CN109976875A - A kind of data monitoring method and device of super fusion cloud computing system - Google Patents
A kind of data monitoring method and device of super fusion cloud computing system Download PDFInfo
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- CN109976875A CN109976875A CN201910154144.5A CN201910154144A CN109976875A CN 109976875 A CN109976875 A CN 109976875A CN 201910154144 A CN201910154144 A CN 201910154144A CN 109976875 A CN109976875 A CN 109976875A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
- G06F2009/45591—Monitoring or debugging support
Abstract
The present invention relates to field of computer technology, provide data monitoring method, device, computer equipment and the computer readable storage medium of a kind of super fusion cloud computing system.This method comprises: obtaining the identification information of the super fusion all-in-one machine in each super aggregators；The sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information；The monitoring reference data of the virtual machine is obtained with the super corresponding relationship for merging all-in-one machine and the sampled data according to virtual machine；The virtual machine is monitored according to the monitoring reference data, effectively virtual machine can be monitored.
Description
Technical field
The invention belongs to field of computer technology more particularly to it is a kind of it is super fusion cloud computing system data monitoring method,
Device, computer equipment and computer readable storage medium.
Background technique
Super fusion cloud computing system is a kind of distributed memory system of object-oriented.Super fusion refers in same set of equipment
In not only have the resources such as calculating, network, storage and server virtualization and technology, multiple super aggregators can also pass through
Network polymerization gets up, and realization is extending transversely, and forms unified resource pool.And money included in super fusion cloud computing system
It can be mainly divided into hardware resource and the resource for virtual machine distribution in the pond of source, wherein the resource for virtual machine distribution is hard
It further integrates or splits on the basis of part resource and is obtained.
Currently, for can not also effectively be monitored in super fusion cloud computing system for the resource of virtual machine distribution, and
The operation of resource pool in super fusion cloud computing system can be real-time and accurately obtained for the monitoring for the resource distributed for virtual machine
Situation, to realize that the reasonable distribution of resource pool provides reference frame.Therefore, prior art presence can not be to super fusion cloud computing system
The problem of resource in system for virtual machine distribution is monitored.
Summary of the invention
In view of this, the embodiment of the invention provides data monitoring method, device, the meters of a kind of super fusion cloud computing system
Calculate machine equipment and computer readable storage medium, with solve in the prior art can not in super fusion cloud computing system for virtual machine
The problem of resource of distribution is monitored.
The first aspect of the embodiment of the present invention provides a kind of data monitoring method of super fusion cloud computing system, described super
Fusion cloud computing system includes multiple super aggregators and switch, and each super aggregators include multiple super melt
All-in-one machine is closed, multiple super fusion all-in-one machines carry out network connection by the switch and form resource pool, according to
Computing resource in super fusion all-in-one machine is invented multiple virtual machines by user demand, and each super fusion all-in-one machine has unique
Identification information；It is characterized in that, the data monitoring method includes:
Obtain the identification information of the super fusion all-in-one machine in each super aggregators；
The sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information；
The prison of the virtual machine is obtained with the super corresponding relationship for merging all-in-one machine and the sampled data according to virtual machine
Survey reference data；
The virtual machine is monitored according to the monitoring reference data.
The second aspect of the embodiment of the present invention provides a kind of storage resource distributor of super fusion cloud computing system, packet
It includes:
First obtains module, for obtaining the identification information of the super fusion all-in-one machine in each super aggregators；
Second obtains module, for obtaining the sampling in each super fusion all-in-one machine operational process based on the identification information
Data；
Third obtains module, for being obtained according to virtual machine with the super corresponding relationship for merging all-in-one machine and the sampled data
To the monitoring reference data of the virtual machine；
Monitoring modular, for being monitored according to the monitoring reference data to the virtual machine.
The third aspect of the embodiment of the present invention provides a kind of computer equipment, including memory, processor and storage
In the memory and the computer program that can run on the processor, which is characterized in that the processor executes institute
It is performed the steps of when stating computer program
Obtain the identification information of the super fusion all-in-one machine in each super aggregators；
The sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information；
The prison of the virtual machine is obtained with the super corresponding relationship for merging all-in-one machine and the sampled data according to virtual machine
Survey reference data；
The virtual machine is monitored according to the monitoring reference data.
The fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, the computer-readable storage
Media storage has computer program, and the computer program performs the steps of when being executed by processor
Obtain the identification information of the super fusion all-in-one machine in each super aggregators；
The sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information；
The prison of the virtual machine is obtained with the super corresponding relationship for merging all-in-one machine and the sampled data according to virtual machine
Survey reference data；
The virtual machine is monitored according to the monitoring reference data.
In the embodiment of the present invention, the identification information of the super fusion all-in-one machine in each super aggregators is obtained first,
The sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information, is then melted according to virtual machine with super
The corresponding relationship and the sampled data for closing all-in-one machine obtain the monitoring data of the virtual machine, pass through the monitoring data
The virtual machine is monitored, effectively virtual machine can be monitored.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is the schematic diagram of super fusion cloud computing system provided in an embodiment of the present invention；
Fig. 2 is the implementation process signal of the data monitoring method for the super fusion cloud computing system that the embodiment of the present invention one provides
Figure；
Fig. 3 is the structural schematic diagram of the data monitoring device of super fusion cloud computing system provided by Embodiment 2 of the present invention；
Fig. 4 is the structural schematic diagram that third provided in an embodiment of the present invention obtains module；
Fig. 5 is another structural schematic diagram of data monitoring device of super fusion cloud computing system provided in an embodiment of the present invention；
Fig. 6 is the another structural schematic diagram of data monitoring device of super fusion cloud computing system provided in an embodiment of the present invention；
Fig. 7 is the another structural schematic diagram of data monitoring device of super fusion cloud computing system provided in an embodiment of the present invention；
Fig. 8 is the schematic diagram for the computer equipment that the embodiment of the present invention three provides.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific
The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, in case unnecessary details interferes description of the invention.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.
Fig. 1 shows the schematic diagram of super fusion cloud computing system provided in an embodiment of the present invention.As shown in Figure 1, described super
Fusion cloud computing system includes multiple super aggregators and switch, and each super aggregators include multiple super melt
All-in-one machine is closed, multiple super fusion all-in-one machines carry out network connection by the switch and form resource pool, according to
Computing resource in super fusion all-in-one machine is invented multiple virtual machines by user demand, and each super fusion all-in-one machine has unique
Identification information.
Embodiment one:
Fig. 2 shows the implementation processes of the data monitoring method of the super fusion cloud computing system of the offer of the embodiment of the present invention one
Schematic diagram.As shown in Fig. 2, data monitoring method of the super fusion cloud computing system specifically comprises the following steps 101 to step
104。
Step 101: obtaining the identification information of the super fusion all-in-one machine in each super aggregators.
Step 102: the sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information.
For step 101 and step 102, wherein the sampled data each super fusion in super fusion storage system
The super fusion all-in-one machine of at least one of node, and the data content of sampled data is then the index according to preset monitoring to be monitored
Data carry out the sample information that real-time sampling obtains.
Since sampled data is the sampled data to hardware resource in super fusion all-in-one machine operational process, and melt entirely super
Closing has many super fusion all-in-one machines in storage system, therefore, these sampled datas are just needed on label in acquisition
Corresponding identification information is distinguish, in general, being all using the physical label of super fusion all-in-one machine as the mark of the sampled data
Know the acquisition source that information is used to illustrate the sampled data.
It, can be by each super fusion all-in-one machine of super fusion storage system for the data acquisition in this step
It runs corresponding data acquisition service and carries out data acquisition operations, data content collected can be by the customized determination of system simultaneously
Acquisition is oriented to the hardware resource in super fusion all-in-one machine by the data acquisition service, for example can be set to super fusion
The parameters such as storage resource, processor in all-in-one machine occupy, memory uses monitor periodically or in real time.For specifically counting
According to acquisition mode, the embodiment of the present invention is then not construed as limiting.
Step 103: the void is obtained with the super corresponding relationship for merging all-in-one machine and the sampled data according to virtual machine
The monitoring reference data of quasi- machine.
