Load Testing Engine Reproducing Production Traffic Patterns
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Solution Overview
Problem
Existing load testing systems fail to accurately simulate real-world traffic patterns, making it difficult to replicate production issues effectively.
Innovation Solution
The method involves capturing real-world traffic from VPC flow logs, Load Balancers, and API Gateways, and using a distributed load testing engine to reproduce these patterns by leveraging computing nodes in multiple regions, allowing for accurate simulation of traffic from different geographic locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fake load patterns are generated by existing load testing systems, then load testing can be performed, but the accuracy of simulating real-world traffic patterns deteriorates
Solution Approach 1:
The patent captures real production traffic data and creates copies of actual traffic patterns to use in load testing. Instead of generating synthetic fake traffic, the system records genuine user requests, responses, and timing information from production environments, then replays these captured patterns against test systems to accurately replicate real-world behavior and identify bottlenecks.
2Measurement precision
If real production traffic is captured and replayed, then accuracy of bottleneck identification improves, but system complexity increases
Solution Approach 1:
The system performs preliminary capture and analysis of production traffic patterns before conducting load tests. By pre-processing and storing real traffic data in a reusable format, the system eliminates the need for complex real-time generation of realistic traffic patterns during testing, simplifying the overall system architecture while maintaining high measurement precision.
Data Source
AI summary
Implementations for providing load testing services that access logs as a basis for generating simulated traffic patterns are described. The access logs may be used to generate a pattern of events. The pattern of events may indicate a number of occurrences of an event at various times in a time period. The events may be distributed to geographically dispersed computing nodes to cause simulation of requests from different geographic locations using the pattern of events.