Cloud Management Connectivity Assurance via Protected Configurations
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Solution Overview
Problem
Cloud management systems face challenges in maintaining connectivity with network devices due to unintended configuration changes, which can lead to loss of management capabilities and inability to rollback such changes.
Innovation Solution
The cloud management system learns and aggregates network connectivity data to generate a protected configuration for network devices, preventing configuration changes that could disrupt connectivity and identifying root causes of connectivity loss, allowing for corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud management systems allow configuration changes on network devices, then network adaptability and management flexibility are improved, but connectivity reliability deteriorates due to unintended configuration changes that can disrupt connectivity
Solution Approach 1:
The system performs preliminary actions by learning and aggregating network connectivity data before configuration changes are made. It identifies connectivity paths and generates protected configurations in advance, so when a configuration change is proposed, the system can predict its impact on connectivity before the change is applied, preventing unintended disruptions.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring network connectivity data and using this information to inform configuration change decisions. When connectivity is lost, the system provides feedback about the root cause and suggests corrective actions, creating a closed-loop system that learns from past events and improves future connectivity assurance.
2Reliability
If cloud management systems implement connectivity assurance mechanisms, then connectivity reliability is improved, but system complexity increases due to the need to learn and aggregate network connectivity data
Solution Approach 1:
The system applies self-service by automatically learning and aggregating network connectivity data without requiring manual intervention. The cloud management system autonomously discovers connectivity paths, identifies protected configurations, and generates alerts when connectivity is at risk, reducing the operational burden on network administrators while maintaining high connectivity reliability.
3Reliability
If cloud management systems provide comprehensive connectivity monitoring, then connectivity reliability is improved, but information processing requirements increase, leading to longer response times for identifying root causes
Solution Approach 1:
The system extracts only the essential connectivity information needed for assurance, rather than processing all available network data. By focusing on learning and aggregating specific connectivity paths and protected configurations, the system reduces information processing overhead while maintaining comprehensive monitoring capabilities, enabling faster identification of root causes when connectivity issues occur.
Data Source
AI summary
The disclosed technology relates a system is configured to generate a protected configuration for a network device based on network connectivity data for a plurality of devices in a managed network associated with a cloud management system. The system is further configured to receive a configuration change for the managed network, determine that the configuration change is incompatible with the protected configuration, and generate a notification that the configuration change is incompatible with the protected configuration.