Service resource determination method and device, equipment and storage medium

Abstract

The invention provides a service resource determination method and device, equipment and a storage medium, and the method comprises the steps: obtaining a target resource type and a to-be-estimated energy measurement parameter, determining a target energy measurement reference value matched with the to-be-estimated energy measurement parameter in a preset reference scheme list, calculating a proportional relation between the to-be-estimated energy measurement parameter and the target energy measurement reference value, and determining a service resource according to the proportional relation. Determining resource specification configuration information corresponding to the target energy reference value, and determining target resource specification configuration information in a preset configuration sorting list corresponding to the target resource type based on the proportional relation and the resource specification configuration information corresponding to the target energy reference value; according to the method, the corresponding resource specification configuration information is dynamically calculated by matching the energy quantity parameter with the reference value in the benchmark scheme list in combination with the proportional relation and the configuration sorting list, so that inaccurate resource allocation caused by empirical judgment is avoided, the accuracy of the resource specification configuration information is effectively improved, and the user experience is improved. And the phenomenon of insufficient resource support or redundant resource waste caused by inaccurate resource allocation is reduced.

Description

Technical Field

[0001] The present application relates to the field of Internet resource management, and in particular to a method, apparatus, device and storage medium for determining service resources. Background Art

[0002] Against the backdrop of the continuous development of Internet technology and the accelerated process of digital transformation, cloud computing has become the core infrastructure supporting modern service architecture and software development. With the maturity of cloud-native technology stacks and the popularization of microservice architecture, the dependence on cloud resources for newly established services and development projects has significantly increased. It is usually necessary to dynamically allocate diversified resources such as elastic cloud servers, cloud databases, cache database clusters, and cloud search services to meet complex needs such as real-time data processing. This also causes the cloud resource supply model to transform from a static resource pool to a dynamic service grid, forming a complex resource matrix.

[0003] However, in the practice of cloud resource allocation, manual experience is mainly relied upon to estimate the energy data formed by user scale and user concurrency, and based on this, preset resource specifications are matched. Due to its high subjectivity, it is difficult to quantify the differences in resource performance requirements under different business scenarios, which often leads to inaccurate resource allocation. In burst traffic scenarios, insufficient resources are allocated during the implementation of new projects due to the inability to accurately calculate manual experience. In the allocation process, excessive estimation of resource demand or different collaborative configuration ratios of multiple resource types in the empirical model may lead to the allocation of too many redundant resources, resulting in a waste of cloud resources. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a service resource determination method, apparatus, device and storage medium to solve the above technical problems.

[0005] The present application provides a service resource determination method, which includes: obtaining a target resource type and an energy parameter to be estimated, the energy parameter being used to characterize a quantitative parameter of user scale and / or user concurrency; determining a target energy reference value that matches the energy parameter to be estimated in a preset benchmark scheme list, the preset benchmark scheme list including multiple energy reference values and resource specification configuration information corresponding to each energy reference value; calculating a proportional relationship between the energy parameter to be estimated and the target energy reference value, and determining the resource specification configuration information corresponding to the target energy reference value; based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, determining the target resource specification configuration information in a preset configuration sorting list corresponding to the target resource type.

[0006] In one embodiment of the present application, after determining the target resource specification configuration information in the preset configuration sorting list corresponding to the target resource type, the method also includes: sending the energy parameters to be estimated and the target resource specification configuration information to the terminal, and issuing a re-inspection request; if the terminal feedback is that the re-inspection is correct, the preset benchmark plan list is updated according to the energy parameters to be estimated and the target resource specification configuration information.

[0007] In one embodiment of the present application, the construction of the preset configuration ranking list includes: obtaining multiple groups of specification configurations under each resource type, each group of specification configurations including specification type, number of chip cores, memory capacity and storage space; determining the specification weight value of each group of specification configurations based on the preset specification coefficient corresponding to the specification type in each group of specification configurations, the number of chip cores and the memory capacity, and the specification weight value is used to characterize the performance of each group of specification configurations; sorting multiple groups of specification configurations in the same resource type according to the specification weight value of each group of specification configurations to obtain a configuration ranking list for each resource type.

