The OpenTelemetry Collector is a service that receives telemetry, processes it, and exports it to one or more backends. It’s optional — most applications send spans directly from the SDK to Phoenix — but it unlocks centralized policy, multi-backend fan-out, dynamic routing, and tail sampling that the SDK can’t express.

Anatomy of a Collector

Collectors are composed of pipelines. Each pipeline chains three component types:

Component	Role
Receiver	Listens for incoming telemetry (OTLP over gRPC, OTLP over HTTP, Jaeger, Zipkin, …).
Processor	Transforms, filters, enriches, batches, or samples spans as they flow through.
Exporter	Sends the processed telemetry out — to Phoenix, to another backend, to multiple backends, to disk.

All components and pipelines are defined in a single config.yaml. The Collector’s flexibility comes from how those components are composed.

OpenTelemetry Collector architecture: receivers → processors → exporters in a pipeline

For the canonical specification, see OpenTelemetry Collector documentation.

Deployment Models

Three common ways to deploy a Collector:

Model	How it works	Best for
Agent	Collector runs alongside the application — as a sidecar container, a daemonset, or a local process.	Simple setups, clear 1:1 mapping between app and collector.
Gateway	A central collector receives from many applications.	Centralized policy, credential management, single point of egress.
Hybrid	Agent collectors forward to a centralized gateway.	Large environments — distributed collection plus centralized processing.

Common Use Cases

Reasons to put a Collector between your applications and Phoenix:

Use case	What the Collector does
Filtering	Drop spans by name, attribute, or pattern using a `filter` processor — useful for cutting noise from health checks or known-uninteresting paths.
PII redaction or attribute modification	Use a `transform` processor to scrub sensitive fields, hash user IDs, or replace values before export.
Fan-out to multiple backends	Send the same spans to Phoenix and a long-term storage system, or to Phoenix and a metrics backend, without duplicating instrumentation in the app.
Project routing	Use a `routing` connector to send spans to different Phoenix projects (or different Phoenix instances) based on span attributes — for example, splitting tenant traffic. Phoenix itself doesn’t expose multi-project routing in the SDK; the Collector is where that logic belongs.
Tail sampling	Buffer complete traces and decide which to keep based on outcome (error spans, slow requests, specific attributes).
Credential centralization	Application code stays free of Phoenix Cloud API keys; the Collector handles authentication at a single chokepoint.
Tail-end batching	Reduce the number of network round-trips from your fleet to Phoenix by batching across applications at the Collector.

Common Pitfalls

A few Collector failure modes to know about:

Forgetting Phoenix Cloud authentication — when exporting to Phoenix Cloud or any authenticated Phoenix instance, the Collector needs to add Authorization: Bearer <api-key> to outbound requests. Use the headers_setter extension or set them in the exporter configuration. Local Phoenix doesn’t require auth.
Modifying shared span objects across pipelines — when one pipeline mutates a span, every other pipeline that processes the same span sees the modification. Use a routing connector to duplicate spans cleanly before fan-out.
No batch processor at the end of the pipeline — for production volumes, the last processor in a pipeline should be a batch processor. Without it, the Collector exports one span at a time, which is inefficient.
Wrong Collector endpoint — applications need to point at the Collector’s OTLP endpoint (gRPC: :4317, HTTP: :4318), not at Phoenix directly. Mixing the two is a common source of “why are some spans missing?” debugging.
Receiver missing include_metadata: true — when a centralized gateway uses inbound request metadata for routing (e.g., reading the target Phoenix project from a header), the receiver has to be told to make that metadata available. Without it, the routing extension has nothing to read.

Where the Collector Fits

Both with and without a Collector, your application code looks the same — the Exporter points at an OTLP endpoint. The difference is just which OTLP endpoint:

Without Collector:
  App → Exporter → http://localhost:6006 (or Phoenix Cloud)

With Collector:
  App → Exporter → Collector → (processors) → Phoenix (and/or other backends)

Start without a Collector. Add one when you need centralized policy, multi-backend fan-out, tail sampling, or routing logic the SDK can’t express.

You’ve completed the OpenTelemetry and OpenInference reference

Every concept in this section — signals, the four OTel components, the Phoenix helpers, OpenInference conventions, span kinds, instrumentation approaches, context, sampling, and the Collector — is now in your toolbox. Time to instrument:

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OpenTelemetry Collector

Anatomy of a Collector

Deployment Models

Common Use Cases

Common Pitfalls

Where the Collector Fits

You’ve completed the OpenTelemetry and OpenInference reference

Set up tracing

​Anatomy of a Collector

​Deployment Models

​Common Use Cases

​Common Pitfalls

​Where the Collector Fits

​You’ve completed the OpenTelemetry and OpenInference reference

Set up tracing

Anatomy of a Collector

Deployment Models

Common Use Cases

Common Pitfalls

Where the Collector Fits

You’ve completed the OpenTelemetry and OpenInference reference