeasure.
The present invention is by arranging the mode of different monitoring strategies for different computing node territory, carry out information gathering, comprehensive concrete collection physical resource, virtual resource and the relevant information of service carried on resource, according to image data, dynamic conditioning is carried out to the resource under cloud computing platform; Meanwhile, for image data, can analyze, and then may can prevent in advance by problems faced the resource under cloud computing platform; At a moment that fault occurs, can automatically report to the police timely.
Accompanying drawing explanation
Accompanying drawing described herein is used to provide a further understanding of the present invention, and form a application's part, schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Figure 1 shows that the intelligent monitoring analytical model structure chart of the embodiment of the present invention 1;
Figure 2 shows that the intelligent monitoring analyzing and processing flow chart of the embodiment of the present invention 2.
Embodiment
Hereinafter also describe the present invention in detail with reference to accompanying drawing in conjunction with the embodiments.It should be noted that, when not conflicting, the embodiment in the application and the feature in embodiment can combine mutually.
The invention provides intelligent monitoring analytical method under a kind of cloud computing, comprise the following steps:
Monitoring strategies maintenance module issues monitoring strategies to information acquisition module;
Information acquisition module, according to described monitoring strategies, carries out data monitoring and monitored results is sent to resource allocation module, alarm module, trend prediction module;
Monitored results described in resource allocation module, alarm module, trend prediction module analysis, carries out control treatment.
Wherein, information acquisition module according to described monitoring strategies, carry out data monitoring and monitored results is sent to resource allocation module, alarm module, trend prediction module process be:
Information acquisition module, according to described monitoring strategies, periodically gathers the relevant information of physical resource, virtual resource, application service, and feeds back to resource allocation module, alarm module, trend prediction module.
Wherein, monitored results described in resource allocation module, alarm module, trend prediction module analysis, the process of carrying out control treatment is:
The monitor data of resource allocation module to the collection of the information acquisition module feedback received carries out analyzing and according to the adjustable strategies preset, by control command module, carries out resource adjustment;
The monitor data of collection of alarm module to the information acquisition module feedback received is analyzed, when the keystone resources under cloud platform exceed or lower than the threshold values arranged time, automatic trigger alerts;
The monitor data of trend prediction module to the collection of the information acquisition module feedback received carries out periodic analysis and according to analysis result, formulates countermeasure.
Wherein, the monitor data of resource allocation module to the collection of the information acquisition module feedback received carries out analyzing also according to the adjustable strategies preset, and by control command module, the process of carrying out resource adjustment is:
The monitor data of resource allocation module to the collection of the information acquisition module feedback received is analyzed, if when physical services Duty-circle is lower than preset value, notifies that the control command module in described physical services node performs standby command; If during described physical services node oepration at full load, automatically borrow reserved resource.
Wherein, described keystone resources comprises the utilance of resource, the access index of application; The mode of automatic trigger alerts comprises use note, mail alarm.
Wherein, intelligent monitoring management end comprises: monitoring strategies maintenance module 1, resource allocation module 2, trend prediction module 3, alarm module 4; Physical services node comprises: information acquisition module 5, control command module 6.
Wherein, the mode that information acquisition module carries out data monitoring comprises: periodically monitoring or monitor in real time.
Figure 1 shows that the intelligent monitoring analytical model structure chart of the embodiment of the present invention 1, be described as follows: as shown in Figure 1, mainly comprise: monitoring strategies maintenance module 1, resource allocation module 2, trend prediction module 3, alarm module 4, information acquisition module 5, control command module 6.Information acquisition module 5, control command module 6 is positioned at physical services node.
Intelligent monitoring management end (comprising: monitoring strategies maintenance module 1, resource allocation module 2, trend prediction module 3, alarm module 4) safeguard monitoring strategies, by policy distribution, the information acquisition module of each physical services node is ordered to gather the relevant information of physical resource, virtual resource, application service; And analyzed by the monitor data gathered these, dynamic adaptation is carried out to resource, the failure condition that may occur future is prevented in time and taken measures, can Timeliness coverage processing to the alarm situation triggered.
Monitoring strategies maintenance module 1: this module is safeguarded the monitoring strategies (as shown in table 1) of physical services node group and issued monitoring strategies to the information acquisition module 5 in physical services node; Information acquisition module 5 in physical services node, according to the monitoring strategies that monitoring strategies maintenance module 1 issues, carries out data monitoring (can be periodically monitoring, also can be real-time monitoring).Wherein, multiple physical services node forms a physical services node group.
Table 1
As shown in table 1, the monitoring strategies that multiple physical services node is corresponding can be identical, also can be different.
Which data the service that monitoring strategies comprises in the physical resource, virtual resource and the resource that arrange under physical node should monitor, such as: cpu busy percentage, memory usage, application access complications, application state.
