Intelligent water affair light application rapid building system based on modularization

Abstract

The invention relates to the technical field of water affair management, and discloses a modularization-based intelligent water affair light application rapid building system, which comprises a template library management module, which is used for storing and managing a plurality of preset function templates, and each function template is used for executing a specific function in water affair management; the parameter configuration module communicates with the template library management module and is used for performing parameterization configuration on the selected function template according to user requirements, and the parameterization configuration comprises data source configuration, operation parameter setting and output option selection; and the system combination and deployment module is used for combining the function templates subjected to parameterization configuration into a complete application system, and deploying the application system into a running environment through a containerization technology and a Kubernetes arrangement tool. Through modular design and template library management, the system can be rapidly configured and deployed according to different water affair management requirements, the construction time of the system is greatly shortened, and the system adapts to rapidly changing business requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of water management, and in particular to a modular-based intelligent water management light application rapid construction system. Background Art

[0002] In recent years, with the acceleration of urbanization and the rapid development of social economy, the demand for water management has been growing. Traditional water management systems face many challenges in meeting the water needs of modern cities, such as complex system deployment, difficult expansion, high maintenance costs, slow response speed, etc. These problems are particularly prominent in specific business scenarios such as water supply scheduling, sewage treatment, pipe network monitoring and water quality testing, which seriously affect the efficiency and service quality of water management.

[0003] Traditional water management systems usually adopt a monolithic architecture with tightly coupled system functions, which often requires downtime for system upgrades, maintenance or expansion, affecting the continuity and stability of the system. In addition, due to the high degree of customization and complexity of the system, water management systems in different scenarios need to be redesigned and developed, resulting in a long development cycle, high implementation costs, and difficulty in meeting rapidly changing business needs.

[0004] In this context, how to provide a water management system that can be quickly deployed, flexibly configured, and efficiently operated has become an urgent need for the current construction of smart water services. Especially in the face of the growing demand for urban water supply and drainage management, the system not only needs to have good scalability and maintainability, but also should have the characteristics of real-time monitoring, automated management, and safety and compliance to ensure the efficiency and reliability of water management.

[0005] Although existing solutions have improved the flexibility of the system to a certain extent through modular design and automated deployment technology, there are still many deficiencies in actual application. For example, the coupling degree between system modules is high, which often requires large-scale adjustments to the entire system when expanding business or upgrading the system. The application of traditional containerization technology also faces problems such as complex configuration and inconsistent environment, and cannot fully guarantee the consistent operation of the system on multiple platforms and in multiple environments.

[0006] In order to solve the above problems, a new smart water management system is urgently needed, which can realize rapid construction, flexible configuration, stable operation and convenient maintenance of the system through modularization, microservice architecture and containerized deployment technology, so as to improve the overall efficiency and service quality of the water management system and meet the needs of modern urban water management. Summary of the invention

[0007] In view of the shortcomings of the prior art, the present invention provides a modular smart water light application rapid construction system, which solves the problems in the prior art such as complex system deployment, difficult expansion, high maintenance cost, slow response speed, and high coupling between system modules leading to inconvenience in upgrading and expansion.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: a modularized smart water affairs light application rapid construction system, comprising: A template library management module, used to store and manage multiple preset function templates, each of which is used to perform a specific function in water management; A parameter configuration module, communicating with the template library management module, is used to perform parameter configuration on the selected function template according to user requirements, wherein the parameter configuration includes data source configuration, operation parameter setting and output option selection; A system combination and deployment module is used to combine the parameterized and configured function templates into a complete application system, and deploy the application system into the operating environment through containerization technology and Kubernetes orchestration tools; An operation monitoring and maintenance module is used to monitor the system status in real time during the operation of the application system, and automatically alarm and handle abnormal situations; The system expansion and upgrade module is used to support the function expansion and version upgrade of the application system, and the function expansion and version upgrade are achieved by dynamically loading new function templates and automatic deployment.

