Method and device for determining system deployment resource demand, equipment and storage medium

Abstract

The embodiment of the invention discloses a method and device for determining system deployment resource requirements, equipment and a storage medium. The method comprises the steps of obtaining a project document corresponding to a to-be-deployed system; performing complexity analysis on the to-be-deployed system according to the configuration file to obtain function point complexity, code complexity and interface complexity corresponding to the to-be-deployed system; determining the system complexity of the to-be-deployed system according to the function point complexity, the code complexity and the interface complexity; and determining a resource demand for deploying the to-be-deployed system according to the system complexity. Therefore, on one hand, the function point complexity analysis, the code complexity analysis and the interface complexity analysis are carried out on the system to be deployed, so that comprehensive analysis can be carried out on different dimensions of the system to be deployed, and more accurate preliminary evaluation on resources required by system deployment is realized; and on the other hand, the resource demand of the deployment system does not need to be evaluated manually, so that the automation degree of the resources required by the deployment system can be improved, and the efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, apparatus, device and storage medium for determining system deployment resource requirements. Background Art

[0002] In modern information systems, the key to ensuring efficient and stable operation of the system is to reasonably evaluate and allocate system deployment resources. In order for a computer system or software application to operate normally, it is necessary to conduct a demand assessment in advance. System resource requirements refer to the hardware and software conditions that must be met in order for a computer system or software application to operate normally. These requirements usually include but are not limited to the following aspects: processor requirements, memory requirements, storage space requirements, and bandwidth requirements.

[0003] In related technologies, when a system is about to go online, a resource assessment document is usually filled out through manual evaluation based on project experience. This document needs to go through repeated communication and has problems such as strong subjectivity and poor efficiency, which makes it difficult to accurately and efficiently determine system resource requirements. Summary of the invention

[0004] To solve the above technical problems, the embodiments of the present application provide a method, apparatus, device and storage medium for determining system deployment resource requirements, so as to improve the accuracy and efficiency of determining system deployment resource requirements.

[0005] According to one aspect of an embodiment of the present application, a method for determining system deployment resource requirements is provided, including: obtaining a project document corresponding to a system to be deployed; wherein the project document includes a configuration file for designing the system to be deployed; performing a complexity analysis on the system to be deployed based on the configuration file to obtain function point complexity, code complexity and interface complexity corresponding to the system to be deployed; determining the system complexity of the system to be deployed based on the function point complexity, the code complexity and the interface complexity; and determining the resource requirements for deploying the system to be deployed based on the system complexity.

[0006] In some embodiments, the configuration file includes a requirement specification and a design document; the complexity analysis of the system to be deployed based on the configuration file to obtain the function point complexity corresponding to the system to be deployed includes: functional identification of the requirement specification and the design document to obtain the number of function points corresponding to the system to be deployed; matching the function point complexity corresponding to the number of function points from a preset database; wherein the preset database stores the correspondence between the number of function points and the complexity of function points; or, obtaining the complexity coefficient corresponding to each function point, summing all the complexity coefficients based on the number of function points, and obtaining the function point complexity corresponding to the system to be deployed.

[0007] In some embodiments, the configuration file also includes a code repository, in which all codes of the system to be deployed are stored; performing complexity analysis on the system to be deployed according to the configuration file to obtain the code complexity corresponding to the system to be deployed includes: parsing all codes stored in the code repository to obtain code attribute information corresponding to the system to be deployed; wherein the code attribute information includes code volume coefficient, code circle complexity, code class coupling and inheritance depth; obtaining attribute weight coefficients corresponding to the code volume coefficient, the code circle complexity, the code class coupling and the inheritance depth respectively; performing weighted summation processing on the code volume coefficient, the code circle complexity, the code class coupling and the inheritance depth by using the attribute weight coefficient to obtain the code complexity corresponding to the system to be deployed.

[0008] In some embodiments, the configuration file also includes an interface document; performing complexity analysis on the system to be deployed according to the configuration file to obtain the interface complexity corresponding to the system to be deployed, including: identifying the interface document to obtain interface information corresponding to the system to be deployed; wherein the interface information includes the number of interfaces, input parameters of each interface, output parameters of each interface, and whether each interface has a preset function; determining the complexity of each interface according to the interface information; performing weighted averaging processing on the complexity of each interface based on the number of interfaces to obtain the interface complexity corresponding to the system to be deployed.

[0009] In some embodiments, determining the system complexity of the system to be deployed based on the function point complexity, the code complexity and the interface complexity includes: obtaining complexity weight coefficients corresponding to the function point complexity, the code complexity and the interface complexity respectively; performing weighted summation processing on the function point complexity, the code complexity and the interface complexity according to the complexity weight coefficients to obtain the system complexity of the system to be deployed.

[0010] In some embodiments, the resource requirements include computing power storage requirements and network requirements; determining the resource requirements for deploying the system to be deployed based on the system complexity includes: adjusting the preset cluster standard resource unit size based on the system complexity to obtain the computing power storage requirements of the system to be deployed; and identifying the requirement specification to obtain a user activity prediction value, and determining the network requirements of the system to be deployed based on the user activity prediction value.

[0011] In some embodiments, after determining the resource requirements for deploying the system to be deployed according to the system complexity, the method further includes: obtaining a configuration update file corresponding to the system to be deployed; and determining the resource update requirements for deploying the system to be deployed according to the configuration update file.

