Cloud OnRamp SaaS Policy Provisioning with Dynamic SD-WAN Routing
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Solution Overview
Problem
Traditional application-aware routing policies for SaaS applications rely on predefined paths and static routes, failing to consider real-time network performance and lack flexibility, leading to suboptimal path selection and requiring complex, error-prone manual configurations.
Innovation Solution
An automated SDWAN manager system that uses real-time monitoring and existing network information to dynamically generate optimized network policies for SaaS applications, minimizing human intervention and reducing configuration errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional application-aware routing policies use predefined paths and static routes, then configuration is simpler, but network performance optimization is poor and flexibility is limited
Solution Approach 1:
The patent implements dynamic routing policies that automatically adjust network paths based on real-time performance metrics. The system continuously monitors network conditions and dynamically modifies routing decisions, replacing static predefined paths with adaptive, condition-based routing that optimizes performance while maintaining manageable complexity through automation.
Solution Approach 2:
The system employs automated policy generation that self-configures optimal routing policies without requiring manual intervention. The automated generation process analyzes network topology and performance data to create optimized routing configurations, eliminating the trade-off between complexity and adaptability by making the system self-optimizing.
2Reliability
If manual configuration processes are used for Cloud OnRamp, then customization is possible, but error rates increase and configuration time extends
Solution Approach 1:
The patent implements automated policy generation that eliminates manual configuration processes. The system automatically generates optimized routing policies by analyzing network topology and performance data, thereby eliminating human errors while reducing configuration time. This self-service approach directly addresses both reliability and time efficiency concerns.
Solution Approach 2:
The system incorporates continuous monitoring of network performance metrics that provides feedback to the policy generation process. This feedback mechanism ensures that generated policies are optimized based on actual network conditions, improving reliability while maintaining rapid configuration through automation rather than manual processes.
3Productivity
If static routing paths are used, then configuration is more stable, but real-time network performance optimization is lost
Solution Approach 1:
The patent implements self-optimizing routing that automatically monitors network performance and adjusts paths without manual intervention. The system continuously collects performance metrics and autonomously makes routing decisions to optimize network efficiency, eliminating the need for complex manual monitoring and control while achieving superior productivity compared to static routing.
Solution Approach 2:
The system employs continuous feedback loops that monitor real-time network performance metrics and use this information to dynamically adjust routing decisions. This feedback-driven approach enables the system to optimize network efficiency automatically, replacing static paths with adaptive routing that responds to changing conditions without requiring complex manual control mechanisms.
Data Source
AI summary
In one aspect, a method includes accessing network topology data associated with a network, where the network topology data identifies a set of network devices, classifying respective network devices of the set of network devices based on a type of network device and interface information associated with the respective network devices, determining default values based on the network topology data and classification of the respective network devices, generating executable code for configuring a policy for the network based on the default values, and implementing the policy on the network.