CN103023969A - Cloud platform scheduling method and system - Google Patents
Cloud platform scheduling method and system Download PDFInfo
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- CN103023969A CN103023969A CN201210460394XA CN201210460394A CN103023969A CN 103023969 A CN103023969 A CN 103023969A CN 201210460394X A CN201210460394X A CN 201210460394XA CN 201210460394 A CN201210460394 A CN 201210460394A CN 103023969 A CN103023969 A CN 103023969A
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Abstract
The invention relates to the technology of cloud computation, and discloses a cloud platform scheduling method and system. The method comprises the following steps of acquiring performance data of application, determining whether the application should be subjected to capacity expansion or reduction according to the performance data, and executing capacity expansion operation if the application should be subjected to the capacity expansion, otherwise executing capacity reduction operation. According to the embodiment of the invention, the running state of the application can be monitored by periodically acquiring the performance data of the application, the capacity of the application is automatically expanded when high-load operation is applied, and the capacity of the application is automatically reduced when low-load operation is applied, so that the application is dynamically regulated, and the whole running performance of a cloud platform is improved.
Description
Technical field
The present invention relates to cloud computing technology, especially relate to a kind of cloud dispatching platforms method and system.
Background technology
User's application deployment is after on the cloud platform, the state of the state of using in running and cloud platform node is dynamic change, during very possible cause the cloud platform can't bring into play optimum performance because node is unavailable, use the reasons such as unusually withdrawing from, use the high capacity operation that breaks down.
The inventor finds in realizing process of the present invention, it is normally in service that existing technology can only know whether this application is in according to the current state of using, the category that belongs to static scheduling, whether but can't judge application still can normally move down, can't know whether application is in high capacity operation or low load running, more can't carry out accommodation according to the demand of using and namely dynamically adjust, so finally still can cause the cloud platform can't bring into play optimum performance.
Summary of the invention
In view of this, the purpose of the embodiment of the invention provides a kind of cloud dispatching platforms method and system, can't dynamically adjust and causes the cloud platform can't bring into play the problem of optimum performance for application to solve.
On the one hand, the embodiment of the invention provides a kind of cloud dispatching platforms method, and described method comprises:
Obtain the performance data of application;
Judge described application whether needs dilatation or capacity reducing according to described performance data,
If need dilatation then to carry out the dilatation operation, if need capacity reducing then to carry out the capacity reducing operation.
Preferably:
Described performance data comprises uses current number of request;
Describedly judge described application whether needs dilatation or capacity reducing according to described performance data, specifically comprise:
Obtain the ratio of the largest request number of described current number of request and described application;
Need dilatation if described ratio is then judged greater than first threshold, need capacity reducing if described ratio is then judged less than Second Threshold.
Preferably, described dilatation operation specifically comprises:
Obtain the performance data of node;
Judge the whether high capacity operation of described node according to described performance data, if not, then with described application dilatation to described node.
Preferably, describedly judge that according to described performance data described node whether after the high capacity operation, also comprises:
If, then with the application schedules on the described node to other node.
Preferably, before carrying out the operation of described dilatation operation or capacity reducing, also comprise:
Obtain the time of the last dilatation of described application or capacity reducing and the time difference of current time;
Judge according to the described time difference whether dilatation or capacity reducing be frequent, if then carry out the operation of described dilatation operation or capacity reducing no longer downwards.
On the other hand, the embodiment of the invention provides a kind of cloud dispatching platforms system, and described system comprises:
The application performance acquisition module is used for obtaining the performance data of application;
Dilatation capacity reducing judge module is used for judging described application whether needs dilatation or capacity reducing according to described performance data, if need dilatation then to trigger the dilatation module, if need capacity reducing then to trigger the capacity reducing module;
The dilatation module is used for carrying out the dilatation operation;
The capacity reducing module is used for carrying out the capacity reducing operation.
Preferably:
Described performance data comprises uses current number of request;
Described dilatation capacity reducing judge module specifically comprises:
Number of request ratio obtains submodule, is used for obtaining the ratio of the largest request number of described current number of request and described application;
Number of request ratio in judgement submodule is then judged greater than first threshold and is needed dilatation if be used for described ratio, needs capacity reducing if described ratio is then judged less than Second Threshold.
Preferably, described dilatation module specifically comprises:
Joint behavior data acquisition submodule is for the performance data of obtaining node;
Submodule is judged in high capacity, be used for judging the whether high capacity operation of described node according to described performance data, if not, then with described application dilatation to described node.
Preferably, described dilatation module also comprises:
The balanced submodule of node is used for when described high capacity judges that submodule judges that described node is in high capacity and moves, with the application schedules on the described node to other node.