[0008] In one embodiment of the present application, the construction of the preset benchmark solution list includes: obtaining historical service resource configuration information and dividing at least two energy reference values; determining a set of specification parameters adapted to each of the energy reference values in the configuration priority list of each resource type based on the historical service resource configuration information; establishing an association relationship between each of the energy reference values and a set of specification parameters adapted in the configuration priority list of each resource type to obtain a preset benchmark solution list.

[0009] In one embodiment of the present application, determining the target energy reference value that matches the energy parameter to be estimated in the preset benchmark scheme list includes: if the energy parameter to be estimated is equal to any energy reference value in the preset benchmark scheme list, then the equal energy reference value is determined as the target energy reference value; if the energy parameter to be estimated is greater than the largest energy reference value in the preset benchmark scheme list, then the largest energy reference value is determined as the target energy reference value; if the energy parameter to be estimated is less than the smallest energy reference value in the preset benchmark scheme list, then the smallest energy reference value is determined as the target energy reference value; if the energy parameter to be estimated is greater than the smallest energy reference value in the preset benchmark scheme list and less than the largest energy reference value in the preset benchmark scheme list, and is not equal to any energy reference value in the preset benchmark scheme list, then the two energy reference values closest to the energy parameter to be estimated are determined as the target energy reference values.

[0010] In one embodiment of the present application, calculating the proportional relationship between the energy parameter to be estimated and the target energy reference value includes: if the target energy reference value includes one energy reference value, then calculating the proportional relationship by the ratio of the energy parameter to be estimated and the target energy reference value; if the target energy reference value includes two energy reference values, then calculating the proportional relationship by the ratio of the difference between the two energy reference values and the energy parameter to be estimated.

[0011] In one embodiment of the present application, based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, the target resource specification configuration information is determined in the preset configuration sorting list corresponding to the target resource type: the target specification weight value is determined in the preset configuration sorting list corresponding to the target resource type according to the resource specification configuration information corresponding to the target energy reference value; the estimated weight value is determined according to the proportional relationship and the target specification weight value, and the group of specification configurations with the smallest difference between the specification weight value and the estimated weight value in each group of specification configurations in the preset configuration sorting list corresponding to the target resource type is determined as the target resource specification configuration information.

[0012] An embodiment of the present application also provides a service resource determination device, which includes: a target information acquisition module, used to obtain a target resource type and an energy parameter to be estimated, wherein the energy parameter is used to characterize a quantitative parameter of user scale and / or user concurrency; a matching information determination module, used to determine a target energy reference value that matches the energy parameter to be estimated in a preset benchmark scheme list, wherein the preset benchmark scheme list includes multiple energy reference values and resource specification configuration information corresponding to each energy reference value; calculate the proportional relationship between the energy parameter to be estimated and the target energy reference value, and determine the resource specification configuration information corresponding to the target energy reference value; a resource configuration determination module, used to determine the target resource specification configuration information in the preset configuration sorting list corresponding to the target resource type based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value.

[0013] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements a service resource determination method as described in any one of the above embodiments.

[0014] An embodiment of the present application further provides a computer-readable storage medium having computer-readable instructions stored thereon. When the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the service resource determination method as described in any one of the above embodiments.

[0015] The present application provides a service resource determination method, apparatus, device and storage medium, which obtains the target resource type and the energy parameter to be estimated, determines the target energy reference value that matches the energy parameter to be estimated in a preset benchmark scheme list, calculates the proportional relationship between the energy parameter to be estimated and the target energy reference value, and determines the resource specification configuration information corresponding to the target energy reference value. Based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, the target resource specification configuration information is determined in a preset configuration sorting list corresponding to the target resource type. The present application avoids inaccurate resource allocation caused by empirical judgment by matching the energy parameter with the reference value in the benchmark scheme list, combining the proportional relationship and the configuration sorting list to dynamically calculate the corresponding resource specification configuration information. This can effectively improve the accuracy of resource specification configuration information and reduce the phenomenon of insufficient resource support or waste of redundant resources due to inaccurate resource allocation.