Information acquisition module 5, this module is the module of intelligent monitoring most critical, the indices information of resource under responsible collection cloud computing platform, especially performance information; Be arranged on physical services node, receive the monitoring strategies that monitoring strategies maintenance module 1 issues, periodically gather the relevant information of physical resource, virtual resource, application service, and feed back to resource allocation module, alarm module, trend prediction module.
Resource allocation module 2: the monitor data of the collection that the information acquisition module 5 received feeds back is analyzed, when finding that certain physical resource, virtual resource are fully loaded or load is very low, according to the adjustable strategies preset, the supply of adjustresources: when physical services Duty-circle is lower than preset value, notifies that the control command module 6 of this physical services node operates accordingly (such as: standby with energy-conservation); When finding physics service node oepration at full load, automatically borrow reserved resource, with balanced load, Deterministic service normally runs.
Control command module 6: be arranged in physical services node, mainly communicates with resource allocation module 2, and when needs elastic telescopic resource, this control command module 6 receives the order of resource allocation module, performs actual act; This control command module 6 mainly operates for physical resource, resources of virtual machine and application service process, it receives the order practical operation resource of resource allocation module 2, such as: standby, wake physical services node up, close virtual machine, restart certain application service.
Alarm module 4: the monitor data of the collection that the information acquisition module 5 received feeds back is analyzed, when the keystone resources (such as: the utilance of resource, the access index of application) under cloud platform exceed or lower than arrange threshold values time, automatic trigger alerts (such as: use the means such as note, mail to carry out timely auto-alarming), ensures that keeper can process in time.
Trend prediction module 3: periodic analysis is carried out to the monitor data of the collection that the information acquisition module 5 that receives feeds back and according to analysis result, formulate countermeasure: such as: the resource utilization of a certain period in compare cycle or in the cycle, the use peak period of the middle resource of a certain period (such as: one day) in measurement period or in the cycle and low peak period, formulate more reasonably resource usage policy to facilitate user; And the traffic-operating period allowing user in predicting future by statistics, in time precautionary measures are carried out for the fault that may occur.
The monitor data of trend prediction module to the collection of the information acquisition module feedback received carries out periodic analysis and according to analysis result, the process formulating countermeasure is:
The utilization rate of resource in a certain period in measurement period or in the cycle, if be greater than preset value, then forbids the time of the business that user's access privileges is low or the low business of restricting user access priority; Such as: adding customer service is the business that priority is high, and inquiry business is the business that priority is low.
Or
In a certain period in measurement period or in the cycle, the utilization rate of resource, if be greater than preset value, then forbids that user accesses the access time of the business of onrelevant relation or the business of restricting user access onrelevant relation.
Business is divided into: relevant business and onrelevant relation business.
Relevant business refers to: have incidence relation between business, such as: registering service and authentication business are the business (only have and log in and after certification, could access concrete business) with incidence relation.
The business of onrelevant relation refers to: do not have incidence relation between business, such as: inquiry business, systems axiol-ogy business.
Analyze the monitor data gathered, the service condition of Main Analysis resource, the following period of time CPU how long, internal memory, the basic resources such as storages can be used up, statistics application when visit capacity greatly so that cloud computing platform keeper effectively manages cloud resource.
Figure 2 shows that the intelligent monitoring analyzing and processing flow chart of the embodiment of the present invention 2, be described as follows:
Step 201: monitoring strategies maintenance module issues monitoring strategies to information acquisition module;
Step 202: information acquisition module, according to described monitoring strategies, carries out data monitoring;
Wherein, information acquisition module is according to described monitoring strategies, and the process of carrying out data monitoring is:
Information acquisition module, according to described monitoring strategies, periodically gathers the relevant information of physical resource, virtual resource, application service, and feeds back to resource allocation module, alarm module, trend prediction module.
Step 203: the monitor data of resource allocation module to the collection of the information acquisition module feedback received carries out analyzing and according to the adjustable strategies preset, by control command module, carry out resource adjustment;
Step 204: the monitor data of collection of alarm module to the information acquisition module feedback received is analyzed, when the keystone resources under cloud platform exceed or lower than the threshold values arranged time, automatic trigger alerts;
Step 205: the monitor data of trend prediction module to the collection of the information acquisition module feedback received carries out periodic analysis and according to analysis result, formulate countermeasure.
Wherein, step 203,204, the execution of 205 do not have sequencing, can perform simultaneously.