[0009] Preferably, the template library management module includes: A template layered architecture, wherein the template layered architecture comprises a plurality of industry template layers and a functional template layer; The industry template layer presets multiple industry templates according to different water management scenarios, and each industry template corresponds to a group of functional templates; Each functional template consists of multiple sub-modules, including a data input module, a data processing module and a visualization module. The functional template is defined by a domain-specific language (DSL), which describes the structure of the template, input and output interfaces, parameterized configuration items and its dependencies with other modules.

[0010] Preferably, the template library management module further includes: The template version control submodule is used to manage version updates of function templates. The version control submodule manages template update records through Git or similar version control systems, and supports version rollback and viewing and recovery of template historical versions.

[0011] Preferably, the parameter configuration module includes: A dynamic form generator is used to generate a parameter configuration form according to the specific requirements of the function template selected by the user. The dynamic form includes a data source connection information configuration field, a data synchronization rule selection field, and an output result visualization option configuration field; The data source connection information configuration field is used to input the connection information of the data source, including but not limited to IP address, port number, database type, and authentication information; The data synchronization rule selection field is used to configure the data refresh frequency and synchronization rules; The output result visualization option configuration field is used to select and configure the visualization style of the output data, including line chart, pie chart, bar chart, and dashboard visualization options.

[0012] Preferably, the parameter configuration module also includes: The data source verification submodule verifies the validity of the data source connection through the RESTful API. The verification submodule automatically verifies the input connection information when the configuration form is submitted, and returns an error prompt when the verification fails.

[0013] Preferably, the system combination and deployment module includes: Docker container packaging tool, used to encapsulate the parameterized function template into an independent Docker image, wherein the Docker image includes the application code, runtime environment, and required dependent libraries of the function template; The Kubernetes orchestration submodule is used to deploy function templates through Pods in Kubernetes. The Pods dynamically allocate computing resources, network configurations, and persistent storage volumes according to the operating requirements of the function templates.

[0014] Preferably, the Kubernetes orchestration submodule includes: The service automatic discovery and configuration submodule is used to automatically configure the internal DNS name and IP address of the service during the deployment of the function template, ensure stable communication between services through the Kubernetes Service object, and support automatic expansion and load balancing of services.

[0015] Preferably, the operation monitoring and maintenance module includes: A central log management submodule is used to centrally collect the operation logs of each functional module in the system, including access logs, error logs, and operation logs. The log management submodule stores the log data in Elasticsearch or a similar log management system; The Kibana integration submodule is used to perform real-time visual analysis of the log data, support viewing the system operation status through the dashboard, set alarm rules and automatically generate alarm notifications when anomalies are detected in the log.

[0016] Preferably, the central log management submodule further includes: The log archiving and auditing submodule is used to regularly archive and encrypt the operation logs and provide long-term log preservation. The auditing function records detailed logs of system operations, including user logins, configuration changes, and permission management. All audit logs are stored in a read-only database in an unalterable manner. Preferably, the system expansion and upgrade module includes: The rolling update submodule is used to gradually replace the container instances of the old version through the rolling update mechanism of Kubernetes when the system version is upgraded, and automatically roll back to the previous version when the upgrade fails.

[0017] Working principle: By decomposing the functions of the water management system into independent functional modules and storing them in the template library, users can select and customize functional modules through the dynamic parameter configuration interface. The system adopts a microservice architecture, encapsulates the configured modules into Docker images, and deploys them in containers through Kubernetes, achieving cross-platform consistency and efficient operation of the system. During operation, the system continuously tracks and manages the operating status of the system through real-time data monitoring, log management and performance optimization tools to ensure the stability and scalability of the service. In addition, the system also supports regular maintenance, automatic backup, rolling updates and rollback functions, and provides an open API interface and plug-in mechanism, allowing users to perform secondary development to meet different business needs. This working principle realizes the rapid construction, flexible deployment, efficient operation and convenient maintenance of the water management system, solves the problems of complex deployment and difficult expansion in traditional systems, and provides strong technical support for smart water management.

[0018] The present invention provides a modularized smart water service light application rapid construction system, which has the following beneficial effects: 1. Through modular design and template library management, the system can be quickly configured and deployed according to different water management needs, greatly shortening the system construction time and adapting to rapidly changing business needs.

[0019] 2. The system of the present invention provides a dynamic parameter configuration interface, and users can customize functional modules according to specific business needs, including data sources, operating parameters and output forms, to ensure the flexibility of system configuration and business adaptability.

