Low-code platform application copying and distributing method and device, equipment and medium

Abstract

The invention relates to a low-code platform application copying and distributing method and device, equipment and a medium, and the method comprises the steps: receiving an application copying request of a target tenant, analyzing the environment state information of the target tenant, and determining a corresponding application copying strategy and an application distributing strategy through an intelligent distributing algorithm; copying copy data of the source application according to the application copy strategy, and adapting the copy data according to the application distribution strategy to meet the configuration requirements of the target tenant; determining a corresponding distribution path based on the environment state information of the target tenant by using an intelligent path optimization algorithm, and executing the distribution operation of the application according to the distribution path; and after the target tenant completes application distribution and configuration, sending distribution confirmation information. The application has the effect of improving the application copying and distributing efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of application replication and distribution, and in particular, to a method, apparatus, device and medium for replication and distribution of applications on a low-code platform. Background Art

[0002] At present, low-code platforms have become the main tool for enterprises to quickly build applications and are widely used in the development, deployment and maintenance of enterprise-level applications. These platforms usually allow users to build customized applications with lower programming complexity through graphical interfaces and preset modules.

[0003] The existing low-code platform application replication method replicates and distributes applications through static configuration and preset rules. It lacks intelligent analysis and dynamic adaptation of the target tenant environment, and lacks dynamic evaluation of the target tenant environment. As a result, corresponding modifications need to be made after application replication and distribution, reducing configuration efficiency.

[0004] The above-mentioned existing technical solutions have the following defects: the existing low-code platform application replication method replicates and distributes applications through static configuration and preset rules, resulting in low efficiency of application replication and distribution, so there is room for improvement. Summary of the invention

[0005] In order to improve the efficiency of application replication and distribution, the present application provides a low-code platform application replication and distribution method, device, equipment and medium.

[0006] The above-mentioned invention objective of the present application is achieved through the following technical solutions: A low-code platform application replication and distribution method, the low-code platform application replication and distribution method comprising: Receive an application replication request from a target tenant, analyze the environment status information of the target tenant, and determine a corresponding application replication strategy and application distribution strategy through an intelligent distribution algorithm; According to the application replication strategy, copy data of the source application, and adapt the copy data according to the application distribution strategy to meet the configuration requirements of the target tenant; Using an intelligent path optimization algorithm, based on the environment status information of the target tenant, a corresponding distribution path is determined, and a distribution operation of the application is performed according to the distribution path; After the target tenant completes the application distribution and configuration, a distribution confirmation message is sent.

[0007] By adopting the above technical solution, the application replication and distribution strategy is determined through the intelligent distribution algorithm, and the replication and distribution process can be automatically adjusted dynamically according to the network and resource conditions of the target tenant. This not only improves the efficiency of data transmission, but also avoids failures caused by environmental incompatibility, thereby significantly improving the overall performance and stability of the system; by replicating data and adapting to the target tenant configuration, it can ensure that the data format and functional modules are compatible with the target tenant's environment, avoid application crashes or data corruption caused by incompatibility issues, and improve system reliability and application availability; by optimizing the distribution path through the intelligent path optimization algorithm, it can reduce data transmission delays and improve bandwidth utilization, thereby improving data distribution efficiency, avoiding bottlenecks and congestion during transmission, and ensuring efficient and stable application deployment; by distributing confirmation information, it can timely feedback the distribution results of the application, ensure the transparency and traceability of the distribution process, reduce the need for manual intervention, and improve user experience.

[0008] In one example, the present application may be further configured as follows: analyzing the environment status information of the target tenant and determining the corresponding application replication strategy and application distribution strategy through an intelligent distribution algorithm specifically includes: Obtain the environment status information of the target tenant, and evaluate the resource availability and network load of the environment status information through an intelligent distribution algorithm; The corresponding application replication strategy and application distribution strategy are selected according to the evaluation result.

[0009] By adopting the above technical solution and evaluating the resource availability and network load of the target tenant, it is possible to dynamically adjust the replication and distribution strategy according to the actual environment of the target tenant. This not only avoids overload and resource bottlenecks, but also ensures efficient distribution of applications under different network loads and resource conditions, thereby improving the system's response speed and stability, reducing the possibility of distribution failure, and ensuring business continuity.