Wherein, in super fusion metacomputing system, for each virtual machine, the virtual machine merges all-in-one machine with super
Corresponding relationship be it is determining, according to determining corresponding relationship obtain virtual machine it is corresponding it is super fusion all-in-one machine sampled data,
Using the sampled data as the monitoring reference data of virtual machine.
Step 103 specifically may include step 201 and step 202, and details are as follows:
Step 201: according to virtual machine and the super corresponding relationship for merging all-in-one machine, determining the corresponding super fusion of each virtual machine
All-in-one machine.
The hardware resource that the corresponding relationship can be in single super fusion all-in-one machine corresponds to multiple virtual machines, is also possible to
The hardware resource of multiple super fusion all-in-one machines corresponds to single virtual machine, can also be hardware resource and void in super fusion all-in-one machine
Quasi- machine corresponds.It should be noted that virtual machine is corresponding with super fusion all-in-one machine in above-mentioned super fusion cloud computing system
Relationship can be any one in above-mentioned three kinds of corresponding relationships, and any two kinds coexist or three kinds coexist.
The corresponding super fusion one of virtual machine is determined specific corresponding to relationship with the super all-in-one machine that merges according to each virtual machine
Machine.
Step 202: sampled data being extracted according to the identification information of the corresponding super fusion all-in-one machine, according to the sampling
Data obtain the monitoring reference data of each virtual machine.
Have determined that the corresponding super fusion all-in-one machine of virtual machine in step 201, then it is further corresponding super according to this
It merges all-in-one machine identification information and extracts sampled data, the monitoring reference number by the set of these sampled datas as each virtual machine
According to.For example, obtaining storage resource occupancy, the processor occupancy, memory usage of the corresponding super fusion all-in-one machine of virtual machine
Deng as monitoring reference data.
Step 104: the virtual machine being monitored according to the monitoring reference data.
The monitoring reference data according to obtained in step 103 is monitored virtual machine.It should be noted that in this step
In, only partial virtual machine can be monitored according to the needs to virtual machine actual monitoring, then correspondingly obtain and need to monitor
Virtual machine it is corresponding it is super fusion all-in-one machine sampled data, to realize the flexibility of monitoring.
As an embodiment of the present invention, the monitoring reference data includes in monitoring time point and the resource pool
The quantity of the virtual machine run on the monitoring time point, after step 104, further includes:
Step 301: the monitoring data being ranked up by the timing of monitoring time point, generate one group for the virtual machine
Time series data；The time series data include sequence after monitoring time point and on the monitoring time point virtual machine number
Amount.
Wherein, monitoring time point can be as unit of hour, minute or second, for example, generating one group for the virtual machine
Monitoring time point is the time series data of minute, as table 1 is shown in the date that some is currently determined in 8 a.m. to 12 noon
The quantity of virtual machine.
Table 1:
| Monitoring time point | Virtual machine quantity |
| 8:00 | 10 |
| 8:10 | 11 |
| 8:20 | 11 |
| 8:30 | 10 |
| 8:40 | 12 |
| 8:50 | 12 |
| 9:00 | 13 |
| 9:10 | 14 |
| 9:20 | 13 |
| 9:30 | 14 |
| 9:40 | 15 |
| 9:50 | 15 |
| 10:00 | 16 |
| 10:10 | 16 |
| 10:20 | 17 |
| 10:30 | 18 |
| 10:40 | 19 |
| 10:50 | 20 |
| 11:00 | 20 |
| 11:10 | 21 |
| 11:20 | 21 |
| 11:30 | 22 |
| 11:40 | 23 |
| 11:50 | 24 |
| 12:00 | 25 |
Step 302: the virtual machine quantity in the preset time period after current time is predicted according to the time series data.
Wherein, preset time period can be as unit of number of days, hour or minute.
Time series data input prediction model obtained in step 301 is analyzed, prediction model therein can be for certainly
Regression-Integral moving average model.
Wherein, the basic thought of autoregression integral moving average model is: prediction object is formed over time
Data sequence (operation data in such as embodiment of the present invention) is considered as a random sequence, with mathematical model come approximate description this
Sequence, the model value can be predicted in the preset time period after current time not from the past value of time series and now
Future value to be worth, and predict meets the changing rule of past value.
