CN117632470A - Service processing method, device, equipment, storage medium and program product - Google Patents
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Abstract
The application relates to a service processing method, a device, equipment, a storage medium and a program product, and relates to the technical field of cloud computing, wherein the method comprises the following steps: under the condition that the service processing system performs service processing, current resource use information of a cloud platform to which the service processing system belongs is obtained, resource scheduling information of the cloud platform is determined according to the current resource use information, and then resources of the cloud platform are scheduled according to the resource scheduling information of the cloud platform, so that the service processing system performs service processing. The method improves the flexible allocation of resources to the service processing system.
Description
Technical Field
The present disclosure relates to the field of cloud computing technologies, and in particular, to a service processing method, apparatus, device, storage medium, and program product.
Background
With the development of internet technology, more and more users face business processing systems.
In the case where the access amount of the service processing system is drastically increased, a problem of slow response of the service processing system may occur. In the related art, in order to ensure the response speed of a service processing system, a larger resource is generally allocated to the service processing system.
However, the related art service processing method is not flexible enough for resource allocation of the service processing system.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a service processing method, apparatus, device, storage medium, and program product that can more flexibly allocate resources for a service processing system.
In a first aspect, the present application provides a service processing method, where the method includes:
under the condition that a service processing system performs service processing, acquiring current resource use information of a cloud platform to which the service processing system belongs;
determining resource scheduling information of the cloud platform according to the current resource use information;
and scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform so as to enable the service processing system to perform service processing.
In one embodiment, determining resource scheduling information of the cloud platform according to current resource usage information includes:
and inputting the current resource use information into a preset resource scheduling model, and analyzing the current resource use information through resource scheduling to obtain the resource scheduling information of the cloud platform.
In one embodiment, determining resource scheduling information of the cloud platform according to current resource usage information includes:
Acquiring a preset elastic expansion strategy; the elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information;
acquiring a target resource threshold range to which current resource use information belongs in an elastic expansion strategy;
and determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information.
In one embodiment, the process of constructing the elastic expansion strategy includes:
acquiring historical access quantity of a service processing system;
analyzing the historical access amount, and determining a plurality of resource thresholds for triggering elastic expansion of the service processing system and corresponding historical resource scheduling information;
and determining an elastic telescoping strategy according to the plurality of resource thresholds and the corresponding historical resource scheduling information.
In one embodiment, scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform includes:
determining scheduling operation and resource allocation information of the cloud platform according to the resource scheduling information;
if the scheduling operation is a resource capacity expansion operation, deploying a newly added virtual machine for the cloud platform according to the resource allocation information;
And if the scheduling operation is the resource capacity shrinking operation, deleting the virtual machine corresponding to the resource allocation information from the cloud platform.
In one embodiment, the current resource usage information includes processor usage and/or memory usage.
In a second aspect, the present application further provides a service processing apparatus, where the apparatus includes:
the acquisition module is used for acquiring current resource use information of the cloud platform to which the service processing system belongs under the condition that the service processing system performs service processing;
the determining module is used for determining resource scheduling information of the cloud platform according to the current resource use information;
and the scheduling module is used for scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform so as to enable the service processing system to process the service.
In a third aspect, embodiments of the present application provide a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of the method provided by any of the embodiments of the first aspect described above when the computer program is executed.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method provided by any of the embodiments of the first aspect described above.
In a fifth aspect, embodiments of the present application also provide a computer program product comprising a computer program which, when executed by a processor, implements the steps of the method provided by any of the embodiments of the first aspect described above.
