AI for Root Cause Analysis: The Problem Isn't the Models, It's the Data

💻 The main difficulty of AI Root Cause Analysis (RCA) lies not in the reasoning capabilities of the models, but in the quality of the data infrastructure.

In a Coroot experiment, 11 models, including Gemma 4 31B, successfully distinguished failure causes from symptoms; however, errors occurred due to poor formatting or context transmission.

🌍 The industry focus is shifting from searching for more powerful LLMs to designing reliable data pipelines that provide models with clean and structured context.

👤 When creating DevOps agents, it is more important to improve the quality of input data and tool-calling capabilities than to switch to the most expensive models.

Source 1: https://coroot.com/blog/hard-part-of-ai-root-cause-analysis-is-no-longer-the-model/