Automated Load Balancer Discovery via Traffic Flow Analysis
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Solution Overview
Problem
In networked systems, identifying load balancers is challenging as their identity is typically unknown a priori, affecting network performance and analysis.
Innovation Solution
A computer-implemented system that automatically identifies load balancers by collecting data from network communications, using a load balancer detector to match inbound and outbound flow sizes across timestamp windows, and applying criteria to determine if a system is a load balancer, even in cases with multiple IP addresses or combined requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated load balancer discovery is implemented, then network analysis capability is improved, but system complexity increases
Solution Approach 1:
The system performs self-discovery of load balancers by automatically monitoring network traffic and analyzing flow patterns without requiring manual configuration or prior knowledge of load balancer identities. The detection mechanism uses observed traffic characteristics to autonomously identify load balancers and establish their roles in the network topology.
Solution Approach 2:
The system continuously monitors network traffic flows and uses the observed patterns to refine its identification of load balancers. By analyzing the relationship between inbound and outbound traffic sizes and patterns, the system feedback-adjusts its understanding of network topology and load balancer positions, improving detection accuracy over time.
2Measurement precision
If comprehensive network traffic monitoring is performed, then load balancer detection accuracy is improved, but data processing requirements increase
Solution Approach 1:
The system extracts only the essential characteristics needed for load balancer identification from the comprehensive network traffic data. Specifically, it focuses on analyzing flow sizes, traffic patterns, and connection behaviors rather than processing every packet detail, thereby reducing data processing requirements while maintaining detection accuracy.
Solution Approach 2:
The network traffic monitoring is segmented into discrete flow units that can be independently analyzed. By dividing the continuous network traffic into manageable flow segments with specific characteristics (source, destination, size, timing), the system can process traffic data efficiently without being overwhelmed by the total volume of network communications.
Data Source
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AI summary
Computer-implemented systems and methods automatically identify computers that act as load balancers on a digital communications network, using data collected from one or more computers on that network. Once a load balancer has been identified, the communications between two hosts may be connected across the identified load balancer, thereby making it possible to better analyze the behavior of hosts and applications on that network.