According to the service processing method, the device, the equipment, the storage medium and the program product, under the condition that the service processing system performs service processing, the current resource use information of the cloud platform to which the service processing system belongs is obtained, the resource scheduling information of the cloud platform is determined according to the current resource use information, and then the resources of the cloud platform are scheduled according to the resource scheduling information of the cloud platform, so that the service processing system performs service processing. According to the method, the service processing system is deployed on the cloud platform, and the cloud platform is subjected to resource scheduling according to the current resource use information of the cloud platform, so that the resources of the service processing system can be dynamically adjusted, when the resource demand is large, the resources of the service processing system are increased, when the resource demand is small, the resources of the service processing system are reduced, the response speed of the service processing system is high, and meanwhile, the resource utilization rate of the service processing system is guaranteed, so that the resources of the service processing system are flexibly allocated.
Drawings
FIG. 1 is an application environment diagram of a business processing method in one embodiment;
FIG. 2 is a flow diagram of a business processing method in one embodiment;
FIG. 3 is a flow chart of a business processing method according to another embodiment;
FIG. 4 is a flow chart of a business processing method in another embodiment;
FIG. 5 is a flow chart of a business processing method according to another embodiment;
FIG. 6 is a schematic diagram of a business processing method in one embodiment;
FIG. 7 is a flow chart of a business processing method according to another embodiment;
FIG. 8 is a block diagram of a business processing device in one embodiment;
fig. 9 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The service processing method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein cloud platform 102 communicates with server 104 over a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. Wherein cloud platform 102 deploys business processing system 106. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.
The service processing system refers to a software system for managing and executing the internal service flow of an organization. Taking a banking institution as an example, a bank can be used as a proxy channel for selling the money and souvenir from a bank-note company, the business processing system can be a noble metal mall of the bank, the noble metal mall can issue the souvenir, and a user can purchase the souvenir through the noble metal mall.
Taking appointment or second to kill commemorative coins as an example, under the condition that the heat of the commemorative coins is high, the problem of low response speed of the noble metal mall can occur, and under the condition that no special second killing scene exists, most of the noble metal malls are in an idle state, and the resource utilization rate of the noble metal malls is not high. Namely, under the condition of different service processing heat, the requirements on the peak capacity of the service processing dictionary load-relieving are different, if the whole service processing system is configured according to the maximum load, the resource waste of the service processing system can be caused when the service processing requirement is smaller, and the operation cost is increased.
Based on the above, the embodiment of the application provides a service processing method, which can deploy a service processing system on a cloud platform, acquire current resource usage information of the cloud platform in real time, dynamically adjust resources on the cloud platform according to the current resource usage information of the cloud platform so as to adapt to the requirements of the service processing system, thereby flexibly distributing resources for the service processing system, and ensuring higher resource utilization rate and quick response speed.
In one embodiment, as shown in fig. 2, a service processing method is provided, and the method is applied to the server in fig. 1 for illustration, and includes the following steps:
s201, under the condition that the service processing system performs service processing, current resource use information of a cloud platform to which the service processing system belongs is obtained.
Under the condition that a service processing system in the cloud platform performs service processing, a server acquires current resource use information of the cloud platform to which the service processing system belongs from the cloud platform.
The resource may be a physical resource in the cloud platform, including a processor and a memory, and the current resource usage information may be current physical resource usage information of the cloud platform, where the current resource usage information includes a processor usage rate and/or a memory usage rate of the cloud platform.
The method for acquiring the current resource usage information of the cloud platform to which the service processing system belongs may be that the cloud platform may send the current resource usage information to the server in real time; the method for obtaining the current resource usage information of the cloud platform to which the service processing system belongs may also be that the server accesses the cloud platform and reads the current resource usage information of the cloud platform.
S202, determining resource scheduling information of the cloud platform according to the current resource use information.
The resource scheduling information may be information on how to schedule the resources in the cloud platform, for example, the resource scheduling information may include reducing the resources and the amount of resources to be reduced for the cloud platform, or adding the resources and the amount of resources to be added for the cloud platform, and so on. The amount of resources may be a processor (Central Processing Unit, CPU) core amount and/or a memory amount.
In one embodiment, determining resource scheduling information of the cloud platform according to current resource usage information includes: and inputting the current resource use information into a preset resource scheduling model, and analyzing the current resource use information through resource scheduling to obtain the resource scheduling information of the cloud platform.
