Observability

Lance can publish operational metrics to your monitoring stack. The table below is the authoritative catalogue of the metrics Lance emits, shared verbatim with the Rust lance::metrics module documentation.

--8<-- "rust/lance/src/metrics.md"

Collecting metrics

Lance emits through the metrics crate facade, so it is not tied to a specific backend — you install a recorder/exporter and route the metrics wherever you like. Metrics are available from both the Rust and Python APIs.

Rust

Enable the metrics feature on the lance crate:

toml

lance = { version = "...", features = ["metrics"] }

Then install any metrics-compatible recorder once at startup, before opening datasets. For example, with metrics-exporter-prometheus:

rust

metrics_exporter_prometheus::PrometheusBuilder::new()
    .install()
    .expect("install Prometheus recorder");

Any recorder works — Prometheus, StatsD, an OpenTelemetry bridge, and so on. When no recorder is installed, emission is a cheap no-op.

Python

Unlike Rust, the Python bindings do not let you plug in an arbitrary recorder: bridging one across the FFI boundary into the Rust metrics facade would be complicated and inefficient. Instead pylance standardizes on OpenTelemetry, which has good Python support, as its recorder.

The pylance wheels are built with the metrics feature enabled. Install the OpenTelemetry extra and call instrument_lance_metrics, which registers Lance's metrics as observable instruments on your OpenTelemetry MeterProvider:

bash

pip install "pylance[otel]"

python

from lance.otel import instrument_lance_metrics

# Uses the global MeterProvider; pass meter_provider=... to target a specific one.
instrument_lance_metrics()

From there the metrics flow through whatever OpenTelemetry pipeline you have configured (OTLP, Prometheus, console, …). Because OpenTelemetry has no asynchronous histogram instrument, histograms are exported Prometheus-style as three observable counters: <name>_bucket, <name>_count, and <name>_sum. Each <name>_bucket sample carries an le ("less than or equal") attribute giving that bucket's inclusive upper bound in the metric's unit; the bucket count is cumulative, covering every observation at or below le. For example, a lance_object_store_request_duration_seconds_bucket sample with le="0.5" counts all requests that completed in 0.5 seconds or less, while le="+Inf" is the total count.