[0016] The foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are incorporated into and constitute a part of the specification, illustrating embodiments consistent with the present application and, together with the specification, serving to explain the principles of the present application. It is obvious that the drawings described below are merely some embodiments of the present application, and a person of ordinary skill in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0018] Figure 1 is a schematic diagram of an exemplary system architecture shown in an exemplary embodiment of the present application;

[0019] Figure 2 is a flowchart of a method for determining service resources according to an exemplary embodiment of the present application;

[0020] Figure 3 is a schematic diagram of a device for determining service resources according to an exemplary embodiment of the present application;

[0021] Figure 4 It is a structural diagram of a computer system of an electronic device shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0022] The following will describe the embodiments of the present application with reference to the accompanying drawings and specific embodiments. Those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for the purpose of illustrating the present application and are not intended to limit the scope of protection of the present application.

[0023] The illustrations provided in the following embodiments are merely schematic illustrations of the basic concept of the present application. Therefore, the illustrations only show components related to the present application and are not drawn according to the number, shape, and size of components in actual implementation. In actual implementation, the type, quantity, and proportion of each component may be changed arbitrarily, and the component layout may also be more complex.

[0024] In the following description, a large number of details are discussed to provide a more thorough explanation of the embodiments of the present application. However, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present application difficult to understand.

[0025] The term "and / or" used in this application describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. The character " / " generally indicates that the associated objects are in an "or" relationship.

[0026] Figure 1 It is a schematic diagram of an exemplary system architecture shown in an exemplary embodiment of the present application.

[0027] Reference Figure 1As shown, the system architecture may include a project database 110 and a computer device 120. The computer device 120 obtains the target resource type and the energy parameter to be estimated from the project database 110, determines the target energy reference value that matches the energy parameter to be estimated in the preset benchmark solution list, calculates the proportional relationship between the energy parameter to be estimated and the target energy reference value, and determines the resource specification configuration information corresponding to the target energy reference value. Based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, the target resource specification configuration information is determined in the preset configuration sorting list corresponding to the target resource type. The above-mentioned computer device 130 refers to a computing power support device for carrying the program implementation environment for executing the service resource determination method, which includes but is not limited to microcomputers, server clusters, and virtual machines; the above-mentioned project database 110 is used to monitor and record resource types and energy parameters during project implementation.

[0028] Schematically, the computer device 130 obtains the target resource type and the energy parameter to be estimated in the project database 110, determines the target energy reference value that matches the energy parameter to be estimated in the preset benchmark scheme list, calculates the proportional relationship between the energy parameter to be estimated and the target energy reference value, and determines the resource specification configuration information corresponding to the target energy reference value. Based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, the target resource specification configuration information is determined in the preset configuration sorting list corresponding to the target resource type; the present application avoids inaccurate resource allocation caused by empirical judgment by matching the energy parameter with the reference value in the benchmark scheme list, combining the proportional relationship and the configuration sorting list to dynamically calculate the corresponding resource specification configuration information, and can effectively improve the accuracy of the resource specification configuration information and reduce the phenomenon of insufficient resource support or waste of redundant resources due to inaccurate resource allocation.

[0029] Figure 2 is a flowchart of a method for determining service resources according to an exemplary embodiment of the present application. The method for determining service resources can be Figure 1 The implementation environment can be implemented in other implementation environments, and the above implementation environment is not specifically limited here. Figure 2 As shown, the flowchart of the service resource determination method includes at least steps S210 to S230, which are described in detail as follows:

[0030] In step S210 , the target resource type and the energy parameters to be estimated are obtained.

[0031] In one embodiment of the present application, the above-mentioned energy parameters are used to characterize the quantitative parameters of user scale and / or user concurrency. In some embodiments, the energy parameters can be expressed based on the specific numerical value of the user scale, or can be expressed based on the specific numerical value of the user concurrency. In some other embodiments, the energy parameters can also be expressed by weighted summing the specific numerical value of the user scale and the specific numerical value of the user concurrency. The representation form of the energy parameters is not specifically limited here.

[0032] In one embodiment of the present application, the target resource type refers to the specific service type that needs to be configured in the cloud computing environment. In some implementable environments, the target resource types include elastic cloud servers, cloud databases, cache database clusters, and cloud search services. Among them, elastic cloud servers (ECS) are a type of virtual computing resource that can be flexibly configured and expanded on demand. It pools physical server resources through virtualization technology based on cloud computing technology. Users can independently select CPU, memory, storage and other configurations, and can quickly deploy, elastically expand or reduce resources; cloud databases are database services based on cloud computing technology. Traditional database functions are deployed on cloud servers, supporting elastic expansion of storage and computing resources. It has high availability, automatic backup and disaster recovery capabilities, and does not require the management of underlying hardware, and can be used on demand through the network; the cache database cluster is a cluster system that interconnects multiple cache database servers through a distributed architecture. Through mechanisms such as data sharding and replica synchronization, it achieves elastic expansion of cache capacity and processing power, and has both high concurrent read and write performance and data reliability; the cloud search service is an intelligent search solution based on cloud computing architecture, which deploys search engine functions in the cloud, supports real-time indexing and retrieval of massive data, has distributed cluster processing capabilities, can elastically expand computing and storage resources, provides high concurrent query, word segmentation analysis and semantic understanding and other functions, and quickly obtains structured or unstructured data.