Specifically, the current resource usage information is input into a preset resource scheduling model, the resource scheduling model analyzes the current resource usage information, and the resource scheduling model outputs the resource scheduling information of the cloud platform.
Alternatively, the resource scheduling model may be trained from some underlying neural network model, such as, for example, including but not limited to, a deep learning network model, a deep convolutional neural network model, a residual neural network (Residual Neural Network, resNet) model, and so forth.
S203, scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform so as to enable the service processing system to process the service.
And scheduling the resources of the cloud platform according to the obtained resource scheduling information of the cloud platform so as to enable the service processing system to perform service processing.
For example, if the resource scheduling information of the cloud platform includes the resource amount to be reduced, performing capacity shrinking operation on the cloud platform, and controlling the cloud platform to reduce the corresponding resource amount; if the resource scheduling information of the cloud platform comprises the resource quantity to be enlarged, carrying out capacity expansion operation on the cloud platform, and controlling the cloud platform to increase the corresponding resource quantity.
In the service processing method provided by the embodiment of the application, under the condition that the service processing system performs service processing, current resource use information of a cloud platform to which the service processing system belongs is acquired, resource scheduling information of the cloud platform is determined according to the current resource use information, and then resources of the cloud platform are scheduled according to the resource scheduling information of the cloud platform, so that the service processing system performs service processing. According to the method, the service processing system is deployed on the cloud platform, and the cloud platform is subjected to resource scheduling according to the current resource use information of the cloud platform, so that the resources of the service processing system can be dynamically adjusted, when the resource demand is large, the resources of the service processing system are increased, when the resource demand is small, the resources of the service processing system are reduced, the response speed of the service processing system is high, and meanwhile, the resource utilization rate of the service processing system is guaranteed, so that the resources of the service processing system are flexibly allocated.
In one embodiment, as shown in fig. 3, determining resource scheduling information of the cloud platform according to current resource usage information includes the following steps:
s301, acquiring a preset elastic expansion strategy; the elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information.
The elastic expansion strategy represents a strategy for carrying out elastic expansion on resources of the cloud platform according to the use resource information of the cloud platform, namely, carrying out capacity expansion operation on the cloud platform when the use resource information of the cloud platform is large, and carrying out capacity reduction operation on the cloud platform when the use resource information of the cloud platform is small.
The elastic expansion strategy can be pre-constructed, and can be obtained from a database. Alternatively, the flexible policies may be constructed based on historical access information of the business processing system.
Specifically, in one embodiment, as shown in fig. 4, the construction process of the elastic expansion strategy includes the following steps:
s401, obtaining the historical access quantity of the service processing system.
The access amount of the service processing system is the number of service processing requests received by the service processing system from a user, and the flow and the heat of the service processing system can be measured through the access amount. The historical access amount of the service processing system is the access amount of the service processing system in the historical time.
The access amount of the service processing system at each moment is stored in a historical database, so that the historical access amount of the service processing system can be obtained from the database, wherein the historical access amount can be the access amount of the service processing system in a preset historical time period.
S402, analyzing the historical access amount, and determining a plurality of resource thresholds and corresponding historical resource scheduling information of the service processing system triggering elastic expansion.
The resource threshold may represent a system load threshold of elastic expansion of a cloud platform to which the service processing system belongs.
The historical access amount of the service processing system can be analyzed through a preset statistical algorithm, and a plurality of resource thresholds and corresponding historical resource scheduling information for triggering elastic expansion of the service processing system are determined. Specifically, the historical access amount is used as input of a statistical algorithm, and the statistical algorithm is operated to perform statistical analysis on the historical access amount by using the statistical algorithm, so as to obtain a plurality of resource thresholds and corresponding historical resource scheduling information.
S403, determining an elastic expansion strategy according to the plurality of resource thresholds and the corresponding historical resource scheduling information.
