Cloud-Agnostic Network Model for Legacy Integration
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Solution Overview
Problem
Current solutions for integrating an existing cloud network into a target cloud network face challenges due to mismatched network and connectivity models, especially when legacy code does not follow established guidelines, leading to incomplete integration and increased complexity.
Innovation Solution
A method involving a multi-site orchestrator that inventories network resources, generates mappings, and creates logical resources to represent these in a cloud-agnostic network configuration model, allowing for the provisioning of a target cloud network, thereby enabling a more comprehensive and successful integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If legacy cloud network resources are integrated into a target cloud network, then network connectivity and functionality are improved, but integration complexity and mismatches increase due to legacy code not following established guidelines
Solution Approach 1:
The patent introduces a cloud-agnostic network configuration model as an intermediary layer between the existing cloud network and the target network. This model acts as a mediator that translates legacy network resources into a standardized representation, enabling integration without direct complexity from legacy systems. The multi-site orchestrator uses this intermediary model to manage mappings between different network resource types across cloud providers.
Solution Approach 2:
The patent segments the integration process into distinct phases: inventorying network resources, generating mappings, creating logical resources in the cloud-agnostic model, and provisioning the target network. This segmentation allows complex integration tasks to be broken down into manageable steps, reducing overall integration complexity while maintaining reliable connectivity.
2Adaptability or versatility
If a cloud-agnostic network configuration model is created to represent existing cloud network resources, then adaptability to different cloud environments is improved, but computational resource usage and processing time increase
Solution Approach 1:
The patent creates a virtual copy of the existing cloud network in the form of a cloud-agnostic network configuration model. This model replicates the essential structure and connectivity information of the legacy network without physically migrating resources, enabling adaptability to different cloud environments through a standardized representation rather than full replication of all network details.
Solution Approach 2:
The patent performs preliminary inventorying and mapping of network resources before the actual integration. By pre-processing and creating the cloud-agnostic model in advance, the system prepares the necessary transformation logic and resource mappings, reducing computational overhead during the actual provisioning phase and improving overall efficiency.
3Manufacturing precision
If network resources are inventoried and mapped in detail, then integration accuracy is improved, but processing time and system complexity increase
Solution Approach 1:
The patent applies partial action by inventorying and mapping only the essential network resources and connectivity information needed for integration, rather than processing every detail of the entire legacy network. The cloud-agnostic model captures sufficient semantic information to enable accurate integration while avoiding the time-consuming processing of redundant or unnecessary network details.
Data Source
AI summary
This disclosure describes techniques for integrating an existing cloud network into a new cloud network. The techniques may include inventorying network resources of an existing cloud network in a multi-cloud network environment. The techniques may also include creating logical resources to represent the network resources of the existing cloud network in a cloud-agnostic network configuration model. In some examples, a target cloud network may be provisioned using the cloud-agnostic network configuration model.


