Network Configuration Update via Document Topology Analysis
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Solution Overview
Problem
Complex network configurations in modern datacenters, especially software-defined networks, make it difficult for administrators to identify and align existing network configurations with desired documentation, leading to challenges in making necessary configuration changes.
Innovation Solution
A system and method that uses network documentation, including diagrams and written descriptions, to update network configurations by interpreting symbols and text using Natural Language Processing and image processing techniques, creating an update topology, and comparing it to the existing configuration to identify changes and implement updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network administrators manually analyze complex network configurations to align with documentation, then configuration accuracy can be maintained, but time consumption and operational difficulty increase significantly
Solution Approach 1:
The patent replaces manual mechanical analysis of network configurations with automated image processing and natural language processing systems. The system captures network configuration images, processes them through AI models to extract topology information, and automatically generates configuration files, eliminating the need for administrators to manually compare diagrams with actual configurations.
Solution Approach 2:
The system enables the network configuration management process to serve itself by automatically extracting topology information from images, generating configuration files, and updating network devices without human intervention. The automated workflow includes capturing configuration images, processing them through AI models, generating configuration scripts, and pushing updates to devices autonomously.
2Device complexity
If traditional manual methods are used to update network configurations from documentation, then system complexity remains low, but the difficulty of detecting and measuring configuration differences increases
Solution Approach 1:
The patent replaces manual visual comparison methods with automated image processing and natural language processing systems. The system uses AI models to extract topology information from network configuration images, automatically identifies differences between documented and actual configurations, and generates update scripts without requiring administrators to manually analyze complex diagrams.
3Productivity
If automated configuration updates are implemented without documentation alignment, then productivity increases, but configuration reliability and accuracy decrease
Solution Approach 1:
The patent performs preliminary actions by capturing network configuration images and processing them through AI models before actual configuration updates are applied. The system extracts topology information from images, generates configuration files in advance, and validates them against the processed documentation, ensuring accuracy before deployment to network devices.
Solution Approach 2:
The system implements feedback mechanisms by continuously comparing processed documentation with actual network configurations, identifying differences, and validating generated configuration updates before application. This closed-loop approach ensures that automated updates maintain alignment with documented requirements, preserving reliability while enabling rapid deployment.
Data Source
AI summary
Systems and methods are disclosed for updating network configuration documentation. In an example, a user can upload network configuration documentation with updates to a network to a server. The server can create an update topology corresponding to the documentation by identifying symbols that represent network components. The server can identify changes by comparing the update topology to a configuration data of an existing network. For example, the address of a gateway or the connections to the gateway can change. The server can cause the changes to be presented to a user, such as by highlighting the changes in a diagram. The user can confirm the changes, such as with a conversational workflow, and the server can save the changes to a database. The system can also send commands to the applicable network components to effectuate the confirmed changes.