AI-Generated IaC for Cloud Infrastructure Configuration

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Solution Overview

Problem

Configuring cloud infrastructure resources is challenging due to the vast number of available cloud platforms and resources, requiring technical expertise and is prone to errors, leading to delays in software development or deployment.

Innovation Solution

A system utilizing artificial intelligence, specifically machine learning-based language models, generates Infrastructure-as-Code (IaC) from natural language requests to configure cloud platforms, iteratively refining configurations until the desired state is achieved, and supports multiple cloud platforms without the need for extensive repositories or indexes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If users manually configure cloud infrastructure resources, then technical expertise and knowledge are required, but the process is cumbersome and error-prone

Engineering Contradiction:

Improveease of configurationVSAvoidconfiguration accuracy

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The patent introduces an AI assistant as an intermediary between users and cloud infrastructure configuration. The assistant translates natural language requests into accurate infrastructure configurations, eliminating the need for users to directly interact with complex configuration systems. This mediator handles the translation and validation, ensuring both ease of operation and configuration accuracy simultaneously.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces manual mechanical configuration processes with an AI-based automated system. Instead of users manually selecting and configuring resources through complex interfaces, the system uses machine learning models to automatically generate and validate configurations based on natural language descriptions, substituting human expertise with an automated intelligent system.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If users manually configure cloud resources, then technical expertise is required, but the process causes delays in software development or deployment

Engineering Contradiction:

Improvedeployment speedVSAvoidconfiguration time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent implements preliminary action by having the AI assistant prepare and validate infrastructure configurations before deployment. The system proactively generates complete, validated configurations based on natural language requests, eliminating the need for users to perform time-consuming manual configuration steps during the deployment process.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent substitutes manual mechanical configuration operations with automated AI-driven configuration generation. The machine learning model rapidly translates natural language requests into ready-to-deploy infrastructure configurations, dramatically reducing the time required compared to manual resource selection and configuration.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Adaptability or versatility

If the system supports multiple cloud platforms, then versatility is improved, but the complexity of managing different resource types increases

Engineering Contradiction:

Improvecloud platform compatibilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent applies universality by designing a unified AI assistant that can handle multiple cloud platforms through a single interface. The system uses a common natural language understanding layer that works across AWS, Azure, GCP, and other platforms, translating diverse cloud resource requirements into platform-specific configurations automatically, thus achieving multi-platform support without increasing user-side complexity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The AI assistant serves as a universal intermediary that abstracts the complexity of different cloud platforms from the user. It translates high-level natural language requests into platform-specific configurations, handling the complexity of multiple resource types and platform differences internally while presenting a simple unified interface to users.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20250321746A1Artificial intelligence based configuration of computing infrastructure on cloud platforms

Publication Date: 2025.10.16 PULUMI CORP

AI summary

A system receives a natural language request for configuring a computing infrastructure using a cloud platform. The system executes a machine learning based language model to generate infrastructure-as-code (IaC) to configure a cloud platform to obtain the desired computing infrastructure. The system may display the IaC generated by the machine learning based language model via a user interface as an example for use by the user. The system may send instructions to the cloud platform to provision computing infrastructure in accordance with the IaC obtained from the machine learning based language model. The system may repeatedly determine whether the desired computing infrastructure is deployed on the cloud platform and if the computing infrastructure currently provisioned on the cloud platform fails to match the desired computing infrastructure according to the natural language request, the system reconfigures the computing infrastructure deployed on the cloud platform.