CN112596995A - Capacity determination method and device based on cluster architecture - Google Patents
Capacity determination method and device based on cluster architecture Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
- G06F11/3433—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment for load management
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/3006—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/3024—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a central processing unit [CPU]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3442—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment for planning or managing the needed capacity
Abstract
The invention discloses a capacity determination method and a capacity determination device based on a cluster architecture, which can determine the upper limit parameter of CPU utilization rate of a computer forming a target cluster architecture; determining the CPU use upper limit value of the target cluster architecture at least through the CPU use upper limit parameter according to the cluster type of the target cluster architecture; determining a CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period; and determining whether the current capacity of the target cluster architecture meets the capacity requirement in the next period at least according to the CPU use upper limit value and the CPU predicted value. According to the invention, through the CPU use upper limit value and the determined CPU predicted value, whether the capacity of the cluster architecture can meet the capacity requirement of a future cycle can be scientifically and accurately determined, the number of computers in the cluster architecture can be conveniently and timely adjusted, the cluster architecture is prevented from being overloaded, and the computer resource utilization efficiency of the target cluster architecture is effectively improved.
Description
Technical Field
The invention relates to the technical field of computer processing, in particular to a capacity determination method and device based on a cluster architecture.
Background
The cluster architecture refers to a large computer service system which is composed of a plurality of mutually independent computers and utilizes a high-speed communication network, and each cluster node is an independent server for running respective services. These servers may communicate with each other, cooperatively provide applications, system resources, and data to users, and be managed in a single system mode.
Because the load to be borne is constantly changed in the process of providing the computing processing service by the cluster architecture, when the capacity required for bearing the load is larger than the capacity that can be provided by the cluster architecture, the cluster architecture is easily overloaded, and a computer failure is caused. When the capacity required by the load is much smaller than the capacity that can be provided by the cluster architecture, the computer resources of the cluster architecture cannot be effectively utilized, and the utilization efficiency of the computer resources is reduced.
Disclosure of Invention
In view of the foregoing problems, the present invention provides a method and an apparatus for determining capacity based on a cluster architecture, which overcome the foregoing problems or at least partially solve the foregoing problems, and the technical solution is as follows:
a capacity determination method based on a cluster architecture comprises the following steps:
determining a CPU utilization upper limit parameter of a computer forming a target cluster architecture, wherein the target cluster architecture is formed by at least three computers with the same configuration;
determining the CPU use upper limit value of the target cluster architecture at least through the CPU use upper limit parameter according to the cluster type of the target cluster architecture;
determining a CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period;
and determining whether the current capacity of the target cluster architecture meets the capacity requirement of the next period at least according to the CPU use upper limit value and the CPU predicted value.
Optionally, the determining a CPU utilization upper limit parameter of a computer constituting the target cluster architecture includes:
the method comprises the steps of carrying out gradual linear load increase processing on computers forming a target cluster architecture, and when the current processing performance of the computers is reduced to a preset percentage relative to the initial processing performance before the gradual linear load increase processing is not carried out, determining the CPU utilization rate of the computers under the current processing performance condition as the CPU utilization rate upper limit parameter of the computers.
Optionally, the cluster types of the target cluster architecture include a hot standby type and a cold standby type.
Optionally, the determining, according to the cluster type of the target cluster architecture, the CPU usage upper limit value of the target cluster architecture at least by the CPU usage upper limit parameter includes:
and when the cluster type of the target cluster architecture is the hot standby type, determining the CPU utilization upper limit value of the target cluster architecture according to the CPU utilization upper limit parameter and the number of the computers forming the target cluster architecture.
Optionally, the determining, according to the cluster type of the target cluster architecture, the CPU usage upper limit value of the target cluster architecture at least by the CPU usage upper limit parameter includes:
and when the cluster type of the target cluster architecture is a cold standby type, determining the CPU utilization upper limit parameter as the CPU utilization upper limit value of the target cluster architecture.