[0033] In step S220 , a target energy reference value matching the energy parameter to be estimated is determined in a preset reference solution list.

[0034] In one embodiment of the present application, the above-mentioned preset benchmark scheme list includes multiple energy reference values and resource specification configuration information corresponding to each energy reference value, wherein verified energy thresholds and resource configuration combinations are stored. Specifically, a key-value pair database can be used to store energy reference values and their corresponding CPU core number, memory capacity and other configuration parameters.

[0035] In one embodiment of the present application, the process of constructing a preset configuration sorting list includes obtaining multiple groups of specification configurations under each resource type, each group of specification configurations including specification type, number of chip cores, memory capacity and storage space, wherein the specification type refers to the hardware or software architecture classification of the resource configuration, which can be specifically implemented using parameters such as server model, database engine type or cache middleware version, and the performance differences of different architectures can be quantified through preset specification coefficients; the number of chip cores refers to the computing power indicator of the processor unit, which can be specifically implemented through statistics of the number of physical cores or logical threads; memory capacity refers to the accessible memory space available at runtime, which can be specifically measured in gigabytes or terabytes, and this parameter determines the system's concurrent processing capability.

[0036] The specification weight value of each group of specification configurations is determined based on the preset specification coefficient, number of chip cores and memory capacity corresponding to the specification type in each group of specification configurations. The specification weight value is used to characterize the performance of each group of specification configurations. In some embodiments, the specification weight value of each group of specification configurations is determined by multiplying the numerical values of the preset specification coefficient, number of chip cores and memory capacity corresponding to the specification type. The specification weight value of each group of specification configurations can also be determined by weighted summing the numerical values of the preset specification coefficient, number of chip cores and memory capacity corresponding to the specification type.

[0037] According to the specification weight values of each specification configuration group, multiple groups of specification configurations in the same resource type are sorted to obtain a configuration sorting list for each resource type. When constructing a configuration sorting list, it is first necessary to collect multiple groups of specification configuration data under the same resource type. By setting coefficients for different specification types, for example, setting the coefficient of a general-purpose server to 1 and a dedicated server to 2, the impact of architectural differences on performance can be reflected. The specification weight value of each group of specification configurations is then determined by multiplying the preset specification coefficient corresponding to the specification type, the number of chip cores, and the memory capacity. After the calculation is completed, all configurations are sorted from high to low according to the weight value to form a performance sorting list that can be quickly retrieved.

[0038] In one embodiment of the present application, the target energy reference value refers to a benchmark value that is closest to or most closely matches the energy parameter to be estimated. Specifically, it can be achieved through numerical comparison and interval division, for example, by judging the size relationship between the energy parameter to be estimated and the energy reference value in the preset benchmark scheme list.

[0039] If the quantity parameter to be estimated is equal to any quantity reference value in the preset benchmark scheme list, the equal quantity reference value will be determined as the target quantity reference value.

[0040] If the energy parameter to be estimated is greater than the largest energy reference value in the preset benchmark list, the largest energy reference value is determined as the target energy reference value. For example, if the energy parameter to be estimated is 1500, and the largest reference value in the preset list is 1000, 1000 is selected as the target value.

[0041] If the energy parameter to be estimated is less than the minimum energy reference value in the preset benchmark list, the minimum energy reference value is determined as the target energy reference value. For example, if the energy parameter to be estimated is 150, and the minimum reference value in the preset list is 200, 200 is selected as the target value.

