Differential Node Configuration Visualization for Network Policy Compliance
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Solution Overview
Problem
Managing networks with diverse node configurations is challenging due to variations in operating systems, hardware, and software, leading to unpredictable installation consequences and the need for effective visualization and policy compliance across nodes.
Innovation Solution
A scan engine identifies attributes for each node, computes variance measures, and displays them in a differential grid view using color, texture, or pattern indicators, with a policy engine defining compliance policies and visualizing policy failures, allowing operators to reconfigure outlier nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network administrators manually monitor and compare node configurations, then configuration compliance can be maintained, but the time and effort required increases significantly for large networks
Solution Approach 1:
The system enables automated self-monitoring of node configurations through the scan engine that automatically discovers and compares configuration attributes across nodes without requiring manual administrator intervention for each comparison
Solution Approach 2:
Manual configuration monitoring and comparison tasks are replaced by an automated scan engine that uses software agents to collect, transmit, and analyze configuration data, substituting human mechanical effort with automated computational processes
2Measurement precision
If detailed configuration data is collected from all nodes, then comprehensive variance analysis is possible, but the complexity of managing and visualizing the data increases
Solution Approach 1:
The configuration data is segmented into discrete attributes that can be independently analyzed and visualized. The differential grid view divides the network into node segments, allowing administrators to focus on specific configuration aspects rather than overwhelming detailed data from all nodes
Solution Approach 2:
The system uses color-coded visual indicators in the differential grid view to represent configuration variance levels, transforming complex numerical data into intuitive visual patterns that are easy to interpret at a glance
3Reliability
If configuration differences between nodes are identified, then policy violations can be detected, but the difficulty of determining which nodes to reconfigure increases
Solution Approach 1:
The differential grid view provides immediate visual feedback about configuration variances and policy compliance status for each node, enabling administrators to quickly identify which nodes require reconfiguration based on their position and visual indicators in the grid
Data Source
AI summary
An operator node is configured to generate a visualization of the configurations of nodes communicatively coupled to the operator node via a network. The operator node scans target nodes in a network and identifies a set of attributes describing various configuration properties of each node. The operator node compares corresponding attributes across nodes and determines for each attribute a measure of variance. The variance for each attribute is displayed in a grid view, allowing a user to observe the level of similarity or dissimilarity of each attribute across the target nodes of the network. The operator node also defines and implements a policy describing a set of configuration properties with which target nodes must comply. The operator node determines if one or more target nodes is in violation of the policy, displays a differential visualization associated with each policy failure event, and enables an operator to re-configure target nodes accordingly.