A deployment method, system, device, and storage medium for on-demand system deployment

Abstract

This invention relates to the field of computer technology and discloses a deployment method, system, device, and storage medium for on-demand system deployment. The method includes: determining the relevant values ​​of each undeployed business platform within the system using a pre-trained association evaluation model; obtaining deployment condition values ​​input by the user; and, based on the deployment condition values ​​and the relevant values ​​of each undeployed business platform relative to deployed business platforms in terms of their call relationships, selecting business platforms that meet the deployment condition values ​​from among the undeployed business platforms as platforms to be deployed, and deploying the platforms to be deployed into the system. The deployment method disclosed in this application solves the technical problems of inflexible deployment and inability to deploy according to user needs, achieving on-demand deployment, enabling the association of data from other business domains, improving the richness of displayed data content, enhancing the user experience of multi-business platform deployment, and having simple control conditions, making it easy and convenient to use and improving the user experience.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a deployment method, system, device and storage medium for on-demand system deployment. Background Technology

[0002] In the field of system development technology, the creation and deployment of the system deployment environment (also known as the application runtime environment) is the foundation for the debugging and testing of application functions, and can lay a solid foundation for the subsequent full-process testing and production launch of the application system.

[0003] In existing technologies, when deploying multiple business platforms in a system, users typically select each platform sequentially for deployment. However, only a single business platform can be deployed at a time, making it impossible to deploy multiple business platforms in a coordinated manner. This deployment method lacks flexibility, results in a limited range of data presented to users, and fails to deploy multi-dimensional data based on user needs. Summary of the Invention

[0004] The purpose of this invention is to provide at least one deployment method, system, device, and storage medium for on-demand system deployment, which can at least solve the technical problems of inflexible deployment and inability to deploy according to user needs, and can at least achieve on-demand deployment, be able to associate data from other business areas, improve the richness of displayed data content, enhance the user's experience of multi-business platform deployment, and have simple control conditions, making it simple and convenient to use, thereby improving the user experience.

[0005] To address the aforementioned technical problems, at least one embodiment of this application provides a deployment method for on-demand system deployment, comprising:

[0006] A pre-trained correlation evaluation model is used to determine the correlation values ​​of each undeployed business platform relative to the deployed business platform in terms of call relationships within the system;

[0007] Obtain the deployment condition value input by the user; the deployment condition value is used to describe the degree of correlation between the deployed business platform and the non-deployed business platform being called in terms of the calling relationship;

[0008] Based on the deployment condition values ​​and the relevant values ​​of each undeployed business platform relative to the deployed business platform in terms of the call relationship, business platforms that meet the deployment condition values ​​are selected from the undeployed business platforms as platforms to be deployed, and the platforms to be deployed are deployed to the system.

[0009] At least one embodiment of this application also provides a deployment system for on-demand system deployment, comprising:

[0010] The correlation value calculation unit is used to determine the correlation value of each undeployed business platform relative to the deployed business platform in terms of call relationship using a pre-trained correlation evaluation model;

[0011] The data acquisition unit is used to acquire deployment condition values ​​input by the user; the deployment condition values ​​are used to describe the degree of correlation between the deployed business platform and the non-deployed business platform being called in terms of the calling relationship;

[0012] The business platform association filtering unit is used to filter out business platforms that meet the deployment condition values ​​as platforms to be deployed from among the undeployed business platforms based on the deployment condition values ​​and the relevant values ​​of each undeployed business platform relative to the deployed business platform in terms of the call relationship.

[0013] The deployment unit is used to deploy the platform to be deployed into the system.

[0014] At least one embodiment of this application also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the deployment method described above.

[0015] At least one embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the deployment method described above.

[0016] The system, system, device, and storage medium provided in the embodiments of this application provide an on-demand deployment method, system, device, and storage medium that can select business platforms that meet the deployment conditions from various undeployed business platforms as platforms to be deployed based on the deployment condition values ​​input by the user and the relevant values ​​determined by the association evaluation model. When the user adjusts the deployment condition values, the filtering results are adjusted adaptively, thereby achieving on-demand deployment. It can associate data from other business areas, improve the richness of the displayed data content, and diversify the displayed data areas, enhancing the user's experience of multi-business platform deployment. Moreover, the control conditions are simple, making it easy and convenient to use and improving the user experience.

