Cross-Platform RPA System Using Docker and Kubernetes
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Solution Overview
Problem
Traditional robotic process automation (RPA) systems face challenges in being deployed and run across different operating systems, limiting their applicability in diverse business environments.
Innovation Solution
A cross-platform RPA system is developed, comprising an automation process development platform, a control center, and a robot, all built using languages and technologies like GoLang, Python, and JavaScript, enabling cross-platform deployment and operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RPA software is developed based on Microsoft OS technology architecture, then it can run smoothly on Windows platform, but it becomes difficult to run on platforms other than Windows
Solution Approach 1:
The patent implements a universal RPA software architecture that can execute on multiple operating systems (Windows, Linux, macOS, and domestic OS) by replacing the Windows-specific technology stack with cross-platform alternatives: GoLang programming language, Linux operating system, Docker containerization, and Kubernetes orchestration. This enables the same RPA software to function reliably across diverse platforms without requiring separate versions for each OS.
2Productivity
If RPA software relies on Windows-specific technology architecture, then automation processes can be executed efficiently on Windows, but deployment on other operating systems is limited
Solution Approach 1:
The patent introduces Docker containers as an intermediary layer between the RPA software and the underlying operating system. The Docker container packages the RPA application with all its dependencies, creating a portable execution environment that can run consistently across different OS platforms. Kubernetes serves as another intermediary for orchestration and resource management, enabling efficient deployment and execution of RPA processes on Linux-based systems while maintaining productivity.
3Device complexity
If RPA system is designed for specific operating system, then system complexity is reduced, but the system cannot be deployed in diverse business environments
Solution Approach 1:
The patent segments the RPA system into independent, modular components: the RPA application itself, Docker container runtime environment, Kubernetes orchestration layer, and underlying operating system. This segmentation allows each component to be developed, deployed, and managed independently while working together seamlessly. The modular architecture reduces overall system complexity by creating clear boundaries and interfaces between components, while simultaneously enabling deployment in diverse business environments through the flexible Docker-Kubernetes stack.
Data Source
AI summary
Provided are a robotic process automation system and method across operating systems. The system includes an automation process development platform, a control center, and a robot. The automation process development platform is configured to design a corresponding automation business process according to a business scenario requirement, translate the automation business process into a corresponding process code, perform cross-platform encapsulation on the process code, and package the encapsulated cross-platform process code and send the encapsulated cross-platform process code to the control center. The control center is configured to schedule the robot deployed in different operating systems to execute the automation business process corresponding to the cross-platform process code. The robot is configured to download the cross-platform process code to a local operating system, call a process parser of a corresponding category to perform process parsing on the cross-platform process code, and execute the parsed automation business process.