Multi-cloud low-code development basic platform system

Abstract

The invention discloses a multi-cloud low-code development basic platform system, which comprises a cloud native architecture key technology, a low-code platform oriented to general development, a low-code platform oriented to data development and a low-code platform oriented to industrial field management and control, and is characterized in that the cloud native architecture key technology is the basis of the low-code development platform; the low-code platform for general development is based on cloud computing and a visualization technology and comprises a model visualization module, a page visualization module, a process visualization module and an application visualization module. The data development-oriented low-code platform provides one-stop full-link intelligent data construction and management services of data integration, specification definition, data modeling, data research and development, data extraction, data asset management and data service; the low-code platform for industrial field management and control provides unified OT data assets, configurable data analysis and unified industrial data service through data asset standardization construction.

Description

Technical Field

[0001] The present invention relates to the field of computers, and in particular to a multi-cloud low-code development basic platform system. Background Art

[0002] Research on multi-cloud low-code technology for enterprises is still in its infancy. Regarding platform architecture design and implementation, L Tang et al. from Shandong Jiaotong University discussed demand-driven business process design to enable low-code development of enterprise resource management systems. A research team from Shanghai University focused on low-code development of complex product data management, leveraging data AAS technology within digital twins. J Michael et al. from RWTH Aachen University in Germany implemented low-code configuration and reconfiguration using a language plug-in and model-driven approach. Chen Bin et al. from Zhejiang University proposed a low-code model for building management systems and provided solutions to the difficulties of API design. Wang Peng et al. from Huazhong University of Science and Technology proposed a manufacturing execution system design for multi-source heterogeneous data fusion, focusing on heterogeneous system integration solutions, data source quality evaluation models, and discrete workshop data models. Regarding the functional module design of low-code frameworks, J. Wang et al. from the Beijing University of Aeronautics and Astronautics proposed a framework for rapid and convenient industrial application development, offering features such as drag-and-drop process design, one-click process deployment and operation, and data monitoring. R. Sanchis et al. from the Polytechnic University of Valencia described the current characteristics of the emerging low-code field and analyzed benchmarks of existing low-code development platforms for the manufacturing industry to identify currently missing capabilities. However, the research frameworks and architectures described in these studies fall far short of industry business needs and lack breakthrough technological advancements for multi-cloud low-code development. Summary of the Invention

[0003] The purpose of the present invention is to provide a multi-cloud low-code development basic platform system to solve the problems raised in the above background technology.

[0004] To achieve the above-mentioned purpose, the present invention provides a multi-cloud low-code development infrastructure platform system, including key cloud-native architecture technologies, a low-code platform for general development, a low-code platform for data development, and a low-code platform for industrial site management and control, wherein:

[0005] Key cloud-native architecture technologies are the foundation of low-code development platforms, including lightweight container technology, loosely coupled microservice architecture technology, declarative API technology, and process management technology.

[0006] The low-code platform for general development is based on cloud computing and visualization technology, and meets the general, non-core, scattered, and relatively low-specialization needs of enterprises. It includes model visualization modules, page visualization modules, process visualization modules, and application visualization modules.

[0007] The low-code platform for data development provides one-stop, full-link intelligent data construction and management services, including data integration, specification definition, data modeling, data R&D, data extraction, data asset management, and data services. The core modules are the data autonomous analysis module, the data dimension modeling module, and the data service management module.

[0008] The low-code platform for industrial site management and control is built through data asset standardization, providing unified OT data assets, configurable data analysis, and unified industrial data services.

[0009] Furthermore, the lightweight container technology is based on the Kubernetes architecture, and each container has a unique writable file system and resource quota. At the same time, multiple isolated operating system environments are implemented on a single host in a multi-cloud architecture.

[0010] Furthermore, the loosely coupled microservice architecture technology analyzes and constructs a low-coupling and high-cohesion microservice architecture, distributes containers at the bottom layer, implements container granularity isolation, keeps the split services running independently, and ensures the security and stability of the application.