Step 303: obtaining the hardware specification of virtual machine.
Wherein, hardware specification includes the memory size and CPU core number of virtual machine.
Step 304: virtual machine quantity and institute according to predicting in the preset time period after current time
The hardware specification for stating virtual machine obtains demand of the virtual machine to hardware resource in the preset time period after the current time
Amount.
Wherein, demand of the virtual machine to memory in the demand of hardware resource in the preset time period after current time
Equal to the quantity of virtual machine multiplied by the corresponding memory size of each virtual machine, the demand etc. of CPU in the demand of hardware resource
In virtual machine quantity multiplied by the corresponding CPU core number of each virtual machine.
Step 305: to the demand of hardware resource and super being melted according to the current capacities of the resource pool, the virtual machine
The hardware specification of all-in-one machine is closed, determines the super fusion all-in-one machine demand within the period in the future.
For step 305, it is assumed that memory size is 500GB in the current capacities of the resource pool, and CPU core number is 40, institute
State that virtual machine is 600GB to the demand of hardware resource and CPU core number is 60, then memory size needs dilatation 100GB, CPU
Nucleus number needs to increase by 20, it is assumed that the hardware specification of virtual machine is with 4GB memory and 2 CPU core numbers, it is determined that at least needs to increase
The super fusion all-in-one machine quantity added, 100GB/4GB=25 are greater than 20/2=10, therefore finally need to increase by 25 super fusion one
Machine.
As an embodiment of the present invention, by predicting the preset time period after current time according to time series data
Virtual machine quantity, the super fusion all-in-one machine demand of the following special time period is obtained further according to virtual machine quantity, due to introducing
It can reflect the time series data of the history growth trend of virtual machine quantity to obtain the preset time period institute after current time
The virtual machine quantity needed, so as to improve the prediction accuracy to super fusion all-in-one machine demand.
As an embodiment of the present invention, the monitoring data include in monitoring time point and the resource pool in institute
The type and quantity of the virtual machine run on monitoring time point are stated, after step 104, further includes:
Step 401: being classified according to the type of virtual machine to the monitoring data, and by the sorted monitoring number
It is ranked up according to by the timing of monitoring time point, generates one group of time series data for each type of virtual machine；The time series data
Quantity including monitoring time point and same type of virtual machine corresponding with the monitoring time point.
In this step, type of virtual machine is distinguished according to the hardware specification of virtual machine, for example, virtual machine can be divided into small
Type virtual machine, medium-sized virtual machine, large-scale virtual machine.It, can will be large-scale in super fusion cloud computing system as one embodiment
The hardware specification of virtual machine is set as with 8G memory and 4 CPU core numbers, is in 4G by the hardware setting of medium-sized virtual machine
Deposit with 2 CPU core numbers, set the hardware specification of small virtual machine to 2G memory and 1 CPU core number.
Wherein, monitoring time point can hour, minute or second be unit, for example, generating one group of prison for the virtual machine
The time series data that time point is minute is surveyed, as table 2 is shown in the date that some is currently determined three in 8 a.m. to 12 noon
The quantity of the virtual machine of seed type.
Table 2:
| Monitoring time point | Large-scale virtual machine quantity | Medium-sized virtual machine quantity | Small virtual machine quantity |
| 8:00 | 10 | 25 | 18 |
| 8:10 | 11 | 26 | 19 |
| 8:20 | 11 | 26 | 19 |
| 8:30 | 10 | 25 | 18 |
| 8:40 | 12 | 27 | 20 |
| 8:50 | 12 | 27 | 20 |
| 9:00 | 13 | 28 | 21 |
| 9:10 | 14 | 29 | 22 |
| 9:20 | 13 | 28 | 21 |
| 9:30 | 14 | 29 | 22 |
| 9:40 | 15 | 30 | 23 |
| 9:50 | 15 | 30 | 23 |
| 10:00 | 16 | 31 | 24 |
| 10:10 | 16 | 31 | 24 |
| 10:20 | 17 | 32 | 25 |
| 10:30 | 18 | 33 | 26 |
| 10:40 | 19 | 34 | 27 |
| 10:50 | 20 | 35 | 28 |
| 11:00 | 20 | 35 | 28 |
| 11:10 | 21 | 36 | 29 |
| 11:20 | 21 | 36 | 29 |
| 11:30 | 22 | 37 | 30 |
| 11:40 | 23 | 38 | 31 |
| 11:50 | 24 | 39 | 32 |
| 12:00 | 25 | 40 | 33 |
Step 402: the time series data according to every group predicts that the preset time period after current time is all types of respectively
Virtual machine quantity.
