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arXiv · 2506.22185

Autonomic Microservice Management via Agentic AI and MAPE-K Integration

Matteo Esposito·Alexander Bakhtin·Noman Ahmad·Mikel Robredo·Ruoyu Su·Valentina Lenarduzzi·Davide Taibi
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Abstract

While microservices are revolutionizing cloud computing by offering unparalleled scalability and independent deployment, their decentralized nature poses significant security and management challenges that can threaten system stability. We propose a framework based on MAPE-K, which leverages agentic AI, for autonomous anomaly detection and remediation to address the daunting task of highly distributed system management. Our framework offers practical, industry-ready solutions for maintaining robust and secure microservices. Practitioners and researchers can customize the framework to enhance system stability, reduce downtime, and monitor broader system quality attributes such as system performance level, resilience, security, and anomaly management, among others.

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Matteo Esposito, Alexander Bakhtin, Noman Ahmad, Mikel Robredo, Ruoyu Su, Valentina Lenarduzzi, Davide Taibi. 2025-06-27. Autonomic Microservice Management via Agentic AI and MAPE-K Integration. https://arxiv.org/abs/2506.22185

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