[0012] In some embodiments, according to an aspect of an embodiment of the present application, a device for determining system deployment resource requirements is provided, the device comprising: an acquisition module, configured to acquire a project document corresponding to the system to be deployed; wherein the project document comprises a configuration file for designing the system to be deployed; an analysis module, configured to perform a complexity analysis on the system to be deployed according to the configuration file, and obtain the function point complexity, code complexity and interface complexity corresponding to the system to be deployed; a first determination module, configured to determine the system complexity of the system to be deployed according to the function point complexity, the code complexity and the interface complexity; a second determination module, configured to determine the resource requirements for deploying the system to be deployed according to the system complexity.

[0013] According to one aspect of an embodiment of the present application, an electronic device is provided, 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 the method for determining system deployment resource requirements as described above.

[0014] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer executes the above-mentioned method for determining system deployment resource requirements.

[0015] In the technical solution provided in the embodiments of the present application, on the one hand, by performing complexity analysis on the system to be deployed according to the configuration file, the functional point complexity, code complexity and interface complexity corresponding to the system to be deployed are obtained, so that complexity analysis and judgment can be performed on different dimensions of the system to be deployed, thereby achieving a more accurate preliminary assessment of the resources required for system deployment; on the other hand, the resource requirements of the deployment system can be automatically determined through complexity, without the need to manually evaluate the resource requirements of the deployment system, which can improve the degree of automation of the resources required for the deployment system, thereby improving efficiency.

[0016] It should be understood that 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 drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0018] Figure 1 is a schematic diagram of an exemplary implementation environment of the present application;

[0019] Figure 2 is a flow chart of determining system deployment resource requirements shown in an exemplary embodiment of the present application;

[0020] Figure 3 yes Figure 2 Step S220 in the illustrated embodiment is a flow chart of performing function point analysis on the system to be deployed according to the configuration file in an exemplary embodiment;

[0021] Figure 4 yes Figure 2 Step S220 in the illustrated embodiment is a flow chart of performing function point analysis on the system to be deployed according to the configuration file in another exemplary embodiment;

[0022] Figure 5 yes Figure 2 Step S220 in the illustrated embodiment is a flow chart of performing code analysis on the system to be deployed according to the configuration file in an exemplary embodiment;

[0023] Figure 6 yes Figure 2 Step S220 in the illustrated embodiment is a flow chart of performing interface analysis on the system to be deployed according to the configuration file in an exemplary embodiment;

[0024] Figure 7 yes Figure 2 Step S230 in the illustrated embodiment is a flow chart of determining the system complexity of the system to be deployed in an exemplary embodiment;

[0025] Figure 8 is a flow chart of a method for determining system deployment resource requirements shown in another exemplary embodiment of the present application;

[0026] Fig. 9 It is a structural diagram of a device for determining system deployment resource requirements according to an exemplary embodiment of the present application;

[0027] Fig.10 It is a schematic diagram of the structure of a computer system of an exemplary electronic device of the present application. DETAILED DESCRIPTION

[0028] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments that are the same as the present application. Instead, they are only examples of devices and methods that are the same as some aspects of the present application as detailed in the attached claims.

[0029] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in the form of an application program, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0030] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0031] It should be noted that the "multiple" mentioned in this application refers to two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship.

[0032] The following is an introduction and explanation of the technical terms and background technologies involved in this application:

[0033] System deployment resource requirements: System deployment resource requirements specifically refer to the hardware and software conditions that must be met in order for a computer system or software application to function properly. These requirements usually include but are not limited to the following:

[0034] Processor requirements: Indicates the minimum processor speed, model, or number of cores required. For example, some high-performance software may require a multi-core processor to support parallel processing tasks.

[0035] Memory requirement: defines the minimum amount of memory required to run the system or application. For memory-intensive applications, this value may be quite high.

[0036] Storage space: refers to the amount of hard disk space required to install and run the system or application. This includes not only the space occupied by the program itself, but also additional storage requirements such as data files and cache.

[0037] Bandwidth requirement: refers to the amount of communication bandwidth required for data transmission when running the system or application.

[0038] In related technologies, as the system is about to go online, a resource assessment document is usually filled out through manual evaluation based on project experience. This document needs to go through repeated communication and has problems such as strong subjectivity and poor efficiency, which makes it difficult to accurately and efficiently determine the system resource requirements.

[0039] Based on this, the present application proposes a method, apparatus, device and storage medium for determining the resource requirements for system deployment. On the one hand, by performing a complexity analysis on the system to be deployed according to the configuration file, the functional point complexity, code complexity and interface complexity corresponding to the system to be deployed are obtained, so that complexity analysis and judgment can be performed on different dimensions of the system to be deployed, thereby achieving a more accurate preliminary assessment of the resources required for system deployment. On the other hand, the resource requirements of the deployment system can be automatically determined through complexity, without the need to manually evaluate the resource requirements of the deployment system, which can improve the degree of automation of the resources required for the deployment system, thereby improving efficiency.

[0040] See also Figure 1 , Figure 1 FIG. 1 is a schematic diagram of an exemplary implementation environment of the present application. Figure 1 As shown, the implementation environment includes a terminal device 110 and a server 120. A wired or wireless communication connection is pre-established between the terminal device 110 and the server 120.

[0041] The terminal device 110 can be an electronic device such as a mobile phone, a computer or a computer, but is not limited to this. The terminal device 110 can generally refer to one of multiple terminals. This embodiment only uses the terminal device 110 as an example. Those skilled in the art can know that the number of the above terminals can be more or less. For example, the above terminal can be only one, or the above terminal can be dozens or hundreds, or more. At this time, the implementation environment of the method for determining the system deployment resource requirements also includes other terminals. The embodiment of the present application does not limit the number and type of terminal devices. The user can import the project document corresponding to the system to be deployed through the display interface of the terminal device 110, and then send the project document corresponding to the system to be deployed to the server 120 through the terminal device 110. The server 120 performs a complexity analysis on the system to be deployed according to the configuration file, and obtains the function point complexity, code complexity and interface complexity corresponding to the system to be deployed; determines the system complexity of the system to be deployed according to the function point complexity, code complexity and interface complexity; determines the resource requirements for deploying the system to be deployed according to the system complexity.