In this step, moving average model is integrated according to autoregression and predicts the preset time after current time respectively
The all types of virtual machine quantity of section, prediction process is identical as step 302, and details are not described herein.
Step 403: obtaining the hardware specification of all types of virtual machines.
Wherein, hardware specification includes the memory size and CPU core number of all types of virtual machines.
Step 404: according to virtual machine quantity all types of in the preset time period after the current time predicted
With the hardware specification of all types of virtual machine, obtain all types of virtual in the preset time period after the current time
Demand of the machine to hardware resource.
Step 405: according to the current capacities of the resource pool, all types of virtual machine to the demand of hardware resource
And the hardware specification of super fusion all-in-one machine, determine the super fusion all-in-one machine in the preset time period after the current time
Demand.
For step 404, for the virtual machine of each type, realize that process is identical as step 303, details are not described herein.
As an embodiment of the present invention, by predicting the preset time period after current time according to time series data
Virtual machine quantity, the super fusion all-in-one machine demand of the following special time period is obtained further according to virtual machine quantity, due to introducing
It is default after current time to obtain to reflect the time series data of the history growth trend of different type virtual machine quantity
Virtual machine quantity needed for period, and fully considered the growth trend of different type virtual machine, so as to improve to super
Merge the prediction accuracy of all-in-one machine demand.
As an embodiment of the present invention, after step 104, further includes:
Step 501: when receiving monitoring inquiry request, when obtaining the address information and monitoring in the monitoring inquiry request
Between section.
Step 502: virtual machine being determined according to the address information, inquires the prison of the virtual machine in the monitoring time section
Survey reference data.
For step 501 and step 502, wherein the content for monitoring inquiry request is defaulted as virtual resource, then described in acquisition
Monitor inquiry request in address information, virtual machine is determined according to the address information, then judge again to virtual machine whether
In monitoring, if the virtual machine in monitoring, inquires the monitoring reference data of the virtual machine in the monitoring time section.Into one
The monitoring reference data can also be fed back to user terminal in order to which user intuitively understands and monitors inquiry request pair by step ground
The operating condition for the virtual machine answered.
In the embodiment of the present invention, the identification information of the super fusion all-in-one machine in each super aggregators is obtained first,
The sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information, is then melted according to virtual machine with super
The corresponding relationship and the sampled data for closing all-in-one machine obtain the monitoring data of the virtual machine, pass through the monitoring data
The virtual machine is monitored, effectively virtual machine can be monitored, there is stronger practicability and ease for use.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
Embodiment two:
Referring to FIG. 3, it illustrates the data monitoring devices of super fusion cloud computing system provided by Embodiment 2 of the present invention
Structural schematic diagram.The data monitoring device 30 of super fusion cloud computing system includes: that the first acquisition module 31, second obtains module
32, third obtains module 33 and monitoring modular 34.Wherein, the concrete function of each module is as follows:
First obtains module 31, for obtaining the identification information of the super fusion all-in-one machine in each super aggregators.
Second obtains module 32, for obtaining adopting in each super fusion all-in-one machine operational process based on the identification information
Sample data.
Third obtains module 33, for according to virtual machine and the super corresponding relationship for merging all-in-one machine and the sampled data
Obtain the monitoring reference data of the virtual machine.
Monitoring modular 34, for being monitored according to the monitoring reference data to the virtual machine.
Optionally, as shown in figure 4, third acquisition module 33 includes:
Determination unit 331, for determining that each virtual machine is corresponding according to virtual machine and the super corresponding relationship for merging all-in-one machine
Super fusion all-in-one machine.