And integrating the plurality of resource thresholds and the corresponding historical resource scheduling information to obtain an elastic expansion strategy. The elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information.
For example, in the resource threshold range [ a, B ], the corresponding resource scheduling information is K1; within the resource threshold range (B, C), the corresponding resource scheduling information is K2 and so on; wherein A, B and C may represent resource thresholds, and K1 and K2 may represent corresponding resource scheduling information; it is understood that C is greater than B and B is greater than A.
It should be noted that, if the resources are processor resources and memory resources, the elastic expansion policy includes a processor resource threshold range and a correspondence between the memory resource threshold range and the resource scheduling information. For example, in the processor resource threshold range [ A1, B1] and the memory resource threshold range [ A2, B2], the corresponding resource scheduling information is Q1; the corresponding resource scheduling information is Q2 in the processor resource threshold range (B1, C1) and the memory resource threshold range (B2, C2), Q3 in the processor resource threshold range [ A1, B1] and the memory resource threshold range (B2, C2], Q4 in the processor resource threshold range (B1, C1) and the memory resource threshold range (B2, C2), and the like, wherein A1, B1 and C1 can represent the processor resource threshold, A2, B2 and C2 can represent the memory resource threshold, and the like, wherein Q1 and Q2 can represent the corresponding resource scheduling information, and it is understood that C1 is larger than B1, B1 is larger than A1, C2 is larger than B2, and B2 is larger than A2.
S302, a target resource threshold range of the current resource use information in the elastic expansion strategy is obtained.
And determining a target resource threshold range corresponding to the current resource use information according to the elastic expansion strategy, namely determining the target resource threshold range to which the current resource use information belongs in the elastic expansion strategy.
For example, when the current resource usage information is D and D is within the above-mentioned resource threshold range (B, C), it is determined that (B, C) is the target resource threshold range. Alternatively, the current resource usage information includes a processor resource of D1, a memory resource of D2, and D1 is within [ A1, B1], D2 is within (B2, C2], then the target resource threshold range is a processor resource threshold range [ A1, B1] and a memory resource threshold range (B2, C2].
S303, determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information.
And according to the corresponding relation between the resource threshold range and the resource scheduling information, namely the elastic telescopic strategy, acquiring target resource scheduling information corresponding to the target resource threshold range from the corresponding relation, and determining the target resource scheduling information as the current resource scheduling information of the cloud platform.
For example, if the target resource threshold range is (B, C), determining that the resource scheduling information of the cloud platform is K2; if the target resource threshold range is the processor resource threshold range [ A1, B1] and the memory resource threshold range (B2, C2], the resource scheduling information of the cloud platform is Q4.
In the service processing method provided by the embodiment of the application, a preset elastic expansion strategy is obtained, and a target resource threshold range of current resource use information in the elastic expansion strategy is obtained, wherein the elastic expansion strategy comprises a corresponding relation between the resource threshold range and resource scheduling information; and then determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information. In the method, the elastic expansion strategy comprises the corresponding relation between the resource threshold range and the resource scheduling information, so that the resource scheduling information of the cloud platform is obtained from the preset elastic expansion strategy according to the current resource use information, the accuracy of the current resource scheduling information of the cloud platform can be ensured, and the response speed and the resource utilization rate of a service processing system in the cloud platform are ensured.
In one embodiment, as shown in fig. 5, scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform includes:
s501, determining scheduling operation and resource allocation information of the cloud platform according to the resource scheduling information.
The resource scheduling information may include scheduling operation and resource allocation information. Therefore, the scheduling operation and the resource allocation information in the resource scheduling information can be directly determined as the scheduling operation and the resource allocation information of the cloud platform. Optionally, the scheduling operation includes a resource capacity expansion operation and a resource capacity reduction operation, and the resource allocation information includes a processor allocation amount and a memory allocation amount.
