Cloud Orchestrator for On-Demand RPA Robot Provisioning
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Solution Overview
Problem
The inefficiency of maintaining continuously running robots in local computing infrastructure for robotic process automation (RPA) due to high costs, as they often operate idle and require significant maintenance.
Innovation Solution
Implementing cloud-based management of RPA robots using a cloud orchestrator that allows for on-demand creation, provisioning, and scheduling of robots in a cloud computing environment, enabling efficient resource utilization and cost reduction by using virtual machines and virtual private networks to access local networks securely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RPA robots are continuously running on local computing infrastructure, then reliability and availability are improved, but operational cost and resource waste increase due to idle robots
Solution Approach 1:
The patent implements dynamic robot provisioning where robots are spun up on-demand in the cloud computing environment based on job requirements and spun down when not in use. This dynamic allocation allows the system to maintain high availability when needed while minimizing operational costs during idle periods, directly resolving the contradiction between reliability and energy loss.
Solution Approach 2:
The patent introduces a cloud computing environment as an intermediary between the user and the RPA robot execution. This intermediary enables on-demand robot creation and management, allowing users to access robots only when needed without maintaining continuous local infrastructure, thus reducing operational costs while maintaining availability.
2Ease of operation
If local computing infrastructure is used for RPA, then direct access to local networks is improved, but device complexity and maintenance requirements increase
Solution Approach 1:
The patent uses a cloud-based orchestrator and virtual machine infrastructure as intermediaries to manage network access. The orchestrator handles job distribution and robot management, while virtual machines provide secure access to local networks through controlled connections. This eliminates the need for users to maintain complex local RPA infrastructure while preserving network access capabilities.
Solution Approach 2:
The patent creates virtual machine copies in the cloud that replicate the necessary RPA environment and capabilities. These virtual copies enable robots to execute workflows and access networks without requiring physical local infrastructure, simplifying the user's device complexity while maintaining operational functionality.
3Loss of energy
If cloud-based RPA robots are used on-demand, then operational cost is reduced, but robot creation and provisioning time increases
Solution Approach 1:
The patent implements pre-configured robot templates and images that are prepared in advance in the cloud computing environment. When a job is submitted, the orchestrator can quickly instantiate robots from these pre-prepared templates rather than creating them from scratch, significantly reducing provisioning time while maintaining the cost benefits of on-demand cloud deployment.
Solution Approach 2:
The patent enables dynamic adjustment of robot parameters such as scaling the number of robots, changing resource allocation, and modifying execution configurations based on job requirements. This flexibility allows the system to optimize both cost and provisioning time by adjusting parameters like robot count and specification to match actual workload demands.
Data Source
AI summary
Systems and methods for implementing robotic process automation (RPA) in the cloud are provided. An instruction for managing an RPA robot is received at an orchestrator in a cloud computing environment from a user in a local computing environment. In response to receiving the instruction, the instruction for managing the RPA robot is effectuated.