Scale Testing Scenario Generator for High Interaction Volume
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Solution Overview
Problem
Existing scale testing methods lack efficiency in simulating high interaction volumes, limiting the effectiveness of testing devices under high user loads, connections, and bandwidth conditions.
Innovation Solution
The system generates and optimizes scenarios for scale testing by parsing and optimizing packet captures, converting them into immutable scenarios that can be executed in tracks with varying concurrency levels, using a scheduler to manage resources and prioritize execution based on memory and OS thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing scale testing methods are used to simulate high interaction volumes, then the device can be tested under high user loads and connections, but the testing efficiency is low and the achievable interaction volume is limited
Solution Approach 1:
The system performs preliminary actions by capturing real network traffic patterns before testing, analyzing them to extract realistic interaction sequences, and pre-configuring test scenarios based on actual usage data. This preparation work enables the testing system to efficiently generate high volumes of realistic interactions without wasting time on unrealistic or redundant test cases, thereby resolving the contradiction between achieving high interaction volumes and maintaining testing efficiency
Solution Approach 2:
The system creates copies of real network traffic patterns by capturing actual communications between hosts and device under test, then replicating these patterns at scaled-up volumes. Instead of generating synthetic test traffic, the system copies authentic interaction sequences and multiplies them to achieve high interaction volumes while preserving realism, thus improving both the quantity of interactions and the efficiency by avoiding unrealistic test scenarios
2Reliability
If packet captures are processed for scale testing, then realistic test scenarios can be generated, but processor cycles and memory usage increase
Solution Approach 1:
The system extracts only the essential elements from captured packet data needed for scale testing, such as interaction sequences, timing patterns, and protocol structures, while discarding redundant details like specific payload contents or unnecessary header information. This selective extraction maintains test scenario realism by preserving critical behavioral patterns while significantly reducing the processing burden and memory requirements
Solution Approach 2:
The system performs preliminary analysis and optimization of packet captures before they are used in scale testing. During this preliminary phase, the captured traffic is parsed, validated, and transformed into optimized test scenario definitions that retain realism but require fewer processor cycles to execute, thus resolving the contradiction between reliability and energy use
3Quantity of substance
If high concurrency levels are used in scale testing, then more realistic load conditions are achieved, but resource allocation becomes more complex and difficult to manage
Solution Approach 1:
The system implements dynamic resource allocation that automatically adjusts to varying concurrency levels during scale testing. The resource manager monitors system state and dynamically allocates or deallocates resources based on current test demands, enabling the system to handle high concurrency levels efficiently without requiring complex static configurations, thus resolving the contradiction between achieving high concurrency and managing resource allocation complexity
Data Source
AI summary
Various example embodiments are directed to scale testing based on scenarios. A computer system may receive a scenario, which may comprise a plurality of scenario objects including, a first host, a second host, a plurality of transports, a plurality of variables and a plurality of steps. The computer system may also receive a pattern. The scenario may be processed to generate a processed scenario. The computer system may execute a first track including executing a plurality of concurrencies of the processed scenario according to the pattern.