Optionally, the determining, according to at least the CPU usage upper limit value and the CPU predicted value, whether the current capacity of the target cluster architecture meets the capacity requirement of the next cycle includes:
under the condition that the CPU predicted value is not smaller than the CPU use upper limit value, determining that the current capacity of the target cluster architecture does not meet the capacity requirement of the next period;
and under the condition that the CPU predicted value is smaller than the CPU use upper limit value, determining that the current capacity of the target cluster architecture meets the capacity requirement of the next period.
Optionally, after determining that the current capacity of the target cluster architecture meets the capacity requirement of the next period, the method further includes:
and determining the number of the computers with the target cluster architecture capable of being scaled according to the CPU predicted value, the CPU utilization upper limit parameter and the number of the computers forming the target cluster architecture.
A capacity determination apparatus based on a cluster architecture, comprising: a CPU utilization upper limit parameter determining unit, a CPU utilization upper limit value determining unit, a CPU predicted value determining unit and a capacity requirement judging unit,
the CPU utilization upper limit parameter determining unit is used for determining the CPU utilization upper limit parameters of computers forming a target cluster architecture, wherein the target cluster architecture is formed by at least three computers with the same configuration;
the CPU use upper limit value determining unit is used for determining the CPU use upper limit value of the target cluster architecture at least through the CPU use rate upper limit parameter according to the cluster type of the target cluster architecture;
the CPU predicted value determining unit is used for determining the CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period;
and the capacity requirement judging unit is used for determining whether the current capacity of the target cluster architecture meets the capacity requirement of the next period at least according to the CPU use upper limit value and the CPU predicted value.
Optionally, the CPU utilization upper limit parameter determining unit is specifically configured to perform gradual linear load increase processing on a computer constituting a target cluster architecture, and when the current processing performance of the computer is reduced to a preset percentage relative to an initial processing performance before the gradual linear load increase processing is not performed, determine the CPU utilization of the computer under the current processing performance condition as the CPU utilization upper limit parameter of the computer.
Optionally, the capacity requirement determining unit is specifically configured to determine that the current capacity of the target cluster architecture does not meet the capacity requirement of the next period when the CPU predicted value is not less than the CPU usage upper limit value;
the capacity requirement determining unit is further specifically configured to determine that the current capacity of the target cluster architecture meets the capacity requirement of the next period when the CPU predicted value is smaller than the CPU usage upper limit value.
By means of the technical scheme, the capacity determining method and device based on the cluster architecture can determine the CPU utilization upper limit parameter of a computer forming the target cluster architecture; determining the CPU use upper limit value of the target cluster architecture at least through the CPU use upper limit parameter according to the cluster type of the target cluster architecture; determining a CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period; and determining whether the current capacity of the target cluster architecture meets the capacity requirement in the next period at least according to the CPU use upper limit value and the CPU predicted value. According to the invention, through the CPU use upper limit value and the determined CPU predicted value, whether the capacity of the cluster architecture can meet the capacity requirement of a future cycle can be scientifically and accurately determined, the number of computers in the cluster architecture can be conveniently and timely adjusted, the cluster architecture is prevented from being overloaded, and the computer resource utilization efficiency of the target cluster architecture is effectively improved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart illustrating a capacity determination method based on a cluster architecture according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating another capacity determining method based on a cluster architecture according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating another capacity determining method based on a cluster architecture according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating another capacity determining method based on a cluster architecture according to an embodiment of the present invention;
fig. 5 is a flowchart illustrating another capacity determining method based on a cluster architecture according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram illustrating a capacity determining apparatus based on a cluster architecture according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As shown in fig. 1, a capacity determining method based on a cluster architecture according to an embodiment of the present invention may include:
s100, determining a CPU utilization upper limit parameter of a computer forming a target cluster architecture, wherein the target cluster architecture is formed by at least three computers with the same configuration.
The upper limit parameter of the usage rate of the CPU (Central Processing Unit) is an upper limit value at which the computer can stably provide computing Processing services. The configuration of the computers that make up the target cluster architecture is the same.
Optionally, the embodiment of the present invention may perform a stress test on the computer, and determine the upper limit parameter of the CPU utilization of the computer.
Specifically, the embodiment of the present invention may perform a gradual linear load increase process on a computer constituting a target cluster architecture, and when a current processing performance of the computer is reduced to a preset percentage relative to an initial processing performance before the gradual linear load increase process is not performed, determine a CPU utilization of the computer under the current processing performance condition as a CPU utilization upper limit parameter of the computer.