Acquiring unit 332, for extracting sampled data according to the identification information of the corresponding super fusion all-in-one machine, according to
The sampled data obtains the monitoring reference data of each virtual machine.
Optionally, as shown in figure 5, the data monitoring device 30 of super fusion cloud computing system further include:
Generation module 35 is the virtual machine for being ranked up the monitoring data by the timing of monitoring time point
Generate one group of time series data；The time series data include monitoring time point after sequence and on the monitoring time point it is virtual
The quantity of machine；
First prediction module 36, for being predicted in the preset time period after current time according to the time series data
Virtual machine quantity.
4th obtains module 37, for obtaining the hardware specification of virtual machine.
5th obtains module 38, for virtual in the preset time period after current time according to predicting
The hardware specification of machine quantity and the virtual machine obtains virtual machine in the preset time period after the current time and provides to hardware
The demand in source.
First determining module 39, for according to the current capacities of the resource pool, the virtual machine to the need of hardware resource
The hardware specification of the amount of asking and super fusion all-in-one machine, determines the super fusion all-in-one machine demand within the period in the future.
Optionally, as shown in fig. 6, the data monitoring device 30 of super fusion cloud computing system further include:
Categorization module 310, for being classified according to the type of virtual machine to the monitoring data, and by sorted institute
It states monitoring data to be ranked up by the timing of monitoring time point, generates one group of time series data for each type of virtual machine；It is described
Time series data includes the quantity of monitoring time point and same type of virtual machine corresponding with the monitoring time point.
Second prediction module 311 is predicted default after current time respectively for the time series data according to every group
Period all types of virtual machine quantity；
6th obtains module 312, for obtaining the hardware specification of all types of virtual machines.
7th obtains module 313, for according to all types of in the preset time period after the current time predicted
Virtual machine quantity and all types of virtual machine hardware specification, obtain in the preset time period after the current time
Demand of all types of virtual machines to hardware resource.
Second determining module 314, for according to the current capacities of the resource pool, all types of virtual machine to hardware
The hardware specification of the demand of resource and super fusion all-in-one machine, determines in the preset time period after the current time
Super fusion all-in-one machine demand.
Optionally, as shown in fig. 7, the data monitoring device 30 of super fusion cloud computing system further include:
Receiving module 315 when for receiving monitoring inquiry request, obtains the address information in the monitoring inquiry request
With monitoring time section.
Enquiry module 316 inquires the void in the monitoring time section for determining virtual machine according to the address information
The monitoring data of quasi- machine.
In the embodiment of the present invention, the identification information of the super fusion all-in-one machine in each super aggregators is obtained first,
The sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information, is then melted according to virtual machine with super
The corresponding relationship and the sampled data for closing all-in-one machine obtain the monitoring data of the virtual machine, pass through the monitoring data
The virtual machine is monitored, effectively virtual machine can be monitored, there is stronger practicability and ease for use.
Embodiment three:
Fig. 8 is the schematic diagram for the computer equipment that the embodiment of the present invention three provides.As shown in figure 8, the calculating of the embodiment
Machine equipment 8 includes: processor 80, memory 81 and is stored in the memory 81 and can run on the processor 80
Computer program 82, such as the data monitoring method program of super fusion cloud computing system.The processor 80 executes the meter
The step in the data monitoring method embodiment of above-mentioned each super fusion cloud computing system, such as Fig. 2 are realized when calculation machine program 82
Shown step 101 is to 104.Alternatively, the processor 80 realizes that above-mentioned each device is implemented when executing the computer program 82
The function of each unit in example, such as the function of module 31 to 34 shown in Fig. 3.
Illustratively, the computer program 82 can be divided into one or more module/units, it is one or
Multiple module/units are stored in the memory 81, and are executed by the processor 80, to complete the present invention.Described one
A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for
Execution of the computer program 82 in the data monitoring device 8 of the super fusion cloud computing system of the computer equipment is described
Process.For example, the computer program 82, which can be divided into the first acquisition module, the second acquisition module, third, obtains module
And monitoring modular, the concrete function of each module are as follows:
First obtains module, for obtaining the identification information of the super fusion all-in-one machine in each super aggregators.
