Graph-Based Network Configuration Change Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Network service outages and disruptions often result from misconfigurations in network devices, which are difficult to identify and resolve due to the complexity of enterprise networks, leading to wasted time and productivity loss.
Innovation Solution
A configuration change identification server uses graph-based techniques to programmatically collect and compare network device configurations over time, generating a forensic timeline of changes to isolate misconfigurations and provide early warnings for risky changes, thereby minimizing and quickly resolving networking issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration changes are made by network administrators, then network device functionality can be updated and maintained, but the risk of misconfiguration increases leading to network service outages and disruptions
Solution Approach 1:
The system performs preliminary analysis of configuration changes before they are applied to network devices. By comparing proposed configurations against historical data, dependency graphs, and best practices, the system identifies potential misconfigurations and issues before they can cause service outages, thus preventing harmful effects before they occur.
Solution Approach 2:
The system implements continuous monitoring and feedback loops that track configuration changes, device performance, and service health. When misconfigurations are detected or potential issues are identified, the system provides immediate feedback to administrators and can automatically trigger remediation actions, creating a closed-loop system that continuously improves network reliability.
2Loss of time
If comprehensive configuration monitoring and analysis is implemented, then misconfigurations can be identified and resolved quickly, but the complexity of the network management system increases
Solution Approach 1:
The system introduces an intermediary configuration management platform that sits between network administrators and the actual network devices. This intermediary handles the complexity of comprehensive monitoring, analysis, and comparison tasks, while presenting a simplified interface to administrators. The intermediary automatically performs graph-based analysis, historical comparison, and issue identification, reducing the perceived complexity for users while enabling comprehensive monitoring.
Solution Approach 2:
The network management system is divided into modular components: configuration collection modules, graph generation modules, comparison modules, analysis modules, and remediation modules. Each module handles a specific aspect of configuration management independently, making the overall complex system manageable through clear separation of concerns. This segmentation allows the system to perform comprehensive monitoring without overwhelming administrators with a monolithic complex interface.
3Measurement precision
If detailed forensic timelines of configuration changes are generated and analyzed, then the root cause of network issues can be identified more accurately, but the computational resources and processing time required increase
Solution Approach 1:
The system applies partial analysis by focusing computational resources on the most critical and recent configuration changes, rather than analyzing every single configuration event in equal detail. By using dependency graphs to identify which configuration blocks are most likely to cause issues and prioritizing analysis of changes in high-risk areas, the system achieves high measurement precision for root cause identification while avoiding the computational expense of exhaustive analysis of all configuration data.
Data Source
AI summary
In one example, a logical representation of a first graph is generated. The first graph indicates a configuration of a network device in a network at a first time. The first graph includes a first node representative of a first configuration block of the network device, a second node representative of a second configuration block of the network device, and a first link that indicates, by connecting the first node and the second node, that the first configuration block is associated with the second configuration block. The logical representation of the first graph is compared to a logical representation of a second graph that indicates an actual or planned configuration of the network device at a second time subsequent to the first time. In response, one or more changes in the configuration of the network device from the first time to the second time are identified.