[0042] If the energy parameter to be estimated is greater than the smallest energy reference value in the preset benchmark solution list and less than the largest energy reference value in the preset benchmark solution list, and is not equal to any energy reference value in the preset benchmark solution list, the two energy reference values closest to the energy parameter to be estimated will be determined as the target energy reference value. For example, if the energy parameter to be estimated is 1500, and there are two adjacent reference values in the list, 1400 and 1600, both will be selected as the target value.

[0043] In step S230 , a proportional relationship between the energy parameter to be estimated and the target energy reference value is calculated, and resource specification configuration information corresponding to the target energy reference value is determined.

[0044] In one embodiment of the present application, the above-mentioned proportional relationship refers to the mathematical relationship between the energy parameter to be estimated and the target energy reference value, which can be specifically implemented by linear proportionality or nonlinear interpolation, and is used to quantify the difference in resource requirements of the scenario to be estimated relative to the benchmark case. For example, when the target energy reference value is a single value, the proportional relationship directly reflects the multiple of the energy to be estimated relative to the benchmark value; when there are two adjacent benchmark values, the difference ratio is used to determine the relative position of the energy to be estimated within the two benchmark intervals.

[0045] In one embodiment of the present application, if the target energy reference value includes an energy reference value, the proportional relationship is calculated by the ratio of the energy parameter to be estimated to the target energy reference value. If the energy parameter to be estimated exactly matches a reference value in the baseline solution, the resource specification configuration corresponding to the reference value is directly adopted. In this case, the proportional relationship is 1:1, and there is no need to adjust the resource configuration parameters.

[0046] In one embodiment of the present application, if the target energy reference value includes two energy reference values, the proportional relationship is calculated by the ratio of the difference between the two energy reference values and the energy parameter to be estimated. Wherein, the difference refers to the numerical interval between the two energy reference values, which can be implemented by absolute value subtraction operation to build a dynamic interpolation calculation model. When the energy to be estimated does not directly hit the benchmark value and is between two adjacent benchmark values, the position weight relative to the two benchmark points is determined by calculating the ratio of the difference between the parameter and the smaller benchmark value and the total difference between the two benchmark values. When the energy to be estimated is in the benchmark interval, the present application uses the difference ratio to establish a dynamic weight model, which avoids the resource allocation overload or underload caused by simply using adjacent benchmark values, maintains the original configuration efficiency when the benchmark value is fully matched, and realizes efficient reuse and dynamic expansion of the benchmark scheme.

[0047] In step S240 , based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, the target resource specification configuration information is determined in a preset configuration sorting list corresponding to the target resource type.

[0048] In one embodiment of the present application, the above-mentioned preset configuration sorting list constructs a priority sequence based on performance indicators. The construction of the above-mentioned preset benchmark solution list includes obtaining historical service resource configuration information and dividing it into at least two energy reference values, wherein the historical service resource configuration information refers to the resource usage record of the deployed service, which can be implemented by using resource configuration logs stored in a database, such as recording parameters such as the number of CPU cores, memory capacity, and storage space. These historical data provide actual case support for establishing a benchmark solution and can reflect the resource demand pattern in real scenarios. The energy reference value refers to the numerical interval used to divide the resource demand level, which can be implemented by using the user scale or user concurrency value. For example, the user scale is divided into three levels of 1000, 5000, and 10000, which can discretize complex demands and facilitate matching resource specifications in different scale scenarios.

[0049] In one embodiment of the present application, a set of specification parameters that are adapted to each energy reference value is determined in the configuration priority ranking list of each resource type based on historical service resource configuration information, and an association relationship is established between each energy reference value and a set of specification parameters that are adapted in the configuration priority ranking list of each resource type to obtain a preset benchmark solution list. According to the configuration ranking list, the specification parameters with the closest weight value are selected in each energy level. For example, a combination of a dedicated 16-core CPU and 64GB memory is selected in the 5000 user level, and finally a mapping relationship between the energy reference value and the specific specification parameters is established to form a preset benchmark solution list that can be adjusted dynamically. The benchmark solution established based on historical data can adapt to the resource configuration requirements of different energy levels, achieve accurate matching of specification parameters through the configuration ranking list, improve the rationality and scalability of the resource allocation solution, and in the case of burst traffic, the benchmark solution can provide a reliable reference for dynamic resource adjustment and reduce the resource allocation error rate.