Second obtains module, for obtaining the sampling in each super fusion all-in-one machine operational process based on the identification information
Data.
Third obtains module, for being obtained according to virtual machine with the super corresponding relationship for merging all-in-one machine and the sampled data
To the monitoring reference data of the virtual machine.
Monitoring modular, for being monitored according to the monitoring reference data to the virtual machine.
The computer equipment 8 can be the calculating such as desktop PC, notebook, palm PC and cloud server and set
It is standby.The computer equipment may include, but be not limited only to, processor 80, memory 81.It will be understood by those skilled in the art that
Fig. 8 is only the example of computer equipment, does not constitute the restriction to computer equipment, may include more more or less than illustrating
Component, perhaps combine certain components or different components, such as the computer equipment can also be set including input and output
Standby, network access equipment, bus etc..
Alleged processor 80 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 81 can be the internal storage unit of the computer equipment 8, such as the hard disk of computer equipment 8
Or memory.The memory 81 is also possible to the External memory equipment of the computer equipment 8, such as the computer equipment 8
The plug-in type hard disk of upper outfit, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital,
SD) block, flash card (Flash Card) etc..Further, the memory 81 can also both include the computer equipment 8
Internal storage unit also includes External memory equipment.The memory 81 is for storing the computer program and the calculating
Other programs and data needed for machine equipment.The memory 81, which can be also used for temporarily storing, have been exported or will be defeated
Data out.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also
To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system
The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
In embodiment provided by the present invention, it should be understood that disclosed device/terminal device and method, it can be with
It realizes by another way.For example, device described above/terminal device embodiment is only schematical, for example, institute
The division of module or unit is stated, only a kind of logical function partition, there may be another division manner in actual implementation, such as
Multiple units or components can be combined or can be integrated into another system, or some features can be ignored or not executed.Separately
A bit, shown or discussed mutual coupling or direct-coupling or communication connection can be through some interfaces, device
Or the INDIRECT COUPLING or communication connection of unit, it can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or
In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation
All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program
Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on
The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program generation
Code can be source code form, object identification code form, executable file or certain intermediate forms etc..The computer-readable medium
It may include: any entity or device, recording medium, USB flash disk, mobile hard disk, magnetic that can carry the computer program code
Dish, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory (RAM,
Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium etc..It should be noted that described
The content that computer-readable medium includes can carry out increasing appropriate according to the requirement made laws in jurisdiction with patent practice
Subtract, such as does not include electric carrier signal and electricity according to legislation and patent practice, computer-readable medium in certain jurisdictions
Believe signal.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of data monitoring method of super fusion cloud computing system, the super fusion cloud computing system includes multiple super fusion sections
Point and switch, each super aggregators include multiple super fusion all-in-one machines, multiple super fusion all-in-one machines
By the switch carry out network connection form resource pool, according to user demand by it is super fusion all-in-one machine in calculating
Resource invents multiple virtual machines, and each super fusion all-in-one machine has unique identification information；It is characterized in that, the data prison
Survey method includes:
Obtain the identification information of the super fusion all-in-one machine in each super aggregators；
The sampled data in each super fusion all-in-one machine operational process is obtained based on the identification information；
Joined according to virtual machine with the monitoring that the super corresponding relationship for merging all-in-one machine and the sampled data obtain the virtual machine
Examine data；
The virtual machine is monitored according to the monitoring reference data.
2. the data monitoring method of fusion cloud computing system as described in claim 1 super, which is characterized in that according to virtual machine with
The monitoring reference data that the corresponding relationship of super fusion all-in-one machine and the sampled data obtain the virtual machine includes:
According to virtual machine and the super corresponding relationship for merging all-in-one machine, the corresponding super fusion all-in-one machine of each virtual machine is determined；
Sampled data is extracted according to the identification information of the corresponding super fusion all-in-one machine, is obtained according to the sampled data each
The monitoring reference data of virtual machine.