Present invention also offers intelligent monitoring analytical system under a kind of cloud computing, comprising: monitoring strategies maintenance module, information acquisition module, resource allocation module, alarm module, trend prediction module; Monitoring strategies maintenance module is connected with information acquisition module; Information acquisition module is connected with resource allocation module, alarm module, trend prediction module respectively;
Monitoring strategies maintenance module, for issuing monitoring strategies to information acquisition module;
Information acquisition module, for according to described monitoring strategies, carries out data monitoring and monitored results is sent to resource allocation module, alarm module, trend prediction module;
Resource allocation module, the monitor data for the collection to the information acquisition module feedback received carries out analyzing and according to the adjustable strategies preset, by control command module, carries out resource adjustment;
Alarm module, for analyzing the monitor data of collection of the information acquisition module feedback received, when the keystone resources under cloud platform exceed or lower than the threshold values arranged time, automatic trigger alerts;
Trend prediction module, the monitor data for the collection to the information acquisition module feedback received carries out periodic analysis and according to analysis result, formulates countermeasure.
Trend prediction module, also for
The utilization rate of resource in a certain period in measurement period or in the cycle, if be greater than preset value, then forbids the time of the business that user's access privileges is low or the low business of restricting user access priority;
Or
In a certain period in measurement period or in the cycle, the utilization rate of resource, if be greater than preset value, then forbids that user accesses the access time of the business of onrelevant relation or the business of restricting user access onrelevant relation.
The present invention is by arranging the mode of different monitoring strategies for different computing node territory, carry out information gathering, comprehensive concrete collection physical resource, virtual resource and the relevant information of service carried on resource, according to image data, dynamic conditioning is carried out to the resource under cloud computing platform; Meanwhile, for image data, can analyze, and then may can prevent in advance by problems faced the resource under cloud computing platform; At a moment that fault occurs, can automatically report to the police timely.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. an intelligent monitoring analytical method under cloud computing, is characterized in that, comprise the following steps:
Monitoring strategies maintenance module issues monitoring strategies to information acquisition module;
Information acquisition module, according to described monitoring strategies, carries out data monitoring and monitored results is sent to resource allocation module, alarm module, trend prediction module;
Monitored results described in resource allocation module, alarm module, trend prediction module analysis, carries out control treatment.
2. method according to claim 1, is characterized in that: information acquisition module according to described monitoring strategies, carry out data monitoring and monitored results is sent to resource allocation module, alarm module, trend prediction module process be:
Information acquisition module, according to described monitoring strategies, periodically gathers the relevant information of physical resource, virtual resource, application service, and feeds back to resource allocation module, alarm module, trend prediction module.
3. method according to claim 1, is characterized in that: monitored results described in resource allocation module, alarm module, trend prediction module analysis, and the process of carrying out control treatment is:
The monitor data of resource allocation module to the collection of the information acquisition module feedback received carries out analyzing and according to the adjustable strategies preset, by control command module, carries out resource adjustment;
The monitor data of collection of alarm module to the information acquisition module feedback received is analyzed, when the keystone resources under cloud platform exceed or lower than the threshold values arranged time, automatic trigger alerts;
The monitor data of trend prediction module to the collection of the information acquisition module feedback received carries out periodic analysis and according to analysis result, formulates countermeasure.
4. method according to claim 3, it is characterized in that: the monitor data of resource allocation module to the collection of the information acquisition module feedback received carries out analyzing also according to the adjustable strategies preset, by control command module, the process of carrying out resource adjustment is:
The monitor data of resource allocation module to the collection of the information acquisition module feedback received is analyzed, if when physical services Duty-circle is lower than preset value, notifies that the control command module in described physical services node performs standby command; If during described physical services node oepration at full load, automatically borrow reserved resource.
5. method according to claim 3, is characterized in that: described keystone resources comprises the utilance of resource, the access index of application; The mode of automatic trigger alerts comprises use note, mail alarm.
6. method according to claim 1, is characterized in that: intelligent monitoring management end comprises: monitoring strategies maintenance module 1, resource allocation module 2, trend prediction module 3, alarm module 4; Physical services node comprises: information acquisition module 5, control command module 6.
7. method according to claim 1, is characterized in that: the mode that information acquisition module carries out data monitoring comprises: periodically monitor or monitor in real time.
8. method according to claim 3, is characterized in that: the monitor data of trend prediction module to the collection of the information acquisition module feedback received carries out periodic analysis and according to analysis result, the process formulating countermeasure is:
The utilization rate of resource in a certain period in measurement period or in the cycle, if be greater than preset value, then forbids the time of the business that user's access privileges is low or the low business of restricting user access priority;
Or
In a certain period in measurement period or in the cycle, the utilization rate of resource, if be greater than preset value, then forbids that user accesses the access time of the business of onrelevant relation or the business of restricting user access onrelevant relation.
