Edge Microservice Deployment With Visual Dependency Mapping
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Solution Overview
Problem
Existing container editing tools for deploying microservices on edge devices, such as Docker Compose and Docker Swarm, are complex and prone to confusion when managing large numbers of microservices, especially in industrial applications with unique network restrictions and real-time performance requirements.
Innovation Solution
A graphical management tool is used to establish a dependence relationship between edge devices and software module mirror images, automatically converting this relationship to a configuration file for deployment, and allocating communication port numbers, thereby simplifying the deployment process and adapting to specific industrial demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If container editing tools (Docker Compose, Docker Swarm) are used to deploy microservices, then microservice deployment capability is provided, but system complexity increases and dependence relationship management becomes difficult
Solution Approach 1:
The patent introduces an intermediary component that acts as a translator between the simple drag-and-drop graphical interface and the complex container orchestration tools. This intermediary automatically generates the necessary configuration files and commands, shielding users from the underlying complexity while maintaining full microservice deployment capability.
Solution Approach 2:
The patent replaces the manual mechanical process of writing and managing complex configuration files with an automated graphical interface system. Users interact through intuitive visual operations (drag-and-drop) instead of manually editing YAML or JSON configuration files, thereby reducing operational complexity while maintaining deployment functionality.
2Ease of operation
If manual configuration file editing is used for microservice deployment, then deployment control is achieved, but work efficiency decreases and errors increase
Solution Approach 1:
The system enables self-service deployment by automatically generating configuration files based on user actions in the graphical interface. The system itself performs the tedious configuration writing task, extracting necessary parameters from visual operations and autonomously creating the deployment manifests, thereby dramatically improving productivity while maintaining deployment control.
Solution Approach 2:
The patent performs preliminary actions by pre-generating configuration files and validating dependencies before actual deployment execution. The system prepares all necessary configuration data in advance based on the graphical interface operations, ensuring correctness before the deployment process begins, which prevents errors and improves efficiency.
3Loss of information
If dependence relationships between microservices are manually managed, then relationship tracking is possible, but confusion increases with large numbers of microservices
Solution Approach 1:
The patent transitions dependence relationship management from a textual/dimensional configuration file approach to a visual spatial representation in the graphical interface. Dependencies are displayed as visual connections and relationships in the graphical workspace, allowing users to comprehend and manage complex microservice dependencies through spatial visualization rather than parsing text-based configuration files.
4Ease of operation
If graphical management tools are used to simplify deployment, then ease of operation improves, but automation capability must be enhanced
Solution Approach 1:
The system implements feedback mechanisms where the graphical interface continuously monitors user actions and automatically updates the generated configuration files in real-time. As users drag and drop components or configure relationships visually, the system provides immediate feedback by updating the corresponding configuration data, ensuring consistency between the visual representation and the actual deployment configuration.
Data Source
AI summary
Various embodiments include a software module deployment method comprising: acquiring a self-description file of at least one edge device with a management device, the self-description file at least describing a software running environment and hardware resource information of the edge device; deploying a software module mirror image on a suitable edge device and establishing a connection relationship between different software module instances deployed on the edge device; automatically allocating, with the management device, a port number to be used when communication is actually performed to each software module instance deployed on the edge device; and generating a configuration file according to the software module instance deployed on each edge device, the connection relationship between different software module instances on the edge device, and the port number.