microsoft / OpenRCA
[ICLR'25] OpenRCA: Can Large Language Models Locate the Root Cause of Software Failures?
Why this job: matched by what the repo talks about: language, model, large, failure
What it does
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.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 21 days ago
- Stars
- 451
- +2 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 50% closed
- 5 still open
- Pull requests
- 15 merged
- 9 waiting
- Releases
- None
- Never published
- No contributing guide
- Security policy (opens in new tab)
- Code of conduct (opens in new tab)
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More: languages, topics and project record
Languages
- Python 100%
- Shell <1%
- Dockerfile <1%
Topics
- benchmark
- rca
- root-cause-analysis
- large-language-models
- llm
- software-engineering
- llm-agent
Project record
- JobEvals and observability
- StatusListed
- Commits47
- Forks56
- Watching5
- Stars in 28 days+18
- CreatedOct 30, 2024
- First seen by usNov 7, 2026
- CheckedNov 8, 2026