Traces Overview - Bluejay Docs

Getting Started

Key Concepts

Test

Monitor

Integrations

Administration

What are Traces?

As part of your voice-agent stack, traces are used to monitor and observe the behavior of your application in real-time. They provide insights into the execution flow, latency, and performance of your system. Bluejay accepts traces for two purposes:

Production observability — link traces to call evaluations via the /v1/evaluate endpoint
Simulation analysis — link traces to simulation results via the /v1/update-simulation-result endpoint

Sending Traces to Bluejay

Bluejay supports any traces that conform to the OpenTelemetry standard, this includes OpenInference, Langfuse, OpenLLMetry, and more.

Using the OpenTelemetry SDK

Configure the OpenTelemetry SDK to export traces to Bluejay:

from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.sdk.resources import SERVICE_NAME, Resource

endpoint = "https://otlp.getbluejay.ai/v1/traces"
resource = Resource.create({SERVICE_NAME: "<your_service_name>"})

tracer_provider = trace_sdk.TracerProvider(resource=resource)
headers = {
    "X-API-KEY": "[BLUEJAY PROVISIONED API KEY]"
}

tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint, headers=headers)))

OpenAI Example:

from opentelemetry.instrumentation.openai import OpenAIInstrumentor

OpenAIInstrumentor().instrument(tracer_provider=tracer_provider)

Using LiveKit

LiveKit requires additional setup — see the LiveKit Traces guide.

Next Steps

Traces for Observability

Link traces to production conversation evaluations.

Traces for Simulations

Link traces to simulation results.

​What are Traces?

​Sending Traces to Bluejay

​Using the OpenTelemetry SDK

​Using LiveKit

​Next Steps