CN116708322A - Resource allocation method, device, equipment and medium - Google Patents
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- 238000013468 resource allocation Methods 0.000 title claims abstract description 56
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
- H04L47/82—Miscellaneous 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
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- G06—COMPUTING; CALCULATING OR COUNTING
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- 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
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5077—Logical partitioning of resources; Management or configuration of virtualized resources
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The disclosure provides a resource allocation method, a device, equipment, a medium and a program product, which can be applied to the technical fields of cloud computing and finance. The method comprises the following steps: responding to a received resource allocation request of a user positioned in a target area within a preset time interval, and acquiring resource demand information contained in the resource allocation request; determining the average value of the number of processors required by each virtual machine associated with the resource demand information according to the resource demand information; determining the total number of resources of the physical machine associated with the virtual machine under the condition that the average value meets a preset threshold value; and configuring required computing resources and storage resources for the user located in the target area according to the first resource proportion value and the total number of resources, wherein the resource proportion value is determined according to the storage capacity.
Description
Technical Field
The present disclosure relates to the field of cloud computing and financial technology, and in particular, to a resource allocation method, apparatus, device, medium, and program product.
Background
With the development of data center business and the deep transformation of architecture, the requirements for optimizing the aggregation construction area of the data center are put forward in the related matters of overall construction of the data center, the green data center is taken as a core, the latest technology and best practice of intelligent operation are combined, the factors such as resource investment and implementation period are comprehensively considered, and the optimal resource architecture is configured according to the principles of low investment, quick response and energy conservation and open flow, so that the green low-carbon data center is realized.
In the process of implementing the method, the problem that the resource measuring method is complex and the measuring period is too long exists in that the resource configuration is performed after the condition of manually measuring and calculating the required resources through the resource architecture post is found; and the method and the device have the advantages that the required resources are required to be calculated again according to the change of the user demands, and the problem that calculation errors easily occur when repeated complex works are repeated for many times, so that the resource allocation is unreasonable and the resources are wasted.
Disclosure of Invention
In view of the foregoing, the present disclosure provides a resource allocation method, apparatus, device, medium, and program product.
According to a first aspect of the present disclosure, there is provided a resource allocation method, including:
responding to a received resource allocation request of a user positioned in a target area within a preset time interval, and acquiring resource demand information contained in the resource allocation request;
determining the average value of the number of processors required by each virtual machine associated with the resource demand information according to the resource demand information;
determining the total number of resources of the physical machine associated with the virtual machine under the condition that the average value meets a preset threshold value; and
and configuring required computing resources and storage resources for the user positioned in the target area according to the first resource proportion value and the total number of resources, wherein the resource proportion value is determined according to the storage capacity.
According to an embodiment of the present disclosure, determining, from resource demand information, a mean value of a number of processors required for each virtual machine associated with the resource demand information includes:
analyzing the resource demand information to obtain first quantity information of the virtual machines associated with the resource demand information;
and determining the average value of the number of processors required by each virtual machine according to the first number information and the second number information of the processors required by each virtual machine.
According to an embodiment of the present disclosure, in a case where it is determined that the average value satisfies a preset threshold, determining a total number of resources of a physical machine associated with the virtual machine includes:
under the condition that the average value meets a preset threshold value, the number information of the initial virtual processors is obtained after the processors required by the physical computer are subjected to super-division preset multiple calculation;
determining the number information of the target virtual processors according to the number information of the initial virtual processors and the emergency calculation resource proportion value;
and inputting the first quantity information, the second quantity information and the quantity information of the target virtual processors into a preset algorithm, and outputting the total number of resources of the physical machines associated with the virtual machines.
According to an embodiment of the present disclosure, the storage capacity includes a first storage capacity and a second storage capacity;
The above resource allocation method further comprises:
and determining a first resource proportion value according to the first storage capacity which can be supplied by each storage physical machine and the second storage capacity which is required by each calculation physical machine.
According to an embodiment of the present disclosure, the above-mentioned resource allocation method further includes:
determining a first storage capacity according to the hard disk storage capacity used by the storage physical machine and a preset constraint proportion value;
the second storage capacity is determined based on the third storage capacity required by the virtual machine.
According to an embodiment of the present disclosure, a first resource proportion value is used to characterize proportion information of computing resources and storage resources;
according to the first resource proportion value and the total number of resources, configuring required computing resources and storage resources for the user positioned in the target area, wherein the method comprises the following steps:
determining information of computing resources accounting for the total number of resources and information of storage resources accounting for the total number of resources according to the first resource proportion value;
multiplying the information of the computing resources accounting for the total number of resources by the total number of resources to obtain computing resources;
and multiplying the information of the storage resources accounting for the total number of the resources by the total number of the resources to obtain the storage resources.
