Automated Cloud Connectivity via SD-WAN Tagging
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Solution Overview
Problem
Enterprise networks with complex topologies face challenges in establishing and managing network connectivity, leading to lower uptime and stability, as well as a lack of desirable features due to the increased strain on network administrators.
Innovation Solution
The implementation of automated methods and systems for connecting on-premises sites to cloud resources using software-defined wide-area networks (SD-WAN) and software-defined cloud infrastructure (SDCI), which involve configuring virtual cross-connects, border gateway protocol (BGP) parameters, and tagging virtual networks to establish secure and dynamic connections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automated methods and systems are implemented for connecting on-premises sites to cloud resources, then the workload on network administrators is reduced and connectivity stability is improved, but the device complexity and initial configuration requirements increase
Solution Approach 1:
The system enables automated self-service through programmatic interfaces that allow the system to automatically discover cloud resources, map them to on-premises network segments, and establish connections without requiring manual administrative intervention for each connection. The automated workload mapping system performs these tasks autonomously based on predefined policies and resource tags.
Solution Approach 2:
The patent introduces an intermediary automated workload mapping system that acts as a mediator between on-premises network administrators and cloud resources. This intermediary handles the complex configuration tasks, resource discovery, and connection management, shielding administrators from complexity while maintaining ease of operation.
2Adaptability or versatility
If diverse and complex network topologies are implemented to fulfill enterprise demands, then network functionality and adaptability are improved, but network stability and uptime are reduced
Solution Approach 1:
The patent segments the complex network connectivity problem into manageable components by automatically discovering individual cloud resources, mapping them to specific on-premises network segments, and establishing dedicated connections for each. This segmentation approach maintains network functionality while improving stability through organized, modular connection management.
Solution Approach 2:
The system implements dynamic connection management that automatically adapts to changing network demands and cloud resource availability. Connections are dynamically established, modified, or terminated based on real-time conditions, allowing the network to maintain both adaptability and stability through automated adjustment rather than static complex configurations.
3Device complexity
If manual methods are used for establishing and managing network connectivity, then device complexity is reduced, but time consumption and connectivity stability are increased
Solution Approach 1:
The system performs preliminary actions by pre-configuring automated discovery mechanisms, establishing mapping policies in advance, and pre-defining connection parameters. When cloud resources are deployed or modified, the system automatically executes the predefined connection establishment process, significantly reducing the time required compared to manual configuration while maintaining manageable complexity through automation.
Solution Approach 2:
The patent replaces manual mechanical configuration processes with automated programmatic systems. Instead of administrators manually configuring each connection, the system uses automated workload mapping, resource discovery, and connection establishment processes that execute programmatically, reducing both time consumption and the burden of complexity management.
4Productivity
If automated workload mapping and dynamic connection establishment are implemented, then productivity and connectivity speed are improved, but device complexity and configuration requirements are increased
Solution Approach 1:
The automated workload mapping system performs self-service by automatically discovering cloud resources, determining appropriate on-premises network segments based on resource tags and policies, and establishing connections without requiring detailed manual configuration. This self-service approach improves productivity while managing complexity through autonomous operation.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor cloud resource states, connection status, and network conditions. Based on this feedback, the system automatically adjusts and maintains optimal connections, improving productivity through rapid adaptation while managing complexity through closed-loop control rather than static complex configurations.
Data Source
AI summary
The present technology pertains to receiving a tag associating at least one routing domain in an on-premises site with at least one virtual network in a cloud environment associated with a cloud service provider. The present technology also pertains to the automation of populating route and propagation tables with the cloud service provider.