This paper is published in Volume-6, Issue-1, 2020
Area
Machine Learning
Author
Sudipto Nandan
Org/Univ
Oracle India Pvt. Ltd., Bengaluru, Karnataka, India
Pub. Date
16 February, 2020
Paper ID
V6I1-1242
Publisher
Keywords
Anomaly Detection, Benchmarking, Isolation Forest, Performance Testing, Principal Component Analysis, Regression Results, Web Application

Citationsacebook

IEEE
Sudipto Nandan. Performance Benchmark using Machine Learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Sudipto Nandan (2020). Performance Benchmark using Machine Learning. International Journal of Advance Research, Ideas and Innovations in Technology, 6(1) www.IJARIIT.com.

MLA
Sudipto Nandan. "Performance Benchmark using Machine Learning." International Journal of Advance Research, Ideas and Innovations in Technology 6.1 (2020). www.IJARIIT.com.

Abstract

Software Performance testing is one of the important aspects of testing a product. It is more important when we have a cloud application, i.e. not a standalone application but a web application. Many of us use various tools like JMeter to test the performance of different web requests. But how do we analyze the results of JMeter? A failed Request is easy to catch. What about performance degradation? How do we know if a request performed worse than the previous runs or not? How do we take into consideration other environmental parameters – memory, processing power, operating system limits, etc? Performance benchmark using machine learning is one of the ways using which we can take care of some of these manual study and detection of performance regressions which may otherwise go unnoticed.
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