[0050] In one embodiment of the present application, the target specification weight value is determined in the preset configuration sorting list corresponding to the target resource type according to the resource specification configuration information corresponding to the target energy reference value, the estimated weight value is determined according to the proportional relationship and the target specification weight value, and the group of specification configurations with the smallest difference between the specification weight value and the estimated weight value in each group of specification configurations in the preset configuration sorting list corresponding to the target resource type is determined as the target resource specification configuration information. Among them, the estimated weight value refers to the dynamic adjustment value obtained by scaling the target specification weight value in combination with the proportional relationship, which can be specifically implemented by linear interpolation or geometric scaling algorithm, and is used to map the actual user demand to the resource performance indicator; the minimum difference means that the absolute difference between the specification weight value and the estimated weight value reaches the minimum value, which can be specifically implemented by traversing the sorting list or binary search algorithm, and is used to accurately match performance requirements and resource configurations.

[0051] After determining the resource configuration specifications corresponding to the target energy reference value, the configuration specification weights from the preset ranked list are extracted as baseline performance indicators. Based on the proportional relationship between the energy parameter to be estimated and the baseline energy reference value, the baseline specification weights are dynamically adjusted to generate estimated weights that reflect actual demand. The ranked list of configurations corresponding to the target resource type is then traversed, and the absolute difference between the weights of each configuration specification and the estimated weights is calculated. The configuration set with the smallest difference is selected as the target resource configuration specification information.

[0052] In one embodiment of the present application, after determining the target resource specification configuration information in the preset configuration sorting list corresponding to the target resource type, the energy parameters to be estimated and the target resource specification configuration information are sent to the terminal, and a re-inspection request is issued. If the terminal feedback is that the re-inspection is correct, the preset benchmark scheme list is updated according to the energy parameters to be estimated and the target resource specification configuration information. Among them, the re-inspection request refers to a request instruction that triggers the terminal to conduct a secondary verification of the resource specification configuration results. Specifically, it can be achieved by transmitting a data packet through a preset API interface and attaching a verification mark. This mechanism is used to ensure the accuracy of the resource configuration results. The specific re-inspection process can be obtained by relevant technical personnel verifying the implementation results of the energy parameters to be estimated and the target resource specification configuration information. The above-mentioned judgment condition for re-inspection is the confirmation signal returned by the terminal, which can be achieved through digital signature verification or check code comparison.

[0053] In one embodiment of the present application, after the resource specification configuration information is generated, the system automatically encapsulates the energy parameters to be estimated and the target resource specification configuration information into structured data, and pushes it to the terminal through an encrypted channel. After receiving the data packet, the terminal device displays the corresponding relationship between the resource configuration scheme and the energy parameters through a visual interface, and the technical personnel perform a secondary verification of the rationality of the configuration. After obtaining a feedback signal confirming that it is correct, the system uses the currently valid energy parameters to be estimated and the target resource specification configuration information as new data samples, dynamically updates the preset benchmark scheme list, and adds energy reference values and corresponding resource specification configuration information to the preset benchmark scheme list. By establishing a closed-loop mechanism for terminal review and dynamic update of the benchmark list, the resource configuration model has self-learning capabilities, can continuously optimize the calculation accuracy of the resource configuration model, significantly improves the adaptability and accuracy of resource specification matching, and overcomes the resource configuration deviation caused by the solidification of manual experience.

[0054] The present application provides a service resource determination method, apparatus, device and storage medium, which obtains the target resource type and the energy parameter to be estimated, determines the target energy reference value that matches the energy parameter to be estimated in a preset benchmark scheme list, calculates the proportional relationship between the energy parameter to be estimated and the target energy reference value, and determines the resource specification configuration information corresponding to the target energy reference value. Based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, the target resource specification configuration information is determined in a preset configuration sorting list corresponding to the target resource type. The present application avoids inaccurate resource allocation caused by empirical judgment by matching the energy parameter with the reference value in the benchmark scheme list, combining the proportional relationship and the configuration sorting list to dynamically calculate the corresponding resource specification configuration information. This can effectively improve the accuracy of resource specification configuration information and reduce the phenomenon of insufficient resource support or waste of redundant resources due to inaccurate resource allocation.

[0055] The following describes an embodiment of the device of the present application, which can be used to execute the service resource determination method in the above embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the service resource determination method in the above embodiment of the present application.