[0017] In some optional embodiments, step 2. of selecting business platforms that meet the deployment condition values ​​from among the undeployed business platforms as platforms to be deployed, based on the deployment condition values ​​and the relevant values ​​of each undeployed business platform relative to the deployed business platform in terms of call relationships, includes:

[0018] S11. Calculate the difference between the deployment condition value and the relevant value corresponding to each undeployed business platform;

[0019] S12. The undeployed business platforms whose absolute values ​​of the differences are less than a preset difference threshold are identified as the platforms to be deployed.

[0020] By calculating the difference between the deployment condition value and each undeployed business platform, it is easy to filter out business platforms that meet the deployment condition value as platforms to be deployed. This allows for the determination of undeployed business platforms related to deployed business platforms by combining relevant values ​​with the deployment condition value. This enables users to adjust the platforms to be deployed after adjusting the deployment condition value, thus achieving on-demand deployment.

[0021] In some optional embodiments, deploying the platform to be deployed to the system includes:

[0022] A pop-up display window will be used to showcase the platforms to be deployed.

[0023] In response to the user's confirmation of the currently displayed platform to be deployed, the platform to be deployed is deployed to the system.

[0024] By displaying various platforms to be deployed in a showcase window, users can easily view the associated business platforms identified by the entered deployment condition values. This allows users to further confirm whether to deploy using the currently displayed platforms, making the deployment of business platforms more flexible and accurate, truly achieving on-demand deployment. If there are too many or too few business platforms currently displayed, users can directly adjust the entered deployment condition values, making it simple, convenient, and improving the user experience.

[0025] In some optional embodiments, the method further includes:

[0026] An adjustment operation area is generated in the area of ​​the deployment condition values ​​input by the user, so that the user can adjust the deployment condition values;

[0027] After the pop-up display window for showcasing the platform to be deployed is displayed, the following is also included:

[0028] In response to the user's operation of adjusting the deployment condition value through the adjustment operation area, based on the adjusted deployment conditions, steps S11-S12 are re-executed to determine a new platform to be deployed, and the display window is updated.

[0029] By providing an adjustment operation area, users can easily adjust the deployment condition values ​​directly through the adjustment operation area, thereby facilitating on-demand adjustment of the platform to be deployed, improving usage flexibility, and realizing on-demand deployment.

[0030] In some optional embodiments, the adjustment operation area includes a slidable drag bar; the user adjusts the deployment condition value through the adjustment operation area, including: the user sliding the drag bar to adjust the deployment condition value.

[0031] The deployment condition value can be adjusted by sliding the drag bar, improving the ease of operation and user experience.

[0032] In some optional embodiments, the pre-training process of the association evaluation model includes:

[0033] Obtain historical datasets from each of the business platforms within the system;

[0034] Based on the historical datasets of each business platform, determine the data type corresponding to the data in each business platform, and extract feature data for evaluating the calling relationship between the business platforms based on the data type;

[0035] Using the feature data, an association evaluation model is constructed to evaluate the relevant values ​​of the call relationships between the various business platforms within the system. The association evaluation model is then trained using the historical dataset to obtain the trained association evaluation model.

[0036] In some optional embodiments, before determining the correlation values ​​of each undeployed business platform relative to the deployed business platforms in terms of call relationships using a pre-trained correlation evaluation model, the method further includes:

[0037] In response to a user's deployment instruction for a target business platform, the system acquires data from the target business platform and deploys the data to the system to form a deployed business platform. Attached Figure Description

[0038] One or more embodiments are illustrated by way of example with reference to the accompanying drawings, and these illustrative descriptions do not constitute a limitation on the embodiments.

[0039] Figure 1 This is a flowchart of a system deployment method for on-demand deployment provided in one embodiment of this application. Figure 1 ;

[0040] Figure 2 This is the flow of step 103 in the deployment method provided in one embodiment of this application. Figure 1 ;

[0041] Figure 3 This is the flow of step 103 in the deployment method provided in one embodiment of this application. Figure 2 ;

[0042] Figure 4 This is the flow of step 103 in the deployment method provided in one embodiment of this application. Figure 3 ;

[0043] Figure 5 This is a flowchart of the process of constructing an association evaluation model in the deployment method provided in one embodiment of this application. Figure 1 ;

[0044] Figure 6 This is a schematic diagram of a deployment system provided in another embodiment of this application;

[0045] Figure 7 This is a schematic diagram of the structure of an electronic device provided in another embodiment of this application;

[0046] Figure 8 This is a schematic diagram of the structure of a computer-readable storage medium provided in another embodiment of this application. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the various embodiments of this application to help readers better understand this application. However, the technical solutions claimed in this application can be implemented even without these technical details and various changes and modifications based on the following embodiments. The division of the various embodiments below is for the convenience of description and should not constitute any limitation on the specific implementation of this application. The various embodiments can be combined with and referenced by each other without contradiction.