[0010] In one example, the present application may be further configured as follows: selecting the corresponding application replication strategy and application distribution strategy according to the evaluation result specifically includes: When the evaluation result shows that the network load and resource availability of the target tenant reach a preset first replication and distribution threshold, a full replication strategy is selected and a real-time distribution operation is performed; When the evaluation result shows that the network load and resource availability of the target tenant reach the second replication distribution threshold and are lower than the first replication distribution threshold, a batch replication strategy is selected, and the distribution time is adjusted according to the network load; When the evaluation result is that the network load and the resource availability of the target tenant are lower than the second replication distribution threshold, a decentralized storage strategy is selected and a batch distribution operation is performed.

[0011] By adopting the above technical solution and selecting the most appropriate application replication and distribution strategy based on the evaluation results, the replication method and distribution strategy can be flexibly adjusted according to different network loads and resource availability conditions. This ensures that even when resources are tight or the network load is high, data transmission can still be carried out smoothly to avoid overload or congestion, thereby improving the efficiency and reliability of the entire system and ensuring the successful deployment of the application.

[0012] In one example, the present application may be further configured as follows: the adaptation of the replicated data according to the application distribution strategy to meet the configuration requirements of the target tenant specifically includes: Acquire the technology stack of the target tenant, and adjust the format of the copied data according to the technology stack; Acquire the functional requirements of the target tenant, and adjust the functional module of the replicated data according to the functional requirements; The permission requirement of the target tenant is obtained, and the permission control rule of the copied data is adjusted according to the permission requirement.

[0013] By adopting the above technical solution, by adjusting the format of the copied data according to the target tenant's technology stack, it is possible to ensure that the application is perfectly compatible with the target tenant's technology environment, avoid data errors and operational anomalies caused by format mismatch, and thus improve the stability of the application; by adjusting the functional modules of the copied data according to the functional requirements of the target tenant, it is possible to accurately deploy specific functions according to tenant needs, reduce unnecessary functional overhead, and improve the tenant's usage experience and satisfaction; by adjusting the data permission control rules according to the target tenant's permission requirements, it is possible to ensure that the data maintains strict security and compliance during the distribution process, avoid data leakage or unauthorized access, and ensure the security of tenant data.

[0014] In one example, the present application may be further configured as follows: the use of the intelligent path optimization algorithm to determine the corresponding distribution path based on the environment status information of the target tenant specifically includes: Performing a transmission node evaluation on the environment status information of the target tenant through an intelligent path optimization algorithm to obtain a corresponding evaluation result; The transmission nodes are sorted in availability according to the evaluation result, and one or more transmission nodes are selected in the order of availability according to the distribution strategy.

[0015] By adopting the above technical solution and evaluating the transmission nodes, it is possible to accurately analyze the performance of each node and select the optimal path for data distribution, thereby avoiding delays and congestion caused by inefficient or overloaded paths and ensuring efficient and stable data transmission. By sorting the transmission nodes according to their availability and selecting the best nodes according to the distribution strategy, it is possible to reasonably distribute the load while ensuring transmission efficiency, avoid overloading certain nodes, improve the overall distribution efficiency, and ensure that even if a node has a problem, the data can still be distributed smoothly, thus ensuring the redundancy and stability of the distribution process.

[0016] In one example, the present application may be further configured as follows: the intelligent path optimization algorithm is used to perform a transmission node evaluation on the environmental status information of the target tenant to obtain a corresponding evaluation result, specifically including: Monitoring bandwidth information, delay information and load information of the transmission node in real time, and converting the bandwidth information, delay information and load information of the transmission node into numerical values; The bandwidth value, delay value and load value of the transmission node are input into a preset availability calculation formula to obtain the availability score corresponding to the transmission node, and generate the evaluation result, wherein T is the availability score, a is the bandwidth value, b is the delay value, c is the load value, and k1, k2, and k3 are preset proportion values.

[0017] By adopting the above technical solution, through real-time monitoring of the bandwidth, delay and load information of the transmission nodes, the performance of each node can be comprehensively evaluated to ensure that the optimal path is selected during data distribution, thereby reducing unnecessary delays and bandwidth waste; by inputting the bandwidth, delay and load values ​​of the transmission nodes into the availability calculation formula for weighted processing, the comprehensive performance of each node can be accurately evaluated, so as to select the best transmission node, improve data transmission efficiency, reduce transmission bottlenecks in the distribution process, and ensure that data can be smoothly distributed with the optimal resource configuration in the shortest time.