[0042] Server 120 can be an independent physical server or a server cluster or distributed system composed of multiple physical servers. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), as well as big data and artificial intelligence platforms.

[0043] See also Figure 2 , Figure 2 is a flowchart of determining system deployment resource requirements shown in an exemplary embodiment of the present application. The method can be applied to Figure 1 The implementation environment shown is specifically executed by the server 120 in the implementation environment. It should be understood that the method can also be applied to other exemplary implementation environments and be specifically executed by devices in other implementation environments. This embodiment does not limit the implementation environment to which the method is applicable.

[0044] The following describes in detail the method for determining system deployment resource requirements proposed in an embodiment of the present application, taking the server as the specific execution entity.

[0045] like Figure 2 As shown, in an exemplary embodiment, the method for determining system deployment resource requirements includes at least steps S210 to S240, which are described in detail as follows:

[0046] Step S210: Obtain the project document corresponding to the system to be deployed.

[0047] Among them, the project documentation includes configuration files used to design the system to be deployed.

[0048] In an embodiment of the present application, a user sends a configuration file to a server through a terminal device. The configuration file includes a requirements specification, a design document, a code repository, and an interface document. Among them, the requirements specification includes functional requirements information and activity information. In some embodiments, the functional requirements information includes a requirements overview and a requirements list. The requirements overview describes the overall requirements of the system to be deployed. Each requirement corresponds to a functional point. The requirements list includes a specific description of each requirement, page requirements, and business rules. The design document includes the business process design, front-end and back-end interaction design, and page design corresponding to each requirement. The interface document includes interface information for front-end and back-end interaction; wherein the interface information includes the number of interfaces, the input parameters of each interface, the output parameters of each interface, and whether each interface has a preset function. The code repository is used to store code information of the system to be deployed; wherein the code information includes all codes involved in the system to be deployed, code modification records, and the number of lines of code.

[0049] Step S220, performing complexity analysis on the system to be deployed according to the configuration file, and obtaining the function point complexity, code complexity and interface complexity corresponding to the system to be deployed.

[0050] It is understandable that the configuration file in the embodiment of the present application includes a requirement specification, a design document, a code repository, and an interface document. By performing a complexity analysis on the system to be deployed through the configuration file to obtain the corresponding function point complexity, code complexity, and interface complexity, it is possible to implement complexity analysis in multiple dimensions including function point analysis, code analysis, and interface analysis, thereby being able to more accurately determine the resource requirements for deploying the system to be deployed.

[0051] In some embodiments, function point analysis is used to evaluate the scale of software. It measures the size of software based on its functional characteristics, combined with the user functions provided by the software, rather than specific implementation details. Through function point analysis, the scale of the system can be understood in a more intuitive way. Code analysis is used to evaluate the complexity of code from the dimensions of time complexity and space complexity, cyclomatic complexity, code volume, etc. from the front-end and back-end codes, as one of the inputs for resource requirement assessment of the deployment system. Interface analysis is used to analyze the complexity of the front-end and back-end systems and system interaction interfaces, including the number and type of interfaces, the number of interface input and output parameters, exception handling logic, etc.

[0052] Combination Figure 3 As shown, Figure 3 yes Figure 2 Step S220 in the illustrated embodiment is a flowchart of performing function point analysis on the system to be deployed according to the configuration file in an exemplary embodiment, which at least includes steps S310 to S320, which are described in detail as follows:

[0053] Step S310, perform function identification on the requirement specification and the design document to obtain the number of function points corresponding to the system to be deployed.

[0054] It can be understood that since the requirements specification includes functional requirement information, the functional requirement information includes a requirements overview and a requirements list. The requirements overview describes the overall requirements of the system to be deployed. Each requirement corresponds to a functional point. The requirements list includes a specific description of each requirement, page requirements and business rules, etc. At the same time, the design document includes the business process design, front-end and back-end interaction design and page design corresponding to each requirement. One requirement corresponds to one functional point. By performing functional identification on the requirements specification and design documents, the number of functional points corresponding to the system to be deployed can be accurately determined.

[0055] In some embodiments, a recognition model is pre-set in the server. The recognition model is a deep learning model for semantic recognition. By inputting the requirement specification and design document into the recognition model for function recognition, the number of function points corresponding to the system to be deployed can be accurately determined.

[0056] Step S320: Match the function point complexity corresponding to the number of function points from a preset database.

[0057] The corresponding relationship between the number of function points and the complexity of the function points is stored in the preset database.

[0058] In the embodiment of the present application, by directly setting up a preset database, testing is performed in advance, and the correspondence between the number of different function points and the complexity of different function points is collected, and then stored in the preset database in advance. This facilitates subsequent direct matching in the database, improves the speed of determining the complexity of the function points, and can improve the efficiency of determining resource requirements to a certain extent.

[0059] Combination Figure 4 As shown, Figure 4 yes Figure 2 Step S220 in the illustrated embodiment is a flowchart of performing function point analysis on the system to be deployed according to the configuration file in another exemplary embodiment, which at least includes steps S410 to S420, which are described in detail as follows:

[0060] Step S410, performing functional identification on the requirement specification and the design document to obtain the number of functional points corresponding to the system to be deployed.

[0061] Step S420, obtaining the complexity coefficient corresponding to each function point, summing up all the complexity coefficients based on the number of function points, and obtaining the complexity of the function points corresponding to the system to be deployed.