According to an embodiment of the present disclosure, the above-mentioned resource allocation method further includes:
Setting the quantity information of the virtual machines matched with the single computer physical machine as preset quantity information under the condition that the average value does not meet the preset threshold value;
according to the preset quantity information and the first quantity information of the virtual machines associated with the resource demand information, configuring required computing resources for users positioned in a target area;
determining a second resource proportion value according to the fourth storage capacity and the first storage capacity required by the virtual machine;
and according to the second resource proportion value and the computing resource, configuring the required storage resource for the user positioned in the target area.
A second aspect of the present disclosure provides a resource allocation apparatus, comprising:
the acquisition module is used for responding to the received resource allocation request of the user positioned in the target area within the preset time interval and acquiring the resource demand information contained in the resource allocation request;
the first determining module is used for determining the average value of the number of processors required by each virtual machine associated with the resource demand information according to the resource demand information;
the second determining module is used for determining the total number of resources of the physical machine associated with the virtual machine under the condition that the average value meets the preset threshold value; and
And the configuration module is used for configuring required computing resources and storage resources for the users positioned in the target area according to the first resource proportion value and the total number of resources, wherein the first resource proportion value is determined according to the storage capacity.
A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the resource allocation method described above.
A fourth aspect of the present disclosure also provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the above-described resource allocation method.
A fifth aspect of the present disclosure also provides a computer program product comprising a computer program which, when executed by a processor, implements the above-described resource allocation method.
According to the embodiment of the disclosure, the average value of the number of processors required by each virtual machine associated with the resource demand information is determined according to the resource demand information, and the method for determining the resources is simplified according to the difference of the number of processors required by each virtual machine associated with the resource demand information. Under the condition that a preset threshold value is met, computing resources and storage resources are determined through the total number of the resources and the proportion value of the resources, corresponding resources are configured for users located in a target area, and the configuration is performed after manual repeatability measurement is not needed for changing the demands of the users, so that the resource configuration efficiency is improved, the reasonable configuration of the resources is realized, and the resources are saved.
Drawings
The foregoing and other objects, features and advantages of the disclosure will be more apparent from the following description of embodiments of the disclosure with reference to the accompanying drawings, in which:
FIG. 1 schematically illustrates an application scenario diagram of a resource allocation method, apparatus, device, medium and program product according to an embodiment of the present disclosure;
FIG. 2 schematically illustrates a flow chart of a resource allocation method according to an embodiment of the disclosure;
FIG. 3 schematically illustrates a flow chart of a method of determining a mean of the number of processors required for each virtual machine associated with resource demand information according to resource demand information, according to an embodiment of the disclosure;
FIG. 4 schematically illustrates a method flow diagram for determining a total number of resources of a physical machine associated with a virtual machine in the event that a determination is made that a mean value meets a preset threshold, in accordance with an embodiment of the present disclosure;
FIG. 5 schematically illustrates a flow chart of a resource allocation method according to another embodiment of the present disclosure;
FIG. 6 schematically illustrates a block diagram of a resource allocation apparatus according to an embodiment of the disclosure; and
fig. 7 schematically illustrates a block diagram of an electronic device adapted to implement a resource allocation method according to an embodiment of the disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
In the technical scheme of the disclosure, the related data (such as including but not limited to personal information of a user) are collected, stored, used, processed, transmitted, provided, disclosed, applied and the like, all conform to the regulations of related laws and regulations, necessary security measures are adopted, and the public welcome is not violated.
In the technical scheme of the embodiment of the disclosure, the authorization or consent of the user is obtained before the personal information of the user is obtained or acquired.
In the process of implementing the present disclosure, it is found that, in a cloud computing scenario, with the advent of virtual machine technology, cloud services obtain large-scale applications, a large number of users continuously move an infrastructure to the cloud, and in order to meet the increasing demands of users for cloud services, cloud service providers need to continuously input servers to a resource pool to support normal operation of cloud services. The virtual machine is installed on a server for providing cloud services. How the data center rapidly configures the resources required by the user through corresponding resource measurement and calculation is more important. The existing resource configuration is carried out after the condition of manually measuring and calculating the required resources through a resource architecture post, so that the problems of complex resource measuring and calculating method and overlong measuring and calculating period exist; and the method and the device have the advantages that the required resources are required to be calculated again according to the change of the user demands, and the problem that calculation errors easily occur when repeated complex works are repeated for many times, so that the resource allocation is unreasonable and the resources are wasted.
