Cloud Environment Deployment via Configuration Management
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Solution Overview
Problem
The deployment of cloud environments across large organizations is hindered by heterogeneity in cloud services and technologies, requiring extensive manual intervention and taking weeks to complete, while existing automated methods are limited by hardware architecture and user data restrictions.
Innovation Solution
A method for rapid, automatic deployment of a cloud environment using a configuration management database to store and generate data for software components, reducing user input through a user interface and orchestrator-driven deployment sequence, with data validation and testing to ensure security and adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual deployment methods are used to accommodate heterogeneous cloud services and technologies, then adaptability to different organizational needs is improved, but deployment time increases to weeks and complexity increases
Solution Approach 1:
The system dynamically changes deployment parameters by automatically generating configuration data including random IP addresses, hostnames, and security credentials. This allows the same deployment framework to adapt to heterogeneous cloud environments without manual reconfiguration, reducing deployment time while maintaining adaptability to different organizational needs
Solution Approach 2:
The deployment system performs self-service by automatically discovering hardware architecture, generating configuration data, and deploying software components without requiring manual intervention. The system self-adapts to different cloud services and technologies through automated configuration generation, eliminating the time-consuming manual deployment process while preserving adaptability
2Productivity
If existing automated deployment methods are used, then deployment speed is improved, but restrictions on hardware architecture and user data reduce adaptability
Solution Approach 1:
The deployment system achieves universality by implementing a hardware-agnostic configuration generation approach that can deploy across diverse hardware architectures including virtual machines, bare metal servers, and containers. The system generates universal configuration data that adapts to different hardware types without requiring architecture-specific automation scripts, maintaining both high deployment speed and broad hardware adaptability
Solution Approach 2:
The system segments the deployment process into independent configuration generation and execution phases. By generating configuration data separately from the actual deployment execution, the system can adapt to different hardware architectures through configurable parameters without sacrificing deployment speed. This segmentation allows flexible adaptation to various hardware types while maintaining automated efficiency
3Ease of operation
If user-provided data is used for deployment, then initial setup is simplified, but security is reduced due to opaque data requirements
Solution Approach 1:
The system introduces an intermediary configuration generation layer between user input and actual deployment. Instead of requiring users to directly provide sensitive deployment data, the system generates secure configuration data (IP addresses, credentials, hostnames) as intermediaries that bridge user requirements with secure deployment practices. This maintains ease of operation while enhancing security through automated credential generation
Data Source
AI summary
A method for the rapid, automatic, and adaptative deployment of a cloud environment that is secure, that adapts to different hardware architectures, network architectures, cloud services, technologies, and user needs, and that requires minimal user input. Configuration data may be generated for a collection of software components, which may include user inputs and randomly generated data. This data may be stored in a configuration database that is updated as deployment proceeds. Available hardware such as servers, storage, and networks may be discovered automatically and added to the configuration database. An initial software component may be deployed to coordinate subsequent steps, and then additional software components may be deployed in a sequence that considers dependencies. Software components may be organized into deployment groups. Users may select subsets of the components to deploy. The deployed cloud environment may be tested and validated automatically.