[0020] 3. Through containerization technology (such as Docker) and microservice architecture, the system of the present invention can maintain consistent operating results on different platforms and environments, ensuring the efficiency and portability of the system.

[0021] 4. The system of the present invention integrates real-time data monitoring, log management, performance optimization and automatic expansion functions, which can continuously track the operating status of the system, detect and handle anomalies in a timely manner, and ensure the stability and high availability of the system.

[0022] 5. The system of the present invention provides comprehensive log management and security auditing functions, records all key operations, ensures the traceability of system operations, and meets security and compliance requirements.

[0023] 6. The system of the present invention supports regular maintenance and automatic backup to ensure data security and long-term stable operation of the system. The rolling update and rollback mechanism allows the system to upgrade the version without affecting the business, and quickly recover when problems occur, reducing the upgrade risk.

[0024] 7. The system of the present invention provides an open API and plug-in mechanism to support the development and integration of new functional modules. Users can perform secondary development according to specific needs to further enhance the functionality and adaptability of the system and meet the customized needs of different industries and scenarios.

[0025] In summary, the present invention significantly improves the construction efficiency, operation efficiency, maintenance convenience and business adaptability of the smart water management system, solves the problems of complex deployment, difficult expansion and high maintenance cost in traditional systems, and provides strong technical support for the efficient management of smart water services. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the modules of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] Example: Please see attached Figure 1 The embodiment of the present invention provides a modularized smart water affairs light application rapid construction system, including: System initial configuration 1.1 Template library management In this embodiment, the template library management module is the core component of the system, responsible for storing and managing various preset functional templates to support different water management scenarios. The template library is designed with a layered architecture, and each industry or business scenario has an independent template set to ensure that it can flexibly adapt to various application requirements.

[0029] Template library structure design: The template library adopts a layered architecture, in which the industry template layer contains template sets suitable for water supply scheduling, pipe network monitoring, water quality testing and other scenarios. Each template set is further divided into multiple functional templates, which are composed of sub-modules such as data input module, data processing module, and visualization module. This layered design not only improves the reusability of templates, but also simplifies the management and update of templates.

[0030] Template creation and updating: In this embodiment, developers use a specific DSL (domain-specific language) to create a functional template. DSL can accurately define the structure, input and output interfaces, and parameterized configuration items of the template to ensure that the template can accurately reflect business needs. Template updates are managed through the Git version control system. All changes have version records and support rollback. This version management mechanism ensures that if a problem occurs during template updates, the system can quickly restore to the previous stable version to avoid business interruptions.

[0031] Template library access and selection: Users access the template library through the web interface and select the appropriate template according to specific business needs. Each template comes with a detailed documentation description, including applicable scenarios, input data requirements, output result examples, configuration methods, etc., to help users quickly understand and apply the template. In this way, users can easily select the appropriate template for different water management needs and quickly build an application system.

[0032] The template library management module provides a foundation for the rapid construction of the entire system. Through reasonable template selection and version management, the system can be flexibly configured in different application scenarios to ensure the smooth development of business.

[0033] 1.2 Parameter Configuration In this embodiment, the parameter configuration module provides a flexible and powerful interface, allowing users to perform detailed parameter configuration of the function template according to specific business needs. This is a key link in the system configuration stage, which can convert the user's business needs into specific operating instructions of the system.

[0034] Parameter configuration interface design: The parameter configuration interface uses dynamic form generation technology to automatically generate a configuration form based on the template selected by the user. The configuration form includes data source configuration, operation parameter settings, output option selection, etc. The dynamic form generator can automatically generate corresponding configuration fields according to the requirements of the template, making the configuration process more intuitive and efficient.

[0035] Data source configuration: In this embodiment, the system supports obtaining data from different data sources (such as SCADA systems, sensor networks, historical databases, and third-party APIs). The user enters the connection information of the data source (such as IP address, port, database type, authentication information, etc.) in the configuration interface, and the system verifies the validity of the connection through the RESTful API. After successful configuration, the system binds the data source to the function template to ensure accurate import and processing of data.