[0048] To facilitate understanding of the embodiments of this application, relevant content regarding system deployment will be introduced first.

[0049] In the field of system development technology, the creation and deployment of the system deployment environment (also known as the application runtime environment) is the foundation for the debugging and testing of application functions, and can lay a solid foundation for the subsequent full-process testing and production launch of the application system.

[0050] Currently, more and more business platforms with various functions are being deployed into the system. In the existing technology, when multiple business platforms are deployed to the system, they can usually only be deployed one by one, and it is not possible to deploy multiple business platforms in a related manner. The deployment method is not flexible enough, the data displayed to users is singular, and it is not possible to deploy multi-dimensional data according to user needs.

[0051] To address the aforementioned technical problem of inflexible deployment that cannot be adapted to user needs, this invention proposes a system deployment method for on-demand deployment. The implementation details of the system deployment method for on-demand deployment in this embodiment are described below. The following content is only for ease of understanding and is not essential for implementing this solution.

[0052] Example 1:

[0053] The on-demand deployment method of this embodiment can be applied to electronic devices with communication, computing, and data storage capabilities. The specific process can be as follows: Figure 1 As shown, steps 101-103 are included, specifically:

[0054] Step 101: Use a pre-trained association evaluation model to determine the correlation values ​​of each undeployed business platform relative to the deployed business platform in terms of call relationships within the system;

[0055] Specifically, step 101 belongs to the preprocessing stage of system deployment. By using the correlation evaluation model to determine the relevant values ​​of each business platform in the call relationship, the relevant values ​​can be used to select business platforms that meet the deployment conditions for use in the later stage.

[0056] In some examples, the association evaluation model is an algorithmic AI model that classifies the domain models of various business platforms in the system. The corresponding business platform is input into the association evaluation model, and a pre-processed classification index value is obtained based on the content of the business domain in which the business platform belongs. This value evaluates the relevance of the business platform to the system's deployed business platforms in terms of call relationships. This allows for the convenient filtering of undeployed business platforms related to the system's deployed business platforms for association deployment.

[0057] Step 102: Obtain the deployment condition value input by the user; the deployment condition value is used to describe the degree of correlation between the deployed business platform and the non-deployed business platform being called in terms of the calling relationship;

[0058] Specifically, the deployment condition values ​​entered by the user determine the scope of the project deployment based on their needs. If the user's needs are broad and require more system resources, a larger deployment condition value will result in more business platforms being selected for deployment, thus increasing the displayed service resources and satisfying the user's needs. Conversely, if the user's needs are narrow, a smaller deployment condition value will result in fewer business platforms being selected for deployment, reducing the displayed service resources and thus satisfying the user's needs while conserving server system resources.

[0059] In some examples, when the deployment condition value describes the relevance between the deployed business platform and the invoked undeployed business platform in the call relationship, a larger deployment condition value makes it easier to correlate the deployed business platform and the invoked undeployed business platform in the call relationship. This allows more undeployed business platforms to easily meet the deployment condition value, resulting in more business platforms to be deployed using the deployment condition value, and thus increasing the number of service resources displayed, thereby satisfying the user's needs. Conversely, a smaller deployment condition value makes it more difficult to correlate the deployed business platform and the invoked undeployed business platform in the call relationship. Users can achieve on-demand deployment and flexible associated deployment by inputting different deployment condition values.

[0060] Step 103: Based on the deployment condition values ​​and the relevant values ​​of each undeployed business platform relative to the deployed business platform in terms of the call relationship, select the business platforms that meet the deployment condition values ​​from the undeployed business platforms as the platforms to be deployed, and deploy the platforms to be deployed to the system.

[0061] Specifically, during the screening process, the relevant values ​​of each undeployed business platform are analyzed in turn to identify business platforms that meet the deployment criteria as platforms to be deployed. The number of platforms to be deployed is positively correlated with the deployment criteria values ​​entered by the user.