9. an intelligent monitoring analytical system under cloud computing, is characterized in that, comprising: monitoring strategies maintenance module, information acquisition module, resource allocation module, alarm module, trend prediction module; Monitoring strategies maintenance module is connected with information acquisition module; Information acquisition module is connected with resource allocation module, alarm module, trend prediction module respectively;
Monitoring strategies maintenance module, for issuing monitoring strategies to information acquisition module;
Information acquisition module, for according to described monitoring strategies, carries out data monitoring and monitored results is sent to resource allocation module, alarm module, trend prediction module;
Resource allocation module, the monitor data for the collection to the information acquisition module feedback received carries out analyzing and according to the adjustable strategies preset, by control command module, carries out resource adjustment;
Alarm module, for analyzing the monitor data of collection of the information acquisition module feedback received, when the keystone resources under cloud platform exceed or lower than the threshold values arranged time, automatic trigger alerts;
Trend prediction module, the monitor data for the collection to the information acquisition module feedback received carries out periodic analysis and according to analysis result, formulates countermeasure.
10. method according to claim 9, is characterized in that: trend prediction module, also for
The utilization rate of resource in a certain period in measurement period or in the cycle, if be greater than preset value, then forbids the time of the business that user's access privileges is low or the low business of restricting user access priority;
Or
In a certain period in measurement period or in the cycle, the utilization rate of resource, if be greater than preset value, then forbids that user accesses the access time of the business of onrelevant relation or the business of restricting user access onrelevant relation.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090119673A1 (en) * | 2007-11-06 | 2009-05-07 | Credit Suisse Securities (Usa) Llc | Predicting and managing resource allocation according to service level agreements |
| CN101937368A (en) * | 2010-08-31 | 2011-01-05 | 苏州阊亦宏环保科技有限公司 | Cloud computation-oriented data center management system |
| CN101945370A (en) * | 2010-09-25 | 2011-01-12 | 中兴通讯股份有限公司 | Method and system for implementing dynamic strategy control |
| CN101986274A (en) * | 2010-11-11 | 2011-03-16 | 东软集团股份有限公司 | Resource allocation system and resource allocation method in private cloud environment |
| CN102232282A (en) * | 2010-10-29 | 2011-11-02 | 华为技术有限公司 | Method and apparatus for realizing load balance of resources in data center |
| CN102307241A (en) * | 2011-09-27 | 2012-01-04 | 上海忠恕物联网科技有限公司 | Cloud calculation resource disposition method based on dynamic prediction |
| CN102707995A (en) * | 2012-05-11 | 2012-10-03 | 马越鹏 | Service scheduling method and device based on cloud computing environments |
| CN102843223A (en) * | 2011-06-22 | 2012-12-26 | 中兴通讯股份有限公司 | Method and system of data retransmission |
| CN103095533A (en) * | 2013-02-22 | 2013-05-08 | 浪潮电子信息产业股份有限公司 | Timed monitoring method in cloud calculating system platform |
| CN103152352A (en) * | 2013-03-15 | 2013-06-12 | 北京邮电大学 | Perfect information security and forensics monitoring method and system based on cloud computing environment |
| CN103220337A (en) * | 2013-03-22 | 2013-07-24 | 合肥工业大学 | Cloud computing resource optimizing collocation method based on self-adaptation elastic control |
| CN103268115A (en) * | 2013-06-14 | 2013-08-28 | 鲁电集团有限公司 | Power demand side monitoring system and method |
| CN103283209A (en) * | 2011-04-18 | 2013-09-04 | 北京新媒传信科技有限公司 | Application service platform system and implementation method thereof |
| CN103401699A (en) * | 2013-07-18 | 2013-11-20 | 深圳先进技术研究院 | Cloud data center security monitoring early warning system and method |
| CN103414748A (en) * | 2013-07-12 | 2013-11-27 | 广东电子工业研究院有限公司 | Cloud platform monitoring architecture and monitoring realizing method thereof |
-
2013
- 2013-12-13 CN CN201310687023.XA patent/CN103684916A/en active Pending
-
2014
- 2014-11-19 CN CN201410664711.9A patent/CN104378262A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090119673A1 (en) * | 2007-11-06 | 2009-05-07 | Credit Suisse Securities (Usa) Llc | Predicting and managing resource allocation according to service level agreements |
| CN101937368A (en) * | 2010-08-31 | 2011-01-05 | 苏州阊亦宏环保科技有限公司 | Cloud computation-oriented data center management system |
| CN101945370A (en) * | 2010-09-25 | 2011-01-12 | 中兴通讯股份有限公司 | Method and system for implementing dynamic strategy control |
| CN102232282A (en) * | 2010-10-29 | 2011-11-02 | 华为技术有限公司 | Method and apparatus for realizing load balance of resources in data center |
| CN101986274A (en) * | 2010-11-11 | 2011-03-16 | 东软集团股份有限公司 | Resource allocation system and resource allocation method in private cloud environment |
| CN103283209A (en) * | 2011-04-18 | 2013-09-04 | 北京新媒传信科技有限公司 | Application service platform system and implementation method thereof |
| CN102843223A (en) * | 2011-06-22 | 2012-12-26 | 中兴通讯股份有限公司 | Method and system of data retransmission |
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