TWI763650B - A method and apparatus for obtaining application cluster capacity - Google Patents

Abstract

Embodiments of the present application provide a method and apparatus for obtaining the capacity of an application cluster, wherein the method specifically includes: setting a simulated application cluster to be tested, the application cluster includes at least two test machines; Perform an overall pressure measurement to obtain the average single-machine capacity of the test machine; and calculate and obtain the capacity of the application cluster according to the total pressure of the application cluster and the average single-machine capacity of the test machine. In the embodiment of the present application, by setting up a simulated application cluster to be tested, and performing an overall stress test on multiple test machines of the entire simulated application cluster, a more accurate and more realistic average single-machine capability can be obtained, and a more accurate application cluster can be obtained. capacity.

Description

A method and apparatus for obtaining application cluster capacity

The present application relates to the field of computer technology, and in particular, to a method for obtaining the capacity of an application cluster and an apparatus for obtaining the capacity of an application cluster.

When determining the capacity ratio of each application, it is necessary to first calculate the capacity of each application cluster, where the capacity is the number of resource instances (or the number of machines) required by the application cluster. At present, the capacity of computing application clusters is mostly calculated manually or by means of single-machine pressure measurement.

Among them, the manual estimation method is to first estimate the capacity to be achieved or the total pressure of the application cluster, as well as the capacity of a single machine, and then divide the expected capacity (or the estimated total pressure) by the estimated single-machine capacity. Get the overall capacity of the application cluster. After the capacity of all applications is obtained according to this method, the capacity ratio calculation of each application can be performed.

The single-machine stress testing method uses stress testing tools to test a single machine to obtain the single-machine capability of the single machine, and then divide the desired capability by the single-machine capability obtained through the single-machine stress testing to obtain the overall capacity of the application cluster.

Then, the single-machine capacity obtained by the above two methods will be affected by various external factors, and the obtained value is not reliable enough, which will affect the accuracy of the overall capacity of the application cluster. For example, when a single-machine stress test of an application is performed, other VM resources of the host where the current VM (Virtual Manufacturing) is located are idle, which will lead to the problem of overestimating the single-machine capacity, and then use the expected capacity to calculate the overall capacity of the application. There will be too much data bias. In addition, the business flow model of the big promotion is also quite different from the normal business flow model, which is also a factor affecting the inaccurate capacity estimation.

The purpose of the invention of the embodiments of the present application is to provide a method for obtaining the capacity of an application cluster, which can improve the accuracy of the overall capacity of the application cluster.

Correspondingly, the embodiment of the present application further provides an apparatus for obtaining the capacity of an application cluster, so as to ensure the implementation and application of the above method.

In order to solve the above problem, the present application discloses a method for obtaining the capacity of an application cluster, which includes: setting a simulated application cluster to be tested, the application cluster including at least two test machines; performing overall compression on the test machines of the application cluster The average single-machine capacity of the test machine is obtained; the capacity of the application cluster is obtained by calculation according to the total pressure of the application cluster and the average single-machine capacity of the test machine.

Preferably, performing an overall stress test on the test machines of the application cluster to obtain the average single-machine capability of the test machines includes: performing an overall stress test on the test machines of the application cluster according to a preset initial pressure value; Adjust the pressure value; when the pressure value reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster, obtain the average single-machine capacity of the test machine.

Preferably, the adjusting the pressure value includes: when the initial pressure value triggers the current limiting threshold of the application cluster, reducing the pressure value according to a preset pitch.

Preferably, obtaining the average single-machine capability of the test machine includes: when the load capacity of the application cluster reaches a shrinking threshold for elastic scaling, shrinking the application cluster; When the load capacity of the application cluster reaches the capacity expansion threshold of the elastic scaling, the average number of requests per second of the test machines of the application cluster is taken as the average single-machine capacity of the test machines.

Preferably, the reducing the capacity of the application cluster includes: gradually reducing the capacity of the application cluster according to a preset capacity reduction ratio.

Preferably, the method further includes: after acquiring the capacities of all application clusters, calculating the capacity ratio of a single application cluster among all application clusters.

Preferably, the method further comprises: adjusting the capacity of the application cluster according to the bearing capacity of the planned application cluster.