[0011] Furthermore, the model visualization module provides multiple model creation methods for building entity data objects in applications through visualization tools, including a drag-and-drop creation mode for business personnel and a data definition mode for technical personnel, as well as a historical tracing function and model version control function for developing models, supporting data access, data synchronization, and read-write separation in the process of data persistence.

[0012] Furthermore, the page visualization module includes form design, list design and form setting functions, supports custom component integration, and realizes custom design capabilities of forms, lists, and dashboards.

[0013] Furthermore, the process visualization module provides the ability to provide basic process services through a graphical process designer and drag-and-drop process creation, mainly including process definition, process triggering, to-do processing, and process tracking steps.

[0014] Furthermore, the application visualization module is a visual designer that realizes the rapid construction of the system framework through menu configuration, instance management, and page management.

[0015] Furthermore, the low-code data autonomous analysis module supports the rendering of multi-dimensional, grouped-dimensional, and single-dimensional scenarios, realizing the monitoring and comparative analysis of data in different scenarios; for the analysis and exploration of complex data, it provides an intelligent data query engine to realize the rapid separation of dimensional indicators in the data, and uses the chart analysis capabilities of intelligent graphics recommendation technology to intelligently filter out charts that can be used for data display based on the selected dimensions and indicators, helping users choose the most appropriate analysis charts.

[0016] Furthermore, the low-code data dimension modeling module designs and creates dimensional models, detailed models, business indicators, and technical indicators online according to business conditions, and quickly materializes the models into the corresponding data engines; in the subsequent modeling process, it supports building models from the platform standard library, unifying model semantics, and realizing unified standard management and control of model construction; and realizes customized domain algorithm models, providing data services to the outside world in a service-oriented manner, and realizing the deep integration of data and mechanisms.

[0017] Furthermore, the low-code data service management module splits the platform services into different microservices, deploys them independently using containers as carriers, monitors cluster nodes and Pod resources in a fine-grained, multi-dimensional, and all-round manner, automatically distributes loads based on monitoring indicators, and realizes the integration of container health checks, automatic alarms, and elastic scaling, and provides online publishing services. When the data API is published, the container is used as a carrier to receive the publishing request, and based on the real-time operation status of each node and the resource group configuration selected by the user, if the node machine or container fails during operation, the master node will automatically repair the fault, otherwise other node machines will be re-designated for deployment.

[0018] Compared with the prior art, the present system and method have the following advantages:

[0019] 1. To address the challenges of diverse environments, complex configurations, and difficult management, we provide lightweight container technology to enable containerized environments, facilitating deployment and management. To address the issues of poor system stability, maintainability, and operational efficiency caused by numerous complex business modules, we reduce system complexity by improving loosely coupled microservices architecture technology.

[0020] 2. In response to the problem that existing low-code platforms lack deep customization for the steel industry and are difficult to meet various needs, we independently develop a series of low-code components such as data processing, model building, and visualization for process-oriented industries such as steel. According to the needs of the steel industry, we optimize and innovate the performance of scheduling, modeling, visualization and other algorithms, including multi-source heterogeneous distributed data processing and development technology, online data processing designer technology, etc.

[0021] 3. Auxiliary tools and technologies for the entire process of low-code application writing, debugging, publishing, and operation and maintenance, including code-free online intelligent dimensional modeling tools, online data processing designer technology, task publishing technology for debugging-production dual environments, online publishing of cloud data services, service operation monitoring and management, etc., to achieve visual orchestration of task processes, online execution, debugging and efficient deployment. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A system architecture diagram for a multi-cloud low-code development infrastructure platform. DETAILED DESCRIPTION

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0024] like Figure 1 Shown is the system structure diagram of the present invention, including key technologies of cloud-native architecture, a low-code platform for general development, a low-code platform for data development, and a low-code platform for industrial site management and control.

[0025] Cloud-native architecture is the foundation of low-code development platforms. It includes lightweight container technology, loosely coupled microservices architecture, declarative APIs, and process management. Lightweight container technology enables containerized environments, facilitating deployment and management. The cloud-native architecture of loosely coupled microservices reduces system complexity and improves stability, maintainability, and operational efficiency.

