Data Center Model Generation via Automated Switch Discovery
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Solution Overview
Problem
Current configuration management databases (CMDBs) in large-scale data centers face challenges in maintaining accurate and up-to-date information about devices and their dependencies, leading to limited effectiveness in managing complex networked systems.
Innovation Solution
Automatically generating a data model of the data center by collecting inventory data, switch-to-switch relationship data, and switch-to-server relationship data using protocols like ICMP, SNMP, CDP, and LLDP, and persisting this information to create a comprehensive mapping of devices and their connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual updates are used to keep CMDB information current, then information accuracy can be maintained, but the time and resources required become excessive
Solution Approach 1:
The system enables automatic self-updating of CMDB information by having devices and virtual machines self-register and self-report their configuration changes through agents or discovery protocols, eliminating the need for manual updates while maintaining information accuracy
Solution Approach 2:
The system implements continuous feedback loops where configuration data is automatically collected from devices, validated against the CMDB, and updated in real-time or near-real-time, ensuring information remains current without manual intervention
2Reliability
If detailed device relationship information is collected to improve troubleshooting and impact analysis, then the usefulness of the CMDB increases, but the complexity of data collection and management increases
Solution Approach 1:
The system performs preliminary automatic discovery of device relationships, topologies, and dependencies before troubleshooting or impact analysis is needed, pre-populating the CMDB with comprehensive relationship data so that when issues arise, the information is already available without requiring complex real-time data collection
Solution Approach 2:
The system uses universal discovery protocols and standardized data models that can collect relationship information from multiple device types and scenarios through a single unified approach, reducing the complexity that would otherwise require different collection methods for each device type
Data Source
AI summary
Systems and methods provide for automatically generating a data model of a data center. Inventory data identifying devices in the data center is obtained by querying the devices and/or extracting the data from existing data sources. In addition, switch-to-switch data regarding the linking relationships among switches is obtained by querying the switches in the data center using a discovery protocol. Further, switch-to-server relationship data regarding the linking relationships between switches and servers is obtained at least in part by querying switches in the data center for MAC table data to identify the MAC addresses of servers connected to the switches. The inventory data, switch-to-switch relationship data, and switch-to-server relationship data is persisted to the data model of the data center, thereby providing information identifying devices within the data center and the dependencies and relationships among the devices.