Preferably, the adjusting the capacity of the application cluster according to the bearing capacity of the planned application cluster includes: adjusting the capacity of the application cluster according to the ratio between the bearing capacity of the planned application cluster and the total pressure of the application cluster capacity.

Preferably, when the number of the application clusters is 1, the application cluster includes: at least two test machines, and when the number of the application clusters is greater than 1, a single application cluster includes: at least one test machine.

The embodiment of the present application further discloses an apparatus for obtaining the capacity of an application cluster, including: a simulation unit, configured to set a simulated application cluster to be tested, the application cluster includes at least two test machines; a pressure measurement unit, configured as Perform an overall stress test on the test machines of the application cluster to obtain the average single-machine capacity of the test machines; the capacity calculation unit is configured to calculate the total pressure of the application cluster and the average single-machine capacity of the test machines. Get the capacity of the application cluster.

Preferably, the pressure measurement unit includes: an initialization subunit, configured to perform an overall pressure measurement on the testing machines of the application cluster according to a preset initial pressure value; an adjustment subunit, configured to adjust the pressure value; an acquisition subunit The unit, when the pressure value reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster, obtains the average single-machine capability of the test machine.

Preferably, the obtaining subunit includes: a shrinking subunit, configured to shrink the application cluster when the load capacity of the application cluster reaches a shrinking threshold for elastic scaling; a determining subunit, configured to When the application cluster is scaled down until the load capacity of the application cluster reaches the capacity expansion threshold of the elastic scaling, the average number of requests per second of the test machines of the application cluster is taken as the average single-machine capacity of the test machine.

Preferably, the apparatus further includes: a capacity adjustment unit configured to adjust the capacity of the application cluster according to the bearing capacity of the planned application cluster.

Compared with the prior art, the embodiments of the present application include the following advantages: by setting up a simulated application cluster to be tested, and performing an overall pressure test on multiple test machines of the entire simulated application cluster, the embodiment of the present application can obtain a more accurate and The real average single-machine capacity, and then a more accurate application cluster capacity can be obtained.

501‧‧‧Simulation Unit

502‧‧‧Pressure measurement unit

503‧‧‧Capacity Calculation Unit

601‧‧‧Initialization Subunit

602‧‧‧Regulation sub-unit

603‧‧‧Get subunit

701‧‧‧Shrinkage sub-unit

702‧‧‧Determining subunits

801‧‧‧Capacity Adjustment Unit

FIG. 1 is a flow chart of the steps of an embodiment of a method for obtaining the capacity of an application cluster according to the present application; FIG. 2 is a method implementation of a test machine of the application cluster to be tested in the present application to perform an overall stress test to obtain the average single-machine capacity of the test machine. Fig. 3 is a flow chart of steps of an embodiment of a method for obtaining the average single-machine capacity of a test machine in the present application; Fig. 4 is a flow chart of steps of another embodiment of a method of obtaining application cluster capacity of the present application; Fig. 5 is a structural block diagram of an embodiment of an apparatus for obtaining application cluster capacity according to the present application; FIG. 6 is a structural block diagram of a pressure measurement unit in the present application; FIG. 7 is a structural block diagram of an obtaining sub-unit in the present application; 8 is a structural block diagram of another embodiment of an apparatus for obtaining application cluster capacity according to the present application.

In order to make the above objects, features and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and specific embodiments.

Referring to FIG. 1 , a flowchart of steps of a method for obtaining application cluster capacity according to the present application is shown, which may specifically include the following steps:

Step 101: Set a simulated application cluster to be tested, and the application cluster may include at least two test machines.

In the embodiment of the present application, first prepare an environment for measuring the capacity ratio of multiple application clusters, and determine the application cluster that needs to perform capacity calculation. The application cluster may be one or multiple; wherein, in the application cluster When the number of application clusters is 1, the application cluster may specifically include: at least two test machines, and when the number of the application clusters is greater than 1, a single application cluster may specifically include: at least one test machine. In this step, the device for obtaining the capacity of the application cluster (hereinafter referred to as the device) firstly sets up a simulation environment corresponding to the determined application cluster that needs to perform capacity measurement, that is, sets up a simulation environment that is exactly the same as the application cluster that needs to perform capacity measurement. application cluster. The difference between the simulation environment set by the device and the actual application cluster may be that the application cluster in the simulation environment cannot provide external access and is only used for capacity measurement.

