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What you need before configuring the exporter
- A .NET application and a target runtime compatible with the OpenTelemetry package versions you choose.
- A Langfuse project’s public and secret keys, plus the OTLP endpoint for the project’s region. Keep the secret key in a secret manager or deployment environment, not source control.
- A decision about whether to export via OTLP over HTTP/protobuf or gRPC. OpenTelemetry documents both exporter protocols; use the endpoint and protocol combination required by your destination. See the Langfuse OpenTelemetry integration guide and OpenTelemetry .NET exporter documentation.
Install the .NET OpenTelemetry packages
For an ASP.NET Core application, add the hosting integration, ASP.NET Core instrumentation, and OTLP exporter packages. The official OpenTelemetry ASP.NET Core guide uses these packages. Select versions that fit your supported .NET runtime and dependency policy rather than assuming one version is right for every application.
Register tracing and configure OTLP export
Register OpenTelemetry with the application’s service collection, assign a useful service name, enable inbound ASP.NET Core request instrumentation, and configure an OTLP exporter. The essential registration shape is:
builder.Services.AddOpenTelemetry()
.ConfigureResource(resource => resource
.AddService(serviceName: builder.Environment.ApplicationName))
.WithTracing(tracing => tracing
.AddAspNetCoreInstrumentation()
.AddOtlpExporter(options =>
{
// Set the Langfuse regional OTLP endpoint, protocol,
// and authentication headers for this deployment.
}));Use the Langfuse OTLP traces endpoint for the project’s region, with the documented /api/public/otel base path. Configure Basic authentication with the project’s public and secret keys, and include x-langfuse-ingestion-version=4 for current v4 ingestion. The exact endpoint and header setup belong in deployment configuration; consult Langfuse’s integration instructions for the correct regional values and the OpenTelemetry exporter documentation for protocol configuration.
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Instrument meaningful application and model work
Start with automatic request spans
AddAspNetCoreInstrumentation() can create spans for inbound ASP.NET Core HTTP requests. It does not automatically establish that a chosen model-provider SDK records model names, prompts, completions, token usage, or cost.
Add spans for operations that matter
Use .NET’s ActivitySource and Activity APIs to describe important operations in your application, such as retrieval, tool execution, or a model call. OpenTelemetry’s .NET instrumentation documentation explains that its Tracing API is implemented through System.Diagnostics constructs including ActivitySource and Activity: OpenTelemetry .NET instrumentation.
Check the integration documentation for your actual provider and SDK to see what it emits. If it does not provide the model-specific information your evaluations need, add appropriate attributes or spans yourself. The provider and framework are unspecified here, so no particular .NET model-instrumentation package can be recommended.
Verify that Langfuse receives useful traces
- Run the application through a representative request or task.
- Inspect the resulting trace in Langfuse. Confirm that it arrives under the intended project and has a useful service name, span hierarchy, and attributes.
- If model activity is missing, verify the provider’s instrumentation or add application-level spans and metadata; an inbound HTTP span alone does not show the details of nested model work.
- For a short-lived console or evaluation process, flush or shut down the tracer provider after processing so queued telemetry has an opportunity to export.
Choose an evaluation workflow
First decide whether you want repeatable regression checks on fixed inputs or ongoing assessment of production traffic. Langfuse documents both direct OpenTelemetry experiment ingestion and SDK-based dataset experiments; an SDK example in another language should not be mistaken for a .NET runner.
Group OpenTelemetry traces into experiment runs
For direct OTLP experiment ingestion, attach the experiment and item metadata required by Langfuse to the relevant spans. Langfuse’s experiment documentation describes the required attributes and the alternative SDK-runner approach for supported SDK languages. For a .NET application using OTLP directly, follow the documented OpenTelemetry route and ensure the metadata is present on the spans Langfuse uses to group the run.
Run a dataset-based evaluation
For a repeatable offline evaluation, organize representative inputs as a dataset, execute the application’s task logic for each item, and record outputs and evaluator scores. Langfuse’s SDK experiment guide describes dataset items, task functions, and optional evaluators. Its Python or TypeScript runner examples are not evidence of a native .NET runner; a .NET team can use direct OTLP experiment ingestion unless it introduces a separately supported client.
Evaluate production traffic
For live application traffic, use Langfuse’s online evaluation setup and scoring mechanisms rather than treating a fixed dataset run as a substitute for production monitoring. See Langfuse evaluation documentation.
When comparing prompts, models, or application variants, useful evaluation dimensions include task correctness against expected output, relevant policy or safety compliance, latency, token use or cost when the integration records it, and robustness across representative cases. These are dimensions to assess, not guaranteed trace fields or measured outcomes.
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Check legacy ingestion before migrating
Langfuse’s Public API documentation identifies OpenTelemetry trace ingestion as its supported trace-ingestion route and lists November 16, 2026 as the Langfuse Cloud sunset date for the legacy Ingestion API. That date is upcoming as of October 4, 2026. If an existing integration uses the legacy API, check its exporter configuration and plan migration to OTLP.
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