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

July 23, 2024 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: A Comprehensive Survey on Root Cause Analysis in (Micro) Services: Methodologies, Challenges, and Tr"

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Authors Tingting Wang, Guilin Qi arXiv ID 2408.00803 Category cs.SE: Software Engineering Cross-listed cs.AI, cs.CE Citations 12 Venue arXiv.org Last Checked 3 days ago
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.
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