[0018] The second object of the invention is achieved by the following technical solutions: A low-code platform application replication and distribution device, the low-code platform application replication and distribution device comprising: A request receiving module, configured to receive an application replication request from a target tenant, analyze the environment status information of the target tenant, and determine a corresponding application replication strategy and application distribution strategy through an intelligent distribution algorithm; A replication distribution module, used to replicate the replication data of the source application according to the application replication strategy, and adapt the replication data according to the application distribution strategy to meet the configuration requirements of the target tenant; A path optimization module, used to determine a corresponding distribution path based on the environment status information of the target tenant by using an intelligent path optimization algorithm, and to perform a distribution operation of the application according to the distribution path; The receiving confirmation module is used to send distribution confirmation information after the target tenant completes application distribution and configuration.

[0019] By adopting the above technical solution, the application replication and distribution strategy is determined through the intelligent distribution algorithm, and the replication and distribution process can be automatically adjusted dynamically according to the network and resource conditions of the target tenant. This not only improves the efficiency of data transmission, but also avoids failures caused by environmental incompatibility, thereby significantly improving the overall performance and stability of the system; by replicating data and adapting to the target tenant configuration, it can ensure that the data format and functional modules are compatible with the target tenant's environment, avoid application crashes or data corruption caused by incompatibility issues, and improve system reliability and application availability; by optimizing the distribution path through the intelligent path optimization algorithm, it can reduce data transmission delays and improve bandwidth utilization, thereby improving data distribution efficiency, avoiding bottlenecks and congestion during transmission, and ensuring efficient and stable application deployment; by distributing confirmation information, it can timely feedback the distribution results of the application, ensure the transparency and traceability of the distribution process, reduce the need for manual intervention, and improve user experience.

[0020] The third objective of the present application is achieved through the following technical solutions: A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned low-code platform application replication and distribution method are implemented.

[0021] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned low-code platform application replication and distribution method.

[0022] In summary, this application includes the following beneficial technical effects: 1. By determining the application replication and distribution strategy through the intelligent distribution algorithm, the replication and distribution process can be automatically and dynamically adjusted according to the network and resource conditions of the target tenant, which can not only improve the efficiency of data transmission, but also avoid failures caused by environmental incompatibility, thereby significantly improving the overall performance and stability of the system; by replicating data and adapting to the target tenant configuration, it can ensure that the data format and functional modules are compatible with the target tenant's environment, avoid application crashes or data corruption caused by incompatibility issues, and improve system reliability and application availability; by optimizing the distribution path through the intelligent path optimization algorithm, it can reduce data transmission delays and improve bandwidth utilization, thereby improving data distribution efficiency, avoiding bottlenecks and congestion during transmission, and ensuring efficient and stable application deployment; by distributing confirmation information, it can timely feedback the distribution results of the application, ensure the transparency and traceability of the distribution process, reduce the need for manual intervention, and improve user experience; 2. By evaluating the resource availability and network load of the target tenant, the replication and distribution strategies can be dynamically adjusted according to the actual environment of the target tenant. This can not only avoid overload and resource bottlenecks, but also ensure efficient distribution of applications under different network loads and resource conditions, thereby improving the response speed and stability of the system, reducing the possibility of distribution failure, and ensuring business continuity; 3. By selecting the most appropriate application replication and distribution strategy based on the evaluation results, the replication method and distribution strategy can be flexibly adjusted according to different network loads and resource availability conditions. This ensures that even when resources are tight or the network load is high, data transmission can still be carried out smoothly to avoid overload or congestion, thereby improving the efficiency and reliability of the entire system and ensuring the successful deployment of the application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a flow chart of a low-code platform application replication and distribution method in one embodiment of the present application; Figure 2 It is a flowchart for implementing step S10 in the low-code platform application replication and distribution method in one embodiment of the present application; Figure 3 It is a flowchart for implementing step S12 in the low-code platform application replication and distribution method in one embodiment of the present application; Figure 4 It is a flowchart for implementing step S20 in the low-code platform application replication and distribution method in one embodiment of the present application; Figure 5 It is a flowchart for implementing step S30 in the low-code platform application replication and distribution method in one embodiment of the present application; Figure 6 It is a flowchart for implementing step S31 in the low-code platform application replication and distribution method in one embodiment of the present application; Figure 7 It is a principle block diagram of a low-code platform application replication and distribution device in one embodiment of the present application; Figure 8 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below in conjunction with the accompanying drawings.