[0056] Figure 3 This is a schematic diagram of a service resource determination device shown in an exemplary embodiment of the present application. The device can be applied to Figure 2 The method implementation process shown in the figure can be based on Figure 1 The present invention is executed in the implementation environment shown in , and may also be applicable to other exemplary implementation environments and specifically configured in other devices. This embodiment does not limit the implementation environment to which the apparatus is applicable.

[0057] like Figure 3 As shown, the exemplary service resource determination device includes: a target information acquisition module 301 , a matching information determination module 302 and a resource configuration determination module 303 .

[0058] Among them, the target information acquisition module 301 is used to obtain the target resource type and the energy parameter to be estimated, and the energy parameter is used to characterize the quantitative parameters of the user scale and / or user concurrency; the matching information determination module 302 is used to determine the target energy reference value that matches the energy parameter to be estimated in the preset benchmark scheme list, and the preset benchmark scheme list includes multiple energy reference values and resource specification configuration information corresponding to each energy reference value; calculate the proportional relationship between the energy parameter to be estimated and the target energy reference value, and determine the resource specification configuration information corresponding to the target energy reference value; the resource configuration determination module 303 is used to determine the target resource specification configuration information in the preset configuration sorting list corresponding to the target resource type based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value.

[0059] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, which, when executed by one or more processors, enables the electronic device to implement the service resource determination method provided in the above-mentioned embodiments.

[0060] Figure 4 This is a schematic diagram of the structure of a computer system of an electronic device according to an exemplary embodiment of the present application. Figure 4 The computer system 400 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0061] like Figure 4As shown, computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in read-only memory (ROM) 402 or the program loaded from the storage portion into random access memory (RAM) 403, such as executing the method in the above embodiment. Various programs and data required for system operation are also stored in RAM 403. CPU 401, ROM 402 and RAM 403 are connected to each other via a bus. I / O interface 405 is also connected to bus 404, wherein I / O interface 405 refers to an input / output (Input / Output) interface.

[0062] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 408 including a hard disk; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface 405 as needed. Removable media 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., are installed in the drive 410 as needed so that computer programs read therefrom can be installed into the storage section 408 as needed.

[0063] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 409, and / or installed from a removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the various functions defined in the system of the present application are executed.

[0064] The computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. This propagated data signal can take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0065] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0066] In the corresponding drawings of the above embodiments, connecting lines can represent the connection relationship between various components to represent more constituent signal paths (constituent_signalpath) and / or one or more ends of some lines have arrows to indicate the main information flow direction. The connecting lines serve as an identifier and are not a limitation to the scheme itself. Instead, the use of these lines in combination with one or more exemplary embodiments helps to connect circuits or logic units more easily. Any represented signal (determined by design requirements or preferences) may actually include one or more signals that can be transmitted in any direction and can be implemented with any appropriate type of signal scheme.

[0067] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0068] Another aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned method. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist independently and not be incorporated into the electronic device.

[0069] An embodiment of the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements the service resource determination method as described in any one of the above embodiments.

[0070] Although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiment of the application, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0071] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

[0072] The present application can be used in a wide variety of general-purpose or specialized computing system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above.

[0073] Those skilled in the art will readily conceive of other embodiments of the present application after considering the specification and practicing the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of this application and include common knowledge or customary techniques in the art that are not disclosed herein.

[0074] The above content of this application is only a preferred exemplary embodiment of this application and is not intended to limit the implementation scheme of this application. Ordinary technicians in this field can easily make corresponding changes or modifications based on the main ideas and spirit of this application. Therefore, the scope of protection of this application should be the scope of protection required by the claims.

Claims

1. A method for determining service resources, characterized in that: The service resource determination method includes: Obtaining target resource types and capacity parameters to be estimated, where the capacity parameters are used to quantify the user scale and / or concurrent user volume; Determining a target energy reference value that matches the energy parameter to be estimated in a preset benchmark solution list, wherein the preset benchmark solution list includes multiple energy reference values and resource specification configuration information corresponding to each energy reference value; Calculating a proportional relationship between the energy parameter to be estimated and the target energy reference value, and determining resource specification configuration information corresponding to the target energy reference value; Based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, the target resource specification configuration information is determined in a preset configuration sorting list corresponding to the target resource type.