[0062] It is understandable that the specific description, page requirements and business rules of each functional point in the embodiments of the present application may be different, and the business process design, front-end and back-end interaction design and page design corresponding to each requirement are also different. Therefore, the complexity between different functional points is different. The complexity coefficient corresponding to each functional point can be obtained and summed up. In this way, the complexity of the functional points that can be used to characterize all functional points can be obtained, thereby improving the accuracy of determining resource requirements.

[0063] In some embodiments, all complexity coefficients are summed based on the number of function points to obtain the complexity of the function points corresponding to the system to be deployed, including: calculating Obtain the function point complexity corresponding to the system to be deployed; where η func is the complexity of the function points of the system to be deployed, η iis the complexity coefficient corresponding to the i-th function point.

[0064] For example, by identifying the functions of the requirements specification and design documents, the number of function points corresponding to the system to be deployed is 160, and the complexity coefficient corresponding to each function point is matched from the preset database. The corresponding function point complexity is:

[0065] It should be noted that the relevant step contents in the embodiments of the present application are consistent with the corresponding step contents recorded in the aforementioned embodiments. Therefore, for the detailed description of these steps, please refer to the records in the aforementioned embodiments, and the embodiments of the present application will not be repeated here.

[0066] Combination Figure 5 As shown, Figure 5 yes Figure 2 Step S220 in the illustrated embodiment is a flowchart of performing code analysis on the system to be deployed according to the configuration file in an exemplary embodiment, which at least includes steps S510 to S530, which are described in detail as follows:

[0067] Step S510: parse all codes stored in the code repository to obtain code attribute information corresponding to the system to be deployed, wherein the code attribute information includes code volume coefficient, code cyclomatic complexity, code class coupling degree and inheritance depth.

[0068] It is understandable that since code complexity directly affects the resources required for system operation, complexity analysis can more accurately assess the resource consumption of the system under different loads, thereby more accurately determining resource requirements and avoiding excessive or insufficient resources.

[0069] In the embodiments of the present application, the code volume coefficient can reflect the size of the code. Larger code usually means more functions, more complex logic and higher maintenance difficulty. Code cyclomatic complexity is used to measure the structural complexity of the code. The higher the code class coupling, the more difficult it is to reuse and maintain the design. Good software design requirements require a lower degree of coupling. The inheritance depth is used to indicate the number of class definitions that extend to the root of the class hierarchy. The deeper the hierarchy, the more difficult it is to understand where specific methods and fields are defined or redefined. Therefore, the code complexity corresponding to the system to be deployed can be accurately measured by the attributes of multiple dimensions in the code attribute information.

[0070] In some embodiments, the code volume coefficient can be obtained by calculating: Get the code volume factor; where Prop LOC is the code volume factor, LOC code The number of lines of code for all codes stored in the code repository, LOCstandard is a preset standard number of code lines. The number of code lines can be obtained by identifying all the codes in the code repository.

[0071] For example, if the total number of lines of code in the code repository is 250 and the standard number of lines of code is 100, then by calculating The code volume factor is then 2.5.

[0072] In some embodiments, the code cyclomatic complexity can be obtained by parsing all codes stored in the code repository, generating a control flow graph corresponding to the system to be deployed, and calculating the number of nodes and edges in the control flow graph using a preset McCabe metric to obtain the code cyclomatic complexity.

[0073] For example, the number of nodes and edges in the control flow graph is calculated by the preset McCabe metric to obtain the code cyclomatic complexity, including: G =e-n+2 to obtain the code cyclomatic complexity; where V G is the cyclomatic complexity of the code, e is the number of edges in the control flow graph, and n is the number of nodes in the control flow graph.

[0074] In some embodiments, the code class coupling degree may be obtained by parsing all codes in the code repository through a preset measurement component to obtain the code class coupling degree. For example, the preset measurement component may be a component such as Visual Studio Code or IntelliJ IDEA.

[0075] Step S520, obtaining attribute weight coefficients corresponding to the code volume coefficient, the code cyclomatic complexity, the code class coupling degree and the inheritance depth respectively.

[0076] In the embodiment of the present application, by setting the attribute weight coefficients corresponding to different code attribute information, the different code attribute information can be balanced to ensure that each different attribute receives appropriate attention, thereby improving the accuracy of code complexity.

[0077] In some embodiments, obtaining attribute weight coefficients corresponding to code volume coefficient, code cyclomatic complexity, code class coupling degree and inheritance depth respectively includes: matching attribute weight coefficients corresponding to code volume coefficient, code cyclomatic complexity, code class coupling degree and inheritance depth respectively from a preset database. The preset database stores the correspondence between different code attribute information and attribute weight coefficients.

[0078] For example, the attribute weight coefficients corresponding to different code attribute information can all be 1, which can ensure that different code attribute information receives equal attention, achieve a balance between different attributes, and make the determination of code complexity more accurate. In addition, if developers pay more attention to one or more code attribute information before allocating resources, they can set the weight coefficient of the code attribute they focus on to be larger, and the weight coefficients of other code attributes can be set to be smaller. In this way, by dynamically setting the attribute weight coefficients, the final determination of resource requirements can be more in line with user needs.

[0079] Step S530 , performing weighted sum processing on the code volume coefficient, the code cyclomatic complexity, the code class coupling degree and the inheritance depth through the attribute weight coefficient, so as to obtain the code complexity corresponding to the system to be deployed.

[0080] In some embodiments, the Obtain the code complexity corresponding to the system to be deployed; where η code is the code complexity of the system to be deployed, Prop LOC is the code volume factor, V G is the code cyclomatic complexity, μ CBO is the code class coupling degree, μ DIT is the inheritance depth, 4.5 is the standard class coupling degree, and 2 is the standard inheritance depth.