Preferably, described system also comprises:
Scalable appearance time difference acquisition module is used for obtaining the time of the last dilatation of described application or capacity reducing and the time difference of current time;
The shake judge module is for judging according to the described time difference whether dilatation or capacity reducing be frequent, if then do not allow to trigger described dilatation module or capacity reducing module.
The embodiment of the invention is monitored the running status of application by the performance data of periodically obtaining application, when using the high capacity operation to using automatic dilatation, when using low load running to using automatic capacity reducing, realized application is dynamically adjusted, and then improved the performance of cloud platform and integrally operation.In addition, the embodiment of the invention can be carried out load judgment to node to be selected when dilatation is carried out in application, only will use to the node of non-high capacity and carry out dilatation, has also guaranteed the high-performance of cloud platform and integrally operation.In addition, the embodiment of the invention can also judge whether dilatation or capacity reducing be frequent, with the jitter that prevents that frequent dilatation/capacity reducing from bringing.
Description of drawings
In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art, the below will do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art, apparently, accompanying drawing in the following describes only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the flow chart of the embodiment of the invention one method;
Fig. 2 is the schematic diagram of embodiment of the invention two system.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that obtains under the creative work prerequisite.
Referring to Fig. 1, be the flow chart of the embodiment of the invention one.Present embodiment discloses a kind of cloud dispatching platforms method, its basic ideas are: by the performance index of periodic acquisition applications, the performance data of technology and analytical applications (application request number, use and use CPU, use and use the disk number, use and use interior poke), whether normally identification use operation, automatic dilatation is used in operation if application is high capacity, is that automatic capacity reducing is used in low load running if use.Concrete, described method comprises:
S101: the performance data of obtaining application.Wherein said performance data can be the application request number, uses use CPU, use and use disk number, application to use common data or the performance index such as interior poke, and this embodiment of the invention is not limited.In addition, can be periodic to the obtaining of performance data of using, i.e. the performance data of periodic acquisition applications.Can be stored in after described performance data gets access in the database, call in again when needed internal memory and calculate, analyze.
S102: judge described application whether needs dilatation or capacity reducing according to described performance data, if need dilatation then to carry out the dilatation operation, if need capacity reducing then to carry out the capacity reducing operation.
In certain embodiments of the invention, when described performance data comprises when using current number of request, describedly judge described application whether needs dilatation or capacity reducing according to described performance data, specifically can comprise:
Obtain the ratio of the largest request number of described current number of request and described application;
Need dilatation if described ratio is then judged greater than first threshold, need capacity reducing if described ratio is then judged less than Second Threshold.From database, gather the performance data index, calculate percentage, draw the running status of application, and judge to use whether need dilatation or capacity reducing.Certain described first threshold can be identical with described Second Threshold, also can be different.
In addition, described dilatation operation specifically can may further comprise the steps in certain embodiments of the invention:
1) obtains the performance data of node.Can be stored in after the performance data of described node gets access in the database, call in again when needed internal memory and calculate, analyze.
2) judge the whether high capacity operation of described node according to described performance data, if not, then with described application dilatation to described node.From database, gather the performance index data, the computing node load balancing, whether the running status that gets egress is healthy, and whether decision node needs dispatch application to other node.
Wherein: can be periodically to obtain too to obtaining of joint behavior data.The performance data of node can comprise the data such as load, internal memory, CPU, disk, network or take situation.
In addition, in certain embodiments of the invention, be in high capacity when operation when judging described node, can also take further operation, that is: describedly judge that according to described performance data described node whether after the high capacity operation, can also comprise:
If, then with the application schedules on the described node to other node.When dynamic dispatching is carried out in application, can carry out equilibrium to the load of node in passing like this, guarantee the high-performance of whole cloud platform.
In certain embodiments of the invention, before carrying out the operation of described dilatation operation or capacity reducing, can also comprise:
Obtain the time of the last dilatation of described application or capacity reducing and the time difference of current time;
Judge according to the described time difference whether dilatation or capacity reducing be frequent, if then carry out the operation of described dilatation operation or capacity reducing no longer downwards.
Concrete can be when having carried out the operation of dilatation or capacity reducing at every turn, time mark is carried out in this application, when need dilatation or capacity reducing next time again, check first previous time mark, can judge dilatation or whether capacity reducing is more frequent by the difference of time, thus the jittering characteristic of avoiding frequent dilatation, capacity reducing to bring.
