Cloud Data Center Validation Governance Platform
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Solution Overview
Problem
Conventional techniques for using infrastructure as code to develop data centers on cloud platforms fail to provide automated validation and governance during the building, provisioning, and deployment processes, especially for platform-independent declarative specifications.
Innovation Solution
A system that performs end-to-end validation and governance of changes made to a platform-independent declarative specification of a data center by retrieving predefined validation rules, simulating platform-specific metadata representation, and ensuring approval from designated data center entity owner teams, using a cloud platform-independent infrastructure language.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated validation and governance mechanisms are implemented for infrastructure as code, then reliability and security of data center deployments are improved, but device complexity and process overhead increase
Solution Approach 1:
The validation system is segmented into distinct modular components: a validation rule engine that manages validation rules separately, a simulation engine that handles platform-specific metadata generation, and a governance module that manages approval workflows. This segmentation allows each component to be developed, maintained, and scaled independently, reducing overall system complexity while maintaining comprehensive validation and governance capabilities.
Solution Approach 2:
The system performs preliminary validation and simulation actions before actual data center deployment. By validating infrastructure as code against predefined rules and simulating platform-specific metadata generation in advance, the system identifies and corrects issues before they impact production environments, improving reliability while keeping the operational complexity manageable through automated preliminary checks.
2Reliability
If manual validation and approval processes are used for infrastructure as code changes, then governance control is improved, but productivity and deployment speed deteriorate
Solution Approach 1:
The system implements automated feedback loops where validation results and simulation outcomes are immediately returned to the deployment pipeline. Validation rules automatically assess infrastructure as code changes, and approval workflows provide structured feedback to stakeholders. This feedback mechanism maintains strong governance control while enabling rapid iterative improvements and faster deployment cycles compared to purely manual processes.
Solution Approach 2:
The validation system performs self-service validation of infrastructure as code changes against predefined rules without requiring constant manual intervention. The automated validation engine independently assesses code changes, and the simulation engine autonomously generates platform-specific metadata, freeing human operators to focus on strategic decision-making while maintaining governance oversight, thereby improving deployment speed without sacrificing control.
3Adaptability or versatility
If platform-specific metadata representation is simulated for each cloud platform, then adaptability to different cloud platforms is improved, but computing resources and time consumption increase
Solution Approach 1:
The system creates simplified copies or representations of platform-specific metadata through simulation rather than executing full platform deployments. The simulation engine generates mock platform-specific metadata that mirrors the structure and key characteristics of actual cloud platform metadata, enabling validation of platform independence without consuming the full computational resources required for actual platform deployments, thus reducing energy and time consumption while maintaining adaptability.
Data Source
AI summary
A system receives one or more modifications to a platform-independent declarative specification from a set of data center entity owner teams to generate a modified platform-independent declarative specification that captures various aspects for deploying a data center on a target cloud platform. The system performs end-to-end validation of the modifications in multiple phases, starting with validating the modifications based on a set of predefined rules associated with the modified platform-independent declarative specification. When all the multiple phases of validation indicate success, the system a notification of end-to-end validation success in association with the received changes. Each request to modify a data center entity in the platform-independent declarative specification undergoes governance checks to ensure that the approver of the request belongs to a predefined set of owners associated with the data center entity.