[0081] For example, the code volume coefficient is 2.5, the code cyclomatic complexity is 3, the code class coupling is 6, the inheritance depth is 4, and the attribute weight coefficients corresponding to the code attribute information are all 1. By calculating The code complexity of the system to be deployed is 9.

[0082] Combination Figure 6 As shown, Figure 6 yes Figure 2 Step S220 in the illustrated embodiment is a flowchart of performing interface analysis on the system to be deployed according to the configuration file in an exemplary embodiment, which at least includes steps S610 to S630, which are described in detail as follows:

[0083] Step S610: Identify the interface document to obtain interface information corresponding to the system to be deployed.

[0084] The interface information includes the number of interfaces, the input parameters of each interface, the output parameters of each interface, and whether each interface has a preset function. The preset functions include paging function, indexing function, etc. In the embodiment of the present application, if each interface has a paging function, the interface complexity of a single interface is +1; if each interface has an indexing function, the interface complexity of a single interface is +1.

[0085] Step S620: Determine the complexity of each interface according to the interface information.

[0086] In some embodiments, the number of interfaces, the input parameters of each interface, the output parameters of each interface, and whether each interface has a preset function are calculated by a preset algorithm to obtain the complexity of each interface, including: Get the complexity of each interface; where η m is the complexity of the mth interface, Param req Param is the interface input parameter. resp It is the interface output parameter. if(page,1,0) is used to indicate that if the mth interface has paging function, the complexity is +1. if(index,0,1) is used to indicate that if the mth interface does not have index function, the complexity is +1.

[0087] Step S630: Perform weighted average processing on the complexity of each interface based on the number of interfaces to obtain the interface complexity corresponding to the system to be deployed.

[0088] It can be understood that by performing weighted averaging processing on the complexity of each interface, when processing the complexity of different interfaces, the weighted averaging can better balance the relationship between these different interfaces.

[0089] In some embodiments, weighted average processing is performed on the complexity of each interface based on the number of interfaces to obtain the interface complexity corresponding to the system to be deployed, including: calculating Obtain the interface complexity corresponding to the system to be deployed; where η API is the interface complexity corresponding to the system to be deployed, φ is the performance requirement of the system to be deployed, η m is the complexity of the mth interface.

[0090] Step S230, determining the system complexity of the system to be deployed according to the function point complexity, code complexity and interface complexity.

[0091] It can be understood that in the embodiments of the present application, through the three system complexities of function point analysis, code complexity analysis, and interface information analysis, the complexity analysis and judgment of each dimension of the system are performed, which can achieve a preliminary assessment of the resources required for system deployment, and resource allocation based on the system complexity can ensure that each system component obtains appropriate computing and storage resources, which avoids waste caused by excessive resource allocation and performance bottlenecks caused by insufficient resources.

[0092] Combination Figure 7 As shown, Figure 7 yes Figure 2Step S230 in the illustrated embodiment is a flowchart for determining the system complexity of the system to be deployed in an exemplary embodiment, which includes at least steps S710 to S720, which are described in detail as follows:

[0093] Step S710, obtaining complexity weight coefficients corresponding to function point complexity, code complexity and interface complexity respectively.

[0094] In the embodiment of the present application, by setting weight coefficients corresponding to different complexities, different types of complexity can be balanced to ensure that each different type of complexity receives appropriate attention, thereby improving the accuracy of system complexity.

[0095] In some embodiments, obtaining the complexity weight coefficients corresponding to the function point complexity, code complexity, and interface complexity, respectively, includes: matching the complexity weight coefficients corresponding to the function point complexity, code complexity, and interface complexity, respectively, from a preset database. The preset database stores the correspondence between the function point complexity, code complexity, and interface complexity, respectively, and the complexity weight coefficients.

[0096] Step S720, performing weighted summation processing on the function point complexity, code complexity and interface complexity according to the complexity weight coefficient to obtain the system complexity of the system to be deployed.

[0097] In an embodiment of the present application, by performing weighted summation processing on the function point complexity, code complexity and interface complexity through the complexity weight coefficient, the impact of different complexities on the overall complexity of the system can be comprehensively considered, thereby making the system complexity of the system to be deployed more accurate.

[0098] In some embodiments, the function point complexity, code complexity and interface complexity are weighted and summed according to the complexity weight coefficient to obtain the system complexity of the system to be deployed, including: calculating η system =λ1η func +λ2η code +λ3η API Obtain the system complexity of the system to be deployed; where η system is the system complexity of the system to be deployed, λ1,λ2,λ3 are the complexity weight coefficients corresponding to the function point complexity, code complexity and interface complexity respectively, η func is the complexity of the function points of the system to be deployed, η code is the code complexity corresponding to the system to be deployed, η API The interface complexity corresponding to the system to be deployed.

[0099] Step S240: determining resource requirements for deploying the system to be deployed according to the system complexity.

[0100] It should be understood that the resource requirements in the embodiments of the present application include computing power storage requirements and network requirements; among which, computing power storage requirements include the number of CPU cores, CPU memory size and data storage space; network requirements include bandwidth.

[0101] In the embodiment of the present application, the requirement specification includes functional requirement information and activity information; wherein the activity information includes user activity prediction values, such as average user activity and peak user activity. In some embodiments, average user activity is used to characterize user activity in normal time; peak user activity is used to characterize user activity in special scenarios.

[0102] In some embodiments, resource requirements for deploying the system to be deployed are determined based on the system complexity, including: adjusting the preset cluster standard resource unit size based on the system complexity to obtain the computing power and storage requirements of the system to be deployed; and identifying the requirement specification to obtain the user activity prediction value, and determining the network requirements of the system to be deployed based on the user activity prediction value.

