# Tracing and observability

> The `@traced` decorator makes individual execution steps visible in job traces and Maestro dashboards. Use it to annotate the helper functions that do meaningful work, so you can see where time is spent and where a run failed.

The `@traced` decorator makes individual execution steps visible in job traces and Maestro dashboards. Use it to annotate the helper functions that do meaningful work, so you can see where time is spent and where a run failed.

```python
from uipath.tracing import traced

@traced(name="fetch_document", run_type="uipath")
def fetch_document(document_id: str) -> bytes:
    # implementation
    ...

def main(input: Input) -> Output:  # do not trace the entry point
    content = fetch_document(input.document_id)
    return Output(result_id="123")
```

:::important
Do not apply `@traced` to the entry-point function. The runtime already wraps the entire job in its own span; tracing the entry point produces a duplicate, nested span.
:::

## What gets captured

Each traced step records its name, run type, start and end times, and status. Traces are linked to the Orchestrator job so you can navigate from a Maestro process instance down to the individual function step that ran.

## Guidance

- Trace the steps that represent distinct units of work — an external call, an extraction, a transformation.
- Use a clear, stable `name` per step so traces are easy to read across runs.
- Keep `run_type="uipath"` for platform steps.

## Next steps

- [Invoke functions](invoking-functions.md) — see traces from a Maestro process.