Pull logs and metrics

When a deployment misbehaves, start with its logs and metrics. This page covers reading both from the console, the CLI, and the Management API. For metric definitions and Prometheus-style export, see Metrics and the other Observability pages.

Fetch and stream logs

Pull logs to debug an incident, grep for an error, or pipe context into an agent. Fetch a time window (up to 7 days back):

UI
Baseten CLI
REST API

To view logs:

Sign in to your workspace at app.baseten.co and choose Dedicated Inference in the sidebar.
Select your model.
Select the deployment under Deployments.
Choose Logs.

Filter by level or replica, search, or follow live output with the controls at the top of the logs view.

To fetch logs:

baseten model deployment logs --model-id <model-id> --deployment-id <deployment-id> --since 1h

[2026-07-07 10:33:58]: Deploy was a success.
[2026-07-07 10:33:44]: (nvsmp) Completed model.load() execution in 6 ms
[2026-07-07 10:33:44]: (nvsmp) Uvicorn running on http://0.0.0.0:8080 (Press CTRL+C to quit)

The parenthesized prefix on each line is the replica that emitted it.To stream live logs:Pass --tail instead of a time window:

baseten model deployment logs --model-id <model-id> --deployment-id <deployment-id> --tail

[2026-07-07 10:33:44]: (nvsmp) Completed model.load() execution in 6 ms
[2026-07-07 10:33:58]: Deploy was a success.
...

Streaming continues until the deployment leaves a runnable state or you interrupt with Ctrl-C. For machine-readable output, add --output jsonl to stream one JSON log entry per line:

baseten model deployment logs --model-id <model-id> --deployment-id <deployment-id> --tail --output jsonl

{"level":"INFO","message":"Completed model.load() execution in 6 ms","replica":"nvsmp","timestamp":"1783445624380306972"}
{"level":"INFO","message":"Deploy was a success.","replica":"","timestamp":"1783445638726940011"}
...

Narrow the stream with --jq: --jq '.message' extracts one field per line, and --jq 'select(.level=="ERROR") | .message' keeps only error lines.

To fetch logs:

curl "https://api.baseten.co/v1/models/{model_id}/deployments/{deployment_id}/logs" \
  -H "Authorization: Bearer $BASETEN_API_KEY"

{
  "logs": [
    {
      "timestamp": "1783445638726940011",
      "message": "Deploy was a success.",
      "replica": "",
      "request_id": null,
      "level": "INFO"
    },
    {
      "timestamp": "1783445624380306972",
      "message": "Completed model.load() execution in 6 ms",
      "replica": "nvsmp",
      "request_id": null,
      "level": "INFO"
    }
  ]
}

The window defaults to the last 30 minutes; pass start_epoch_millis to widen it, up to 7 days. Timestamps are epoch nanoseconds. The API fetches fixed windows only; to follow logs live, use the CLI’s --tail.

For more information about filters like log level, search patterns, and request ID, see logs and the logs endpoint (beta).

Fetch metrics

Pull metrics to check a deployment’s health from a script: replica count, request volume, and end-to-end latency quantiles.

UI
Baseten CLI
REST API

To view metrics:

Sign in to your workspace at app.baseten.co and choose Dedicated Inference in the sidebar.
Select your model.
Select the deployment under Deployments.
Choose Metrics.

The metrics view charts request rates by status code, latency percentiles, and replica counts. Set the window with the time-range selector at the top.

To fetch metrics:

baseten model deployment metrics --model-id <model-id> --deployment-id <deployment-id>

METRIC                                    QUANTILE  STAT  VALUE
baseten_replicas_active                                       1
baseten_end_to_end_response_time_seconds  0.5                 -
baseten_end_to_end_response_time_seconds  0.9                 -
baseten_end_to_end_response_time_seconds  0.95                -
baseten_end_to_end_response_time_seconds  0.99                -
baseten_end_to_end_response_time_seconds            avg       -

Latency values show - until the deployment has served requests in the window; once it has, a STATUS column also breaks out request counts per response code. The default is a current snapshot; pass --mode summary or --mode series with --since to aggregate over a window instead.