[0025] In one embodiment, if Figure 1 As shown, the present application discloses a low-code platform application replication and distribution method, which specifically includes the following steps: S10: receiving an application replication request from a target tenant, analyzing the target tenant's environment status information, and determining corresponding application replication strategies and application distribution strategies through an intelligent distribution algorithm.

[0026] Specifically, we first obtain the target tenant's application replication request, including the tenant's basic information, the application identifier to be replicated, distribution requirements, etc., receive this information through the API interface, and then conduct a comprehensive analysis of the target tenant's environmental status, such as network bandwidth, computing resources, storage capacity, and the type of operating system used by the tenant. Through comprehensive analysis of this information, we can customize the best application replication and distribution strategy for the target tenant.

[0027] S20: According to the application replication policy, the replication data of the source application is replicated, and the replication data is adapted according to the application distribution policy to meet the configuration requirements of the target tenant.

[0028] Specifically, first, according to the application replication strategy, the required replication data is extracted from the source application, including the source application's functional modules, metadata, business logic, user permissions and other contents. The replication data can be extracted through API calls or database exports. The replication data format may need to be converted according to the target tenant's storage method. The target tenant's technology stack is formatted to make it compatible with the target tenant's technology architecture. Subsequently, the replication data is adapted according to the target tenant's functional requirements and permission settings. It may be necessary to adjust the enabled status of the functional modules, optimize the interface calling method, and modify the permission control rules according to the target tenant's business scenarios to ensure the smooth use and security of the data in the target environment.

[0029] S30: Using an intelligent path optimization algorithm, based on the environment status information of the target tenant, determine a corresponding distribution path, and perform a distribution operation of the application according to the distribution path.

[0030] Specifically, the target tenant's environmental status information is first input into the intelligent path optimization algorithm. The path evaluation is performed by real-time monitoring of the target tenant's network bandwidth, latency, and computing resources. An optimal path is selected for application data distribution by considering the target tenant's network load, transmission speed, bandwidth occupancy, etc. The selected path can be either the tenant's local network or distributed through a cloud platform or other intermediate servers, ensuring that data can reach the target tenant environment efficiently and stably, while reducing the impact of latency and bandwidth bottlenecks on the distribution process.

[0031] S40: After the target tenant completes application distribution and configuration, a distribution confirmation message is sent.

[0032] Specifically, after the target tenant completes the application distribution and configuration, a distribution confirmation message is automatically generated. The confirmation information includes the status of the application distribution, the success or failure mark, the application version number, and the configuration change content. The information can be sent through email, SMS, push notification, etc., to ensure that the target tenant can confirm whether the application is deployed correctly after receiving the distribution confirmation, and can view any errors or warning information that occurred during the distribution process, providing necessary support for subsequent application use and maintenance.

[0033] In one embodiment, if Figure 2 As shown, in step S10, the environment status information of the target tenant is analyzed, and the corresponding application replication strategy and application distribution strategy are determined through the intelligent distribution algorithm, which specifically includes: S11: Obtain the environment status information of the target tenant, and evaluate the resource availability and network load of the environment status information through an intelligent distribution algorithm.

[0034] Specifically, the target tenant's environmental status information is obtained in real time through the API interface or data collection tools. The information includes the target tenant's current network bandwidth, latency, resource usage, storage space, CPU and memory occupancy, etc. The information obtained will be input into the intelligent distribution algorithm for evaluation. The intelligent distribution algorithm first evaluates the network load and analyzes whether the target tenant's network bandwidth is sufficient to meet the application distribution requirements. It then evaluates resource availability, including whether computing resources are sufficient to support the operation of the application, whether storage resources are sufficient, and whether there are other resource bottlenecks. Finally, a comprehensive evaluation result is output as the basis for subsequent strategy selection.

[0035] S12: Select corresponding application replication strategy and application distribution strategy according to the evaluation result.

