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Performance-Based Classification of Users in a Containerized Stock Trading Application Environment Under Load

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Gepubliceerd in:Electronics vol. 14, no. 14 (2025), p. 2848-2874
Hoofdauteur: Rak Tomasz
Andere auteurs: Drabek, Jan, Charytanowicz Małgorzata
Gepubliceerd in:
MDPI AG
Onderwerpen:
Big Data
Machine learning
User behavior
Performance measurement
Data mining
Classification
Applications programs
Reliability
Design
Data analysis
Data collection
User experience
Sustainable development
Automation
Stock exchanges
Resource utilization
Statistical analysis
Workloads
Response time (computers)
Business metrics
Data logging
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Samenvatting:Emerging digital technologies are transforming how consumers participate in financial markets, yet their benefits depend critically on the speed, reliability, and transparency of the underlying platforms. Online stock trading platforms must maintain high efficiency underload to ensure a good user experience. This paper presents performance analysis under various load conditions based on the containerized stock exchange system. A comprehensive data logging pipeline was implemented, capturing metrics such as API response times, database query times, and resource utilization. We analyze the collected data to identify performance patterns, using both statistical analysis and machine learning techniques. Preliminary analysis reveals correlations between application processing time and database load, as well as the impact of user behavior on system performance. Association rule mining is applied to uncover relationships among performance metrics, and multiple classification algorithms are evaluated for their ability to predict user activity class patterns from system metrics. The insights from this work can guide optimizations in similar distributed web applications to improve scalability and reliability under a heavy load. By framing performance not merely as a technical property but as a determinant of financial decision-making and well-being, the study contributes actionable insights for designers of consumer-facing fintech services seeking to meet sustainable development goals through trustworthy, resilient digital infrastructure.
ISSN:2079-9292
DOI:10.3390/electronics14142848
Bron:Advanced Technologies & Aerospace Database