To fetch metrics:

curl "https://api.baseten.co/v1/models/{model_id}/deployments/{deployment_id}/metrics" \
  -H "Authorization: Bearer $BASETEN_API_KEY"

{
  "start_epoch_millis": 1783445679297,
  "end_epoch_millis": 1783445679297,
  "mode": "CURRENT",
  "step_seconds": null,
  "metric_descriptors": [
    {
      "name": "baseten_replicas_active",
      "unit_hint": "COUNT",
      "kind": "GAUGE",
      "label_sets": [{}]
    }
  ],
  "metric_values": [
    {
      "start_epoch_millis": 1783445679297,
      "values": [[1.0]]
    }
  ]
}

metric_values lines up with metric_descriptors by position: the first value array belongs to the first metric, the second to the second, and so on.

For more information about modes, windows, and metric selection, see metrics and the metrics endpoint (beta). For what each metric means, see Metrics.

Fetch environment logs and metrics

Deployment scope answers “what is this specific deployment doing?” Environment scope answers “what is production doing right now?”, which is usually the more useful operational question. An environment spans every deployment that has served it, so environment logs and metrics stay continuous across promotions: during and after a rollout, one view covers the outgoing and incoming deployments. Fetch them from any surface:

UI
Baseten CLI
REST API

To view an environment’s logs and metrics:

Sign in to your workspace at app.baseten.co and choose Dedicated Inference in the sidebar.
Select your model.
On the model overview, choose Logs or View metrics for the environment.

You can also reach the same views from any deployment’s logs or metrics page: choose the environment from the dropdown in the upper left.

To fetch environment logs:Target the environment by name instead of a deployment ID:

baseten model environment logs --model-id <model-id> --environment production --since 1h

[2026-07-09 08:49:09]: (w44tt) Application shutdown complete.
[2026-07-09 08:48:41]: Scaling down replicas due to inactivity
[2026-07-09 08:34:09]: (67wjm) Terminated
...

The same windows and filters as deployment logs apply, including --tail for live streaming and --output jsonl for machine-readable output.To fetch environment metrics:

baseten model environment metrics --model-id <model-id> --environment production

METRIC                                    QUANTILE  STAT  VALUE
baseten_replicas_active                                       1
baseten_end_to_end_response_time_seconds  0.5                 -
baseten_end_to_end_response_time_seconds  0.9                 -
baseten_end_to_end_response_time_seconds  0.95                -
baseten_end_to_end_response_time_seconds  0.99                -
baseten_end_to_end_response_time_seconds            avg       -

The default is a current snapshot; pass --mode summary or --mode series with --since to aggregate over a window. In series mode the window splits at each promotion, so every point reflects the deployment serving the environment at that time.

To fetch environment logs:

curl "https://api.baseten.co/v1/models/{model_id}/environments/production/logs" \
  -H "Authorization: Bearer $BASETEN_API_KEY"

{
  "logs": [
    {
      "timestamp": "1783612149447676900",
      "message": "Application shutdown complete.",
      "replica": "w44tt",
      "request_id": null,
      "level": "INFO"
    }
  ]
}

To fetch environment metrics:

curl "https://api.baseten.co/v1/models/{model_id}/environments/production/metrics" \
  -H "Authorization: Bearer $BASETEN_API_KEY"

{
  "start_epoch_millis": 1783968056212,
  "end_epoch_millis": 1783968056212,
  "mode": "CURRENT",
  "metric_descriptors": [
    {
      "name": "baseten_replicas_active",
      "unit_hint": "COUNT",
      "kind": "GAUGE",
      "label_sets": [{}]
    },
    ...
  ],
  "metric_values": [
    {
      "start_epoch_millis": 1783968056212,
      "values": [[1.0]]
    }
  ]
}

Both endpoints take the same windows and modes as their deployment counterparts.

For more information, see environment logs and environment metrics, and the environment logs and environment metrics (beta) endpoints.

Next steps

Logs and metrics are the read half of every management workflow: check them before and after a mutation.

Terminate a stuck replica you found misbehaving in the logs.
Scale a deployment if metrics show sustained queueing or idle replicas.
Metrics for dashboards and metric definitions.

​Fetch and stream logs

​Fetch metrics

​Fetch environment logs and metrics

​Next steps

Fetch and stream logs

Fetch metrics

Fetch environment logs and metrics

Next steps