The embodiment of the disclosure provides a resource allocation method, which comprises the following steps: responding to a received resource allocation request of a user positioned in a target area within a preset time interval, and acquiring resource demand information contained in the resource allocation request; determining the average value of the number of processors required by each virtual machine associated with the resource demand information according to the resource demand information; determining the total number of resources of the physical machine associated with the virtual machine under the condition that the average value meets a preset threshold value; and configuring required computing resources and storage resources for the user located in the target area according to the first resource proportion value and the total number of resources, wherein the resource proportion value is determined according to the storage capacity.
Fig. 1 schematically illustrates an application scenario diagram of a resource allocation method, apparatus, device, medium and program product according to an embodiment of the present disclosure.
As shown in fig. 1, the application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is a medium used to provide a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 through the network 104 using at least one of the first terminal device 101, the second terminal device 102, the third terminal device 103, to receive or send messages, etc. Various communication client applications, such as a shopping class application, a web browser application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc. (by way of example only) may be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103.
The first terminal device 101, the second terminal device 102, the third terminal device 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (by way of example only) providing support for websites browsed by the user using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as the user request, and feed back the processing result (e.g., the web page, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that, the resource allocation method provided by the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the resource allocation apparatus provided by the embodiments of the present disclosure may be generally disposed in the server 105. The resource allocation method provided by the embodiments of the present disclosure may also be performed by a server or a server cluster that is different from the server 105 and is capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and/or the server 105. Accordingly, the resource allocation apparatus provided by the embodiments of the present disclosure may also be provided in a server or a server cluster that is different from the server 105 and is capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103 and/or the server 105.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
The resource allocation method of the disclosed embodiment will be described in detail below with reference to fig. 2 to 5 based on the scenario described in fig. 1.
Fig. 2 schematically illustrates a flow chart of a resource allocation method according to an embodiment of the present disclosure.
As shown in fig. 2, the resource allocation method 200 of this embodiment includes operations S210 to S240.
In operation S210, in response to a received resource allocation request of a user located in a target area within a preset time interval, resource demand information included in the resource allocation request is acquired.
According to an embodiment of the present disclosure, the preset time interval may be divided in quarters. The target areas may be different resource domains for different campuses. The resource allocation request may be generated by the user while handling the actual service. The resource requirement information may include information on the number of virtual machines required.
The resource domain may refer to each area where resources are logically isolated according to different network areas.
For example, the preset time interval may be any one of a first quarter, a second quarter, a third quarter, and a fourth quarter of a certain year. The target area may be a particular resource domain of a city or campus.
In operation S220, a mean value of the number of processors required for each virtual machine associated with the resource demand information is determined according to the resource demand information.
According to the embodiment of the disclosure, the number information of the needed virtual machines can be determined according to the resource demand information. And determining the average value of the number of processors required by each virtual machine associated with the resource requirement information according to the number information of the required virtual machines and the number information of the processors required by each virtual machine. Wherein the processor may be a Central Processing Unit (CPU).
For example, the number information of the processors required by each virtual machine may be accumulated and summed to obtain total number information of the processors required by all the virtual machines. Dividing the total number information of the processors required by all the virtual machines by the number information of the required virtual machines to obtain the average value of the number of the processors required by each virtual machine.
In operation S230, in case that it is determined that the average value satisfies the preset threshold value, the total number of resources of the physical machines associated with the virtual machine is determined.
According to embodiments of the present disclosure, the preset threshold may be determined based on actual experience. The average value can be compared with a preset threshold value, and the average value is determined to meet the preset threshold value under the condition that the average value is larger than the preset threshold value; and under the condition that the average value is smaller than the preset threshold value, determining that the average value does not meet the preset threshold value. In the case that the average value meets the preset threshold value, the total number of resources of the physical machine associated with the virtual machine can be determined according to a preset algorithm. Namely, building a needed virtual machine and correspondingly putting into a physical machine.
In operation S240, the required computing resources and storage resources are configured for the user located in the target area according to the first resource proportion value and the total number of resources, wherein the resource proportion value is determined according to the storage capacity.
According to embodiments of the present disclosure, the storage capacity required by a computing resource, as well as the storage capacity available to the storage resource, may be determined from the storage capacity. And obtaining a first resource proportion value according to the ratio of the storage capacity required by the computing resource to the storage capacity which can be supplied by the storage resource. According to the proportion of the storage capacity required by the computing resources to the total storage capacity, the computing resources are determined in combination with the total number of resources, so that the required computing resources are configured for the users located in the target area. And determining the storage resources according to the proportion of the storage capacity which can be supplied by the storage resources to the total storage capacity and combining the total number of the resources so as to configure the required storage resources for the users positioned in the target area.