[0026] Traditional business applications are complex in scale, and their large deployment architectures often require downtime for business upgrades or deployments, which is labor-intensive and time-consuming. To improve the utilization and expansion speed of infrastructure resources, a lightweight container method based on the Kubernetes architecture is used to package independent and autonomous services, so that each container has a unique writable file system and resource quota. At the same time, multiple isolated operating system environments can be implemented on a single host in a multi-cloud architecture. Lightweight container technology packages microservices and all the required configurations, dependencies, and environment variables into container images. Containerized deployment technology enables one-click, fast, and convenient deployment, simplifies the setup of container management clusters, and integrates scheduling, configuration, storage, networking, etc. to achieve high-performance, smoothly upgradeable, and scalable container application management services.

[0027] A low-coupling, high-cohesion microservices architecture distributes containers at the bottom layer, achieving granular isolation and independent operation of services. This ensures application security and stability, enabling cloud-native transformation. Microservice partitioning technology splits complex platform applications into multiple loosely coupled, independent modules. Each module is independently mirrored for microservice deployment, supporting image-level grayscale upgrades and releases. This achieves low-coupling, high-cohesion microservice partitioning, effectively improving code reuse, scalability, maintainability, and system stability.

[0028] To address the high similarity of basic functional modules and the high software requirements of general applications, a low-code platform for general application development is being built based on cloud computing and visualization technologies. This platform meets the general, non-core, and scattered needs of enterprises with high software requirements but relatively low professional requirements. Low-code components for general application development are being established, including functional components such as model visualization modules, page visualization modules, process visualization modules, and application visualization modules.

[0029] The model visualization module uses visualization tools to construct entity data objects within applications. It offers multiple model creation methods, including a drag-and-drop creation mode for business personnel and a data definition mode for technical personnel. It also provides model history tracing and version control, supporting underlying operations such as data access, data synchronization, and read-write separation during data persistence, enabling flexible model application. Model visualization abstracts business scenarios, forming different business models, and allows for the design and management of these models, which can then be stored in the platform for reuse.

[0030] The page visualization module includes the functions of developing form design, list design, and form setting. This module provides a wealth of form design components, supports controls such as associated models and sub-forms to realize the interaction and display between multiple model data, supports the integration of custom components, and realizes the custom design capabilities of views such as forms, lists, and dashboards. It provides a visual form design function, through which software applications can be quickly developed in a "building blocks" manner, multi-terminal adaptation can be achieved, and repetitive basic construction work can be reduced. At the same time, based on visual development, it provides the expansion capability of the low-code designer, so that resources of various granularities such as components and functions can be expanded and improved through a small amount of JS scripts, thereby enhancing development capabilities and covering more application areas.

[0031] The process visualization module is used to analyze common business process operations and provides multifunctional, basic, and universal process visualization components. Through a graphical process designer and drag-and-drop process creation, it provides developers with basic process service capabilities. Process visualization mainly includes steps such as process definition, process triggering, to-do processing, and process tracking. The process designer is developed to support customized process definitions, including conditional branches, approval nodes, sub-processes, and other operations. A variety of configuration methods are provided in the approval node, including by person, by role, dynamic query by configuration, and user selection, to meet various process configuration needs.

[0032] The application visualization module is used to quickly build the system framework through a visual designer for menu configuration, instance management, and page management. This includes a visual application designer that provides page, menu, and document design capabilities, as well as menu configuration, page management, and instance management. It organically integrates independent construction models through visualization and business component assembly. Furthermore, a template center is formed with templates covering different industries and business scenarios.

[0033] The low-code platform for data development provides one-stop, full-link intelligent data construction and management services including data integration, specification definition, data modeling, data research and development, data extraction, data asset management, and data services. The low-code platform for data development is built, and the core modules of the platform are the data autonomous analysis module, the data dimension modeling module, and the data service management module.