[0036] Specifically, based on the evaluation results, if the network load and resource availability of the target tenant meet the first replication and distribution threshold, the system will select the full replication strategy and perform real-time distribution operations to ensure that the data can be distributed in the shortest time; if the evaluation results show that the network load and resource availability reach the second replication and distribution threshold, but are lower than the first threshold, the system will select the batch replication strategy to optimize the distribution time according to the network bandwidth and the tenant's load to avoid causing excessive pressure during peak hours; if the evaluation results show that the network load and resource availability are lower than the second threshold, the distributed storage strategy will be selected to reduce the load of each node through distributed storage, and improve the stability of distribution through batch distribution.

[0037] In one embodiment, if Figure 2 As shown, in step S12, the corresponding application replication strategy and application distribution strategy are selected according to the evaluation result, which specifically includes: S121: When the evaluation result shows that the network load and resource availability of the target tenant reach a preset first replication and distribution threshold, a full replication strategy is selected and a real-time distribution operation is performed.

[0038] Specifically, when the evaluation results show that indicators such as the target tenant's network bandwidth and computing resources exceed the first replication and distribution threshold, the system selects a full replication strategy, that is, all data of the target application is copied to the target tenant's environment. No data splitting or delay processing is performed during the distribution process, and the data is transmitted in real time to ensure that the full deployment of the application is completed in a short time. It is suitable for scenarios where the target tenant's network load and computing resources are sufficient to support large-scale concurrent data transmission, for example, bandwidth is above 1Gbps and latency is less than 50ms.

[0039] S122: When the evaluation result shows that the network load and resource availability of the target tenant reach the second replication distribution threshold and are lower than the first replication distribution threshold, a batch replication strategy is selected and the distribution time is adjusted according to the network load.

[0040] Specifically, when the target tenant's network bandwidth and resource availability reach the second replication distribution threshold, the system will select a batch replication strategy. During the replication process, the source application's data will be divided into several batches for gradual replication, reducing the load of a single data transmission and avoiding excessive pressure on the target tenant's network caused by transmitting too much data at one time. At this time, based on the real-time monitored network load, the system automatically adjusts the transmission time and size of each batch of data and selects low-load periods for distribution to maximize the use of available bandwidth and reduce the impact on the business, which is particularly suitable for medium-load target tenant environments.

[0041] S123: When the evaluation result shows that the network load and resource availability of the target tenant are lower than the second replication distribution threshold, a decentralized storage strategy is selected and a batch distribution operation is performed.

[0042] Specifically, when the target tenant's network bandwidth and computing resources are lower than the second replication distribution threshold, the system selects a decentralized storage strategy to disperse the source application's data in multiple locations or servers, which can reduce the load pressure on a single node. At the same time, the data is distributed to the target tenant in batches through multi-path transmission to ensure that the data can reach different storage nodes smoothly and stably. During the implementation of the decentralized storage strategy, data will be transmitted in parallel on multiple transmission paths to ensure that data can be distributed smoothly even if some paths are congested, thereby improving the stability and efficiency of data distribution.

[0043] In one embodiment, if Figure 2 As shown, in step S20, the replicated data is adapted according to the application distribution strategy to meet the configuration requirements of the target tenant, specifically including: S21: Obtain the technology stack of the target tenant and adjust the format of the copied data according to the technology stack.

[0044] Specifically, the target tenant's technology stack information is obtained, including the operating system version, database type, programming language version, etc. used by the target tenant. The system will automatically identify the target tenant's technology stack through API or configuration files, and then format the copied data according to the target tenant's environment. For example, if the target tenant uses a different version of the database system, the system will automatically convert the data into a format supported by the target database and ensure that the data can be correctly parsed and stored in the new environment.

[0045] S22: Acquire the functional requirements of the target tenant, and adjust the functional module for replicating data according to the functional requirements.

[0046] Specifically, the target tenant's requirements for the application function modules are obtained, and the specific functions required by the target tenant may be identified through the function requirement document or API interface provided by the target tenant. The system will adjust the function modules of the replicated data based on these requirements, for example, disabling certain functions that the target tenant does not need, or adding specific business logic to meet the needs of the target tenant, ensuring that the replicated application can accurately match the actual usage scenarios of the target tenant.

[0047] S23: Obtain the permission requirements of the target tenant, and adjust the permission control rules for copying data according to the permission requirements.