Fig. 2 is the schematic diagram of embodiment of the invention two system.Present embodiment provides a kind of cloud dispatching platforms system, and described system comprises:
Application performance acquisition module 201 is used for obtaining the performance data of application;
Dilatation capacity reducing judge module 202 is used for judging described application whether needs dilatation or capacity reducing according to described performance data, if need dilatation then to trigger the dilatation module, if need capacity reducing then to trigger the capacity reducing module;
In addition, described system can also comprise a scheduler module, is used for control with upper module, for example drives with upper module and periodically moves, and coordinates the work of each module, also is used between each module and transmits data.
Preferably:
Described performance data comprises uses current number of request;
Described dilatation capacity reducing judge module specifically comprises:
Number of request ratio obtains submodule, is used for obtaining the ratio of the largest request number of described current number of request and described application;
Number of request ratio in judgement submodule is then judged greater than first threshold and is needed dilatation if be used for described ratio, needs capacity reducing if described ratio is then judged less than Second Threshold.
Preferably, described dilatation module specifically comprises:
Joint behavior data acquisition submodule is for the performance data of obtaining node;
Submodule is judged in high capacity, be used for judging the whether high capacity operation of described node according to described performance data, if not, then with described application dilatation to described node.
Preferably, described dilatation module also comprises:
The balanced submodule of node is used for when described high capacity judges that submodule judges that described node is in high capacity and moves, with the application schedules on the described node to other node.
Preferably, described system also comprises:
Scalable appearance time difference acquisition module is used for obtaining the time of the last dilatation of described application or capacity reducing and the time difference of current time;
The shake judge module is for judging according to the described time difference whether dilatation or capacity reducing be frequent, if then do not allow to trigger described dilatation module or capacity reducing module.
For system embodiment, because it corresponds essentially to embodiment of the method, so relevant part gets final product referring to the part explanation of embodiment of the method.System embodiment described above only is schematic, wherein said unit as the separating component explanation can or can not be physically to separate also, the parts that show as the unit can be or can not be physical locations also, namely can be positioned at a place, perhaps also can be distributed on a plurality of network element.Can select according to the actual needs wherein some or all of module to realize the purpose of present embodiment scheme.Those of ordinary skills namely can understand and implement in the situation of not paying creative work.
The present invention can describe in the general context of the computer executable instructions of being carried out by computer, for example program module.Usually, program module comprises the routine carrying out particular task or realize particular abstract data type, program, object, assembly, data structure etc.Also can in distributed computing environment (DCE), put into practice the present invention, in these distributed computing environment (DCE), be executed the task by the teleprocessing equipment that is connected by communication network.In distributed computing environment (DCE), program module can be arranged in the local and remote computer-readable storage medium that comprises memory device.
One of ordinary skill in the art will appreciate that all or part of step that realizes in the said method execution mode is to come the relevant hardware of instruction to finish by program, described program can be stored in the computer read/write memory medium, here alleged storage medium, as: ROM, RAM, magnetic disc, CD etc.
Also need to prove, in this article, relational terms such as the first and second grades only is used for an entity or operation are made a distinction with another entity or operation, and not necessarily requires or hint and have the relation of any this reality or sequentially between these entities or the operation.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thereby not only comprise those key elements so that comprise process, method, article or the equipment of a series of key elements, but also comprise other key elements of clearly not listing, or also be included as the intrinsic key element of this process, method, article or equipment.Do not having in the situation of more restrictions, the key element that is limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment that comprises described key element and also have other identical element.
The above is preferred embodiment of the present invention only, is not for limiting protection scope of the present invention.Used specific case herein and principle of the present invention and execution mode have been carried out lock stated, the explanation of above embodiment just is used for helping to understand method of the present invention and core concept thereof; Simultaneously, for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications.In sum, this description should not be construed as limitation of the present invention.All any modifications of doing within the spirit and principles in the present invention, be equal to replacement, improvement etc., all be included in protection scope of the present invention.
Claims (10)
1. cloud dispatching platforms method is characterized in that described method comprises:
Obtain the performance data of application;
Judge described application whether needs dilatation or capacity reducing according to described performance data,
If need dilatation then to carry out the dilatation operation, if need capacity reducing then to carry out the capacity reducing operation.
2. method according to claim 1 is characterized in that:
Described performance data comprises uses current number of request;
Describedly judge described application whether needs dilatation or capacity reducing according to described performance data, specifically comprise:
Obtain the ratio of the largest request number of described current number of request and described application;
Need dilatation if described ratio is then judged greater than first threshold, need capacity reducing if described ratio is then judged less than Second Threshold.
3. method according to claim 1 is characterized in that, described dilatation operation specifically comprises:
Obtain the performance data of node;
Judge the whether high capacity operation of described node according to described performance data, if not, then with described application dilatation to described node.
4. method according to claim 3 is characterized in that, describedly judges that according to described performance data described node whether after the high capacity operation, also comprises:
If, then with the application schedules on the described node to other node.
