AI Visual Cloud Infrastructure Diagrams for Sync and Deployment
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Solution Overview
Problem
Current cloud infrastructure management tools require significant manual effort and synchronization challenges between cloud architecture diagrams and code, leading to out-of-sync components and difficulties in rolling back to original versions.
Innovation Solution
A system and method for creating and managing cloud infrastructures using Infrastructure as a Diagram (IAD), which includes an AI-powered visual interface for diagram creation, automatic validation, layout correction, cost estimation, version history, and deployment without Continuous Integration and Continuous Deployment (CI/CD) pipelines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If infrastructure-as-code tools like Terraform are used to automate provisioning, then productivity is improved, but device complexity increases due to need for code validation, CI/CD pipeline setup, and synchronization maintenance
Solution Approach 1:
The patent replaces the mechanical/code-based infrastructure-as-code system with an AI-based visual diagram system. Instead of requiring users to write and validate code snippets in Terraform or similar tools, the system uses AI to automatically generate, validate, and manage cloud infrastructure configurations through visual diagrams. This substitution eliminates the complex code validation and CI/CD pipeline processes while maintaining automation capabilities.
Solution Approach 2:
The patent introduces an AI intermediary layer between the user's visual diagram intentions and the actual cloud infrastructure provisioning. This AI intermediary automatically translates visual diagrams into executable infrastructure configurations, handles validation, and manages synchronization without requiring users to directly interact with complex code systems. The AI acts as a mediator that simplifies the interaction while maintaining full automation.
2Manufacturing precision
If manual code writing and validation is performed for each component, then manufacturing precision is improved, but loss of time increases due to repetitive coding and synchronization maintenance
Solution Approach 1:
The patent implements self-service through AI automation. The system automatically generates code configurations from visual diagrams, performs validation checks, and maintains synchronization without requiring manual intervention. The AI self-services by translating user diagram intentions into accurate infrastructure configurations, eliminating the need for repetitive manual coding while maintaining precision through AI-driven validation.
Solution Approach 2:
The patent performs preliminary actions by pre-validating and pre-configuring infrastructure components before deployment. The AI system proactively checks for configuration errors, validates component compatibility, and ensures synchronization readiness in advance, eliminating the need for time-consuming manual validation during the deployment process while maintaining high precision.
3Ease of operation
If infrastructure changes are made directly in cloud, then ease of operation is improved, but loss of information increases due to lack of synchronization tracking and version control
Solution Approach 1:
The patent implements continuous feedback mechanisms that automatically track, monitor, and report synchronization status between visual diagrams and actual cloud infrastructure. The system provides real-time feedback on configuration drift, version changes, and synchronization state, ensuring that users always have accurate information about the current state of their infrastructure while maintaining ease of direct modification operations.
Solution Approach 2:
The patent creates and maintains accurate copies of infrastructure state information through versioned diagram snapshots and configuration records. Each change to the cloud infrastructure is automatically copied and recorded in the version history, preserving complete information about previous states and enabling accurate tracking of all modifications while maintaining ease of operation.
4Adaptability or versatility
If comprehensive cloud management features are integrated, then adaptability is improved, but device complexity increases due to multiple validation and synchronization mechanisms
Solution Approach 1:
The patent implements universality by designing a single AI-based visual diagram platform that can manage multiple cloud environments (AWS, Azure, GCP, etc.) through unified interfaces. The AI system learns and adapts to different cloud provider specifications, allowing the same diagram-based approach to work across diverse cloud platforms without requiring separate validation and synchronization mechanisms for each provider, thus reducing overall complexity while maintaining versatility.
Data Source
AI summary
Embodiments herein disclose systems and methods for creating and managing the cloud infrastructures. The system receives at least one input as a at least one component related to the cloud architecture on a visual interface from a user for creating an infrastructure as a diagram (IAD) for a cloud architecture. The created infrastructure as a diagram (IAD) is validated. A price estimation is generated by the system based on the at least one component in the infrastructure as a diagram (IAD). The created infrastructure as a diagram (IAD) is approved by a defined approver on receiving at least one approval request from the user. A selected infrastructure as a diagram (IAD) for the cloud infrastructure is deployed by the system on receiving at least one deployment request.