Step 102: Perform an overall stress test on the test machines of the application cluster to obtain the average single-machine capability of the test machines.

After the simulated application cluster to be tested is determined, an overall stress test is performed on the test machine of the application cluster. The pressure measurement is the simulated pressure of the online traffic. Specifically, the pressure measurement tool can be used to regulate the flow pressured on the test machine of the application cluster. The overall pressure measurement process is aimed at multiple test machines under the application cluster at the same time, and, This method can involve the collaborative pressure measurement of multiple application clusters. There is a calling relationship between multiple application clusters, and the traffic of the pressure measurement is also the real traffic on the simulation line. In this way, the overall pressure measurement is closer to the reality than the single-machine pressure measurement.

In the process of the overall stress measurement, this embodiment can directly obtain the limit capabilities of multiple test machines under the application cluster, and then obtain the average single-machine capability of the test machines through mean calculation. It is also possible to introduce an elastic platform during the stress test to expand or shrink the test machine of the application cluster, so as to obtain the average single-machine capability of the test machine. For details, please refer to the description of the subsequent embodiments.

Step 103: Calculate the capacity of the application cluster according to the total pressure of the application cluster and the average single-machine capability of the test machine.

After the single-machine capacity of the test machine is obtained, the capacity of the application cluster can be calculated and obtained according to the estimated or preset total pressure of the application cluster and the average single-machine capacity of the test machine. Specifically, the capacity of the application cluster can be obtained by dividing the total pressure of the application cluster by the average single-machine capability of the test machine. The total pressure value of the application cluster may be preset or estimated according to an existing method, which is not specifically limited here. The total pressure can be obtained in two cases: 1. When there is a preset target value: if the target is 12W this time, the pressure measurement is performed according to 12W; 2. When the target pressure value is not estimated, it is mainly to measure the existing pressure How much stress the total machine resources can withstand.

After the capacities of the multiple application clusters are obtained according to the above method, the capacity ratio of the multiple application clusters can be further adjusted. After combining the elastic platform, the elastic platform will adjust the capacity of each application cluster. Under the condition of limited machine resources, more will be reduced, and less will be expanded. Finally, multiple application clusters will be adjusted by the elastic platform to one suitable for the current pressure. capacity ratio.

In the embodiment of the present application, by setting up a simulated application cluster to be tested, and performing an overall stress test on multiple test machines of the entire simulated application cluster, a more accurate and more realistic average single-machine capability can be obtained, and a more accurate application cluster can be obtained. capacity.

In another embodiment of the present application, the process of performing an overall stress test on a test machine of an application cluster to obtain the average single-machine capability of the test machine, as shown in FIG. 2 , may include:

Step 201 , perform an overall pressure measurement on the test machine of the application cluster according to a preset initial pressure value.

In this step, a pressure measurement tool may be used to perform an overall pressure measurement on the test machine of the simulated application cluster to be tested according to a preset initial pressure value such as a user-specified value.

Step 202, adjust the pressure value.

If the initial pressure value is too small and far from triggering the current limiting threshold of the application cluster, the pressure value may be gradually increased, specifically, the pressure value may be gradually increased according to a preset pitch. If the initial pressure value is set too large and triggers the current limiting threshold of the application cluster, the pressure value needs to be lowered. When reducing the pressure value, the pressure measuring tool can gradually reduce the pressure value according to a preset pitch.

The current limiting threshold of the application cluster is set according to the estimated limit pressure capacity of the application cluster. If the current limit threshold is exceeded, it means that the application cluster has reached the limit of the pressure capacity.

Adjusting the pressure value through the pressure measurement tool can stabilize the pressure, which will neither cause the application cluster to show signs of current limitation nor make the pressure too low.

Step 203, when the pressure value reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster, obtain the average single-machine capability of the test machine.

When the pressure value adjusted by the pressure measurement tool reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster, the average single-machine capacity of the test machine can be obtained.

There are several ways to obtain the average stand-alone capability of the test machine, such as:

Method 1: Calculate according to the maximum value of the pressure value.

After obtaining the maximum value of the above-mentioned pressure value, according to the ratio between the maximum value of the pressure value and the number of test machines included in the application cluster, the average single-machine capacity of the test machines can be obtained.

Method 2: In this method, the process of obtaining the average single-machine capability of the test machine, as shown in Figure 3, may include:

Step 301 , when the load capacity of the application cluster reaches a shrinking threshold for elastic scaling, shrink the application cluster.