[0103] Exemplarily, the preset cluster standard resource unit size is adjusted according to the system complexity to obtain the computing power storage demand requirements of the system to be deployed, including: Obtain the computing power and storage requirements of the system to be deployed; Resource CPU is the computing power and storage requirement of the system to be deployed, η system is the system complexity of the system to be deployed, It is the preset cluster standard resource unit size, where 4C is used to represent the cluster standard CPU core number of 4, 16G is used to represent the cluster standard CPU memory size, and 500M is the cluster standard data storage space.

[0104] For example, the system complexity of the system to be deployed is η system =λ1η func +λ2η code +λ3η API =14, the default cluster standard resource unit size is Then by calculating The computing power and storage requirements are 56 CPU cores, 224G CPU memory, and 7T data storage space.

[0105] Exemplarily, determining the network requirements of the system to be deployed according to the predicted user activity value includes: calculating Obtain the network requirements of the system to be deployed; Resource Band is the network requirement, that is, the bandwidth size of the system to be deployed, User ac is the average user activity, Userpc is the peak user activity, User standard It is the preset standard user activity and 10M is the standard bandwidth.

[0106] For example, identify the requirements specification and obtain the user activity prediction value including the average user activity User ac =200, peak user activity User pc =800, the preset standard user activity User standard =100, then by calculating The network requirement of the system to be deployed is 100M, that is, the bandwidth required by the system to be deployed is 100M.

[0107] See also Figure 8 , Figure 8 is a flowchart of a method for determining system deployment resource requirements shown in another exemplary embodiment of the present application. Figure 8 As shown, in an exemplary embodiment, after determining the resource requirements for deploying the system to be deployed, at least steps S810 to S820 are included, which are described in detail as follows:

[0108] Step S810: Obtain the configuration update file corresponding to the system to be deployed.

[0109] It is understandable that by obtaining the corresponding configuration update file when the system is updated, it is convenient to recalculate the resource requirements when the updated system is deployed, so that the updated system to be deployed can obtain more accurate resource requirements when deployed.

[0110] Step S820: Determine resource update requirements for deploying the system to be deployed according to the configuration update file.

[0111] It is understandable that the configuration update file includes information such as the newly added functional points of the updated system to be deployed, the predicted user activity value of the updated system to be deployed, the number of lines of code of the updated system to be deployed, and the newly added interfaces of the updated system to be deployed. After the system is updated, the resources required to deploy the system need to be recalculated so that the calculated resource requirements can meet the updated system to be deployed. At the same time, it is possible to combine historical data and real-time monitoring data to dynamically evaluate and optimize the system resource requirements.

[0112] In some embodiments, resource update requirements for deploying a system to be deployed are determined based on a configuration update file, including: obtaining a functional complexity difference, a code complexity difference, and an interface complexity difference; summing the functional complexity difference, the code complexity difference, and the interface complexity difference to obtain a system complexity difference; adjusting a preset cluster standard resource unit size based on the system complexity difference to obtain a computing power storage requirement difference for an updated system to be deployed; and determining a network requirement for the updated system to be deployed based on a predicted user activity value.

[0113] In some embodiments, obtaining the functional complexity difference includes: calculating Get the functional complexity difference; where η funcDiff is the functional complexity difference, η func is the complexity of the function points of the system to be deployed before the update, i is the number of function points before the update, q is the number of newly added function points, then i+q is the number of function points after the update, η i is the complexity coefficient corresponding to the i-th function point.

[0114] For example, the number of function points before the update is i=160, the number of newly added function points is q=25, and the function point complexity of the system to be deployed before the update is 2.3. Then, by calculating

[0115] In some embodiments, obtaining the code complexity difference includes: calculating η codeDiff =η' code -η code Obtain the code complexity difference; where η codeDiff is the code complexity difference, η' code is the code complexity corresponding to the updated system to be deployed, η code is the code complexity of the system to be deployed before the update. The calculation method of the code complexity of the system to be deployed after the update is the same as that before the update. It only needs to update the code volume coefficient, code cyclomatic complexity, code class coupling and inheritance depth in the original formula.

[0116] In some embodiments, obtaining the interface complexity difference includes: calculating η APIDiff =η' API -η API Get the interface complexity difference; where η APIDiff is the interface complexity difference, η' API is the interface complexity corresponding to the updated system to be deployed, η APIis the interface complexity corresponding to the system to be deployed before the update. The calculation method of the interface complexity corresponding to the system to be deployed after the update is the same as that before the update, and only the number of interfaces in the original formula needs to be updated.

[0117] In some embodiments, the function complexity difference, the code complexity difference, and the interface complexity difference are summed to obtain the system complexity difference, including: calculating η systemDiff =η funcDiff +η codeDiff +η APIDiff Obtain the system complexity difference; where η systemDiff is the system complexity difference, η funcDiff is the functional complexity difference, η codeDiff is the code complexity difference, η APIDiff is the interface complexity difference.

[0118] In some embodiments, the preset cluster standard resource unit size is adjusted according to the system complexity difference to obtain the updated computing power storage requirement difference of the system to be deployed, including: calculating Obtain the updated computing power and storage requirement difference of the system to be deployed; Resource CPUDiff is the difference in computing power and storage requirements of the updated system to be deployed, η systemDiff is the system complexity difference, It is the preset cluster standard resource unit size, where 4C is used to represent the cluster standard CPU core number of 4, 16G is used to represent the cluster standard CPU memory size, and 500M is the cluster standard data storage space.

[0119] For example, the system complexity difference η systemDiff =0.75, then the difference in computing power and storage requirements of the updated system to be deployed is

[0120] That is, after the iterative update of the system to be deployed, the number of CPU cores required to be added is 3, the size of the CPU memory required to be added is 16G, and the data storage space required to be added is 375M.