According to the embodiment of the disclosure, the average value of the number of processors required by each virtual machine associated with the resource demand information is determined according to the resource demand information, and the method for determining the resources is simplified according to the difference of the number of processors required by each virtual machine associated with the resource demand information. Under the condition that a preset threshold value is met, computing resources and storage resources are determined through the total number of the resources and the proportion value of the resources, corresponding resources are configured for users located in a target area, and the configuration is performed after manual repeatability measurement is not needed for changing the demands of the users, so that the resource configuration efficiency is improved, the reasonable configuration of the resources is realized, and the resources are saved.
FIG. 3 schematically illustrates a flow chart of a method of determining a mean of the number of processors required for each virtual machine associated with resource demand information according to resource demand information, according to an embodiment of the disclosure.
As shown in fig. 3, the method 320 of determining the average value of the number of processors required for each virtual machine associated with the resource demand information according to the resource demand information of this embodiment includes operations S321 to S322.
In operation S321, the resource requirement information is parsed to obtain first number information of virtual machines associated with the resource requirement information.
According to embodiments of the present disclosure, the first number of virtual machines associated with the resource demand information may be used to characterize the number of virtual machines associated with the resource demand information.
In operation S322, a mean value of the number of processors required for each virtual machine is determined according to the first number information and the second number information of the processors required for each virtual machine.
According to the embodiment of the disclosure, the number of the virtual machines associated with the resource requirement information can be determined according to the first number information. And determining the number of the processors required by each virtual machine according to the second number information of the processors required by each virtual machine. And obtaining the total number of the processors required by all the virtual machines associated with the resource demand information according to the number of the virtual machines associated with the resource demand information and the number of the processors required by each virtual machine. And obtaining the average value of the number of processors required by each virtual machine according to the total number and the number of the virtual machines associated with the resource demand information.
For example, the number of CPUs required for each virtual machine associated with the resource demand information is summed up and divided by the number of virtual machines associated with the resource demand information to obtain a mean value of the number of processors required for each virtual machine.
According to the embodiment of the disclosure, the average value of the number of processors required by each virtual machine is determined through the first number of the virtual machines associated with the resource demand information and the second number of the processors required by each virtual machine, and the method for determining the resources is simplified according to the difference of the number of the processors required by each virtual machine associated with the resource demand information, so that the method for determining the resources is beneficial to determining the related information of the physical machines associated with the virtual machines.
Fig. 4 schematically illustrates a flowchart of a method of determining a total number of resources of a physical machine associated with a virtual machine in case the average is determined to meet a preset threshold according to an embodiment of the present disclosure.
As shown in fig. 4, in the case where the average value is determined to satisfy the preset threshold value, the method 430 of determining the total number of resources of the physical machine associated with the virtual machine according to the embodiment includes operations S431 to S433.
In operation S431, under the condition that the average value meets the preset threshold value, the number information of the initial virtual processors is obtained after the processors required by the physical computer are subjected to super division by a preset multiple.
According to embodiments of the present disclosure, the number of initial virtual processors information may be used to characterize the number of initial virtual processors.
For example, the preset threshold may be 8, and in the case that the average value of the number of central processors required by each virtual machine is greater than 8, the central processors required by one computing physical machine may be superdivided by 4 times, so as to obtain 320 initial virtual central processors.
In operation S432, the number information of the target virtual processors is determined according to the number information of the initial virtual processors and the emergency computing resource proportion value.
According to an embodiment of the disclosure, the emergency computing resource proportion value may be determined according to daily operation and maintenance experience according to the fact that related emergency resources are reserved under the conditions of architecture version iteration and daily computing resource downtime. The emergency computing resource scale value may be used to characterize the percentage of computing resources required for the associated emergency resource. The number information of the target virtual processors may be determined according to a product of the number of the initial virtual processors and the emergency computing resource proportion value.
For example, the emergency computing resource proportion value may be 40%. Approximately 320 initial virtual cpus may be multiplied by 40% to yield 192 target virtual cpus.
In operation S433, the first number information, the second number information, and the number information of the target virtual processors are input to a preset algorithm, and the total number of resources of the physical machine associated with the virtual machine is output.
According to embodiments of the present disclosure, the preset algorithm may be constructed according to the number of virtual machines associated with the resource demand information, the number of processors required for each virtual machine, the number of target virtual processors, and the total number of resources of the physical machines associated with the virtual machines.