[0062] In some examples, step 103, such as Figure 2 As shown, it includes:

[0063] S11. Calculate the difference between the deployment condition value and the relevant value corresponding to each undeployed business platform;

[0064] S12. Determine the undeployed business platforms whose absolute values ​​of the differences are less than or equal to a preset difference threshold as the platforms to be deployed;

[0065] In some examples, the currently deployed business platform is denoted as A, and its relevant value is 'a'. The undeployed business platforms are denoted as B, C, D..., and their relevant values ​​relative to the deployed business platforms in terms of call relationships are b, c, d... The deployment condition value input by the user is denoted as X. To calculate whether the relevant value 'b' of the undeployed business platform B meets the deployment condition value X, the following conditional formula is used:

[0066] |ba|<=x;

[0067] If the relevant value b of the undeployed business platform B meets the above conditions, it indicates that the undeployed business platform B is related to the deployed business platform A, and then it is deployed as a platform to be deployed.

[0068] In this embodiment, by selecting business platforms whose deployment conditions match those of currently deployed business platforms based on user-inputted deployment condition values, the system can deploy them as such. The control conditions are simple, requiring no changes to the user's deployment requirements, making it easy and convenient to use. This enriches the data displayed to the user and improves the user experience. Furthermore, multiple related business platforms can be deployed by inputting deployment condition values ​​only once, expanding the scope of user data associated with system platforms. This allows for the display of data content from user-related data platforms and enables on-demand deployment, saving server system resources.

[0069] In some embodiments, prior to step 101, a business platform also needs to be deployed in the system. This deployment method further includes:

[0070] In response to a user's deployment instruction for a target business platform, the system acquires data from the target business platform and deploys the data to the system to form a deployed business platform.

[0071] By first deploying a business platform in the system as an already deployed business platform, it is possible to identify relevant undeployed business platforms based on the already deployed business platform and the deployment condition values ​​input by the user.

[0072] In some embodiments, the step of deploying the platform to be deployed to the system is as follows: Figure 3 As shown, it includes:

[0073] S201. A pop-up display window is used to showcase the platforms to be deployed.

[0074] S202. In response to the user's confirmation of the currently displayed platform to be deployed, the platform to be deployed is deployed to the system.

[0075] By displaying various platforms to be deployed in a showcase window, users can easily view the associated business platforms identified by the entered deployment condition values. This allows users to further confirm whether to deploy using the currently displayed platforms, making the deployment of business platforms more flexible and accurate, truly achieving on-demand deployment. If there are too many or too few business platforms currently displayed, users can directly adjust the entered deployment condition values, making it simple, convenient, and improving the user experience.

[0076] Furthermore, the deployment method also includes: generating an adjustment operation area in the deployment condition value area input by the user, so that the user can adjust the deployment condition value;

[0077] After the pop-up display window for showcasing the platform to be deployed is displayed, as follows: Figure 4 As shown, it also includes:

[0078] S203, in response to the user's operation of adjusting the deployment condition value through the adjustment operation area, based on the adjusted deployment conditions, steps S11-S12 are re-executed to determine a new platform to be deployed, and the display window is updated.

[0079] By providing an adjustment operation area, users can easily adjust the deployment condition values ​​directly through the adjustment operation area, thereby facilitating on-demand adjustment of the platform to be deployed, improving usage flexibility, and realizing on-demand deployment.

[0080] In this embodiment, the adjustment operation area includes a slidable drag bar; the user adjusts the deployment condition value through the adjustment operation area, including: the user slides the drag bar to adjust the deployment condition value.

[0081] The deployment condition value can be adjusted by sliding the drag bar, improving the ease of operation and user experience.

[0082] In some embodiments, the construction process of the correlation evaluation model can be achieved through methods such as... Figure 5 The steps shown are implemented as follows:

[0083] Step 301: Obtain historical datasets for each of the business platforms within the system;

[0084] Step 302: Determine the data type corresponding to the data in each of the business platforms based on the historical datasets of each business platform, and extract feature data for evaluating the calling relationship between the business platforms based on the data type;

[0085] Step 303: Construct an association evaluation model using the feature data to evaluate the relationship between the calls between the various business platforms in the system, and train the association evaluation model using the historical dataset to obtain the trained association evaluation model.

[0086] Specifically, the collected historical datasets are further cleaned and standardized to form a dataset for model building and training.