[0121] In some embodiments, after determining the resource update requirements for deploying the system to be deployed according to the configuration update file, the process further includes: obtaining resource usage rate, and when the resource usage rate is lower than a preset threshold, not updating the resource requirements for the updated system to be deployed.

[0122] For example, after the iterative update of the system to be deployed, the number of CPU cores required to be added is 3, the CPU memory size required is 16G, and the data storage space required is 375M; if the data storage utilization rate of the system to be deployed is 35%, which is lower than the preset data storage threshold of 80%, the data storage space will not be updated.

[0123] In some embodiments, determining the updated network requirements of the to-be-deployed system according to the user activity prediction value includes: calculating Obtain the updated network requirements of the system to be deployed; Resource Band ' is the updated network requirements of the system to be deployed, User ac ' is the updated average user activity, User pc ' is the updated peak user activity, User standard It is the preset standard user activity and 10M is the standard bandwidth.

[0124] For example, by calculating that the network requirement of the updated system to be deployed is 110M, the bandwidth required by the updated system to be deployed is 110M.

[0125] It should be noted that the relevant step contents in the embodiments of the present application are consistent with the corresponding step contents recorded in the aforementioned embodiments. Therefore, for the detailed description of these steps, please refer to the records in the aforementioned embodiments, and the embodiments of the present application will not be repeated here.

[0126] Combination Fig. 9 As shown, Fig. 9 An exemplary embodiment of the present application shows a device for determining resource requirements for system deployment, and the device includes an acquisition module 910, an analysis module 920, a first determination module 930, and a second determination module 940. The acquisition module 910 is configured to acquire a project document corresponding to the system to be deployed; wherein the project document includes a configuration file for designing the system to be deployed; the analysis module 920 is configured to perform a complexity analysis on the system to be deployed according to the configuration file, and obtain the function point complexity, code complexity, and interface complexity corresponding to the system to be deployed; the first determination module 930 is configured to determine the system complexity of the system to be deployed according to the function point complexity, code complexity, and interface complexity; the second determination module 940 is configured to determine the resource requirements for deploying the system to be deployed according to the system complexity.

[0127] The device for determining system deployment resource requirements in the embodiment of the present application can intelligently analyze the project functional logic, the number of interfaces, and the required memory and CPU resources in combination with the code logic complexity assessment, thereby realizing ontology extraction and data fuzzy matching, and realizing highly accurate and efficient system deployment resource analysis; at the same time, the device can support flexible deployment and independent deployment without affecting the business system environment or performance.

[0128] In some embodiments, the configuration file includes a requirement specification and a design document; the analysis module 920 is configured to perform a complexity analysis on the system to be deployed according to the configuration file in the following manner to obtain the function point complexity corresponding to the system to be deployed, including: performing function identification on the requirement specification and the design document to obtain the number of function points corresponding to the system to be deployed; matching the function point complexity corresponding to the number of function points from a preset database; wherein the preset database stores the correspondence between the number of function points and the complexity of function points; or, obtaining the complexity coefficient corresponding to each function point, summing all the complexity coefficients based on the number of function points, and obtaining the function point complexity corresponding to the system to be deployed.

[0129] In some embodiments, the configuration file also includes a code repository, in which all codes of the system to be deployed are stored; the analysis module 920 is configured to perform complexity analysis on the system to be deployed according to the configuration file in the following manner to obtain the code complexity corresponding to the system to be deployed, including: parsing all codes stored in the code repository to obtain code attribute information corresponding to the system to be deployed; wherein the code attribute information includes code volume coefficient, code circle complexity, code class coupling and inheritance depth; obtaining attribute weight coefficients corresponding to the code volume coefficient, code circle complexity, code class coupling and inheritance depth respectively; performing weighted summation processing on the code volume coefficient, code circle complexity, code class coupling and inheritance depth through the attribute weight coefficient to obtain the code complexity corresponding to the system to be deployed.

[0130] In some embodiments, the configuration file also includes an interface document; the analysis module 920 is configured to perform a complexity analysis on the system to be deployed according to the configuration file to obtain the interface complexity corresponding to the system to be deployed, including: identifying the interface document to obtain interface information corresponding to the system to be deployed; wherein the interface information includes the number of interfaces, the input parameters of each interface, the output parameters of each interface, and whether each interface has a preset function; determining the complexity of each interface according to the interface information; performing weighted averaging processing on the complexity of each interface based on the number of interfaces to obtain the interface complexity corresponding to the system to be deployed.

[0131] In some embodiments, the first determination module 930 is configured to determine the system complexity of the system to be deployed based on the function point complexity, code complexity and interface complexity in the following manner, including: obtaining complexity weight coefficients corresponding to the function point complexity, code complexity and interface complexity respectively; performing weighted summation processing on the function point complexity, code complexity and interface complexity according to the complexity weight coefficients to obtain the system complexity of the system to be deployed.

[0132] In some embodiments, resource requirements include computing power storage requirements and network requirements; the second determination module 940 is configured to determine the resource requirements for deploying the system to be deployed according to the system complexity in the following manner, including: adjusting the preset cluster standard resource unit size according to the system complexity to obtain the computing power storage requirements of the system to be deployed; and identifying the requirement specification to obtain the user activity prediction value, and determining the network requirements of the system to be deployed according to the user activity prediction value.

[0133] In some embodiments, the device for determining system deployment resource requirements also includes an update module, which is configured to obtain a configuration update file corresponding to the system to be deployed after determining the resource requirements for deploying the system to be deployed according to the system complexity; and determine the resource update requirements for deploying the system to be deployed according to the configuration update file.

