Network Policy Violation Detection Using Data Samples
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Solution Overview
Problem
Server virtualization in large and dynamic data centers leads to configuration and troubleshooting complexity, with trivial errors potentially causing significant network performance declines and taking weeks to diagnose.
Innovation Solution
A system and method that collect data samples from network nodes, determine policy violations using sensors and a network service sentinel, and generate alerts, reducing troubleshooting time from weeks to minutes by automatically detecting policy breaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual configuration and troubleshooting methods are used in virtualized data centers, then operational flexibility is maintained, but troubleshooting time increases to weeks and complexity increases
Solution Approach 1:
The system implements self-service through automated policy violation detection and alerting. Sensors continuously monitor network traffic and automatically identify policy violations without human intervention. The system generates alerts and notifications autonomously, enabling the network management system to self-diagnose and self-report issues, thereby reducing troubleshooting time from weeks to minutes while managing complexity through automation.
2Productivity
If automated policy violation detection is implemented, then troubleshooting time is reduced to minutes, but system complexity increases
Solution Approach 1:
The system segments the network monitoring function into independent sensors deployed at various network nodes. Each sensor independently monitors its local segment for policy violations. This segmentation distributes the computational burden and simplifies the overall system architecture, allowing automated detection across the entire network while maintaining manageable complexity at each segment level.
Solution Approach 2:
The system introduces sensors as intermediary components between network traffic and the central management system. These sensors act as mediators that automatically detect policy violations in network traffic and translate them into structured alerts. This intermediary layer handles the complexity of policy evaluation and violation detection, freeing the central management system from direct involvement in detailed analysis while maintaining high troubleshooting efficiency.
3Reliability
If continuous network monitoring is implemented to detect policy violations, then network reliability is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic monitoring through sensors that continuously sample network traffic at intervals rather than analyzing every single packet in real-time. This periodic sampling approach maintains network policy compliance detection capability while significantly reducing energy consumption compared to continuous deep packet inspection. The sensors periodically assess traffic patterns and detect policy violations without requiring constant full-bandwidth analysis.
Data Source
AI summary
Disclosed herein are a system, computer-readable medium, and method for enforcing network policies. Samples of data traveling through at least some nodes of a network are collected. It is determined whether a node violated a predefined network policy based on the samples.