3. the data monitoring method of super fusion cloud computing system as described in claim 1, which is characterized in that the monitoring reference
Data include the quantity of the virtual machine run on the monitoring time point in monitoring time point and the resource pool；Described
After being monitored by the monitoring reference data to the virtual machine, further includes:
The monitoring data are ranked up by the timing of monitoring time point, generate one group of time series data for the virtual machine；Institute
State time series data include sequence after monitoring time point and on the monitoring time point virtual machine quantity；
The virtual machine quantity in the preset time period after current time is predicted according to the time series data；
Obtain the hardware specification of virtual machine；
Virtual machine quantity and the virtual machine according to predicting in the preset time period after current time it is hard
Part specification obtains in the preset time period after the current time virtual machine to the demand of hardware resource；
It is hard to the demand of hardware resource and super fusion all-in-one machine according to the current capacities of the resource pool, the virtual machine
Part specification determines the super fusion all-in-one machine demand within the period in the future.
4. the data monitoring method of super fusion cloud computing system as described in claim 1, which is characterized in that the monitoring data
Type and quantity including the virtual machine run on the monitoring time point in monitoring time point and the resource pool, in institute
It states after being monitored by the monitoring reference data to the virtual machine, further includes:
Classified according to the type of virtual machine to the monitoring data, and the sorted monitoring data are pressed into monitoring time
The timing of point is ranked up, and generates one group of time series data for each type of virtual machine；The time series data includes monitoring time
The quantity of point and same type of virtual machine corresponding with the monitoring time point；
The time series data according to every group predicts all types of virtual machine quantity of the preset time period after current time respectively；
Obtain the hardware specification of all types of virtual machines；
According to virtual machine quantity all types of in the preset time period after the current time predicted and described all types of
Virtual machine hardware specification, obtain virtual machine all types of in the preset time period after the current time to hardware resource
Demand；
According to the current capacities of the resource pool, all types of virtual machine to the demand of hardware resource and super fusion one
The hardware specification of body machine determines the super fusion all-in-one machine demand in the preset time period after the current time.
5. data monitoring method as described in claim 1, which is characterized in that it is described by the monitoring reference data to institute
It states after virtual machine is monitored, further includes:
When receiving monitoring inquiry request, the address information and monitoring time section in the monitoring inquiry request are obtained；
Virtual machine is determined according to the address information, inquires the monitoring data of the virtual machine in the monitoring time section.
6. a kind of data monitoring device of the super fusion cloud computing system of super fusion cloud computing system characterized by comprising
First obtains module, for obtaining the identification information of the super fusion all-in-one machine in each super aggregators；
Second obtains module, for obtaining the hits in each super fusion all-in-one machine operational process based on the identification information
According to；
Third obtains module, for obtaining institute with the super corresponding relationship for merging all-in-one machine and the sampled data according to virtual machine
State the monitoring reference data of virtual machine；
Monitoring modular, for being monitored according to the monitoring reference data to the virtual machine.
7. the data monitoring device of super fusion cloud computing system as claimed in claim 6, which is characterized in that third obtains module
Include:
Determination unit, for according to virtual machine and the super corresponding relationship for merge all-in-one machine, determine each virtual machine it is corresponding surpass melt
Close all-in-one machine；
Acquiring unit is adopted for extracting sampled data according to the identification information of the corresponding super fusion all-in-one machine according to described
Sample data obtain the monitoring reference data of each virtual machine.
8. the data monitoring device of super fusion cloud computing system as claimed in claim 6, which is characterized in that further include:
Generation module generates one for being ranked up the monitoring data by the timing of monitoring time point for the virtual machine
Group time series data；The time series data include sequence after monitoring time point and on the monitoring time point virtual machine number
Amount；
First prediction module, for predicting the virtual machine in the preset time period after current time according to the time series data
Quantity；
4th obtains module, for obtaining the hardware specification of virtual machine；
5th obtains module, for the virtual machine quantity according to predicting in the preset time period after current time
With the hardware specification of the virtual machine, virtual machine is obtained in the preset time period after the current time to the need of hardware resource
The amount of asking；
First determining module, for according to the current capacities of the resource pool, the virtual machine to the demand of hardware resource with
And the hardware specification of super fusion all-in-one machine, determine the super fusion all-in-one machine demand within the period in the future.
9. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
The step of any one of 5 the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 5 of realization the method.
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