For example, the total number of resources of the physical machines associated with the virtual machines may be determined based on the cumulative sum of the number of central processors required for each virtual machine divided by the number of target virtual processors.
According to the embodiment of the disclosure, under the condition that the average value meets the preset threshold value, the processor required by the physical machine is oversubscribed by a preset multiple, and under the condition that emergency computing resources are considered, the total number of resources of the physical machine associated with the virtual machine is determined, so that accurate computing resources and storage resources are obtained, and reasonable distribution of the resources is facilitated.
According to an embodiment of the present disclosure, the resource allocation method may further include, in addition to the operations S210 to S240 described above:
And determining a first resource proportion value according to the first storage capacity which can be supplied by each storage physical machine and the second storage capacity which is required by each calculation physical machine.
The storage capacity may include a first storage capacity and a second storage capacity.
According to embodiments of the present disclosure, the first resource proportion value may be determined according to a ratio of the second storage capacity required by each of the computing physical machines to the first storage capacity available to each of the storage physical machines.
According to the embodiment of the disclosure, the first resource proportion value is determined according to the first storage capacity which can be supplied by each storage physical machine and the second storage capacity which is required by each calculation physical machine, and the proportion value of the storage physical machine and the calculation physical machine can be indirectly determined from the perspective of the storage capacity, so that the accurate determination of calculation resources and storage resources is facilitated, the reasonable configuration of the resources can be realized, and the resources are saved.
According to an embodiment of the present disclosure, the resource allocation method may further include, in addition to the above method:
determining a first storage capacity according to the hard disk storage capacity used by the storage physical machine and a preset constraint proportion value; the second storage capacity is determined based on the third storage capacity required by the virtual machine.
According to embodiments of the present disclosure, the preset constraint scaling value may be determined based on actual operational experience in conjunction with high availability of services.
For example, one physical storage machine may house 12 built-in disks, and the size of a single built-in disk may be 7.68T, so that the storage capacity of a hard disk used by a single physical storage machine may be 7.68t×12. The preset constraint ratio value may be 0.9, and the first storage capacity may be 7.68t×12×0.9. If there are three copies of one storage physical machine, the first storage capacity may be 7.68T 12X 0.9/3, i.e., 27.648T.
According to embodiments of the present disclosure, the number of provisionable virtual machines per computing physical machine may be determined from an average of the number of processors required per virtual machine associated with the resource demand information and the number of target virtual processors information. The third storage capacity required for the virtual machines may be determined based on the storage capacity required for each virtual machine and the number of virtual machines available to each computing physical machine.
According to embodiments of the present disclosure, the third storage capacity required by the virtual machine may be taken as the second storage capacity required by each computing physical machine.
According to the embodiment of the disclosure, the number of the virtual machines that can be supplied by each physical computing machine may further determine, according to operation and maintenance experience, a third storage capacity required by the virtual machine according to a preset value and a storage capacity required by each virtual machine when it is determined that the average value of the number of processors required by each virtual machine associated with the resource demand information meets a preset condition.
For example, the storage capacity required for each virtual machine is 400G, and the preset value may be 16 if the average value of the number of processors required for each virtual machine associated with the resource requirement information is 12. The second storage capacity required by the single physical computer may be determined to be 16×400g, and according to the 1T equivalent to 1024G, the second storage capacity required by the single physical computer is obtained to be 6.25T. The first resource proportion value may be 4.42:1.
according to the embodiment of the disclosure, the first resource proportion value can be further determined by determining the first storage capacity and the second storage capacity, so that the computing resources and the storage resources can be rapidly and accurately determined by combining the total number of the resources, reasonable configuration of the resources is realized, the configuration is performed after manual repeatability measurement is not needed for changing the user demands, the working efficiency is improved, and the resources are saved.
According to embodiments of the present disclosure, the first resource proportion value may be used to characterize proportion information of the computing resource and the storage resource.
The configuring the required computing resource and storage resource for the user located in the target area according to the first resource proportion value and the total number of resources may include:
determining information of computing resources accounting for the total number of resources and information of storage resources accounting for the total number of resources according to the first resource proportion value; multiplying the information of the computing resources accounting for the total number of resources by the total number of resources to obtain computing resources; and multiplying the information of the storage resources accounting for the total number of the resources by the total number of the resources to obtain the storage resources.
According to embodiments of the present disclosure, the first resource proportion value may be determined according to a ratio of the second storage capacity required by each of the computing physical machines to the first storage capacity available to each of the storage physical machines.