[0034] The autonomous data analysis module addresses the diverse sources and complex structures of sample data in IoT platforms. It provides rendering capabilities for multiple dimensions, grouped dimensions, and single dimensions, enabling monitoring and comparative analysis of data across different scenarios. For analytical exploration of complex data, the intelligent data query engine rapidly separates dimensional indicators within the data, facilitating the calculation and display of data based on different metrics. Furthermore, the chart analysis capabilities of intelligent graphic recommendation technology intelligently filter charts for data display based on selected dimensions and indicators, helping users select the most appropriate analysis charts.

[0035] The data dimensional modeling module targets the "data + model" dual-drive characteristics of industrial big data. It designs and creates dimensional models, detailed models, business indicators, and technical indicators online based on business conditions, and quickly materializes the models into the corresponding data engine. It provides the ability to build models from the platform's standard library and unify model semantics, thereby facilitating data flow between bases and achieving unified standard management and control of model construction. At the same time, by integrating general algorithms and typical industry algorithm models into the low-code data dimensional modeling module, customized domain algorithm models can be implemented, providing data services to the outside world in a service-oriented manner, and achieving a deep integration of data and mechanisms.

[0036] The data service management module splits the platform services into different microservices, which are independently deployed using containers as carriers. Automated orchestration tools are used to achieve efficient management of platform data services. The data service operation monitoring and management submodule implements fine-grained, multi-dimensional, and all-round monitoring of cluster nodes and Pod resources, automatically distributes loads based on monitoring indicators, and integrates health checks, automatic alarms, and elastic scaling of containers, thereby achieving high availability and load balancing of the cluster. At the same time, it provides online publishing technology for data services. When publishing data APIs, it uses containers as carriers to receive publishing requests. Based on the real-time operating status of each node and the resource group configuration selected by the user, if a node machine or container fails during operation, the master node will automatically repair the failure. Otherwise, other node machines will be re-designated for deployment.

[0037] The data service development module encapsulates the data entity into the form of a data interface, and ultimately provides it to the external application system in the form of a service, thereby realizing the rapid release of the data platform after online development and debugging on the low-code platform.

[0038] Given the diverse nature of industrial system environments, complex configurations, and significant management challenges, process manufacturing industries like steel are characterized by long processes, complex process control, extensive supply chains, and numerous service links. This complex and numerous business modules leads to poor system stability, maintainability, and operational efficiency. Research is underway on lightweight container technology for multi-cloud architectures, enabling multiple isolated operating system environments on a single host within a multi-cloud architecture. Microservice partitioning technology breaks complex platform applications into multiple loosely coupled, independent modules, each with its own independent image for microservice deployment. This supports image-level grayscale upgrades and releases, achieving low-coupling, high-cohesion microservice partitioning. This effectively improves code reuse, scalability, maintainability, and system stability. Research and improvements in loosely coupled microservice architectures reduce system complexity. Collaborating with cloud-native platform low-code data services allows for deep integration of low-code and cloud-native platforms, enabling fine-grained, multi-dimensional, and comprehensive monitoring of cluster nodes and pod resources. Loads are automatically distributed based on monitoring metrics, enabling integrated container health checks, automatic alerting, and elastic scaling, while ensuring efficient communication with the low-code platform.

[0039] Process-based manufacturing industries like steel feature complex, specialized systems and challenging management. This requires the development of a low-code component library for steel industry applications on a common low-code platform. This platform deconstructs the steel industry's business scenarios and on-site data structures, creating a series of low-code components for data processing, model building, visualization, and other areas specific to these industries. Aiming for a "one headquarters, multiple sites" management model, and addressing the complex dimensional modeling process and difficulty achieving standardized management across multiple sites in a multi-cloud, low-code architecture, a low-code, online, intelligent dimensional modeling tool is available. This tool can design and create dimensional models, detailed models, business metrics, and technical indicators online based on business needs, and quickly materialize these models into the corresponding data engines, facilitating data flow between sites and achieving standardized management of model building. A low-code module integrates common equipment components for the steel process industry, including production monitoring, emergency response, and event alarms. This module integrates integrated industrial field equipment, collects large amounts of data from multiple, heterogeneous sources, and enables real-time monitoring of production conditions, ultimately enabling deep customization of low-code components for the steel industry.

