OpenRCA

About

OpenRCA is a benchmark for assessing LLMs' root cause analysis ability in a software operating scenario. When given a natural language query, LLMs need to analyze large volumes of telemetry data to identify the relevant root cause elements. This process requires the models to understand complex system dependencies and perform comprehensive reasoning across various types of telemetry data, including KPI time series, dependency trace graphs, and semi-structured log text.

We also introduce RCA-agent as a baseline for OpenRCA. By using Python for data retrieval and analysis, the model avoids processing overly long contexts, enabling it to focus on reasoning and scalable for extensive telemetry.