[0087] In this embodiment, the base model for the association evaluation model can be selected based on the data type. For example: for text data, deep learning models such as LSTM, GRU, and BERT can be selected. For structured data, traditional machine learning models such as decision trees, random forests, and XGBoost can be selected. Pre-trained models (such as BERT and RoBERTa) can significantly reduce training time and improve model performance. Specifically, this embodiment uses a pre-trained model for construction, selecting an appropriate loss function, such as cross-entropy loss, and an appropriate optimizer, such as Adam or SGD. After construction, the model is trained using a processed historical dataset. The training process includes: performing multiple training epochs, traversing all training data in each epoch; evaluating the model's performance on the validation set at the end of each epoch; and adjusting hyperparameters, such as learning rate and batch size, based on the validation set performance.

[0088] After the association evaluation model is built and trained, it is evaluated and tuned. Evaluation includes assessing the model's performance on a test set and calculating metrics such as accuracy, recall, and F1 score. Tuning involves adjusting the model architecture and hyperparameters based on the evaluation results to improve performance. Different data augmentation methods and regularization techniques can be tried.

[0089] Finally, the trained correlation evaluation model is exported to a deployable format, such as ONNX or TensorFlowSavedModel, and integrated into practical applications, such as web services and mobile applications, to facilitate the determination of relevant values ​​for each undeployed business platform in step 101.

[0090] The on-demand deployment method provided in this embodiment can select business platforms that meet the deployment conditions from among the undeployed business platforms based on the deployment condition values ​​input by the user and the relevant values ​​determined by the association evaluation model as platforms to be deployed. When the user adjusts the deployment condition values, the filtering results are adjusted adaptively, thereby achieving on-demand deployment. It can associate data from other business areas, improve the richness of the displayed data content, and diversify the displayed data areas, enhancing the user's experience of deploying multiple business platforms. Moreover, the control conditions are simple, making it easy and convenient to use and improving the user experience.

[0091] Example 2:

[0092] Another embodiment of this application relates to a system deployment system for on-demand deployment. The implementation details of this system deployment system are described below. The following details are for ease of understanding and are not essential for implementing this solution. A schematic diagram of the system deployment system for on-demand deployment in this embodiment can be seen as follows: Figure 6 As shown, it includes a correlation value calculation unit 801, a data acquisition unit 802, a business platform association filtering unit 803, and a deployment unit 804.

[0093] The correlation value calculation unit 801 is used to determine the correlation value of each undeployed business platform in the system with respect to the deployed business platform in terms of the call relationship using a pre-trained correlation evaluation model;

[0094] The data acquisition unit 802 is connected to the correlation value calculation unit 801 and is used to acquire the deployment condition value input by the user; the deployment condition value is used to describe the degree of correlation between the deployed business platform and the non-deployed business platform being called in terms of the calling relationship;

[0095] The business platform association filtering unit 803 is connected to the relevant value calculation unit 80 and the data acquisition unit 802, and is used to filter out the business platforms that meet the deployment condition values ​​from the undeployed business platforms as the platforms to be deployed based on the deployment condition values ​​and the relevant values ​​of each undeployed business platform relative to the deployed business platform in the calling relationship.

[0096] The deployment unit 804 is connected to the business platform association filtering unit 803 and is used to deploy the platform to be deployed to the system.

[0097] It is worth mentioning that all modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. Furthermore, to highlight the innovative aspects of this application, this embodiment does not introduce units that are not closely related to solving the technical problems proposed in this application; however, this does not mean that other units are absent in this embodiment.

[0098] Example 3:

[0099] Another embodiment of this application relates to an electronic device, such as... Figure 7 As shown, it includes: at least one processor 901; and a memory 902 communicatively connected to the at least one processor 901; wherein the memory 902 stores instructions executable by the at least one processor 901, the instructions being executed by the at least one processor 901 to enable the at least one processor 901 to perform the deployment methods in the above embodiments.

[0100] The memory and processor are connected via a bus, which can include any number of interconnecting buses and bridges, connecting various circuits of one or more processors and memories. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and will not be described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over the wireless medium via an antenna, which further receives data and transmits it to the processor.

[0101] The processor manages the bus and general processing, and also provides various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory is used to store data used by the processor during operation.

[0102] Example 4:

[0103] Another embodiment of this application relates to a computer-readable storage medium, such as... Figure 8 As shown, a computer program 31 is stored. When the computer program 31 is executed by the processor, it implements the above-described method embodiment.

[0104] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0105] Those skilled in the art will understand that the above embodiments are specific embodiments for implementing this application, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of this application.