In this embodiment, elastic scaling is a mechanism for dynamically adjusting the scale of the application cluster according to the load of the online application cluster. This mechanism can not only reduce costs, but also improve the stability of the online application cluster. In an application example of the present application, the above elastic scaling can be implemented through an elastic platform; specifically, when the pressure value reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster, the elastic platform can be triggered to start, the elastic The platform can dynamically adjust the capacity of the application cluster according to the load of the online application cluster.

Specifically, the elastic platform will monitor the load capacity of the application cluster, and set the load shrinkage threshold and expansion threshold (expansion threshold = current limit threshold). When the load capacity of the application cluster reaches the shrinkage threshold, it needs to Scale down the application cluster to reduce the scale of the application cluster. When the load capacity of the application cluster reaches the expansion threshold, it needs to be expanded to increase the scale of the application cluster. For example, 80% of the CPU load can be set as the scaling threshold, and 90% of the CPU load can be set as the scaling threshold.

In this step, when it is detected that the load capacity of the application cluster reaches the shrinkage threshold of the elastic platform, the device shrinks the application cluster, and specifically may gradually shrink the application cluster according to a preset shrinkage ratio.

Step 302, when the application cluster is scaled down until the load capacity of the application cluster reaches the above-mentioned elastic scaling expansion threshold, the average number of requests per second of the test machines of the application cluster is taken as the average single-machine capacity of the test machine.

After scaling down, the load capacity of the application cluster will inevitably increase. When it is detected that the load capacity of the application cluster scaled down to the scale of the application cluster reaches the expansion threshold of the elastic platform, the average per second of the test machine of the application cluster can be calculated. The number of requests is taken as the average single-machine capacity of the test machine.

It can be seen that the device can dynamically adjust the capacity of the application cluster according to the load of the online application cluster by using elastic scaling, which can not only reduce the cost, but also improve the stability of the online application cluster.

After the average single-machine capacity of the test machine is obtained by using the above method, the foregoing step 103 can be performed to calculate and obtain the capacity of the application cluster.

In another embodiment of the present application, as shown in FIG. 4 , the method for obtaining application cluster capacity may further include:

Step 401: Adjust the capacity of the application cluster according to the bearing capacity of the planned application cluster.

This embodiment can be applied to the capacity preparation before the big promotion. When the bearing capacity of the application cluster is planned in advance, the capacity of the application cluster can be adjusted according to the bearing capacity of the planned application cluster.

Specifically, the capacity of the application cluster can be adjusted according to the ratio between the bearing capacity (P) of the planned application cluster and the total pressure (L) of the application cluster, so as to obtain the online environment capacity of the application cluster.

For example, the online environment capacity of the application cluster can be calculated according to the following formula=(P/L)*acquired capacity of the application cluster.

This adjustment process can realize the automatic completion of the large-scale capacity preparation for the application cluster.

In an optional embodiment of the present application, the method may further include: after acquiring the capacities of all application clusters, calculating the capacity ratio of a single application cluster among all application clusters. Assuming that the number of application clusters is 100, the ratio of the capacity of a single application cluster to the capacity of all application clusters can be calculated separately to obtain a corresponding capacity ratio. In this way, when the actual capacity of the planned application cluster cannot meet the capacity requirement of the online environment, the capacity of a single application cluster can be prepared according to the above-mentioned capacity ratio. For example, the online environment capacity Ci of the i-th application cluster is calculated according to the above formula, and the online environment capacity C of all application clusters can be obtained by further calculation. C, the capacity of a single application cluster can be allocated on the basis of R and the above-mentioned capacity ratio.

In order for those skilled in the art to better understand the embodiments of the present application, an example of a method for obtaining application cluster capacity in the present application is given here, and the example may specifically include the following steps:

Step S1, select the test machine to be tested, and place the above-mentioned test machine in an isolated simulation environment, and, in the above-mentioned simulation environment, the above-mentioned test machines can be grouped according to a preset ratio, and the obtained pressure test group can be the same as the one. Application clusters are fulfilled one by one.

