AI Assistants for Incident Lifecycle in a Microservice Environment: A Systematic Literature Review

TL;DR

This systematic review explores how AI assistants are used across the incident lifecycle in microservice environments, highlighting current successes, research gaps, and future opportunities for improving incident management.

Contribution

It provides a comprehensive analysis of existing AI applications in incident management within microservices, identifying research gaps and proposing future directions.

Findings

AI assists improve incident detection and resolution

Research gaps exist in AI integration and real-time response

Future opportunities include enhanced automation and predictive analytics

Abstract

Incidents in microservice environments can be costly and challenging to recover from due to their complexity and distributed nature. Recent advancements in artificial intelligence (AI) offer promising solutions for improving incident management. This paper systematically reviews primary studies on AI assistants designed to support different phases of the incident lifecycle. It highlights successful applications of AI, identifies gaps in current research, and suggests future opportunities for enhancing incident management through AI. By examining these studies, the paper aims to provide insights into the effectiveness of AI tools and their potential to address ongoing challenges in incident recovery.