[0048] Specifically, after obtaining the target tenant's permission requirements, the system will adjust the replicated data according to the tenant's role and permission settings to ensure that each role can only access data that matches its permissions. For example, for the administrator role, the system may enable all functional modules and set full access rights, while for ordinary users, some advanced functions may be disabled and their access to sensitive data may be restricted. Based on the target tenant's permission requirements, the system will automatically adjust the data's access control rules to ensure that it meets the tenant's security and compliance requirements.

[0049] In one embodiment, if Figure 2 As shown, in step S30, the corresponding distribution path is determined based on the target tenant's environmental status information by using the intelligent path optimization algorithm, which specifically includes: S31: Perform transmission node evaluation on the target tenant's environmental status information through an intelligent path optimization algorithm to obtain a corresponding evaluation result.

[0050] Specifically, the bandwidth, delay and load of the transmission nodes are monitored in real time, and this information is collected through network monitoring tools or the log system of the transmission nodes. The bandwidth information is used to determine the maximum data transmission capacity of the current node, the delay information is used to evaluate the impact of delays in the data transmission process, and the load information reflects the resource usage of each node. These data are transmitted to the intelligent path optimization algorithm in real time for evaluation. The algorithm will calculate the comprehensive performance of each node and select the optimal transmission path, thereby determining the most suitable data distribution channel.

[0051] S32: Sort the transmission nodes in terms of availability according to the evaluation result, and select one or more transmission nodes in the order of availability according to the distribution strategy.

[0052] Specifically, the evaluation results standardize the bandwidth, latency and load values ​​of the transmission nodes to obtain the availability score of each node, and sort the nodes according to these scores, giving priority to the transmission node with the highest availability score as the preferred path. If there are multiple transmission nodes with the same high availability score, the system will select one or more backup nodes for parallel distribution according to the distribution strategy to improve the efficiency and stability of data distribution and ensure that data transmission can be completed smoothly under different circumstances.

[0053] In one embodiment, if Figure 2 As shown, in step S31, the target tenant's environmental status information is evaluated by the intelligent path optimization algorithm to obtain the corresponding evaluation results, which specifically include: S311: Monitor the bandwidth information, delay information, and load information of the transmission node in real time, and convert the bandwidth information, delay information, and load information of the transmission node into numerical values.

[0054] Specifically, the network bandwidth monitoring tool is used to obtain the bandwidth usage of each transmission node in real time, the delay information is obtained through the Ping test, and the load information is measured by collecting the resource utilization of the transmission node, such as CPU, memory, storage, etc. All of this information will be converted into standardized values, such as bandwidth utilization converted to a percentage value from 0 to 100, delay converted to a millisecond-level delay value, and load converted to the load ratio of the node's current resources. All values ​​will provide accurate data support for subsequent calculations and path selection.

[0055] S312: Input the bandwidth value, delay value and load value of the transmission node into the preset availability calculation formula T=k1×a-k2×b-k3×c to obtain the availability score corresponding to the transmission node, and generate an evaluation result, where T is the availability score, a is the bandwidth value, b is the delay value, c is the load value, and k1, k2, and k3 are preset proportion values.

[0056] Specifically, the obtained bandwidth value, delay value and load value are substituted into the preset availability calculation formula, and each value is weighted by the proportional coefficients k1, k2, and k3 set in the formula to calculate the availability score of each transmission node. When the bandwidth value and delay value are high, it will have a positive impact on the node's availability score, while when the load value is high, it will reduce the node's availability score. Finally, a comprehensive evaluation result is generated to help determine which transmission nodes are most suitable for data distribution.

[0057] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0058] In one embodiment, a low-code platform application replication and distribution device is provided, and the low-code platform application replication and distribution device corresponds one-to-one to the low-code platform application replication and distribution method in the above embodiment. Figure 7 As shown, the low-code platform application replication and distribution device includes a request receiving module, a replication and distribution module, a path optimization module, and a reception confirmation module. The detailed description of each functional module is as follows: A request receiving module is used to receive an application replication request from a target tenant, analyze the target tenant's environment status information, and determine the corresponding application replication strategy and application distribution strategy through an intelligent distribution algorithm; A replication distribution module is used to replicate the replication data of the source application according to the application replication strategy, and adapt the replication data according to the application distribution strategy to meet the configuration requirements of the target tenant; A path optimization module is used to determine the corresponding distribution path based on the target tenant's environmental status information by using an intelligent path optimization algorithm, and to perform the distribution operation of the application according to the distribution path; The receiving confirmation module is used to send distribution confirmation information after the target tenant completes application distribution and configuration.

