Cloud Site Configuration Automation for Error-Free Deployment
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Solution Overview
Problem
Existing cloud computing infrastructure deployment processes are prone to errors and require significant manual intervention, leading to inefficiencies and inconsistencies in hardware and software configuration.
Innovation Solution
A system and method for automated cloud automation site design that utilizes a network software repository and installation system to implement algorithms for configuring site-specific hardware items, ensuring error-free deployment and interoperability through machine learning and AI-driven validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration processes are used for cloud computing infrastructure deployment, then flexibility in customization is maintained, but error rates increase and operational efficiency decreases
Solution Approach 1:
The system enables self-service through automated configuration where the cloud infrastructure deployment system automatically detects hardware specifications, selects appropriate software algorithms, and configures components without human intervention. The automated configuration system performs self-validation and self-correction, eliminating manual configuration steps that introduce errors while maintaining deployment flexibility through algorithmic decision-making.
Solution Approach 2:
The patent replaces manual mechanical configuration processes with automated software-based systems. The automated configuration system uses software algorithms to detect hardware, select configurations, and deploy software, substituting human operators with automated computational processes. This substitution maintains customization capability through algorithmic flexibility while eliminating human error and improving operational efficiency.
2Productivity
If manual configuration processes are used for cloud computing infrastructure deployment, then adaptability to specific hardware variations is maintained, but productivity and deployment speed decrease
Solution Approach 1:
The system replaces manual configuration mechanics with automated software algorithms that rapidly detect hardware specifications and select appropriate configurations. The automated system processes hardware detection, software selection, and configuration deployment at machine speed, dramatically increasing productivity compared to manual processes while maintaining adaptability through algorithmic decision-making based on hardware characteristics.
Solution Approach 2:
The automated configuration system dynamically changes configuration parameters based on detected hardware specifications. The system adjusts software algorithms, configuration settings, and deployment parameters automatically according to the specific hardware environment, maintaining adaptability to hardware variations while executing at automated speeds that greatly exceed manual configuration capability.
3Reliability
If consistent hardware and software configuration is implemented across cloud sites, then reliability and interoperability improve, but device complexity increases
Solution Approach 1:
The patent implements a universal automated configuration system that handles multiple functions: hardware detection, software algorithm selection, configuration generation, and deployment automation. This multi-functional system provides consistent configuration across different cloud sites and hardware types through a single unified platform, improving interoperability while consolidating complexity into a centralized automated system rather than distributed manual processes.
Solution Approach 2:
The system creates and maintains configuration templates that can be copied and adapted across multiple cloud sites. Once a configuration is validated at one site, it can be replicated to other sites with similar hardware specifications, ensuring consistency and interoperability. The copying mechanism reduces the need to recreate configurations manually at each site, improving reliability while the template management system handles the complexity centrally.
Data Source
AI summary
A system for configuring a network, comprising a network software repository operating on a first processor and configured to store one or more algorithms for each of a plurality of hardware items and to implement version control for each of the one or more algorithms. A network software installation system operating on a second processor is configured to install a current version of one or more algorithms on each of a plurality of site-specific hardware items and to configure each of the plurality of site-specific hardware items to interoperate with each other.