[0036] Running parameter settings: Users can set the template's operating parameters in the configuration form, such as data refresh frequency, analysis cycle, alarm threshold, etc. The system provides default parameter options, and users can adjust them according to specific needs. The adjusted parameters will be updated in real time to the system's preview interface, and users can intuitively view the configuration effect to ensure that the final configuration meets business needs.

[0037] Output option selection: Users can select the output format of the results (such as reports, charts, and alarm information) and configure the output destination (such as local storage, cloud storage, email, etc.). The system supports a variety of visualization options (such as line charts, pie charts, dashboards, etc.), and users can freely select and configure the appearance and data range of the chart to ensure that the data display meets business needs and user aesthetic habits.

[0038] The parameter configuration module relies on the templates provided by the template library management module. Through detailed configuration, it combines the templates with the user's business needs to generate a customized system configuration plan, laying the foundation for the subsequent deployment of the system.

[0039] 2. System combination and deployment 2.1 Module Combination In this embodiment, the system combination and deployment module combines the configured functional templates into a complete application system and deploys it using containerization technology to ensure that the system can run efficiently in different environments.

[0040] Microservice architecture design: Each functional module of the system is designed as an independent microservice, and microservices communicate with each other through the API gateway. The configuration file of each module describes its input and output interfaces, dependencies, operating environment requirements, etc. In this way, the system can flexibly combine different modules to implement complex business logic.

[0041] Integration between modules: In this embodiment, the module combination is orchestrated using Kubernetes. Developers create Pods in Kubernetes based on the dependencies defined in the configuration file. Each Pod contains one or more containers and runs the corresponding microservice modules. The Kubernetes controller automatically allocates computing resources to each Pod based on the requirements in the configuration file and establishes network connections between modules. This integration method ensures that the modules of the system can work together seamlessly, improving the reliability and maintainability of the system.

[0042] Based on the parameter configuration module, the module combination and deployment module combines the configured functional modules into a complete application system, and ensures the efficient operation of the system and the rational allocation of resources through containerization technology.

[0043] 2.2 Containerization and Deployment In this embodiment, the system is containerized and deployed using Docker technology, each functional module is encapsulated into an independent Docker image, and orchestrated and deployed through Kubernetes to ensure that the system can run consistently in different environments.

[0044] Docker container packaging: Each functional module is packaged as a Docker image during development, which includes application code, runtime environment, dependency libraries, etc. When creating an image, the developer writes a Dockerfile to define the image building process, including base image selection, dependency installation, application deployment, and other steps. The system also provides automated build services (such as Jenkins). After each code submission, the system automatically triggers the build process, generates a new image, and pushes it to the image repository (such as Docker Hub).

[0045] Container deployment and orchestration: Kubernetes pulls images from the image repository and creates and starts container instances according to the definition in the configuration file. Container instances communicate with external systems through Services. The Kubernetes Service object provides a fixed internal IP address and DNS name for the container, allowing other containers and external systems to access the service stably. In addition, Kubernetes is also responsible for managing the life cycle of the container, including operations such as starting, stopping, expanding, and reducing, ensuring that the system can be flexibly adjusted according to actual needs.

[0046] The containerization and deployment module is based on module combination and configuration files. Through container technology, each functional module is packaged and deployed to the production environment to ensure that the system can run stably on different platforms.

[0047] 2.3 Configuration and startup In this embodiment, the configuration and startup module is responsible for the initialization configuration, startup management and health check of the system, ensuring that the system can run stably after startup and respond to abnormal situations in a timely manner.

[0048] Initialization configuration: The system reads the initial configuration from the configuration file at startup and applies these configurations to the corresponding microservices. The configuration file includes environment variables, startup parameters, resource quotas, log levels, etc., to ensure that the system can load the correct environment and configuration parameters at startup.

[0049] Up and running: The system manages the startup and lifecycle of microservices through Kubernetes' Deployment object. The Deployment object defines the number of copies of the microservice, update strategy, health check, etc. During the startup process, Kubernetes will pull up container instances one by one and perform health checks after the instances are started to ensure the normal operation of the service. If it detects that the service is unavailable, Kubernetes will automatically restart the container or create a new container instance to ensure the continuous availability of the service.

