Human-AI Collaboration in Cloud-Based Distributed Systems: Automating Resilience Testing

This comprehensive article examines the evolution and current state of resilience testing in cloud-based distributed systems, focusing on integrating artificial intelligence and human expertise.The article explores how traditional testing methodologies have transformed by adopting chaos engineering principles and AIdriven automation, significantly improving system reliability and performance.The article investigates the symbiotic relationship between human analysts and AI systems in testing environments, demonstrating how their collaboration enhances technical capabilities and business outcomes.The article further delves into practical implementation considerations, including infrastructure requirements, monitoring systems, and integration challenges, providing insights into successful deployment strategies for AI-augmented testing frameworks in enterprise environments.

Publication Details

Journal
International Research Journal of Modernization in Engineering Technology and Science
Published
2025-06-03
DOI
https://doi.org/10.56726/irjmets67466
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
0.00
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article

Human-AI Collaboration in Cloud-Based Distributed Systems: Automating Resilience Testing

International Research Journal of Modernization in Engineering Technology and Science
Software System Performance and Reliability
article

Human-AI Collaboration in Cloud-Based Distributed Systems: Automating Resilience Testing

article en

Abstract

This comprehensive article examines the evolution and current state of resilience testing in cloud-based distributed systems, focusing on integrating artificial intelligence and human expertise.The article explores how traditional testing methodologies have transformed by adopting chaos engineering principles and AIdriven automation, significantly improving system reliability and performance.The article investigates the symbiotic relationship between human analysts and AI systems in testing environments, demonstrating how their collaboration enhances technical capabilities and business outcomes.The article further delves into practical implementation considerations, including infrastructure requirements, monitoring systems, and integration challenges, providing insights into successful deployment strategies for AI-augmented testing frameworks in enterprise environments.

International Research Journal of Modernization in Engineering Technology and Science
Openalex Percentile: Top 87%
Software System Performance and Reliability
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