Automated Data Center Mapping via Server Cluster Identification
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Solution Overview
Problem
Existing methods for onboarding data centers into communication networks are inefficient due to manual handling of data center mapping information, which consumes system resources and increases error rates and user interactions.
Innovation Solution
A computer-implemented method and device that automatically receive information about a data center, identify the server cluster type, output a predefined list to a user interface for obtaining mapping information, and store the structured mapping information, including identifiers of materials installed in the data center, in a storage device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual handling of data center mapping information is used, then user control and flexibility are maintained, but system resource consumption increases and error rates increase
Solution Approach 1:
The system automatically performs data center mapping by receiving information about the data center, identifying server cluster types, generating predefined lists, collecting mapping information, and storing structured data without requiring manual intervention. This self-service approach eliminates human errors while reducing system resource consumption associated with manual handling processes.
2Productivity
If manual handling of data center mapping information is used, then flexibility in data entry is maintained, but productivity decreases due to increased user interactions
Solution Approach 1:
The system performs preliminary actions by automatically receiving data center information, identifying server cluster types, and generating predefined lists before the user needs to provide mapping information. This preliminary automation reduces the number of user interactions required while maintaining ease of operation through structured, guided input processes.
3Use of energy by moving object
If automated data center mapping is implemented, then system resource usage is reduced and error handling is minimized, but implementation complexity increases
Solution Approach 1:
The automated mapping system is divided into distinct functional modules: receiving data center information, identifying server cluster types, generating predefined lists, collecting mapping information, and storing structured data. This segmentation manages implementation complexity by creating manageable, independent components that can be developed and maintained separately while achieving overall automation efficiency.
Data Source
AI summary
A computer-implemented method includes receiving information corresponding to a data center, the information including an identifier of a type of the data center, identifying a server cluster type according to the data center type, outputting, to a user interface, a predefined list configured to obtain mapping information from a user, wherein the predefined list and mapping information are structured based on the server cluster type, receiving the mapping information from the user interface in response to the predefined list, wherein the mapping information includes one or more identifiers of material installed in the data center, and storing the structured mapping information in a storage device.