[0050] Health check and fault recovery: In this embodiment, the system regularly checks the health status of microservices through Kubernetes's Liveness Probe and Readiness Probe mechanisms. If a service anomaly is detected, Kubernetes will automatically restart the container instance or create a new instance to ensure the continuous availability of the service. The system logs are automatically collected and stored in a centralized log management system. Operation and maintenance personnel can view the system's operating status and performance indicators through monitoring tools (such as Prometheus and Grafana) and handle abnormal situations in a timely manner.

[0051] The configuration and startup module relies on the previous containerization and deployment. By loading and checking the health of the system configuration files, it ensures that the system can run normally and has the ability to recover quickly after startup.

[0052] 3. System operation and monitoring 3.1 Real-time data monitoring In this embodiment, the real-time data monitoring module is responsible for processing data flowing into the system from different data sources, and performing real-time analysis and alarming according to preset rules, providing real-time feedback on the system operation status to operation and maintenance personnel.

[0053] Data Stream Processing: Data flows into the system from different data sources and is cleaned and converted by the preprocessing module. Preprocessing includes data format conversion, missing value filling, outlier detection and other operations to ensure data accuracy and consistency. The processed data flows into the real-time processing module (such as Apache Kafka, Apache Flink), which analyzes and processes the data according to preset rules, such as calculating statistical values, identifying event patterns, and generating alarm information.

[0054] Visualization and alarm: The processed data is sent to the visualization module through the API interface, and users can view real-time data and historical trends on the dashboard. When the data meets the preset alarm conditions, the system automatically triggers the alarm mechanism and sends alarm information to the operation and maintenance personnel via email, SMS or push notification to ensure that problems can be discovered and handled in a timely manner.

[0055] The real-time data monitoring module is closely related to the operating status of the system. Through real-time processing and analysis of data, it can promptly detect anomalies in system operation and ensure the stability and high availability of the system.

[0056] 3.2 System log and audit In this embodiment, the system log and audit module is responsible for collecting and managing the system's operation logs and auditing the system's operations to ensure the traceability and security of the system's operation records.

[0057] Log management: Logs of all microservices in the system are collected in a central log server (such as Elasticsearch), including access logs, error logs, operation logs, etc. Operation and maintenance personnel can view and analyze logs through log analysis tools such as Kibana to help troubleshoot system problems and improve system maintainability and problem response speed.

[0058] Security Audit: The system records audit logs of all key operations, such as user logins, configuration changes, and permission management. The audit logs record detailed information such as operation time, operator, and operation content, and are stored in a read-only database to ensure that the logs cannot be tampered with. This audit mechanism can help enterprises meet compliance requirements and provide detailed operation records when security incidents occur.

[0059] Based on system operation and monitoring, the system log and audit module provides important data support for operation and maintenance and security management, ensuring the traceability and compliance of the system.

[0060] 3.3 Performance Optimization and Expansion In this embodiment, the performance optimization and expansion module ensures that the system can run efficiently under different load conditions through continuous performance monitoring and automatic expansion mechanism, and performs automatic adjustment when necessary.

[0061] Performance monitoring and tuning: The system's performance monitoring module continuously tracks key performance indicators (such as CPU usage, memory usage, network traffic, database query time, etc.). When a performance indicator exceeds a preset threshold, the system generates a performance report and recommends tuning measures such as adjusting resource allocation, optimizing code, and optimizing queries. Through this continuous monitoring and tuning mechanism, the system can maintain high performance without affecting the user experience.

[0062] Horizontal Scaling and Autoscaling: In this embodiment, the system supports automatic expansion and scaling. Kubernetes' Horizontal PodAutoscaler dynamically adjusts the number of microservice replicas based on real-time load to cope with traffic peaks or save resources. The expansion and scaling process is transparent to users, and the system guarantees service continuity and availability, ensuring stable operation under high load conditions.

[0063] The performance optimization and expansion module ensures the efficient operation of the system under different conditions through monitoring and automatic adjustment, providing guarantee for the stability and flexibility of the system.

