Advanced Performance Diagnostics in Modern Architectures: Thread Dump Analysis as a Key to Sustainable Scalability

Authors

  • Hitesh Jodhavat, Chandra Sekhar Kondaveeti, Rama Krishna Prasad Bodapati

Keywords:

thread dump analysis, sustainable scalability, performance diagnostics, resource utilization, machine learning, deadlock detection, distributed systems.

Abstract

Modern software architectures, characterized by distributed systems and microservices, face significant challenges in maintaining performance and scalability under increasing workloads.This study explores the role of thread dump analysis as a key diagnostic tool for identifying performance bottlenecks and ensuring sustainable scalability. By analyzing thread states, resource utilization, and system behavior under varying load conditions, the research uncovers critical issues such as thread contention, deadlocks, and inefficient resource allocation.

References

Caino-Lores, S., Carretero, J., Nicolae, B., Yildiz, O., & Peterka, T. (2019). Toward high performance computing and big data analytics convergence: The case of spark-diy. IEEE Access, 7, 156929-156955.

Choudhuri, S., & Gupta, A. (2024). Integrating AI with Cloud Engineering for Real-Time Data Processing and Analytics in IoT Applications. Sarcouncil Journal of Engineering and Computer Sciences, 3(7), 8-14.

Geimer, M., Wolf, F., Wylie, B. J., Ábrahám, E., Becker, D., & Mohr, B. (2010). The Scalasca performance toolset architecture. Concurrency and computation: Practice and experience, 22(6), 702-719.

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Published

2025-01-10

How to Cite

Hitesh Jodhavat, Chandra Sekhar Kondaveeti, Rama Krishna Prasad Bodapati. (2025). Advanced Performance Diagnostics in Modern Architectures: Thread Dump Analysis as a Key to Sustainable Scalability . Journal of Computational Analysis and Applications (JoCAAA), 34(1), 418–434. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/2088

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Section

Articles