Application-Aware SD-WAN Routing Policies with Analytics-Based SLA Control
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Solution Overview
Problem
Existing Application-Aware Routing (AAR) policies in SD-WANs are static and reactive, requiring manual configuration and often fail to accurately reflect application requirements, leading to inefficient data routing and potential SLA violations due to outdated policies.
Innovation Solution
An adaptive mechanism for AAR policies that uses an analytics engine to generate and dynamically update routing policies based on network insights, ensuring accurate and proactive path selection to meet application SLAs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static AAR policies are manually configured, then device complexity is reduced, but adaptability to changing network conditions deteriorates
Solution Approach 1:
The system enables self-service by allowing the network to automatically generate and update AAR policies based on real-time traffic analysis and SLA monitoring, eliminating the need for manual policy configuration while maintaining high adaptability to changing network conditions
Solution Approach 2:
The system implements feedback mechanisms where traffic flow data and SLA compliance information are continuously monitored and fed back into the policy generation process, enabling dynamic policy updates that adapt to changing network conditions without manual intervention
2Reliability
If reactive AAR policies are used, then ease of operation is improved, but reliability deteriorates due to SLA violations
Solution Approach 1:
The system performs preliminary action by proactively generating and updating AAR policies before SLA violations occur, using predictive analysis of traffic patterns and network conditions to prevent violations rather than reacting to them after they happen
Solution Approach 2:
The system continuously monitors SLA compliance and uses this feedback to dynamically adjust policies, ensuring reliable SLA adherence through real-time policy optimization rather than static reactive rules
3Productivity
If manual policy updates are performed, then manufacturing precision is improved, but productivity deteriorates due to frequent updates being overlooked
Solution Approach 1:
The system performs self-service by automatically generating and updating policies based on real-time network conditions, eliminating the need for manual updates while maintaining high policy accuracy through continuous algorithmic optimization
Solution Approach 2:
The system ensures continuity of useful action by continuously monitoring network conditions and updating policies in real-time, preventing the deterioration of policy accuracy that occurs when manual updates are overlooked between periodic maintenance windows
4Adaptability or versatility
If preferred paths are set statically, then ease of operation is improved, but adaptability deteriorates when ISP networks change
Solution Approach 1:
The system implements dynamics by transforming static path preferences into dynamic, real-time path selection based on current network conditions, traffic patterns, and SLA requirements, enabling automatic adaptation when ISP networks change without manual reconfiguration
Solution Approach 2:
The system uses feedback from continuous network monitoring and traffic analysis to dynamically adjust preferred paths, ensuring adaptability to ISP network changes while avoiding the complexity of manual path reconfiguration through automated decision-making
Data Source
AI summary
This disclosure describes techniques for improving routing policy awareness in a network. The method includes detecting, by a controller, an application initiated for use at an edge node of a network. Then, generating, by an analytics engine coupled to the controller, analytical data of traffic flow at the edge node of the network wherein the traffic flow is in accordance with a routing policy for routing traffic associated with the application. Further, routing of the traffic through a path from one or more paths configured at the edge node that is in accordance with at least a Service Level Agreement (SLA) for traffic flow. Also, in response to an SLA violation during routing of the traffic, causing an action, by the controller, of routing traffic flow through another path that is in accordance with at least the SLA for traffic flow based on analytical data received of the traffic flow.