S502, if the scheduling operation is a resource capacity expansion operation, deploying a newly added virtual machine for the cloud platform according to the resource allocation information.
And under the condition that the scheduling operation is a resource capacity expansion operation, determining the newly added virtual machine according to the resource allocation information, and deploying the newly added virtual machine in the cloud platform.
The method comprises the steps of determining a new virtual machine according to the allocation amount of a processor and the allocation amount of memory, wherein one or more new virtual machines can be added, the total amount of processor resources of the new virtual machine is the allocation amount of the processor, and the total amount of memory of the new virtual machine is the allocation amount of the memory.
S503, if the scheduling operation is a resource capacity shrinking operation, deleting the virtual machine corresponding to the resource allocation information from the cloud platform.
And under the condition that the scheduling operation is a resource capacity shrinking operation, determining the virtual machine to be deleted in the cloud platform according to the resource allocation information, and then deleting the corresponding virtual machine from the cloud platform.
And determining one or more virtual machines to be deleted in the cloud platform according to the resource allocation information, wherein the total processor resource amount of the virtual machines to be deleted is the processor allocation amount, and the total memory amount of the virtual machines to be deleted is the memory allocation amount.
In the service processing method provided by the embodiment of the application, the scheduling operation and the resource allocation information of the cloud platform are determined according to the resource scheduling information; if the scheduling operation is a resource capacity expansion operation, deploying a newly added virtual machine for the cloud platform according to the resource allocation information; and if the scheduling operation is the resource capacity shrinking operation, deleting the virtual machine corresponding to the resource allocation information from the cloud platform. According to the method, the scheduling operation and the resource allocation information of the cloud platform are determined through the resource scheduling information, and the resource scheduling information is obtained through the current resource use information of the cloud platform, so that the scheduling operation and the resource allocation information of the cloud platform are more suitable for the resource amount of the current cloud platform, and the accuracy of scheduling the resources of the cloud platform according to the scheduling operation and the resource allocation information is higher.
In one embodiment, scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform may further include: determining scheduling operation and resource allocation information of the cloud platform according to the resource scheduling information; if the scheduling operation is a resource capacity expansion operation, adding corresponding resource allocation information for the cloud platform; the adding mode can be to deploy a new virtual machine for the cloud platform according to the resource allocation information, or to add computing resources on the existing virtual machine in the cloud platform, namely to add the processor resource quantity, the memory resource quantity and the like of the existing virtual machine in the cloud platform; if the scheduling operation is a resource capacity shrinking operation, the corresponding resource allocation information is reduced from the cloud platform, wherein the reducing mode may be to delete the virtual machine corresponding to the resource allocation information from the cloud platform, or to reduce the computing resources on the existing virtual machine in the cloud platform, that is, to reduce the processor resource amount, the memory resource amount and the like of the existing virtual machine in the cloud platform.
According to the service processing method, through flexible allocation of resources of the cloud platform, the situation of insufficient resources of the service processing system caused by high service access in the service processing system due to different service warmth can be avoided, and resource waste of the service processing system is reduced in low-load devices of the service processing system.
In one embodiment, the cloud platform includes a plurality of virtual machines, and in the manner of acquiring the current resource usage information of the cloud platform, the current resource usage information of each virtual machine may also be acquired, and the current resource usage information of the cloud platform is determined according to the current resource information of each virtual machine, where the current resource information of the virtual machine may include a resource usage amount and a resource total amount of the virtual machine, and the resource usage total amount and the resource total amount of the cloud platform are determined according to the resource usage amount and the resource total amount of each virtual machine, and the current resource usage information of the cloud platform is determined according to the resource usage total amount and the resource total amount of the cloud platform.