[0064] 4. System maintenance and upgrade 4.1 Regular maintenance and backup In this embodiment, the system maintenance and backup module ensures the long-term stable operation of the system and the security of data through regular system inspection, upgrade and data backup.

[0065] System maintenance plan: The system sets a regular maintenance window during which necessary system checks, upgrades, and backups are performed. The maintenance plan includes operating system updates, container image updates, database optimization, etc. Users will be notified before system maintenance, and a maintenance report will be automatically generated after maintenance is completed to help users understand the maintenance content and system changes.

[0066] Automated backup and recovery: The system uses CronJob to regularly back up key data and configuration files. The backup files are stored in cloud storage and automatically encrypted to ensure data security. In the event of data corruption or system failure, the system can quickly recover from the backup, minimizing business interruption and ensuring stable system operation.

[0067] The system maintenance and backup module ensures the long-term stability of the system and data security through regular maintenance and data backup, providing a guarantee for business continuity.

[0068] 4.2 System Upgrade In this embodiment, the system upgrade module ensures that the continuity of service is not affected during the system upgrade process through a seamless upgrade mechanism and an automatic rollback function.

[0069] Seamless upgrade mechanism: The system upgrade adopts the rolling update mechanism. When Kubernetes updates the microservice image, it replaces the old version of the container instance one by one to ensure that the service is not interrupted. The system will perform a compatibility check before upgrading to ensure that the new version is compatible with the existing configuration and data, reducing the upgrade risk.

[0070] Rollback and recovery: If a problem occurs during the upgrade process, the system can automatically roll back to the version before the upgrade. Kubernetes supports fast rollback by managing the history of Deployment, ensuring that the system can quickly return to a stable state. After an upgrade fails, the system will generate an error report to help developers analyze the problem and further optimize the system.

[0071] The system upgrade module ensures that the system can be updated without affecting business, and can be quickly rolled back when problems occur, thus ensuring the stability and continuity of the system.

[0072] 5. System expansion and secondary development 5.1 Modular Expansion In this embodiment, the modular expansion module allows developers to develop new functional modules according to needs and integrate them seamlessly into the existing system, thereby enhancing the scalability of the system.

[0073] New module development: Developers can develop new functional modules according to their needs. The new module development follows the microservice design principle. Each module runs independently and interacts with other modules through APIs. The system provides SDK and development documents to help developers quickly get started and ensure that the new module is compatible with the existing system.

[0074] Module integration and testing: After development is complete, the new module needs to undergo integration testing. The test environment is consistent with the production environment to ensure that the new module can run seamlessly after integration. After passing the test, the module will be packaged as a Docker image and pushed to the image repository, ready to be deployed to the production environment at any time.

[0075] Modular expansion modules ensure that the system can be flexibly expanded according to business needs, and the functions and performance of the system can be continuously enhanced through the development and integration of new modules.

[0076] 5.2 Secondary development and customization In this embodiment, the secondary development and customization module allows users to perform secondary development according to their own needs through an open API and plug-in mechanism, thereby further expanding the functions and application scope of the system.

[0077] Custom development services: The system provides an open API and plug-in mechanism, allowing users to perform secondary development and customization according to their own needs. Developers can write custom plug-ins to expand the functions of the system, such as adding new data processing logic, customized report generation, special event processing, etc.

[0078] Plugin management and configuration: All plugins are managed through the plugin manager. The plugin manager supports plugin installation, upgrade, uninstallation, configuration, and other operations. Users can configure the plugin's operating parameters, such as startup conditions, input and output data formats, and error handling mechanisms, through configuration files or interfaces to ensure that the plugin can work seamlessly with other parts of the system.

[0079] The secondary development and customization module provides users with the ability to customize the system through open API and plug-in mechanism, enhances the flexibility and adaptability of the system, and meets the personalized needs of different users.

[0080] Although 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 the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A modularized smart water utility light application rapid construction system, characterized in that: include: A template library management module is used to store and manage multiple preset function templates, each of which is used to perform a specific function in water management; A parameter configuration module, communicating with the template library management module, is used to perform parameter configuration on the selected function template according to user requirements, wherein the parameter configuration includes data source configuration, operation parameter setting and output option selection; A system combination and deployment module is used to combine the parameterized and configured function templates into a complete application system, and deploy the application system into the operating environment through containerization technology and Kubernetes orchestration tools; An operation monitoring and maintenance module is used to monitor the system status in real time during the operation of the application system, and automatically alarm and handle abnormal situations; The system expansion and upgrade module is used to support the function expansion and version upgrade of the application system, and the function expansion and version upgrade are achieved by dynamically loading new function templates and automatic deployment.