According to the embodiment of the disclosure, corresponding resources are configured for the user positioned in the target area according to the obtained computing resources and the storage resources, so that reasonable configuration of the resources is realized, resources are saved, and meanwhile, the resource configuration efficiency is improved.
Fig. 5 schematically illustrates a flow chart of a resource allocation method according to another embodiment of the present disclosure.
As shown in fig. 5, the resource allocation method 500 of this embodiment may include operations S510 to S540.
In operation S510, in case that it is determined that the average value does not satisfy the preset threshold value, the number information of virtual machines matching with the single computing physical machine is set as the preset number information.
According to embodiments of the present disclosure, the preset threshold may be determined based on actual experience. The average value may be compared with a preset threshold value, and if the average value is smaller than the preset threshold value, it is determined that the average value does not satisfy the preset threshold value. The preset number information is used for representing the number of virtual machines matched with the single computer physical machine.
For example, the number information of virtual machines matching with a single physical computer may be 20 virtual machines matching with a single physical computer, and 20 virtual machines may be set as the preset number information.
In operation S520, a required computing resource is configured for the user located in the target area according to the preset number information and the first number information of the virtual machines associated with the resource demand information.
According to embodiments of the present disclosure, first number information of virtual machines associated with resource demand information may be used to characterize the number of virtual machines associated with the resource demand information. The number of virtual machines associated with the resource demand information may be divided by the number of virtual machines matching a single computing physical machine to obtain the number of computing physical machines required, and configuring the required computing resources for the user located in the target area according to the number of computing physical machines.
In operation S530, a second resource proportion value is determined according to the fourth storage capacity required by the virtual machine and the first storage capacity.
According to the embodiment of the disclosure, the first storage capacity can be determined according to the hard disk storage capacity used by the storage physical machine and a preset constraint proportion value. The preset constraint proportion value can be determined according to actual operation and maintenance experience in combination with high availability of the service. The fourth storage capacity required by the virtual machine may be determined according to the preset number of information and the storage capacity required by each virtual machine. And determining a second resource proportion value according to the ratio of the fourth storage capacity to the first storage capacity.
For example, one physical storage machine may house 12 built-in disks, and the size of a single built-in disk may be 7.68T, so that the storage capacity of a hard disk used by a single physical storage machine may be 7.68t×12. The preset constraint ratio value may be 0.9, and the first storage capacity may be 7.68t×12×0.9. If there are three copies of one storage physical machine, the first storage capacity may be 7.68T 12X 0.9/3, i.e., 27.648T.
The storage capacity required by each virtual machine is 400G, and the preset number of information can be 20 virtual machines. The fourth storage capacity required by the single physical computer can be determined to be 20 x 400G, and according to the fact that 1T corresponds to 1024G, the fourth storage capacity required by the single physical computer is 7.8125T. The second resource proportion value may be 3.54:1.
in operation S540, the required storage resources are configured for the user located in the target area according to the second resource proportion value and the computing resources.
According to embodiments of the present disclosure, the storage resources may be determined from the second resource proportion value and the computing resources. And configuring the user positioned in the target area according to the determined storage resources.
According to the embodiment of the disclosure, by considering the situation that the average value does not meet the preset threshold value, the computing resource and the storage resource are determined, corresponding resources are configured for the user positioned in the target area, and the configuration is performed after the manual repeatability measurement is not needed for the change of the user demand, so that the resource configuration efficiency is improved, the reasonable configuration of the resources is realized, and the resources are saved.
According to the embodiment of the disclosure, related emergency resources are required to be reserved under the conditions of architecture version iteration and downtime of daily computing resources, and the emergency computing resource proportion value can be determined according to daily operation and maintenance experience. The emergency computing resource scale value may be used to characterize the percentage of computing resources required for the associated emergency resource. For example, the emergency computing resource proportion value may be 40%. Under the condition that the computing resources and the storage resources are determined according to the resource configuration method provided by the disclosure, after the computing resources are newly added with emergency computing resources, corresponding resources are configured for users located in the target area.
According to the embodiment of the disclosure, since the storage pool can be generally built according to 32 storage nodes and the dual resource domains together, the construction situation of the storage pool needs to be comprehensively considered when the storage resources are measured and calculated in different seasons.
Based on the resource allocation method, the disclosure also provides a resource allocation device. The device will be described in detail below in connection with fig. 6.
Fig. 6 schematically shows a block diagram of a resource allocation apparatus according to an embodiment of the present disclosure.
