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The Telemetry page is the single home for every OpenTelemetry signal OpenLIT ingests from your AI applications. Navigate to it at /telemetry. It has four tabs, all backed by the same ClickHouse tables (otel_traces, otel_metrics_*, otel_logs) populated by the OpenTelemetry Collector built into OpenLIT:

Traces

Distributed traces with grouping, a five-view trace detail explorer, and span/resource attributes

AI Analysis

AI-generated review of a trace or span across strengths, improvements, cost, and token efficiency

Metrics

Every OTel metric OpenLIT has received, with a trend chart and data-point detail per metric

Logs

Searchable, filterable OTel log records with a detail view per entry
The Exceptions tab is documented alongside Traces since it reuses the same trace detail explorer - see Traces & Exceptions.

Quickstart: LLM Observability

Production-ready AI monitoring setup in 2 simple steps with zero code changes

Create a dashboard

Create custom visualizations with flexible widgets, queries, and real-time AI monitoring

Integrations

60+ AI integrations with automatic instrumentation and performance tracking

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Frequently asked questions

AI observability is the practice of collecting traces, metrics, and logs from LLM applications and agents so you can understand behavior, cost, latency, and errors in production - OpenLIT does this via standard OpenTelemetry data.
Yes. Logs have their own dedicated explorer under Telemetry, ingested the same way as traces and metrics through the built-in OpenTelemetry Collector’s OTLP receiver.
Yes. The Metrics explorer and Dashboard Widgets read from the same underlying data - use the explorer to inspect a single metric, and dashboards for cross-signal, trend-style visualizations.