2. According to claim 1, a modularized smart water affairs light application rapid construction system is characterized in that: The template library management module includes: A template layered architecture, wherein the template layered architecture comprises a plurality of industry template layers and a functional template layer; The industry template layer presets multiple industry templates according to different water management scenarios, and each industry template corresponds to a group of functional templates; Each functional template consists of multiple sub-modules, including a data input module, a data processing module and a visualization module. The functional template is defined by a domain-specific language (DSL), which describes the structure of the template, input and output interfaces, parameterized configuration items and its dependencies with other modules.

3. According to claim 1, a modularized smart water affairs light application rapid construction system is characterized in that: The template library management module also includes: The template version control submodule is used to manage version updates of function templates. The version control submodule manages template update records through Git or similar version control systems, and supports version rollback and viewing and recovery of template historical versions.

4. According to claim 1, a modularized smart water affairs light application rapid construction system is characterized in that: The parameter configuration module includes: A dynamic form generator is used to generate a parameter configuration form according to the specific requirements of the function template selected by the user. The dynamic form includes a data source connection information configuration field, a data synchronization rule selection field, and an output result visualization option configuration field; The data source connection information configuration field is used to input the connection information of the data source, including but not limited to IP address, port number, database type, and authentication information; The data synchronization rule selection field is used to configure the data refresh frequency and synchronization rules; The output result visualization option configuration field is used to select and configure the visualization style of the output data, including line chart, pie chart, bar chart, and dashboard visualization options.

5. According to claim 1, a modularized smart water affairs light application rapid construction system is characterized in that: The parameter configuration module also includes: The data source verification submodule verifies the validity of the data source connection through the RESTful API. The verification submodule automatically verifies the input connection information when the configuration form is submitted, and returns an error prompt when the verification fails.

6. According to claim 1, a modularized smart water affairs light application rapid construction system is characterized in that: The system combination and deployment module includes: Docker container packaging tool, used to encapsulate the parameterized function template into an independent Docker image, wherein the Docker image includes the application code, runtime environment, and required dependent libraries of the function template; The Kubernetes orchestration submodule is used to deploy function templates through Pods in Kubernetes. The Pods dynamically allocate computing resources, network configurations, and persistent storage volumes according to the operating requirements of the function templates.

7. According to claim 1, a modularized smart water affairs light application rapid construction system is characterized in that: The Kubernetes orchestration submodule includes: The service automatic discovery and configuration submodule is used to automatically configure the internal DNS name and IP address of the service during the deployment of the function template, ensure stable communication between services through the Kubernetes Service object, and support automatic expansion and load balancing of services.

8. According to claim 1, a modularized smart water affairs light application rapid construction system is characterized in that: The operation monitoring and maintenance module includes: A central log management submodule is used to centrally collect the operation logs of each functional module in the system, including access logs, error logs, and operation logs. The log management submodule stores the log data in Elasticsearch or a similar log management system; The Kibana integration submodule is used to perform real-time visual analysis of the log data, support viewing the system operation status through the dashboard, set alarm rules and automatically generate alarm notifications when anomalies are detected in the log.

9. According to claim 1, a modularized smart water affairs light application rapid construction system is characterized in that: The central log management submodule also includes: The log archiving and auditing submodule is used to regularly archive and encrypt the operation logs for storage, providing long-term log preservation. The auditing function records detailed logs of system operations, including user logins, configuration changes, and permission management. All audit logs are stored in a read-only database in an unalterable manner.

10. The modularized smart water affairs light application rapid construction system according to claim 1 is characterized in that: The system expansion and upgrade module includes: The rolling update submodule is used to gradually replace the container instances of the old version through the rolling update mechanism of Kubernetes when the system version is upgraded, and automatically roll back to the previous version when the upgrade fails.

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