Alternatively, the preset percentage may be 20%. For example: monitoring the current processing performance of the computer in real time in the process of gradually increasing the linear load from the initial load 0, determining the CPU utilization rate of the computer under the current processing performance when the current processing performance of the computer is firstly reduced to 20 percent relative to the initial processing performance before the gradually increasing linear load processing, and determining the CPU utilization rate as the CPU utilization rate upper limit parameter of the computer.
Optionally, the cluster types of the target cluster architecture include a hot standby type and a cold standby type.
Wherein each computer in a hot-standby type of cluster architecture provides computational processing services. The cluster architecture of the cold standby type comprises at least one standby computer, and when other computers in the cluster architecture of the cold standby type fail, the standby computer is enabled to replace the failed other computers to provide computing processing service.
S200, determining the CPU use upper limit value of the target cluster architecture at least through the CPU use upper limit parameter according to the cluster type of the target cluster architecture.
Optionally, based on the method shown in fig. 1, as shown in fig. 2, in another capacity determining method based on a cluster architecture provided in the embodiment of the present invention, step S200 may include:
s210, when the cluster type of the target cluster architecture is a hot standby type, determining the CPU usage upper limit value of the target cluster architecture according to the CPU usage upper limit parameter and the number of the computers forming the target cluster architecture.
Optionally, in the embodiment of the present invention, when the cluster type of the target cluster architecture is a hot standby type, according to a formula:
and determining the CPU use upper limit value of the target cluster architecture, wherein U is the CPU use upper limit value of the target cluster architecture, r is a CPU use rate upper limit parameter, and N is the number of computers forming the target cluster architecture.
Optionally, based on the method shown in fig. 1, as shown in fig. 3, in another capacity determining method based on a cluster architecture provided in the embodiment of the present invention, step S200 may include:
and S220, when the cluster type of the target cluster architecture is a cold standby type, determining the upper limit parameter of the CPU utilization rate as the upper limit value of the CPU utilization of the target cluster architecture.
S300, determining the CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period.
The current period and the next period are continuous periods, and the current period is before the next period.
It can be understood that, the average CPU utilization rate of the target cluster architecture in the current cycle can be obtained by dividing the sum of the CPU utilization rates of the computers in the target cluster architecture providing the computation processing service in the current cycle by the number of computers constituting the target cluster architecture.
The load increase prediction coefficient of the next period can be determined by the conventional data analysis prediction method in combination with historical relevant data and empirical judgment. It should be noted that the load increase prediction coefficient is not related to the target cluster architecture, and is equivalent to an external environmental factor.
Optionally, the embodiment of the present invention may be implemented according to a formula:
y＝kx，
and determining the CPU predicted value of the target cluster architecture in the next period, wherein y is the CPU predicted value of the target cluster architecture in the next period, k is the load increase prediction coefficient of the next period, and x is the CPU average utilization rate of the target cluster architecture in the current period.
S400, determining whether the current capacity of the target cluster architecture meets the capacity requirement of the next period at least according to the CPU use upper limit value and the CPU predicted value.
Optionally, based on the method shown in fig. 1, as shown in fig. 4, in another capacity determining method based on a cluster architecture provided in the embodiment of the present invention, step S400 may include:
and S410, determining whether the CPU predicted value is not less than the CPU use upper limit value, if not, executing the step S420, and if so, executing the step S430.
S420, determining that the current capacity of the target cluster architecture does not meet the capacity requirement of the next period.
Optionally, in the embodiment of the present invention, when it is determined that the current capacity of the target cluster architecture does not satisfy the capacity requirement of the next period, information that the capacity of the target cluster architecture needs to be expanded is prompted, so that a relevant technician can timely know the information that the capacity of the target cluster architecture needs to be expanded, and before the next period comes, the number of computers in the target cluster architecture is timely increased.
S430, determining that the current capacity of the target cluster architecture meets the capacity requirement of the next period.
