> ## Documentation Index
> Fetch the complete documentation index at: https://docs.baseten.co/llms.txt
> Use this file to discover all available pages before exploring further.

# Logs

> Scope logs by environment or deployment, then filter by request ID for individual predictions.

When a model is serving hundreds of requests per minute, a single slow or failing prediction can be difficult to isolate from the surrounding noise. Baseten addresses this by assigning a unique request ID to every predict call and returning it in the `X-Baseten-Request-Id` response header. Because each request carries its own ID, you can trace a single prediction through your model's logs without sifting through unrelated entries.

<Note>
  Per-request log filtering requires Truss version 0.15.5 or later. Upgrade with `pip install --upgrade truss`
</Note>

## Scope by environment or deployment

The Logs tab can show entries from a single deployment or from every deployment in an environment. Use the dropdowns at the top of the tab to switch.

Environment scope aggregates logs across every deployment in that environment, including past deployments still serving traffic during a rollout. Use it to follow a request across deployment boundaries or to watch a promotion in progress.

Deployment scope restricts logs to a single deployment ID. Use it to isolate behavior to one version, such as a development deployment.

The same scope applies to live tail and historical search.

## Getting the request ID

The first step is capturing the request ID from the response. Baseten includes it in every predict response, regardless of whether the call is synchronous, asynchronous, or gRPC. The exact location depends on the protocol you're using:

<Tabs>
  <Tab title="HTTP">
    When you make a predict call, include the `-sD-` flag to print response headers alongside the body:

    ```bash theme={"system"}
    curl -sD- -X POST "https://model-{MODEL_ID}.api.baseten.co/production/predict" \
      -H "Authorization: Api-Key $BASETEN_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{"prompt": "Hello"}'
    ```

    The request ID appears as a response header:

    ```
    X-Baseten-Request-Id: 31255019cf83c4d0c7492a5006591e1f502a5
    ```
  </Tab>

  <Tab title="gRPC">
    For gRPC calls, the request ID is in the response trailer metadata rather than an HTTP header. Use the `-vv` flag with `grpcurl` to surface it:

    ```bash theme={"system"}
    grpcurl -vv \
      -H "baseten-authorization: Api-Key $BASETEN_API_KEY" \
      -H "baseten-model-id: model-{MODEL_ID}" \
      -d '{"name": "World"}' \
      model-{MODEL_ID}.grpc.api.baseten.co:443 \
      example.Greeter/SayHello
    ```

    Look for `x-baseten-request-id` in the trailer metadata at the end of the response:

    ```
    x-baseten-request-id: 31255019cf83c4d0c7492a5006591e1f502a5
    ```
  </Tab>

  <Tab title="Async">
    Async predict calls return the request ID in two places: the response header and the JSON body. This makes it easy to capture programmatically without parsing headers:

    ```bash theme={"system"}
    curl -sD- -X POST "https://model-{MODEL_ID}.api.baseten.co/production/async_predict" \
      -H "Authorization: Api-Key $BASETEN_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{"prompt": "Hello"}'
    ```

    ```
    X-Baseten-Request-Id: 31255019cf83c4d0c7492a5006591e1f502a5
    ```

    ```json theme={"system"}
    {"request_id": "31255019cf83c4d0c7492a5006591e1f502a5"}
    ```
  </Tab>
</Tabs>

## Filtering logs by request ID

Once you have a request ID, open the model's logs page and enter it in the search filter bar using the `requestId:` prefix:

```
requestId:31255019cf83c4d0c7492a5006591e1f502a5
```

The view narrows to show only log entries from that request. Each log line also displays the request ID alongside the replica ID, so you can confirm you're looking at the right trace even when scrolling through mixed output.

## Logging with request context

For standard Truss models, Baseten automatically attaches the request ID to any log emitted via Python's `logging` module during a predict call. No configuration is required — just use a logger:

```python theme={"system"}
import logging

logger = logging.getLogger(__name__)

class Model:
    def predict(self, request):
        logger.info("Starting prediction")  # request_id is added automatically
        ...
```

## Custom servers

For standard Truss models, Baseten handles request ID logging automatically through the framework's built-in JSON formatter. No configuration is required.

Custom servers don't have this built-in support, so you'll need to do two things: extract the `x-baseten-request-id` header from incoming requests, and include it as a top-level `request_id` key in your JSON log output. Both steps are covered in the setup guides for [custom HTTP servers](/development/model/custom-server#per-request-logging) and [custom gRPC servers](/development/model/grpc#per-request-logging).