[0040] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A multi-cloud low-code development basic platform system, characterized by: It includes key technologies of cloud-native architecture, a low-code platform for general development, a low-code platform for data development, and a low-code platform for industrial site management and control, including: Key cloud-native architecture technologies are the foundation of low-code development platforms, including lightweight container technology, loosely coupled microservice architecture technology, declarative API technology, and process management technology. The low-code platform for general development is based on cloud computing and visualization technology, and meets the general, non-core, scattered, and relatively low-specialization needs of enterprises. It includes model visualization modules, page visualization modules, process visualization modules, and application visualization modules. The low-code platform for data development provides one-stop, full-link intelligent data construction and management services, including data integration, specification definition, data modeling, data R&D, data extraction, data asset management, and data services. The core modules are the data autonomous analysis module, the data dimension modeling module, and the data service management module. The low-code platform for industrial site management and control is built through data asset standardization, providing unified OT data assets, configurable data analysis, and unified industrial data services.

2. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The lightweight container technology is based on the Kubernetes architecture. Each container has a unique writable file system and resource quota, and at the same time, multiple isolated operating system environments are implemented on a single host in a multi-cloud architecture.

3. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The loosely coupled microservice architecture technology analyzes and builds a low-coupling and high-cohesion microservice architecture, distributes containers at the bottom layer, implements container granularity isolation, keeps the split services running independently, and ensures the security and stability of the application.

4. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The model visualization module is used to build entity data objects in the application through visualization tools, and provides multiple model creation methods, including a drag-and-drop creation mode for business personnel and a data definition mode for technical personnel, as well as a historical tracing function and model version control function for developing models, supporting data access, data synchronization, and read-write separation during data persistence.

5. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The page visualization module includes form design, list design and form setting functions, supports custom component integration, and realizes custom design capabilities of forms, lists, and dashboards.

6. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The process visualization module provides the ability to create processes through a graphical process designer and drag-and-drop, providing basic process services, mainly including process definition, process triggering, to-do processing, and process tracking steps.

7. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The application visualization module is a visual designer that realizes the rapid construction of the system framework through menu configuration, instance management, and page management.

8. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The low-code data autonomous analysis module supports the rendering of multi-dimensional, grouped-dimensional, and single-dimensional scenarios, realizing the monitoring and comparative analysis of data in different scenarios; for the analysis and exploration of complex data, it provides an intelligent data query engine to realize the rapid separation of dimensional indicators in the data, and uses the chart analysis capabilities of intelligent graphics recommendation technology to intelligently filter out charts that can be used for data display based on the selected dimensions and indicators, helping users choose the most appropriate analysis charts.

9. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The low-code data dimensional modeling module is used to design and create dimensional models, detailed models, business indicators, and technical indicators online according to business conditions, and quickly materialize the models into the corresponding data engine; in the subsequent modeling process, it supports building models from the platform standard library, unifying model semantics, and realizing unified standard management and control of model construction; and realizes customized domain algorithm models, providing data services to the outside world in a service-oriented manner, and realizing the deep integration of data and mechanisms.

10. A multi-cloud low-code development basic platform system according to claim 1, characterized in that: The low-code data service management module splits the platform service into different microservices, deploys them independently using containers as carriers, monitors cluster nodes and Pod resources in a fine-grained, multi-dimensional, and all-round manner, automatically distributes loads based on monitoring indicators, realizes integrated health checks, automatic alarms, and elastic scaling of containers, and provides online publishing services. When the data API is published, the container is used as a carrier to receive the publishing request, and based on the real-time operation status of each node and the resource group configuration selected by the user, if the node machine or container fails during operation, the master node will automatically repair the failure, otherwise other node machines will be re-designated for deployment.

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