Claims

1. A deployment method for on-demand system deployment, characterized in that, The deployment method includes: A pre-trained correlation evaluation model is used to determine the correlation values ​​of each undeployed business platform relative to the deployed business platform in terms of call relationships within the system; Obtain the deployment condition value input by the user; the deployment condition value is used to describe the degree of correlation between the deployed business platform and the non-deployed business platform being called in terms of the calling relationship; Based on the deployment condition values ​​and the relevant values ​​of each undeployed business platform relative to the deployed business platform in terms of the call relationship, business platforms that meet the deployment condition values ​​are selected from each undeployed business platform as platforms to be deployed, and the platforms to be deployed are deployed to the system; The pre-training process of the correlation evaluation model includes: Obtain historical datasets from each of the business platforms within the system; Based on the historical datasets of each business platform, determine the data type corresponding to the data in each business platform, and extract feature data for evaluating the calling relationship between the business platforms based on the data type; Using the feature data, an association evaluation model is constructed to evaluate the relevant values ​​of the call relationships between the various business platforms within the system. The association evaluation model is then trained using the historical dataset to obtain the trained association evaluation model. The step of selecting business platforms that meet the deployment criteria from among the undeployed business platforms as platforms to be deployed includes: S11. Calculate the difference between the deployment condition value and the relevant value corresponding to each undeployed business platform; S12. The undeployed business platforms whose absolute values ​​of the differences are less than a preset difference threshold are identified as the platforms to be deployed.

2. The deployment method for on-demand system deployment according to claim 1, characterized in that, Deploying the platform to be deployed to the system includes: A pop-up display window will be used to showcase the platforms to be deployed. In response to the user's confirmation of the currently displayed platform to be deployed, the platform to be deployed is deployed to the system.

3. The deployment method for on-demand system deployment according to claim 2, characterized in that, The method further includes: An adjustment operation area is generated in the area of ​​the deployment condition value input by the user, so that the user can adjust the deployment condition value; After the pop-up display window for showcasing the platform to be deployed is displayed, the following is also included: In response to the user's operation of adjusting the deployment condition value through the adjustment operation area, based on the adjusted deployment conditions, steps S11-S12 are re-executed to determine a new platform to be deployed, and the display window is updated.

4. The deployment method for on-demand system deployment according to claim 3, characterized in that, The adjustment operation area includes a slidable drag bar; the user adjusts the deployment condition value through the adjustment operation area, including: the user slides the drag bar to adjust the deployment condition value.

5. A system deployment method for on-demand deployment according to any one of claims 1-4, characterized in that, Before determining the correlation values ​​of each undeployed business platform relative to the deployed business platform in terms of call relationships using the pre-trained correlation evaluation model, the method further includes: In response to a user's deployment instruction for a target business platform, the system acquires data from the target business platform and deploys the data to the system to form a deployed business platform.

6. A deployment system for on-demand system deployment, characterized in that, include: The correlation value calculation unit is used to determine the correlation value of each undeployed business platform relative to the deployed business platform in terms of call relationship using a pre-trained correlation evaluation model; The data acquisition unit is used to acquire deployment condition values ​​input by the user; the deployment condition values ​​are used to describe the degree of correlation between the deployed business platform and the non-deployed business platform being called in terms of the calling relationship; The business platform association filtering unit is used to filter out business platforms that meet the deployment condition values ​​as platforms to be deployed from among the undeployed business platforms based on the deployment condition values ​​and the relevant values ​​of each undeployed business platform relative to the deployed business platform in terms of the call relationship. A deployment unit is used to deploy the platform to be deployed into the system; The pre-training process of the correlation evaluation model includes: Obtain historical datasets from each of the business platforms within the system; Based on the historical datasets of each business platform, determine the data type corresponding to the data in each business platform, and extract feature data for evaluating the calling relationship between the business platforms based on the data type; Using the feature data, an association evaluation model is constructed to evaluate the relevant values ​​of the call relationships between the various business platforms within the system. The association evaluation model is then trained using the historical dataset to obtain the trained association evaluation model. The process of the business platform association filtering unit filtering the platforms to be deployed includes: S11. Calculate the difference between the deployment condition value and the relevant value corresponding to each undeployed business platform; S12. The undeployed business platforms whose absolute values ​​of the differences are less than a preset difference threshold are identified as the platforms to be deployed.

7. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the deployment method as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the deployment method according to any one of claims 1 to 5.

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