Network Controller Dependency Model for Root Cause Analysis
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Solution Overview
Problem
Current network management systems face challenges in efficiently translating high-level configuration intents into low-level device configurations and detecting conflicts that may arise from new intents, which can impact the functionality of existing network devices.
Innovation Solution
A network management system that uses a controller device to determine resource dependencies through a mathematical dependency model, performing root cause analysis to identify and prevent conflicts, and maintaining backups to restore devices to a previous stable state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a controller device translates high-level configuration intents into low-level device configurations, then network configuration efficiency is improved, but the complexity of detecting and managing conflicts between intents increases
Solution Approach 1:
The system performs preliminary conflict detection by analyzing intent dependencies before deploying configurations to network devices. The controller device constructs a dependency model that identifies potential conflicts between intents in advance, preventing bad states from occurring rather than reacting to them after deployment.
Solution Approach 2:
The patent introduces an intent dependency model as an intermediary layer between high-level intents and low-level device configurations. This model serves as a mediator that analyzes relationships between intents, identifies conflicts, and manages dependencies without requiring direct complex interactions between all intent pairs.
2Reliability
If the controller device maintains backups of device configurations, then network reliability is improved, but the storage requirements and system resources increase
Solution Approach 1:
The system extracts and stores only the essential information needed for restoration - specifically the intent dependency model and key configuration states - rather than maintaining complete redundant backups of all device data. This selective extraction approach provides reliability while minimizing storage consumption.
3Measurement precision
If root cause analysis is performed using a mathematical dependency model, then the precision of failure diagnosis is improved, but the computational time and processing resources increase
Solution Approach 1:
The dependency model is constructed and analyzed in advance during normal operation, establishing the mathematical relationships between intents and device configurations before failures occur. This preliminary modeling enables rapid root cause analysis when failures happen, as the computational framework is already in place and只需 requires querying the pre-established relationships.
Data Source
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AI summary
A controller device manages a plurality of network devices. The controller device includes a memory configured to store a dependency model representing dependencies between resources provided by the network devices and a programmed merge strategy, and one or more processors implemented in circuitry and configured to: determine the resources provided by the network devices; determine relationships between the resources according to the programmed merge strategy; construct the dependency model using the determined relationships; determine that at least one of the resources has experienced a failure; and perform a root cause analysis using the dependency mathematical model to determine a root cause of the failure of the at least one of the resources.