Rack Layout Verification for Custom Data Center Cabling
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Solution Overview
Problem
Designing complex data centers is a costly and error-prone process due to the complexity of configurations and interactions among numerous components, often requiring customization that existing pre-configured architectures cannot fully satisfy, leading to issues like missing parts, incorrect cabling, and lack of configuration data.
Innovation Solution
A solution designer mechanism utilizing microservices to facilitate customized data center design, including phases for rack elevations, point-to-point cabling, bill of materials validation, and supply chain management, supported by an online portal and tools for verification and configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If pre-configured architectures are used, then design time and cost are reduced, but customization capability is limited
Solution Approach 1:
The system segments the data center configuration into modular rack units, each containing standardized components. These modular racks can be independently configured and validated, allowing pre-configured templates to be used while still enabling customization by selecting and combining different rack configurations to meet specific organizational needs.
Solution Approach 2:
The system performs preliminary validation and verification of rack configurations before final deployment. By validating component compatibility, interconnections, and cabling requirements in advance using automated tools, the system enables use of pre-configured architectures while ensuring customization requirements are met, reducing both design time and errors.
2Adaptability or versatility
If extensive customization is performed, then organizational needs are better satisfied, but design complexity and error risk increase
Solution Approach 1:
The system implements automated validation that provides feedback on configuration errors, missing components, and cabling issues during the design phase. This feedback mechanism detects problems early before deployment, reducing error risk associated with customization while allowing extensive organizational-specific configurations.
Solution Approach 2:
The patent introduces automated design validation tools as intermediaries between the customization process and final deployment. These tools act as a mediator that checks configurations, validates component compatibility, and verifies interconnections, thereby managing design complexity and reducing errors without limiting customization capability.
3Manufacturing precision
If manual verification and testing are performed, then configuration accuracy is improved, but time consumption and cost increase
Solution Approach 1:
The system replaces manual verification processes with automated validation tools that use software-based checking mechanisms. These tools automatically validate rack configurations, component placements, interconnections, and cabling requirements, achieving high configuration accuracy while significantly reducing verification time compared to manual processes.
Solution Approach 2:
The validation system performs self-verification by automatically checking configurations against predefined rules and requirements. The system validates its own design outputs without requiring external manual testing, thereby improving configuration accuracy while minimizing additional time consumption.
Data Source
AI summary
Rack-based solution design and verification approaches are disclosed. A list of elements including at least computing resources, storage resources and connection resources for to a proposed data processing architecture is received. A physical layout of the computing resources and the storage resources is evaluated by a first set of microservices to parse configuration data for the computing resources and the storage resources and to evaluate a proposed configuration for the computing resources and the storage resources. Point-to-point connections between the computing resources and the storage resources in the proposed configuration are verified by a second set of microservices. The list of elements can be updated based on the evaluation of the physical layout and the point-to-point connections. A solution architecture is generated based on the updated list of elements, the physical layout, the verified point-to-point connections and the supply chain status information.