Step S2, using a pressure measurement tool, according to a preset initial pressure value n, to perform an overall pressure measurement on the application clusters in the pressure measurement group;

Step S3: In the case that the initial pressure value is set too large, which triggers the current limiting threshold of the application cluster, the pressure measurement tool can gradually reduce the pressure value according to a preset pitch; wherein, the preset pitch can be: s%, the embodiment of the present application does not limit the specific value of the preset pitch;

Step S4, when the current pressure value reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster, start the elastic platform to adjust the capacity of the application cluster;

Step S5, monitor the load capacity of the application cluster through the elastic platform, and set the capacity reduction threshold and expansion threshold of the load capacity (expansion threshold = current limit threshold). The cluster is scaled down to reduce the scale of the application cluster; when an application cluster is scaled down to a certain percentage, the load will definitely reach the expansion threshold of the elastic platform. The average single-machine gps (requests per second, Query Per Second) is used as the average single-machine capacity of the application cluster until the average single-machine capacity of all application clusters is obtained; the above load can specifically include: CPU, request RT (response time, Response Time) Taking CPU as an example, it can be set to 80% as Its shrinkage threshold and 90% are its expansion threshold.

Step S6: Since the expansion threshold of the elastic platform is the same as the current limiting threshold, the pitch of the scaling may exceed the expansion threshold by a few percentage points. In order to accurately calculate the capacity of the application cluster, the above average single machine The capacity is fine-tuned, and the amount of capacity expansion = the total pressure received by the current application cluster/average single-machine capacity; after the fine-tuning of all application clusters is completed, the current capacity of the application cluster, the capacity ratio of a single application cluster, and the current pressure measurement flow L are obtained. ;

Step S7, prepare for large capacity promotion. Specifically, the capacity of the application cluster can be adjusted according to the ratio between the bearing capacity (P) of the planned application cluster and the total pressure (L) of the application cluster, so as to obtain the online environment capacity of the application cluster. ;

Step S8: According to the online environment capacity of the above application cluster, prepare the capacity of the application programs one by one, the more will be reduced, the less will be expanded, and the large-scale promotion capacity preparation is automatically completed in the whole process; wherein, when the actual capacity of the planned application cluster cannot meet the online environment capacity requirements , the capacity of a single application cluster can be prepared according to the above capacity ratio.

It should be noted that, for the sake of simple description, the method embodiments are expressed as a series of action combinations, but those skilled in the art should know that the embodiments of the present application are not limited by the described action sequence, because According to the embodiments of the present application, certain steps may be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present application.

Referring to FIG. 5, it shows a structural block diagram of an embodiment of an apparatus for obtaining application cluster capacity according to the present application, which may specifically include the following units:

The simulation unit 501 is configured to set a simulated application cluster to be tested, and the application cluster includes at least two test machines.

The stress testing unit 502 is configured to perform overall stress testing on the test machines of the application cluster to obtain the average single-machine capability of the test machines.

The capacity calculation unit 503 is configured to calculate and obtain the capacity of the application cluster according to the total pressure of the application cluster and the average single-machine capacity of the test machine.

In the embodiment of the present application, the device sets up a simulated application cluster to be tested through the above-mentioned units, and performs an overall pressure test on multiple test machines of the entire simulated application cluster, so as to obtain a more accurate and more realistic average single-machine capability, and further can Get a more accurate application cluster capacity.

In another embodiment, as shown in FIG. 6 , the pressure measurement unit 502 may specifically include:

The initialization subunit 601 is configured to perform an overall pressure measurement on the test machine of the application cluster according to a preset initial pressure value.

The adjustment subunit 602 is configured to adjust the pressure value.

The obtaining subunit 603 obtains the average single-machine capability of the test machine when the pressure value reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster.

The adjustment subunit 602 may be specifically configured to reduce the pressure value according to a preset pitch when the initial pressure value triggers the current limiting threshold of the application cluster.

In another embodiment, as shown in FIG. 7 , the obtaining subunit 603 may further include:

The shrinking subunit 701 is configured to shrink the application cluster when the load capacity of the application cluster reaches the shrinking threshold of the elastic scaling.

The determining subunit 702 is configured to use the average number of requests per second of the test machines of the application cluster as The average stand-alone capacity of the test machines.

The shrinking subunit 701 may be specifically configured to gradually shrink the application cluster according to a preset shrinking ratio.

In another embodiment, as shown in FIG. 8 , the apparatus may further include:

The capacity adjustment unit 801 is configured to adjust the capacity of the application cluster according to the bearing capacity of the planned application cluster.