Optionally, based on the method shown in fig. 4, as shown in fig. 5, in another capacity determining method based on a cluster architecture according to an embodiment of the present invention, after step S430, the method further includes:
s440, determining the number of the computers with the target cluster architecture capable of being scaled according to the CPU predicted value, the CPU utilization rate upper limit parameter and the number of the computers forming the target cluster architecture.
Optionally, in the embodiment of the present invention, the upper limit value of the CPU usage after the target cluster architecture is reduced by the preset number of computers may be determined according to the upper limit parameter of the CPU usage and the number of computers constituting the target cluster architecture, and then, by comparing the predicted value of the CPU with the upper limit value of the CPU usage expected by the target cluster architecture after the preset number of computers are reduced, it is determined whether the capacity of the target cluster architecture after the preset number of computers are reduced meets the capacity requirement of the next cycle, thereby determining the number of computers of the target cluster architecture that is reduced.
Optionally, the embodiment of the present invention may be implemented according to a formula:
determining the upper limit value of the expected CPU usage after the target cluster architecture is scaled by a preset number of computers, wherein UShrinking deviceAnd (3) reducing the expected CPU use upper limit value after a preset number of computers are accommodated for the target cluster architecture, wherein r is a CPU use rate upper limit parameter, N is the number of computers forming the target cluster architecture, M is the preset number, and M is not less than 0 and is a positive integer.
For example: when M is 1 and
and then, determining that the capacity of the target cluster architecture after 1 computer is reduced can not meet the capacity requirement of the next period. It can be understood that, in the embodiment of the present invention, when it is determined that the current capacity of the target cluster architecture meets the capacity requirement of the next period and it is determined that the capacity of the target cluster architecture after 1 computer is reduced cannot meet the capacity requirement of the next period, information for keeping the current state of the number of computers of the target cluster architecture is prompted.
For example: when M is 1 and
and then determining that the capacity of the target cluster architecture after 1 computer is reduced can meet the capacity requirement of the next period. It can be understood that, in the embodiment of the present invention, under the condition that it is determined that the current capacity of the target cluster architecture meets the capacity requirement of the next period, and the capacity of the target cluster architecture after 1 computer is determined to meet the capacity requirement of the next period, information that the target cluster architecture can accommodate one computer is prompted, so that a relevant technician can timely know information that the target cluster architecture can accommodate one computer, and before the next period comes, the target cluster architecture is timely reduced by a corresponding number of computers.
It can be understood that, in the embodiment of the present invention, when it is determined that the capacity of the target cluster architecture after 1 computer is reduced can meet the capacity requirement of the next period, it may be further determined whether the capacity of the target cluster architecture after 2 computers are reduced can meet the capacity requirement of the next period, and when it is determined that the capacity of the target cluster architecture after 2 computers are reduced can meet the capacity requirement of the next period, it is determined whether the capacity of the target cluster architecture after 3 computers are reduced can meet the capacity requirement of the next period, and so on until it is determined that the capacity requirement of the next period can be met, and the target cluster architecture can reduce the maximum M value of the computer.
The capacity determination method based on the cluster architecture can determine the CPU utilization upper limit parameter of a computer forming the target cluster architecture; determining the CPU use upper limit value of the target cluster architecture at least through the CPU use upper limit parameter according to the cluster type of the target cluster architecture; determining a CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period; and determining whether the current capacity of the target cluster architecture meets the capacity requirement in the next period at least according to the CPU use upper limit value and the CPU predicted value. According to the invention, through the CPU use upper limit value and the determined CPU predicted value, whether the capacity of the cluster architecture can meet the capacity requirement of a future cycle can be scientifically and accurately determined, the number of computers in the cluster architecture can be conveniently and timely adjusted, the cluster architecture is prevented from being overloaded, and the computer resource utilization efficiency of the target cluster architecture is effectively improved.
Corresponding to the foregoing method embodiment, a capacity determining apparatus based on a cluster architecture according to an embodiment of the present invention is shown in fig. 6, and may include: a CPU usage upper limit parameter determining unit 100, a CPU usage upper limit value determining unit 200, a CPU predicted value determining unit 300, and a capacity demand judging unit 400.