As shown in fig. 6, the resource configuration apparatus 600 of this embodiment includes an acquisition module 610, a first determination module 620, a second determination module 630, and a configuration module 640.
The obtaining module 610 is configured to obtain, in response to a received resource allocation request of a user located in a target area within a preset time interval, resource requirement information included in the resource allocation request. In an embodiment, the obtaining module 610 may be configured to perform the operation S210 described above, which is not described herein.
The first determining module 620 is configured to determine, according to the resource requirement information, a mean value of the number of processors required by each virtual machine associated with the resource requirement information. In an embodiment, the first determining module 620 may be configured to perform the operation S220 described above, which is not described herein.
The second determining module 630 is configured to determine a total number of resources of the physical machine associated with the virtual machine if the average value meets a preset threshold. In an embodiment, the second determining module 630 may be configured to perform the operation S230 described above, which is not described herein.
The configuration module 640 is configured to configure required computing resources and storage resources for the user located in the target area according to a first resource proportion value and a total number of resources, where the first resource proportion value is determined according to the storage capacity. In an embodiment, the configuration module 640 may be configured to perform the operation S240 described above, which is not described herein.
According to an embodiment of the present disclosure, the resource configuration device 600 may further comprise a third determination module.
The third determining module is used for determining a first resource proportion value according to the first storage capacity which can be supplied by each storage physical machine and the second storage capacity which is required by each calculation physical machine.
According to an embodiment of the present disclosure, the resource configuration device 600 may further include a fourth determination module and a fifth determination module.
The fourth determining module is used for determining the first storage capacity according to the hard disk storage capacity used by the storage physical machine and a preset constraint proportion value.
The fifth determining module is used for determining the second storage capacity according to the third storage capacity required by the virtual machine.
According to an embodiment of the present disclosure, the resource configuration apparatus 600 may further include an information setting module, a first sub-configuration module, a sixth determination module, and a second sub-configuration module.
The information setting module is used for setting the number information of the virtual machines matched with the single computer physical machine as preset number information under the condition that the average value does not meet the preset threshold value.
The first sub-configuration module is used for configuring required computing resources for users located in the target area according to preset quantity information and first quantity information of the virtual machines associated with the resource demand information.
The sixth determining module is configured to determine a second resource proportion value according to the fourth storage capacity and the first storage capacity required by the virtual machine.
The second sub-configuration module is used for configuring required storage resources for the user positioned in the target area according to the second resource proportion value and the calculation resources.
Any of the acquisition module 610, the first determination module 620, the second determination module 630, and the configuration module 640 may be combined in one module to be implemented, or any of the modules may be split into a plurality of modules, according to embodiments of the present disclosure. Alternatively, at least some of the functionality of one or more of the modules may be combined with at least some of the functionality of other modules and implemented in one module. According to embodiments of the present disclosure, at least one of the acquisition module 610, the first determination module 620, the second determination module 630, and the configuration module 640 may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging the circuitry, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, at least one of the acquisition module 610, the first determination module 620, the second determination module 630, and the configuration module 640 may be at least partially implemented as a computer program module, which when executed, may perform the respective functions.
Fig. 7 schematically illustrates a block diagram of an electronic device adapted to implement a resource allocation method according to an embodiment of the disclosure.
As shown in fig. 7, an electronic device 700 according to an embodiment of the present disclosure includes a processor 701 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. The processor 701 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor 701 may also include on-board memory for caching purposes. The processor 701 may comprise a single processing unit or a plurality of processing units for performing different actions of the method flows according to embodiments of the disclosure.
In the RAM 703, various programs and data necessary for the operation of the electronic apparatus 700 are stored. The processor 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. The processor 701 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 702 and/or the RAM 703. Note that the program may be stored in one or more memories other than the ROM 702 and the RAM 703. The processor 701 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to an embodiment of the present disclosure, the electronic device 700 may further include an input/output (I/O) interface 705, the input/output (I/O) interface 705 also being connected to the bus 704. The electronic device 700 may also include one or more of the following components connected to the I/O interface 705: an input section 706 including a keyboard, a mouse, and the like; an output portion 707 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 708 including a hard disk or the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. The drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read therefrom is mounted into the storage section 708 as necessary.
The present disclosure also provides a computer-readable storage medium that may be embodied in the apparatus/device/system described in the above embodiments; or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, the computer-readable storage medium may include ROM 702 and/or RAM 703 and/or one or more memories other than ROM 702 and RAM 703 described above.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowcharts. The program code, when executed in a computer system, causes the computer system to perform the methods provided by embodiments of the present disclosure.
