A Comprehensive Survey on Root Cause Analysis in (Micro) Services: Methodologies, Challenges, and Trends

TL;DR

This survey reviews various root cause analysis techniques in microservices, highlighting methodologies, challenges, and future trends to improve fault diagnosis and system stability.

Contribution

It provides a comprehensive structured overview of RCA methods in microservices, including recent advancements and future research directions.

Findings

Various RCA methodologies using metrics, traces, logs, and multi-model data

Challenges include complex dependencies and propagative faults in microservices

Future trends involve AI and automation for improved fault diagnosis

Abstract

The complex dependencies and propagative faults inherent in microservices, characterized by a dense network of interconnected services, pose significant challenges in identifying the underlying causes of issues. Prompt identification and resolution of disruptive problems are crucial to ensure rapid recovery and maintain system stability. Numerous methodologies have emerged to address this challenge, primarily focusing on diagnosing failures through symptomatic data. This survey aims to provide a comprehensive, structured review of root cause analysis (RCA) techniques within microservices, exploring methodologies that include metrics, traces, logs, and multi-model data. It delves deeper into the methodologies, challenges, and future trends within microservices architectures. Positioned at the forefront of AI and automation advancements, it offers guidance for future research directions.