[0059] Optionally, the request receiving module specifically includes: The network evaluation submodule is used to obtain the target tenant's environmental status information and evaluate the resource availability and network load of the environmental status information through an intelligent distribution algorithm; The strategy selection submodule is used to select the corresponding application replication strategy and application distribution strategy according to the evaluation results.

[0060] Optionally, the strategy selection submodule specifically includes: A full replication unit, configured to select a full replication strategy and perform a real-time distribution operation when the evaluation result shows that the network load and resource availability of the target tenant reach a preset first replication distribution threshold; A batch replication unit is used to select a batch replication strategy and adjust the distribution time according to the network load situation when the evaluation result shows that the network load situation and resource availability of the target tenant reach the second replication distribution threshold and are lower than the first replication distribution threshold; The distributed storage unit is used to select a distributed storage strategy and perform batch distribution operations when the evaluation result shows that the network load and resource availability of the target tenant are lower than the second replication distribution threshold.

[0061] Optionally, the replication distribution module specifically includes: The data format adjustment submodule is used to obtain the target tenant's technology stack and adjust the format of the copied data according to the technology stack; the function module adjustment submodule is used to obtain the function requirements of the target tenant and adjust the function module of the copied data according to the function requirements; The permission adjustment submodule is used to obtain the permission requirements of the target tenant and adjust the permission control rules for copying data according to the permission requirements.

[0062] Optionally, the path optimization module specifically includes: The path evaluation submodule is used to evaluate the transmission nodes of the target tenant's environmental status information through an intelligent path optimization algorithm to obtain the corresponding evaluation results; The node sorting submodule is used to sort the availability of the transmission nodes according to the evaluation results, and select one or more transmission nodes in the order of availability according to the distribution strategy.

[0063] Optionally, the path evaluation submodule specifically includes: A real-time monitoring unit, used to monitor the bandwidth information, delay information and load information of the transmission node in real time, and perform numerical conversion on the bandwidth information, delay information and load information of the transmission node; The score calculation unit is used to input the bandwidth value, delay value and load value of the transmission node into the preset availability calculation formula T = k1×a-k2×b-k3×c, obtain the availability score corresponding to the transmission node, and generate an evaluation result, wherein T is the availability score, a is the bandwidth value, b is the delay value, c is the load value, and k1, k2, and k3 are preset proportion values. For the specific limitations of the low-code platform application replication and distribution device, please refer to the limitations of the low-code platform application replication and distribution method above, which will not be repeated here. Each module in the above-mentioned low-code platform application replication and distribution device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0064] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a low-code platform application replication and distribution method is implemented.

[0065] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Receive the application replication request from the target tenant, analyze the target tenant's environment status information, and determine the corresponding application replication strategy and application distribution strategy through the intelligent distribution algorithm; According to the application replication policy, the replication data of the source application is replicated, and the replication data is adapted according to the application distribution policy to meet the configuration requirements of the target tenant; Using the intelligent path optimization algorithm, the corresponding distribution path is determined based on the target tenant's environmental status information, and the application distribution operation is performed according to the distribution path; After the target tenant completes application distribution and configuration, a distribution confirmation message is sent.

[0066] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Receive the application replication request from the target tenant, analyze the target tenant's environment status information, and determine the corresponding application replication strategy and application distribution strategy through the intelligent distribution algorithm; According to the application replication policy, the replication data of the source application is replicated, and the replication data is adapted according to the application distribution policy to meet the configuration requirements of the target tenant; Using the intelligent path optimization algorithm, the corresponding distribution path is determined based on the target tenant's environmental status information, and the application distribution operation is performed according to the distribution path; After the target tenant completes application distribution and configuration, a distribution confirmation message is sent.

[0067] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0068] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0069] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A low-code platform application replication and distribution method, characterized in that: The low-code platform application replication and distribution method includes: Receive an application replication request from a target tenant, analyze the environment status information of the target tenant, and determine a corresponding application replication strategy and application distribution strategy through an intelligent distribution algorithm; According to the application replication strategy, copy data of the source application, and adapt the copy data according to the application distribution strategy to meet the configuration requirements of the target tenant; Using an intelligent path optimization algorithm, based on the environment status information of the target tenant, a corresponding distribution path is determined, and a distribution operation of the application is performed according to the distribution path; After the target tenant completes the application distribution and configuration, a distribution confirmation message is sent.