The above-described functions defined in the system/apparatus of the embodiments of the present disclosure are performed when the computer program is executed by the processor 701. The systems, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed over a network medium in the form of signals, downloaded and installed via the communication section 709, and/or installed from the removable medium 711. The computer program may include program code that may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 709, and/or installed from the removable medium 711. The above-described functions defined in the system of the embodiments of the present disclosure are performed when the computer program is executed by the processor 701. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.
According to embodiments of the present disclosure, program code for performing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, such computer programs may be implemented in high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. Programming languages include, but are not limited to, such as Java, c++, python, "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Those skilled in the art will appreciate that the features recited in the various embodiments of the disclosure and/or in the claims may be provided in a variety of combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.
The embodiments of the present disclosure are described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.
Claims (11)
1. A resource allocation method, comprising:
responding to a received resource allocation request of a user positioned in a target area within a preset time interval, and acquiring resource demand information contained in the resource allocation request;
Determining the average value of the number of processors required by each virtual machine associated with the resource demand information according to the resource demand information;
determining the total number of resources of the physical machine associated with the virtual machine under the condition that the average value meets a preset threshold value; and
and configuring required computing resources and storage resources for the user positioned in the target area according to a first resource proportion value and the total number of resources, wherein the first resource proportion value is determined according to storage capacity.
2. The method of claim 1, the determining, from the resource demand information, a mean of the number of processors required for each virtual machine associated with the resource demand information, comprising:
analyzing the resource demand information to obtain first quantity information of the virtual machines associated with the resource demand information;
and determining the average value of the number of processors required by each virtual machine according to the first number information and the second number information of the processors required by each virtual machine.
3. The method of claim 2, wherein the determining the total number of resources of the physical machine associated with the virtual machine if the average is determined to satisfy a preset threshold comprises:
Under the condition that the average value meets a preset threshold value, the processors required by the physical computer are subjected to superdivision preset multiple to obtain the quantity information of the initial virtual processors;
determining the number information of the target virtual processors according to the number information of the initial virtual processors and the emergency computing resource proportion value;
and inputting the first quantity information, the second quantity information and the quantity information of the target virtual processor into a preset algorithm, and outputting the total number of resources of the physical machine associated with the virtual machine.
4. The method of claim 1, wherein the storage capacity comprises a first storage capacity and a second storage capacity;
the method further comprises the steps of:
and determining the first resource proportion value according to the first storage capacity which can be supplied by each storage physical machine and the second storage capacity which is required by each calculation physical machine.
5. The method of claim 4, further comprising:
determining the first storage capacity according to the hard disk storage capacity used by the storage physical machine and a preset constraint proportion value;
and determining the second storage capacity according to the third storage capacity required by the virtual machine.
6. The method of claim 4, the first resource proportion value being used to characterize proportion information of the computing resource and the storage resource;
wherein the configuring the required computing resource and storage resource for the user located in the target area according to the first resource proportion value and the total number of resources includes:
determining information of the computing resources accounting for the total number of resources and information of the storage resources accounting for the total number of resources according to a first resource proportion value;
multiplying the information of the computing resources accounting for the total number of the resources by the total number of the resources to obtain the computing resources;
and multiplying the information of the storage resources accounting for the total number of the resources by the total number of the resources to obtain the storage resources.
7. The method of claim 5, further comprising:
setting the quantity information of the virtual machines matched with the single computer physical machine as preset quantity information under the condition that the average value does not meet a preset threshold value;
configuring the required computing resources for the user located in the target area according to the preset quantity information and the first quantity information of the virtual machines associated with the resource demand information;
Determining a second resource proportion value according to the fourth storage capacity required by the virtual machine and the first storage capacity;
and configuring the needed storage resources for the user positioned in the target area according to the second resource proportion value and the computing resources.
8. A resource allocation apparatus, comprising:
the acquisition module is used for responding to a received resource allocation request of a user positioned in a target area within a preset time interval, and acquiring resource demand information contained in the resource allocation request;
the first determining module is used for determining the average value of the number of processors required by each virtual machine associated with the resource demand information according to the resource demand information;
the second determining module is used for determining the total number of resources of the physical machine associated with the virtual machine under the condition that the average value meets a preset threshold value; and
and the configuration module is used for configuring required computing resources and storage resources for the user positioned in the target area according to a first resource proportion value and the total number of resources, wherein the first resource proportion value is determined according to the storage capacity.
9. An electronic device, comprising:
One or more processors;
storage means for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-7.
10. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method according to any of claims 1-7.
11. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.
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