The capacity adjustment unit 801 may be specifically configured to adjust the capacity of the application cluster according to the ratio between the bearing capacity of the planned application cluster and the total pressure of the application cluster.

Embodiments of the present application further provide an electronic device, including a storage and a processor.

The processor and the storage are connected to each other through a bus; the bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus Standard Architecture) bus bar, etc. The busbars can be classified into address busbars, data busbars, control busbars, and the like.

Wherein, the storage is used to store a program, and specifically, the program may include program code, and the program code includes computer operation instructions. The storage may include high-speed RAM storage, and may also include non-volatile memory, such as at least one disk storage.

The processor is used to read the program code in the storage, and perform the following steps: set up a simulated application cluster to be tested, the application cluster includes at least two test machines; perform an overall stress test on the test machines of the application cluster, Obtain the average single-machine capacity of the test machine; calculate and obtain the capacity of the application cluster according to the total pressure of the application cluster and the average single-machine capacity of the test machine.

As for the apparatus embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and reference may be made to the partial description of the method embodiment for related parts.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments may be referred to each other.

It should be understood by those skilled in the art that the embodiments of the embodiments of the present application may be provided as methods, apparatuses, or computer program products. Accordingly, the embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may employ computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein form.

In a typical configuration, the computing device includes one or more processors (CPUs), an input/output interface, a network interface, and memory. Memory memory may include forms of non-persistent memory, random access memory (RAM) and/or non-volatile memory memory in computer readable media, such as read only memory (ROM) or flash memory memory body (flash RAM). Internal memory is an example of a computer-readable medium. Computer-readable media includes both permanent and non-permanent, removable and non-removable media, and can be implemented by any method or technology for storage of information. Information can be computer readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM). ), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tape, magnetic tape, magnetic disk storage or other magnetic storage device or any other non-transmission medium that may be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include non-persistent computer-readable media (transitory media), such as modulated data signals and carrier waves.

The embodiments of the present application are described with reference to flowcharts and/or block diagrams of methods, terminal devices (systems), and computer program products according to the embodiments of the present application. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing terminal equipment to produce a machine for executing the instructions by the processor of the computer or other programmable data processing terminal equipment Means are created for implementing the functions specified in a flow or flow of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be stored in computer-readable storage capable of directing a computer or other programmable data processing terminal equipment to operate in a particular manner, such that the instructions stored in the computer-readable storage produce an article of manufacture comprising instruction means , the instruction means implements the functions specified in the flow or flow of the flowchart and/or the block or blocks of the block diagram.

These computer program instructions can also be loaded on a computer or other programmable data processing terminal equipment, so that a series of operational steps are performed on the computer or other programmable terminal equipment to produce a computer-implemented process, so that the computer or other programmable terminal equipment The instructions executed on the above provide steps for implementing the functions specified in the flowchart flow or blocks and/or the block or blocks of the block diagrams.

Although the preferred embodiments of the embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once the basic inventive concepts are known. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications that fall within the scope of the embodiments of the present application.

Finally, it should also be noted that in this document, relational terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply these entities or that there is any such actual relationship or sequence between operations. Furthermore, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion such that a process, method, article or terminal that includes a list of elements includes not only those elements, but also a non-exclusive list of elements. other requirements, or also include requirements inherent to such a process, method, article or terminal equipment. Without further limitation, an element defined by the phrase "comprises a..." does not preclude the presence of additional identical elements in the process, method, article or terminal that includes the element.

A method for obtaining the capacity of an application cluster and an apparatus for obtaining the capacity of an application cluster provided by the present application have been described above in detail. In this paper, specific examples are used to illustrate the principles and implementations of the present application, and the description of the above embodiments It is only used to help understand the method of the present application and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific embodiments and application scope. In summary, The contents of this specification should not be construed as limiting the application.