In one embodiment, as shown in fig. 6, taking a service processing system as an example of a noble metal mall, the noble metal mall is deployed in a cloud infrastructure (in a cloud platform), and a noble metal mall background can be put on shelf to participate in a product for second killing activity; after a noble metal mall background is put on a shelf to participate in a product for second killing activity, a noble metal mall management end can check the product for second killing activity, after the check is passed, product information is synchronized to a user end of the noble metal mall, a user can initiate a service processing request to the noble metal mall through the user end of the noble metal mall, namely reserving or second killing the product, a server can acquire current resource use information of a cloud platform in real time, and schedule resources of the cloud platform according to the current resource use information of the cloud platform, and the cloud platform comprises a plurality of cloud servers (virtual machines).
It should be noted that, the whole migration of the service processing system from the traditional server to the cloud platform includes the adaptation of the middleware invoked by the bottom layer.
In an embodiment, the embodiment of the present application further provides a service processing method, taking a service processing system as a precious metal mall as an example, as shown in fig. 7, where the embodiment further includes the following steps:
s701, under the condition that a noble metal mall performs service processing, acquiring current resource use information of a cloud platform to which the noble metal mall belongs; the current resource information includes processor usage and/or memory usage.
S702, acquiring a preset elastic expansion strategy; the elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information.
The construction process of the elastic expansion strategy comprises the following steps: acquiring historical access amount in a resource transfer application; analyzing the historical access amount, and determining a plurality of thresholds for triggering elastic expansion of the resource transfer application and corresponding historical resource scheduling information; and determining an elastic telescoping strategy according to the multiple thresholds and the corresponding historical resource scheduling information.
S703, obtaining a target resource threshold range of the current resource information in the elastic expansion strategy.
And S704, determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information.
S705, determining the scheduling operation of the cloud platform and the corresponding resource allocation information according to the resource scheduling information.
S706, if the scheduling operation is a resource capacity expansion operation, performing the capacity expansion operation for the cloud platform according to the resource allocation information.
Wherein the capacity expansion operation comprises: and deploying a newly added virtual machine for the cloud platform according to the resource allocation information, or adding the resource quantity corresponding to the resource allocation information for the existing virtual machine in the cloud platform according to the resource allocation information.
And S707, if the scheduling operation is a resource capacity reduction operation, performing capacity reduction operation for the cloud platform according to the resource allocation information.
Wherein the volume reduction operation comprises: and deleting the virtual machine corresponding to the resource allocation information from the cloud platform according to the resource allocation information, or reducing the corresponding resource amount from the existing virtual machine of the cloud platform according to the resource allocation information.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a service processing device for implementing the service processing method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in one or more embodiments of the service processing device provided below may refer to the limitation of the service processing method hereinabove, and will not be repeated herein.
In one embodiment, as shown in fig. 8, there is provided a service processing apparatus 800, including: an acquisition module 801, a determination module 802, and a scheduling module 803, wherein:
an obtaining module 801, configured to obtain current resource usage information of a cloud platform to which a service processing system belongs, where the service processing system performs service processing;
a determining module 802, configured to determine resource scheduling information of the cloud platform according to current resource usage information;
and the scheduling module 803 is configured to schedule resources of the cloud platform according to the resource scheduling information of the cloud platform, so that the service processing system performs service processing.
In one embodiment, the determining module 802 includes:
the analysis unit is used for inputting the current resource use information into a preset resource scheduling model, and analyzing the current resource use information through resource scheduling to obtain the resource scheduling information of the cloud platform.
In one embodiment, the determining module 802 includes:
the strategy acquisition unit is used for acquiring a preset elastic telescopic strategy; the elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information;
the first determining unit is used for obtaining a target resource threshold range to which the current resource use information belongs in the elastic expansion strategy;
and the second determining unit is used for determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information.
In one embodiment, the apparatus 800 further comprises:
the historical access amount acquisition module is used for acquiring the historical access amount of the service processing system;
the analysis module is used for analyzing the historical access quantity and determining a plurality of resource thresholds and corresponding historical resource scheduling information, wherein the resource thresholds trigger elastic expansion of the service processing system;
and the strategy determining module is used for determining an elastic telescopic strategy according to the plurality of resource thresholds and the corresponding historical resource scheduling information.
