Under the Hood: Graph Reasoning for Observability

By Engineering Team • Jan 10, 2026

Large Language Models (LLMs) are great at summarization, but they hallucinate. In SRE, a hallucination ("The database is down" when it isn't) is dangerous. That's why Rezmo is built on Graph Reasoning, not just a chatbot.

Beyond the Chatbot

We use a system called LangGraphRCASystem within our backend. It models the troubleshooting process as a Directed Cyclic Graph (DAG). It doesn't just guess; it follows a rigorous scientific method:

1. Observation: The system ingested an alert (e.g., "High Latency").
2. Hypothesis Generation: Based on the service graph, it generates potential causes (e.g., "DB Lock", "CPU Saturation").
3. Verification (The Critical Step): The agent must write a query (PromQL or SQL) to prove or disprove the hypothesis.
4. Conclusion: Only verified facts make it into the final report.

Why this matters

This approach eliminates the "black box" problem. You get a deterministic, evidence-backed report, not just a probability-based guess.