2. The low-code platform application replication and distribution method according to claim 1 is characterized in that: The analyzing the environment status information of the target tenant and determining the corresponding application replication strategy and application distribution strategy through an intelligent distribution algorithm specifically includes: Obtain the environment status information of the target tenant, and evaluate the resource availability and network load of the environment status information through an intelligent distribution algorithm; The corresponding application replication strategy and application distribution strategy are selected according to the evaluation result.

3. The low-code platform application replication and distribution method according to claim 2 is characterized in that: The selecting the corresponding application replication strategy and application distribution strategy according to the evaluation result specifically includes: When the evaluation result shows that the network load and resource availability of the target tenant reach a preset first replication and distribution threshold, a full replication strategy is selected and a real-time distribution operation is performed; When the evaluation result shows that the network load and resource availability of the target tenant reach the second replication distribution threshold and are lower than the first replication distribution threshold, a batch replication strategy is selected, and the distribution time is adjusted according to the network load; When the evaluation result is that the network load and the resource availability of the target tenant are lower than the second replication distribution threshold, a decentralized storage strategy is selected and a batch distribution operation is performed.

4. The low-code platform application replication and distribution method according to claim 1 is characterized in that: Adapting the replicated data according to the application distribution strategy to meet the configuration requirements of the target tenant specifically includes: Acquire the technology stack of the target tenant, and adjust the format of the copied data according to the technology stack; Acquire the functional requirements of the target tenant, and adjust the functional module of the replicated data according to the functional requirements; The permission requirement of the target tenant is obtained, and the permission control rule of the copied data is adjusted according to the permission requirement.

5. The low-code platform application replication and distribution method according to claim 1 is characterized in that: The using of the intelligent path optimization algorithm to determine the corresponding distribution path based on the environment status information of the target tenant specifically includes: Performing a transmission node evaluation on the environment status information of the target tenant through an intelligent path optimization algorithm to obtain a corresponding evaluation result; The transmission nodes are sorted in availability according to the evaluation result, and one or more transmission nodes are selected in the order of availability according to the distribution strategy.

6. The low-code platform application replication and distribution method according to claim 4 is characterized in that: The step of performing transmission node evaluation on the environment status information of the target tenant by using an intelligent path optimization algorithm to obtain a corresponding evaluation result specifically includes: Monitoring bandwidth information, delay information and load information of the transmission node in real time, and converting the bandwidth information, delay information and load information of the transmission node into numerical values; The bandwidth value, delay value and load value of the transmission node are input into the preset availability calculation formula T=k1×a-k2×b-k3×c to obtain the availability score corresponding to the transmission node, and generate the evaluation result, wherein T is the availability score, a is the bandwidth value, b is the delay value, c is the load value, and k1, k2, and k3 are preset proportion values.

7. A low-code platform application replication and distribution device, characterized in that: The low-code platform application replication and distribution device includes: A request receiving module, configured to receive an application replication request from a target tenant, analyze the environment status information of the target tenant, and determine a corresponding application replication strategy and application distribution strategy through an intelligent distribution algorithm; A replication distribution module, used to replicate the replication data of the source application according to the application replication strategy, and adapt the replication data according to the application distribution strategy to meet the configuration requirements of the target tenant; A path optimization module, used to determine a corresponding distribution path based on the environment status information of the target tenant by using an intelligent path optimization algorithm, and to perform a distribution operation of the application according to the distribution path; The receiving confirmation module is used to send distribution confirmation information after the target tenant completes application distribution and configuration.

8. The low-code platform application replication and distribution device according to claim 7, characterized in that: The request receiving module specifically includes: A network evaluation submodule, used to obtain the environment status information of the target tenant, and evaluate the resource availability and network load of the environment status information through an intelligent distribution algorithm; The strategy selection submodule is used to select the corresponding application replication strategy and application distribution strategy according to the evaluation result.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the low-code platform application replication and distribution method as described in any one of claims 1 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it implements the steps of the low-code platform application replication and distribution method as described in any one of claims 1 to 6.

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