5. method according to claim 1 is characterized in that, before carrying out the operation of described dilatation operation or capacity reducing, also comprises:
Obtain the time of the last dilatation of described application or capacity reducing and the time difference of current time;
Judge according to the described time difference whether dilatation or capacity reducing be frequent, if then carry out the operation of described dilatation operation or capacity reducing no longer downwards.
6. cloud dispatching platforms system is characterized in that described system comprises:
The application performance acquisition module is used for obtaining the performance data of application;
Dilatation capacity reducing judge module is used for judging described application whether needs dilatation or capacity reducing according to described performance data, if need dilatation then to trigger the dilatation module, if need capacity reducing then to trigger the capacity reducing module;
The dilatation module is used for carrying out the dilatation operation;
The capacity reducing module is used for carrying out the capacity reducing operation.
7. system according to claim 6 is characterized in that:
Described performance data comprises uses current number of request;
Described dilatation capacity reducing judge module specifically comprises:
Number of request ratio obtains submodule, is used for obtaining the ratio of the largest request number of described current number of request and described application;
Number of request ratio in judgement submodule is then judged greater than first threshold and is needed dilatation if be used for described ratio, needs capacity reducing if described ratio is then judged less than Second Threshold.
8. system according to claim 6 is characterized in that, described dilatation module specifically comprises:
Joint behavior data acquisition submodule is for the performance data of obtaining node;
Submodule is judged in high capacity, be used for judging the whether high capacity operation of described node according to described performance data, if not, then with described application dilatation to described node.
9. system according to claim 8 is characterized in that, described dilatation module also comprises:
The balanced submodule of node is used for when described high capacity judges that submodule judges that described node is in high capacity and moves, with the application schedules on the described node to other node.
10. system according to claim 6 is characterized in that, described system also comprises:
Scalable appearance time difference acquisition module is used for obtaining the time of the last dilatation of described application or capacity reducing and the time difference of current time;
The shake judge module is for judging according to the described time difference whether dilatation or capacity reducing be frequent, if then do not allow to trigger described dilatation module or capacity reducing module.
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| CN103488538A (en) * | 2013-09-02 | 2014-01-01 | 用友软件股份有限公司 | Application extension device and application extension method in cloud computing system |
| CN103561428A (en) * | 2013-10-10 | 2014-02-05 | 东软集团股份有限公司 | Method and system for elastically distributing nodes in short message gateway cluster system |
| CN103782270A (en) * | 2013-10-28 | 2014-05-07 | 华为技术有限公司 | Method for managing stream processing system, and related apparatus and system |
| CN104239150A (en) * | 2014-09-15 | 2014-12-24 | 杭州华为数字技术有限公司 | Method and device for adjusting hardware resources |
| CN104850634A (en) * | 2015-05-22 | 2015-08-19 | 中国联合网络通信集团有限公司 | Data storage node adjustment method and system |
| CN106130753A (en) * | 2016-06-12 | 2016-11-16 | 腾讯科技（深圳）有限公司 | Application performance data gathering system, method, agent client and associated server |
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| CN107977252A (en) * | 2016-10-21 | 2018-05-01 | 中兴通讯股份有限公司 | A kind of capacity reduction method, device and the cloud platform of cloud platform business |
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| WO2017028697A1 (en) * | 2015-08-17 | 2017-02-23 | 阿里巴巴集团控股有限公司 | Method and device for growing or shrinking computer cluster |
| CN106470219A (en) * | 2015-08-17 | 2017-03-01 | 阿里巴巴集团控股有限公司 | The dilatation of computer cluster and capacity reduction method and equipment |
| CN106130753A (en) * | 2016-06-12 | 2016-11-16 | 腾讯科技（深圳）有限公司 | Application performance data gathering system, method, agent client and associated server |
| CN107977252A (en) * | 2016-10-21 | 2018-05-01 | 中兴通讯股份有限公司 | A kind of capacity reduction method, device and the cloud platform of cloud platform business |
| CN110278218B (en) * | 2018-03-14 | 2022-02-15 | 吉旗（成都）科技有限公司 | Container-based data receiving and analyzing method |
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| CN108769100A (en) * | 2018-04-03 | 2018-11-06 | 郑州云海信息技术有限公司 | A kind of implementation method and its device based on kubernetes number of containers elastic telescopics |
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| CN110096339A (en) * | 2019-05-10 | 2019-08-06 | 重庆八戒电子商务有限公司 | A kind of scalable appearance configuration recommendation system and method realized based on system load |
| CN115277713A (en) * | 2022-07-27 | 2022-11-01 | 京东科技信息技术有限公司 | Load balancing method and device |
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