Citation:

Santosh Kumar Kotakonda, 2025. "A Novel Approach to Automated Performance Testing for Web Applications using JMeter and BlazeMeter", ESP Journal of Engineering & Technology Advancements  5(4): 145-149.

Abstract:

Software delivery is accelerated by the use of CI/CD pipelines. However, they are accompanied by a very high risk of introducing performance regression, especially when high-stakes workloads such as those in the financial sector are involved. This paper proposes a methodology known as Continuous Financial Performance Assurance (CFPA) methodology which integrates Apache JMeter for realistic scenario test design, BlazeMeter for scalable cloud execution, and Jenkins automation for pipelining all together. The CFPA methodology brings into existence automated performance Quality Gates based on deep SLOs explicitly mapped to business KPIs, hence making a contribution at the core of this methodology. This SLI-to-KPI correlation model will move performance testing from being reactive in defect-detection to being proactive in financial risk management regarding build promotions that are likely to surpass an organization's allowed financial error budget.

References:

[1] S. Chen and X. Li, "Integrating Automated Performance Quality Gates into CI/CD Pipelines for Critical Systems," Journal of Automated Software Engineering, vol. 28, no. 1, pp. 45-60, 2021.

[2] M. Davis and E. Rodriguez, "Quantifying Financial Risk from Application Latency: An SLI-to-KPI Conversion Model," International Journal of Software Engineering and Knowledge Engineering, vol. 32, no. 5, pp. 601-620, 2022.

[3] A. Gupta and P. Sharma, "Stochastic Load Generation using Poisson Processes for High-Volume Web Application Testing," IEEE Transactions on Reliability, vol. 70, no. 3, pp. 110-125, 2020.

[4] J. Kim, T. Lee, and B. Park, "The Economic Impact of Service Reliability on Customer Churn in Financial Technology," Journal of Financial Data Science, vol. 3, no. 1, pp. 88-105, 2023.

[5] R. Alvarez and L. G. Mendez, "Advanced JMeter Techniques for Dynamic Correlation and Maintainable Scripting in Agile Performance Engineering," ACM Transactions on Software Engineering and Methodology, vol. 30, no. 4, pp. 1-28, 2021.

[6] H. C. Wong and D. K. Lin, "Performance Modeling and Latency Control in Pervasive Mobile Financial Applications," Mobile Networks and Applications, vol. 27, no. 6, pp. 2005-2020, 2022.

[7] E. Clark and N. Singh, "From Operational Metrics to Financial Accounting: Linking Application Performance to Business Accounting Indicators," Management Information Systems Quarterly, vol. 45, no. 2, pp. 501-518, 2020.

[8] S. K. Patel and G. R. Smith, "A Survey of Cloud-Native Performance Testing Platforms for Enterprise-Scale Continuous Testing," Future Generation Computer Systems, vol. 125, pp. 110-125, 2021.

[9] K. L. Johnson and M. A. Peterson, "The Quantified Cost of Waiting: Modeling Conversion Rate Decay Due to Web Latency," Journal of Interactive Technology, vol. 15, no. 4, pp. 401-415, 2023.

Keywords:

Continuous Performance Engineering, Financial Services, JMeter, BlazeMeter, Jenkins, CI/CD, Quality Gates, Service Level Objectives (SLOs), Customer Churn.