The CPU utilization upper limit parameter determining unit 100 is configured to determine a CPU utilization upper limit parameter of a computer constituting a target cluster architecture, where the target cluster architecture is composed of at least three computers having the same configuration.
The CPU utilization upper limit value determining unit 200 is configured to determine, according to the cluster type of the target cluster architecture, a CPU utilization upper limit value of the target cluster architecture at least through the CPU utilization upper limit parameter.
The CPU predicted value determining unit 300 is configured to determine the CPU predicted value of the target cluster architecture in the next cycle according to the average CPU utilization of the target cluster architecture in the current cycle and the load increase prediction coefficient of the next cycle.
The capacity requirement determining unit 400 is configured to determine whether the current capacity of the target cluster architecture meets the capacity requirement of the next period at least according to the CPU usage upper limit value and the CPU prediction value.
Optionally, the CPU utilization upper limit parameter determining unit 100 is specifically configured to perform a gradual linear load increase process on a computer constituting a target cluster architecture, and when a current processing performance of the computer is reduced to a preset percentage relative to an initial processing performance before the gradual linear load increase process is not performed, determine the CPU utilization of the computer under the current processing performance condition as the CPU utilization upper limit parameter of the computer.
Optionally, the cluster types of the target cluster architecture include a hot standby type and a cold standby type.
Optionally, the CPU utilization upper limit value determining unit 200 may be specifically configured to determine, when the cluster type of the target cluster architecture is a hot standby type, the CPU utilization upper limit value of the target cluster architecture according to the CPU utilization upper limit parameter and the number of the computers constituting the target cluster architecture.
Optionally, the CPU utilization upper limit value determining unit 200 may be specifically configured to determine the CPU utilization upper limit parameter as the CPU utilization upper limit value of the target cluster architecture when the cluster type of the target cluster architecture is a cold standby type.
Optionally, the capacity requirement determining unit 400 is specifically configured to determine that the current capacity of the target cluster architecture does not meet the capacity requirement of the next period when the CPU predicted value is not less than the CPU usage upper limit value.
Optionally, the capacity requirement determining unit 400 is further specifically configured to determine that the current capacity of the target cluster architecture meets the capacity requirement of the next period when the CPU predicted value is smaller than the CPU usage upper limit value.
Optionally, another capacity determining apparatus based on a cluster architecture provided in the embodiment of the present invention may further include a capacity-reducible number determining unit.
A scalable number determining unit, configured to determine, after the capacity requirement determining unit 400 determines that the current capacity of the target cluster architecture meets the capacity requirement of the next period, the number of scalable computers of the target cluster architecture according to the CPU prediction value, the CPU utilization upper limit parameter, and the number of computers constituting the target cluster architecture.
The capacity determining device based on the cluster architecture can determine the CPU utilization upper limit parameter of a computer forming the target cluster architecture; determining the CPU use upper limit value of the target cluster architecture at least through the CPU use upper limit parameter according to the cluster type of the target cluster architecture; determining a CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period; and determining whether the current capacity of the target cluster architecture meets the capacity requirement in the next period at least according to the CPU use upper limit value and the CPU predicted value. According to the invention, through the CPU use upper limit value and the determined CPU predicted value, whether the capacity of the cluster architecture can meet the capacity requirement of a future cycle can be scientifically and accurately determined, the number of computers in the cluster architecture can be conveniently and timely adjusted, the cluster architecture is prevented from being overloaded, and the computer resource utilization efficiency of the target cluster architecture is effectively improved.
This application, while depicting operations in a particular order, should not be construed as requiring that the operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous.
It should be understood that the various steps recited in the method embodiments of the present application may be performed in a different order and/or in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present application is not limited in this respect.
In this application, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A capacity determination method based on a cluster architecture is characterized by comprising the following steps:
determining a CPU utilization upper limit parameter of a computer forming a target cluster architecture, wherein the target cluster architecture is formed by at least three computers with the same configuration;
determining the CPU use upper limit value of the target cluster architecture at least through the CPU use upper limit parameter according to the cluster type of the target cluster architecture;
determining a CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period;
and determining whether the current capacity of the target cluster architecture meets the capacity requirement of the next period at least according to the CPU use upper limit value and the CPU predicted value.
