Autonomic Microservice Management via Agentic AI and MAPE-K Integration

TL;DR

This paper introduces a framework combining agentic AI with MAPE-K to enable autonomous management and security of microservices, addressing decentralization challenges in cloud environments.

Contribution

It presents a novel integration of agentic AI with MAPE-K for autonomous microservice anomaly detection and remediation, enhancing system stability and security.

Findings

Effective anomaly detection and remediation demonstrated

Framework customizable for various system attributes

Improves microservice system robustness and security

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.