What does this OpenTelemetry tracing example do?

It evaluates a custom provider that emits OpenTelemetry traces for a RAG agent workflow and asserts directly on those traces—checking that expected spans exist, complete within duration limits, and contain no errors, rather than just validating the final text output.

When should I use this example?

Use it when your LLM application is instrumented with OpenTelemetry and you want to verify internal execution behavior (like confirming a RAG pipeline retrieves exactly 3 documents or finishes within a time budget), provided your provider actually emits OTLP traces that promptfoo can receive.

What assertion types does this example support?

It supports `trace-span-count` (to verify expected spans are present), `trace-span-duration` (to enforce latency limits), and `trace-error-spans` (to track error rates), alongside standard JavaScript assertions.

How is tracing configured in this example?

Tracing is enabled via `metadata: { tracingEnabled: true }` in tests, and the OTLP HTTP receiver is configured on port 4318 to accept JSON-formatted traces.

Prompt Chain

Trace LLM Provider Operations with OpenTelemetry

Name: Opentelemetry Tracing
Availability: OnlineOnly
Author: promptfoo/promptfoo

Promptfoo example asserting directly on OpenTelemetry traces from a simulated RAG agent - span counts, durations and error rates, not just text output.

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Works with opentelemetrygithub

promptfoo/promptfoo

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Updated last month

Source checked Aug 8, 2026

Version 0.122.0

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Why it matters

Enhance your LLM development process by integrating OpenTelemetry tracing into your Promptfoo evaluations. Gain deep visibility into the internal workings of your LLM providers to identify bottlenecks and improve performance.

Outcomes

What it gets done

Instrument Promptfoo evaluations for detailed tracing.

Monitor and analyze LLM provider performance during testing.

Debug and optimize LLM interactions using trace data.

Integrate tracing into your CI/CD pipeline for automated quality checks.

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/pfoo-opentelemetry-tracing | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Opentelemetry Tracing

This promptfoo example asserts directly on OpenTelemetry trace spans emitted by a RAG agent provider, checking span counts, durations, and error rates via promptfoo's trace-based assertions. Use it when the provider under test emits OTLP traces and you need to verify internal execution behavior, not just the final output.

What it does

This promptfoo example evaluates a custom provider (file://provider-simple-traced.js) that emits OpenTelemetry traces for a simulated RAG agent workflow, then asserts directly on those traces rather than just the text output. It checks that expected spans exist (rag_agent_workflow, retrieve_document_*, reasoning_*), that spans complete within duration limits, and that no error spans occur.

When to use - and when NOT to

Use this example when your LLM application is instrumented with OpenTelemetry and you want to verify its internal execution behavior - not just the final answer - such as confirming a RAG pipeline retrieves exactly 3 documents, completes reasoning steps, finishes within a time budget, and does not error. It requires the provider under test to actually emit OTLP traces that promptfoo can receive on its configured OTLP HTTP endpoint; it is not useful for providers that don't produce trace spans.

Inputs and outputs

Each test enables tracing via metadata: { tracingEnabled: true } and asserts on span counts and durations with pattern matching, for example:

    assert:
      # Ensure all expected spans are present
      - type: trace-span-count
        value:
          pattern: 'rag_agent_workflow'
          min: 1
          max: 1

      # Ensure we retrieve exactly 3 documents
      - type: trace-span-count
        value:
          pattern: 'retrieve_document_*'
          min: 3
          max: 3

      # Ensure the overall workflow completes quickly
      - type: trace-span-duration
        value:
          pattern: 'rag_agent_workflow'
          max: 5000 # 5 seconds max

defaultTest adds metric-only assertions (weight: 0) for p95 span duration and an allowed error rate of up to 5% (trace-error-spans with max_percentage: 5), which track metrics without failing the test outright. Tracing itself is configured via:

tracing:
  enabled: true
  otlp:
    http:
      enabled: true
      port: 4318
      acceptFormats: ['json']

Integrations

Runs against a custom traced JavaScript provider and promptfoo's built-in OTLP HTTP receiver (port 4318, JSON format), using the trace-span-count, trace-span-duration, and trace-error-spans assertion types alongside a standard javascript assertion loaded from trace-assertions.js.

Who it's for

Teams building instrumented, multi-step LLM agents (RAG pipelines, tool-calling workflows) who want to assert on internal execution behavior - span counts, latencies, and error rates - not just the final generated text.

Source README

integration-opentelemetry (OpenTelemetry Tracing)

Examples for using OpenTelemetry tracing with promptfoo.

Examples

javascript - Custom JS provider with OTEL tracing (JSON format)
python - Custom Python provider with OTEL tracing (protobuf format)
built-in - Built-in OTEL tracing with standard providers (OpenAI, Anthropic, Azure)

FAQ

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