In one embodiment, the scheduling module 803 includes:
the resource allocation unit is used for determining the scheduling operation and the resource allocation information of the cloud platform according to the resource scheduling information;
The first resource scheduling unit is used for deploying a newly-added virtual machine for the cloud platform according to the resource allocation information if the scheduling operation is a resource capacity expansion operation;
and the second resource scheduling unit is used for deleting the virtual machine corresponding to the resource allocation information from the cloud platform if the scheduling operation is a resource capacity reduction operation.
In one embodiment, the current resource usage information includes processor usage and/or memory usage.
The respective modules in the above-described service processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 9. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing business process data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a business processing method.
It will be appreciated by those skilled in the art that the structure shown in fig. 9 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application applies, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
under the condition that a service processing system performs service processing, acquiring current resource use information of a cloud platform to which the service processing system belongs;
determining resource scheduling information of the cloud platform according to the current resource use information;
and scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform so as to enable the service processing system to perform service processing.
In one embodiment, the processor when executing the computer program further performs the steps of:
and inputting the current resource use information into a preset resource scheduling model, and analyzing the current resource use information through resource scheduling to obtain the resource scheduling information of the cloud platform.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring a preset elastic expansion strategy; the elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information;
acquiring a target resource threshold range to which current resource use information belongs in an elastic expansion strategy;
and determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring historical access quantity of a service processing system;
analyzing the historical access amount, and determining a plurality of resource thresholds for triggering elastic expansion of the service processing system and corresponding historical resource scheduling information;
and determining an elastic telescoping strategy according to the plurality of resource thresholds and the corresponding historical resource scheduling information.
In one embodiment, the processor when executing the computer program further performs the steps of:
determining scheduling operation and resource allocation information of the cloud platform according to the resource scheduling information;
if the scheduling operation is a resource capacity expansion operation, deploying a newly added virtual machine for the cloud platform according to the resource allocation information;
And if the scheduling operation is the resource capacity shrinking operation, deleting the virtual machine corresponding to the resource allocation information from the cloud platform.
In one embodiment, the current resource usage information includes processor usage and/or memory usage.
The steps implemented by the processor in the foregoing embodiments are similar to the principles and technical effects of the foregoing service processing method, and are not repeated herein.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
under the condition that a service processing system performs service processing, acquiring current resource use information of a cloud platform to which the service processing system belongs;
determining resource scheduling information of the cloud platform according to the current resource use information;
and scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform so as to enable the service processing system to perform service processing.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and inputting the current resource use information into a preset resource scheduling model, and analyzing the current resource use information through resource scheduling to obtain the resource scheduling information of the cloud platform.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a preset elastic expansion strategy; the elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information;
acquiring a target resource threshold range to which current resource use information belongs in an elastic expansion strategy;
and determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring historical access quantity of a service processing system;
analyzing the historical access amount, and determining a plurality of resource thresholds for triggering elastic expansion of the service processing system and corresponding historical resource scheduling information;
and determining an elastic telescoping strategy according to the plurality of resource thresholds and the corresponding historical resource scheduling information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining scheduling operation and resource allocation information of the cloud platform according to the resource scheduling information;
if the scheduling operation is a resource capacity expansion operation, deploying a newly added virtual machine for the cloud platform according to the resource allocation information;
And if the scheduling operation is the resource capacity shrinking operation, deleting the virtual machine corresponding to the resource allocation information from the cloud platform.
In one embodiment, the current resource usage information includes processor usage and/or memory usage.
