This page describes what data is provided by LLM observability and how it is used.

Span dataset schema

Spans are ingested to the Tracing/LLM Span dataset.

The LLM Span dataset incorporates additional fields over the Tracing/Span dataset.

LLM Span dataset field	Underlying OpenTelemetry field from which it is derived
`llm_span_type`	Attributes `traceloop.span.kind` and `llm.request.type`
`request_model`	Attribute `llm.request.model`
`response_model`	Attribute `llm.response.model`

The llm_span_type field provides an intuitive categorization of the LLM span. Depending on your application, you may see a mix among the following LLM span types:

agent
chat
tool
workflow
task
embeddings
completion
rerank

For more information about other fields, correlation tags, and other OpenTelemetry span related datasets, read our APM reference documentation

LLM metrics

The following metrics are derived from spans and are available in the Metrics Explorer, and can be used to create and share dashboards and create monitors and alerts:

gen_ai_span_call_count
gen_ai_span_error_count
gen_ai_span_duration
gen_ai_span_duration_lg

Metric dimensions (tags):

environment
service_name
service_namespace
service_version
llm_span_type
is_llm_request
provider
request_model
response_model
status_code
status_message