Automated Cloud Infrastructure Management Transfer
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Solution Overview
Problem
The management and administration of complex distributed computing systems have become increasingly inefficient due to the complexity of scaling, maintaining, and migrating infrastructure across different cloud platforms, leading to difficulties in transitioning existing cloud infrastructure to new management systems without risking operational anomalies or system failures.
Innovation Solution
An automated method for generating parameterized cloud templates that represent already deployed cloud infrastructure, using existing data representations and an infrastructure-discovery service to detect drift and manage the transition, ensuring accurate and efficient management transfer without manual errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual methods are used to transfer cloud infrastructure management, then flexibility and control are maintained, but time consumption and risk of human error increase
Solution Approach 1:
The system performs self-service by automatically generating parameterized cloud templates from existing infrastructure data representations. The infrastructure-discovery service autonomously detects drift and the system automatically manages the transfer process without manual intervention, thereby reducing both time consumption and human error while maintaining high transfer accuracy
Solution Approach 2:
The patent replaces manual mechanical operations with automated computational processes. Instead of manual configuration and transfer operations, the system uses automated template generation, drift detection algorithms, and programmatic infrastructure management to achieve faster and more accurate transfers
2Productivity
If automated management transfer is implemented, then efficiency and speed improve, but complexity of the system increases
Solution Approach 1:
The infrastructure-discovery service acts as an intermediary between the existing cloud infrastructure and the new management system. It generates data representations and detects drift automatically, serving as a bridge that simplifies the overall transfer process while enabling automated management transfer with high efficiency
Solution Approach 2:
The system uses parameterized cloud templates that capture the state and configuration of existing infrastructure as parameters. By transforming infrastructure state into parameterized representations, the system automates the transfer process while managing complexity through structured parameter handling rather than raw configuration management
3Measurement precision
If comprehensive drift detection is performed, then accuracy of template generation improves, but computational overhead increases
Solution Approach 1:
The infrastructure-discovery service extracts only the essential state information and configuration parameters needed for drift detection from the complex cloud infrastructure. By extracting and representing only the critical parameters in data representations, the system achieves accurate drift detection while minimizing computational overhead through selective information extraction
Data Source
AI summary
The current document is directed to an infrastructure-as-code (“IaC”) cloud-infrastructure-management service or system that automatically generates a parameterized cloud template that represents an already deployed cloud-based infrastructure managed by a different cloud-infrastructure-management service or system and that uses the parameterized cloud template to assume management of the already deployed cloud-based infrastructure. The IaC cloud-infrastructure-management service or system uses an infrastructure-discovery service as well as data representations of the already deployed cloud-based infrastructure generated by the different cloud-infrastructure-management service or system to generate the parameterized cloud template and to detect drift in the already deployed cloud-based infrastructure.