The steps of the above embodiment, which are implemented when the computer program is executed by the processor, implement principles and technical effects similar to those of the above service processing method, and are not described herein again.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
under the condition that a service processing system performs service processing, acquiring current resource use information of a cloud platform to which the service processing system belongs;
determining resource scheduling information of the cloud platform according to the current resource use information;
and scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform so as to enable the service processing system to perform service processing.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and inputting the current resource use information into a preset resource scheduling model, and analyzing the current resource use information through resource scheduling to obtain the resource scheduling information of the cloud platform.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a preset elastic expansion strategy; the elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information;
acquiring a target resource threshold range to which current resource use information belongs in an elastic expansion strategy;
and determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring historical access quantity of a service processing system;
analyzing the historical access amount, and determining a plurality of resource thresholds for triggering elastic expansion of the service processing system and corresponding historical resource scheduling information;
and determining an elastic telescoping strategy according to the plurality of resource thresholds and the corresponding historical resource scheduling information.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining scheduling operation and resource allocation information of the cloud platform according to the resource scheduling information;
if the scheduling operation is a resource capacity expansion operation, deploying a newly added virtual machine for the cloud platform according to the resource allocation information;
And if the scheduling operation is the resource capacity shrinking operation, deleting the virtual machine corresponding to the resource allocation information from the cloud platform.
In one embodiment, the current resource usage information includes processor usage and/or memory usage.
The steps of the above embodiment, which are implemented when the computer program is executed by the processor, implement principles and technical effects similar to those of the above service processing method, and are not described herein again.
It should be noted that, the data (including, but not limited to, data for analysis, stored data, displayed data, etc.) referred to in the present application are all information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data are required to comply with the related laws and regulations and standards of the related countries and regions.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. A service processing method, applied to a server, the method comprising:
under the condition that a service processing system performs service processing, acquiring current resource use information of a cloud platform to which the service processing system belongs;
determining resource scheduling information of the cloud platform according to the current resource use information;
and scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform so as to enable the service processing system to perform the service processing.
2. The method of claim 1, wherein determining the resource scheduling information of the cloud platform according to the current resource usage information comprises:
and inputting the current resource use information into a preset resource scheduling model, and analyzing the current resource use information through the resource scheduling to obtain the resource scheduling information of the cloud platform.
3. The method according to claim 1 or 2, wherein determining the resource scheduling information of the cloud platform according to the current resource usage information comprises:
acquiring a preset elastic expansion strategy; the elastic expansion strategy comprises a corresponding relation between a resource threshold range and resource scheduling information;
acquiring a target resource threshold range to which the current resource use information belongs in the elastic expansion strategy;
and determining the resource scheduling information corresponding to the target resource threshold range as the resource scheduling information of the cloud platform according to the corresponding relation between the resource threshold range and the resource scheduling information.
4. A method according to claim 3, wherein the process of constructing the elastic telescoping strategy comprises:
Acquiring historical access quantity of the service processing system;
analyzing the historical access amount, and determining a plurality of resource thresholds and corresponding historical resource scheduling information of the service processing system triggering elastic expansion;
and determining the elastic expansion strategy according to the plurality of resource thresholds and the corresponding historical resource scheduling information.
5. The method according to claim 1 or 2, wherein the scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform includes:
determining scheduling operation and resource allocation information of the cloud platform according to the resource scheduling information;
if the scheduling operation is a resource capacity expansion operation, deploying a newly added virtual machine for the cloud platform according to the resource allocation information;
and if the scheduling operation is a resource capacity shrinking operation, deleting the virtual machine corresponding to the resource allocation information from the cloud platform.
6. The method according to claim 1 or 2, wherein the current resource usage information comprises processor usage and/or memory usage.
7. A service processing apparatus, the apparatus comprising:
the system comprises an acquisition module, a service processing module and a control module, wherein the acquisition module is used for acquiring current resource use information of a cloud platform to which the service processing system belongs under the condition that the service processing system performs service processing;
The determining module is used for determining resource scheduling information of the cloud platform according to the current resource use information;
and the scheduling module is used for scheduling the resources of the cloud platform according to the resource scheduling information of the cloud platform so as to enable the service processing system to perform the service processing.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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