Cloud Network Configuration Analysis for Cross-Region Isolation
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Solution Overview
Problem
The complexity of large-scale, geographically-dispersed cloud-based networks makes it difficult for administrators to analyze and determine network routing criteria, predict network changes, and identify communication issues between resources.
Innovation Solution
Automated network analysis using a reasoning engine to model network conditions, optimize implementation sequences, and ensure compliance with constraints, while maintaining isolation between segments through packet header metadata and segment-specific routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated network analysis using reasoning engine is implemented, then network management efficiency is improved, but device complexity increases
Solution Approach 1:
A reasoning engine is introduced as an intermediary component between network administrators and the complex network infrastructure. The reasoning engine automates the analysis of network configuration data, generates implementation sequences, and predicts network changes, thereby improving network management efficiency without requiring administrators to directly handle the underlying complexity of large-scale geographically-dispersed networks.
2Reliability
If segment-specific routing with packet header metadata is used, then network isolation between segments is improved, but device complexity increases
Solution Approach 1:
The network is divided into multiple isolated segments with segment-specific routing. Packet header metadata including segment identifiers are used to route packets within specific segments, ensuring that network traffic from one segment cannot access resources in another segment unless explicitly permitted. This segmentation approach improves network isolation and security while managing complexity through structured routing rules.
3Measurement precision
If automated analysis of network configuration data is performed, then measurement precision of network conditions is improved, but loss of time for data processing increases
Solution Approach 1:
The system performs preliminary automated analysis of network configuration data by collecting and storing configuration data from multiple network devices, building a comprehensive network model in advance. This preliminary action enables the reasoning engine to quickly query and analyze network conditions without requiring real-time data processing, thereby improving measurement precision while minimizing time loss during actual network operations.
Data Source
AI summary
Systems and methods are provided for obtaining policy data associated with a private network implemented at least partly within a cloud provider network; establishing, based on the policy data, a first segment within the private network, wherein in a first geographic region of the cloud provider network, traffic associated with the first segment is isolated from traffic associated with a second segment of the private network, and wherein in a second geographic region of the cloud provider network, traffic associated with the first segment is isolated from traffic associated with a third segment of the private network; obtaining metadata indicating an isolated network of the cloud provider network is associated with the first segment; and enabling the isolated network to communicate, over the first segment, across the first geographic region and the second geographic region.