[0134] An embodiment of the present disclosure further provides an electronic device, including: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the above method.

[0135] Fig.10 The structure diagram of the computer system suitable for implementing the electronic device of the embodiment of the present application is shown. It should be noted that: Fig.10 The computer system 1000 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.

[0136] like Fig.10As shown, the computer system 1000 includes a central processing unit (CPU) 1001, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1002 or the program loaded from the storage part 1008 to the random access memory (RAM) 1003, such as executing the method in the above embodiment. In the random access memory 1003, various programs and data required for system operation are also stored. The central processing unit 1001, the read-only memory 1002 and the random access memory 1003 are connected to each other through a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0137] The following components are connected to the input / output interface 1005: an input section 1006 including a keyboard, a mouse, etc.; an output section 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the input / output interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed so that a computer program read therefrom is installed into the storage section 1008 as needed.

[0138] 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 through a communication section 1109, and / or installed from a removable medium 1011. When the computer program is executed by a central processing unit (CPU) 1001, various functions defined in the system of the present application are executed.

[0139] The embodiment of the present disclosure also 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 above-mentioned method for determining system deployment resource requirements.

[0140] It should be noted that 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 may include a data signal propagated in a 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, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. A computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0141] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order 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 a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0142] 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. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0143] The present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the method for determining the system deployment resource requirements as described above is implemented. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.

[0144] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. A person skilled in the art can easily make corresponding changes or modifications based on the main concept and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.

Claims

1. A method for determining system deployment resource requirements, characterized in that: include: Obtaining a project document corresponding to the system to be deployed; wherein the project document includes a configuration file for designing the system to be deployed; Performing complexity analysis on the system to be deployed according to the configuration file to obtain the function point complexity, code complexity and interface complexity corresponding to the system to be deployed; Determining the system complexity of the system to be deployed according to the function point complexity, the code complexity and the interface complexity; Determine resource requirements for deploying the system to be deployed according to the system complexity.

2. The method according to claim 1, characterized in that The configuration file includes a requirement specification and a design document; and performing complexity analysis on the system to be deployed according to the configuration file to obtain the complexity of function points corresponding to the system to be deployed includes: Performing functional identification on the requirement specification and the design document to obtain the number of functional points corresponding to the system to be deployed; Match the function point complexity corresponding to the number of function points from a preset database; wherein the preset database stores the corresponding relationship between the number of function points and the function point complexity; or, obtain the complexity coefficient corresponding to each function point, sum all the complexity coefficients based on the number of function points, and obtain the function point complexity corresponding to the system to be deployed.

3. The method according to claim 1, characterized in that The configuration file also includes a code repository, in which all codes of the system to be deployed are stored; The performing complexity analysis on the system to be deployed according to the configuration file to obtain the code complexity corresponding to the system to be deployed includes: Parsing all codes stored in the code repository to obtain code attribute information corresponding to the system to be deployed; wherein the code attribute information includes code volume coefficient, code cyclomatic complexity, code class coupling degree and inheritance depth; Obtaining attribute weight coefficients corresponding to the code volume coefficient, the code cyclomatic complexity, the code class coupling degree, and the inheritance depth respectively; The code volume coefficient, the code cyclomatic complexity, the code class coupling degree and the inheritance depth are weighted and summed up by the attribute weight coefficient to obtain the code complexity corresponding to the system to be deployed.

4. The method according to claim 1, characterized in that The configuration file also includes an interface document; and performing complexity analysis on the system to be deployed according to the configuration file to obtain the interface complexity corresponding to the system to be deployed includes: Identify the interface document to obtain interface information corresponding to the system to be deployed; wherein the interface information includes the number of interfaces, the input parameter of each interface, the output parameter of each interface, and whether each interface has a preset function; Determining the complexity of each interface according to the interface information; A weighted average processing is performed on the complexity of each interface based on the number of interfaces to obtain the interface complexity corresponding to the system to be deployed.

5. The method according to claim 1, characterized in that The determining the system complexity of the system to be deployed according to the function point complexity, the code complexity and the interface complexity includes: Obtaining complexity weight coefficients corresponding to the function point complexity, the code complexity, and the interface complexity respectively; The function point complexity, the code complexity and the interface complexity are weighted and summed according to the complexity weight coefficient to obtain the system complexity of the system to be deployed.

6. The method according to claim 2, characterized in that The resource requirements include computing power storage requirements and network requirements; the determining the resource requirements for deploying the system to be deployed according to the system complexity includes: Adjusting the preset cluster standard resource unit size according to the system complexity to obtain the computing power and storage requirements of the system to be deployed; and The requirement specification is identified to obtain a user activity prediction value, and the network requirement of the system to be deployed is determined according to the user activity prediction value.

7. The method according to claim 1, characterized in that After determining the resource requirements for deploying the system to be deployed according to the system complexity, the method further includes: Obtaining a configuration update file corresponding to the system to be deployed; Determine resource update requirements for deploying the system to be deployed according to the configuration update file.

8. A device for determining system deployment resource requirements, characterized in that: The device comprises: An acquisition module is configured to acquire a project document corresponding to the system to be deployed; wherein the project document includes a configuration file for designing the system to be deployed; An analysis module is configured to perform complexity analysis on the system to be deployed according to the configuration file to obtain the function point complexity, code complexity and interface complexity corresponding to the system to be deployed; A first determination module is configured to determine the system complexity of the system to be deployed according to the function point complexity, the code complexity and the interface complexity; The second determination module is configured to determine the resource requirement for deploying the system to be deployed according to the system complexity.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the method for determining system deployment resource requirements as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the method for determining system deployment resource requirements according to any one of claims 1 to 7.

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