Claims (13)

A method for obtaining the capacity of an application cluster, comprising: setting a simulated application cluster to be tested, the application cluster including at least two test machines; performing an overall pressure test on the test machines of the application cluster, and obtaining the Average single-machine capacity; according to the total pressure of the application cluster and the average single-machine capacity of the test machine, calculate the capacity of the application cluster; wherein, the overall pressure measurement uses a pressure measurement tool to pressurize the test machine of the application cluster The said obtaining the average stand-alone capability of the test machine includes: during the overall stress test process, determining the limit capability of multiple test machines in the application cluster; determining the average stand-alone capability of the test machine according to the limit capability and/or during the overall stress test process, use the elastic platform to expand or shrink the test machine of the application cluster to obtain the average single-machine capacity of the test machine. The method according to item 1 of the scope of the patent application, wherein the performing an overall stress test on the test machine of the application cluster to obtain the average single-machine capability of the test machine includes: according to a preset initial pressure value for the application cluster The overall pressure test is carried out by the test machine; the pressure value is adjusted; When the pressure value reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster, the average single-machine capacity of the test machine is obtained. The method according to claim 2, wherein the adjusting the pressure value comprises: when the initial pressure value triggers the current limiting threshold of the application cluster, reducing the pressure value according to a preset pitch. The method according to item 2 of the scope of the patent application, wherein obtaining the average single-machine capability of the test machine includes: shrinking the application cluster when the load capacity of the application cluster reaches a shrinking threshold for elastic scaling; When the application cluster is scaled down until the load capacity of the application cluster reaches the capacity expansion threshold of the elastic scaling, the average number of requests per second of the test machine of the application cluster is taken as the average single-machine capacity of the test machine. The method according to item 4 of the scope of the patent application, wherein the reducing the capacity of the application cluster includes: gradually reducing the capacity of the application cluster according to a preset capacity reduction ratio. The method according to any one of items 1 to 5 in the scope of the application, wherein the method further includes: after acquiring the capacities of all application clusters, calculating the capacity ratio of a single application cluster among all application clusters. The method according to any one of items 1 to 5 of the scope of the application, wherein the method further comprises: adjusting the capacity of the application cluster according to the bearing capacity of the planned application cluster. The method according to item 7 of the scope of the patent application, wherein the adjusting the capacity of the application cluster according to the bearing capacity of the planned application cluster includes: according to the plan, between the bearing capacity of the application cluster and the total pressure of the application cluster The ratio adjusts the capacity of the application cluster. The method according to any one of items 1 to 5 of the scope of the patent application, wherein when the number of the application clusters is 1, the application cluster includes: at least two test machines, and when the number of the application clusters is greater than 1 , wherein a single application cluster includes: at least one test machine. An apparatus for obtaining the capacity of an application cluster, comprising: a simulation unit configured to set a simulated application cluster to be tested, the application cluster including at least two test machines; a pressure measurement unit configured to set the application cluster to be tested The overall pressure test of the test machine is performed to obtain the average single-machine capacity of the test machine; the capacity calculation unit is configured to calculate and obtain the capacity of the application cluster according to the total pressure of the application cluster and the average single-machine capacity of the test machine; wherein , the overall pressure measurement uses a pressure measurement tool to regulate the flow of the test machine pressurized on the application cluster. The pressure measurement unit includes: a first pressure measurement unit, which is used to determine the application during the overall pressure measurement process. The limit capacity of multiple test machines in the cluster; according to the limit capacity, the average single machine capacity of the test machine is determined; and/or the second pressure measurement unit, which is used to use elastic leveling during the overall pressure measurement process. Expand or shrink the test machine of the application cluster to obtain the average single-machine capacity of the test machine. The device according to claim 10, wherein the pressure measurement unit includes: an initialization subunit configured to perform an overall pressure measurement on the testing machine of the application cluster according to a preset initial pressure value; an adjustment subunit, It is configured to adjust the pressure value; the subunit is obtained, and when the pressure value reaches the maximum value within the pressure value that triggers the current limiting threshold of the application cluster, the average single-machine capacity of the test machine is obtained. The device according to item 11 of the scope of the patent application, wherein the acquiring subunit comprises: a scaling subunit, configured to scale down the application cluster when the load capacity of the application cluster reaches a scaling threshold for elastic scaling; determining a subunit, configured to take the average number of requests per second of the test machine of the application cluster as the average single machine of the test machine when the load capacity of the application cluster is scaled down to the capacity expansion threshold of the elastic scaling ability. The apparatus according to any one of claims 10 to 12, wherein the apparatus further comprises: a capacity adjustment unit configured to adjust the capacity of the application cluster according to the bearing capacity of the planned application cluster.

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