2. The method of claim 1, wherein determining a CPU usage ceiling parameter for the computers comprising the target cluster architecture comprises:
the method comprises the steps of carrying out gradual linear load increase processing on computers forming a target cluster architecture, and when the current processing performance of the computers is reduced to a preset percentage relative to the initial processing performance before the gradual linear load increase processing is not carried out, determining the CPU utilization rate of the computers under the current processing performance condition as the CPU utilization rate upper limit parameter of the computers.
3. The method of claim 1, wherein the cluster types of the target cluster architecture comprise a hot standby type and a cold standby type.
4. The method according to claim 3, wherein the determining, according to the cluster type of the target cluster architecture, the upper limit value of the CPU usage of the target cluster architecture at least through the upper limit parameter of the CPU usage includes:
and when the cluster type of the target cluster architecture is the hot standby type, determining the CPU utilization upper limit value of the target cluster architecture according to the CPU utilization upper limit parameter and the number of the computers forming the target cluster architecture.
5. The method according to claim 3, wherein the determining, according to the cluster type of the target cluster architecture, the upper limit value of the CPU usage of the target cluster architecture at least through the upper limit parameter of the CPU usage includes:
and when the cluster type of the target cluster architecture is a cold standby type, determining the CPU utilization upper limit parameter as the CPU utilization upper limit value of the target cluster architecture.
6. The method of claim 1, wherein determining whether the current capacity of the target cluster architecture meets the capacity requirement of the next cycle based on at least the upper CPU usage limit and the CPU prediction value comprises:
under the condition that the CPU predicted value is not smaller than the CPU use upper limit value, determining that the current capacity of the target cluster architecture does not meet the capacity requirement of the next period;
and under the condition that the CPU predicted value is smaller than the CPU use upper limit value, determining that the current capacity of the target cluster architecture meets the capacity requirement of the next period.
7. The method of claim 6, wherein after the determining that the current capacity of the target cluster architecture meets the capacity requirement of the next cycle, the method further comprises:
and determining the number of the computers with the target cluster architecture capable of being scaled according to the CPU predicted value, the CPU utilization upper limit parameter and the number of the computers forming the target cluster architecture.
8. A capacity determination apparatus based on a cluster architecture, comprising: a CPU utilization upper limit parameter determining unit, a CPU utilization upper limit value determining unit, a CPU predicted value determining unit and a capacity requirement judging unit,
the CPU utilization upper limit parameter determining unit is used for determining the CPU utilization upper limit parameters of computers forming a target cluster architecture, wherein the target cluster architecture is formed by at least three computers with the same configuration;
the CPU use upper limit value determining unit is used for determining the CPU use upper limit value of the target cluster architecture at least through the CPU use rate upper limit parameter according to the cluster type of the target cluster architecture;
the CPU predicted value determining unit is used for determining the CPU predicted value of the target cluster architecture in the next period according to the average CPU utilization rate of the target cluster architecture in the current period and the load increase prediction coefficient of the next period;
and the capacity requirement judging unit is used for determining whether the current capacity of the target cluster architecture meets the capacity requirement of the next period at least according to the CPU use upper limit value and the CPU predicted value.
9. The apparatus according to claim 8, wherein the CPU utilization upper limit parameter determining unit is specifically configured to perform a gradual linear load increase process on a computer constituting a target cluster architecture, and determine the CPU utilization of the computer under the current processing performance condition as the CPU utilization upper limit parameter of the computer when the current processing performance of the computer is reduced to a preset percentage relative to an initial processing performance before the gradual linear load increase process is not performed.
10. The apparatus according to claim 8, wherein the capacity requirement determining unit is specifically configured to determine that the current capacity of the target cluster architecture does not satisfy the capacity requirement of the next cycle when the CPU prediction value is not less than the CPU usage upper limit value;
the capacity requirement determining unit is further specifically configured to determine that the current capacity of the target cluster architecture meets the capacity requirement of the next period when the CPU predicted value is smaller than the CPU usage upper limit value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202011570075.5A CN112596995A (en) | 2020-12-26 | 2020-12-26 | Capacity determination method and device based on cluster architecture |
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