2. The service resource determination method according to claim 1, wherein: After determining the target resource specification configuration information in the preset configuration sort list corresponding to the target resource type, the method further includes: Sending the energy parameters to be estimated and target resource specification configuration information to the terminal and issuing a recheck request; If the terminal feedback indicates that the re-inspection is correct, the preset benchmark solution list is updated according to the energy parameters to be estimated and the target resource specification configuration information.

3. The service resource determination method according to claim 1, wherein: The construction of the preset configuration sorting list includes: Obtain multiple sets of specification configurations for each resource type, including specification type, number of chip cores, memory capacity, and storage space; Determining a specification weight value for each group of specification configurations based on a preset specification coefficient corresponding to the specification type in each group of specification configurations, the number of chip cores, and the memory capacity, wherein the specification weight value is used to characterize the performance of each group of specification configurations; Multiple groups of specification configurations in the same resource type are sorted according to the specification weight values of each group of specification configurations to obtain a configuration sorting list of each resource type.

4. The service resource determination method according to claim 3, characterized in that: The construction of the preset benchmark scheme list includes: Obtain historical service resource configuration information and divide it into at least two energy reference values; Determining a set of specification parameters adapted to each of the energy reference values in a configuration priority list of each resource type according to the historical service resource configuration information; A correlation is established between each of the energy reference values and a set of adapted specification parameters in the configuration priority list of each resource type to obtain a preset benchmark solution list.

5. The service resource determination method according to claim 1, wherein: Determining the target energy reference value that matches the energy parameter to be estimated in the preset benchmark solution list includes: If the quantity parameter to be estimated is equal to any quantity reference value in the preset benchmark plan list, the equal quantity reference value is determined as the target quantity reference value; If the volume parameter to be estimated is greater than the largest volume reference value in the preset benchmark plan list, the largest volume reference value will be determined as the target volume reference value; If the quantity parameter to be estimated is less than the minimum quantity reference value in the preset benchmark plan list, the minimum quantity reference value is determined as the target quantity reference value; If the quantity parameter to be estimated is greater than the smallest quantity reference value in the preset benchmark scheme list and less than the largest quantity reference value in the preset benchmark scheme list, and is not equal to any quantity reference value in the preset benchmark scheme list, the two quantity reference values closest to the quantity parameter to be estimated will be determined as the target quantity reference values.

6. The service resource determination method according to claim 1, wherein: Calculating the proportional relationship between the energy parameter to be estimated and the target energy reference value includes: If the target energy reference value includes an energy reference value, the proportional relationship is calculated by the ratio of the energy parameter to be estimated to the target energy reference value; If the target energy reference value includes two energy reference values, the proportional relationship is calculated by the ratio of the difference between the two energy reference values and the energy parameter to be estimated.

7. The service resource determination method according to any one of claims 1 to 6, characterized in that: Based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value, the target resource specification configuration information is determined in the preset configuration sorting list corresponding to the target resource type: Determine the target specification weight value in the preset configuration sorting list corresponding to the target resource type according to the resource specification configuration information corresponding to the target energy reference value; The estimated weight value is determined based on the proportional relationship and the target specification weight value, and the group of specification configurations with the smallest difference between the specification weight value and the estimated weight value in each group of specification configurations in the preset configuration sorting list corresponding to the target resource type is determined as the target resource specification configuration information.

8. A service resource determination device, characterized in that: The service resource determination device includes: A target information acquisition module is used to obtain the target resource type and the energy parameters to be estimated, wherein the energy parameters are used to quantify the user scale and / or the number of concurrent users; a matching information determination module, configured to determine a target energy reference value that matches the energy parameter to be estimated in a preset benchmark solution list, the preset benchmark solution list including a plurality of energy reference values and resource specification configuration information corresponding to each energy reference value; calculate a proportional relationship between the energy parameter to be estimated and the target energy reference value, and determine the resource specification configuration information corresponding to the target energy reference value; The resource configuration determination module is used to determine the target resource specification configuration information in a preset configuration sorting list corresponding to the target resource type based on the proportional relationship and the resource specification configuration information corresponding to the target energy reference value.

9. An electronic device, characterized in that: It comprises a processor, a memory and a communication bus; the communication bus is used to connect the processor and the memory; the processor is used to execute the computer program stored in the memory to implement the service resource determination method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and the computer program is used to enable a computer to execute the service resource determination method according to any one of claims 1 to 7.

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