Actor tracing

When the tracing extension is configured, the framework automatically creates one span per actor message plus an infrastructure span for inbound cluster-wire envelopes. Spans chain across tells — a message handler that tells another actor passes the active span context, so the receiver’s span links back to the sender’s.

Auto-instrumented spans

Span name	When	Notable attributes
actor.receive	Once per message delivered to onReceive.	actor.path, actor.message.type
cluster.envelope.received	Inbound cross-cluster envelope carrying a parent trace context.	cluster.from, cluster.to.path

For a typical request flow:

Each span carries the trace ID — your tracing backend stitches them into one trace.

Causal chaining

// Within an actor:
override async onReceive(message) {
  // tracer.activeSpan() returns the actor.receive span
  // tell creates an envelope with traceparent set
  this.downstream.tell({ kind: 'derived', from: message.id });
  // The downstream actor's actor.receive span has THIS span as parent
}

tell snapshots the active span context onto the envelope (via tracer.injectContext()). On receive, the framework runs tracer.withActiveSpan(span, ...) to make the actor’s onReceive see the chain.

Across cluster nodes, the same traceparent rides on the wire envelope. The receiving node extracts it; its actor.receive span links back to the sender’s.

Span attributes

// actor.receive attributes:
{
  'actor.path':         'actor-ts://my-app/user/api/sessions/user-42',
  'actor.message.type': 'LoginMessage',
}
// On error the span records the exception and sets an error
// status (span.recordException(err) + span.setStatus('error', …)) —
// there is no error.message attribute.

For cluster envelopes:

// cluster.envelope.received attributes:
{
  'cluster.from':    'actor-ts://my-app@10.0.0.5:2552',
  'cluster.to.path': '/user/api/sessions/user-42',
}

These follow OpenTelemetry semantic conventions where applicable, so off-the-shelf dashboards (Honeycomb, Datadog, Grafana Tempo) work without customization.

Controlling span volume

Auto-instrumentation is all-or-nothing — it’s active whenever you enable a non-Noop tracer, and off (zero overhead) when the tracer is the default NoopTracer. There are no per-category toggles.

To reduce span volume in very-high-throughput systems, sample at the SDK level (see OTel adapter → Sampling) rather than turning categories off — the framework records at full rate, but the SDK exports only a fraction. Turning auto-instrumentation off entirely means installing the NoopTracer, which also disables your manual spans, since they route through the same tracer.

Adding application-level spans

override async onReceive(message) {
  const tracer = this.context.system.extension(TracingExtensionId).get();
  const span = tracer.startSpan('process-order', {
    attributes: {
      'order.id':     message.orderId,
      'order.amount': message.amount,
    },
  });
  try {
    await tracer.withActiveSpan(span, async () => {
      // ... processing ...
    });
    span.setStatus('ok');
  } catch (e) {
    span.recordException(e as Error);
    span.setStatus('error', (e as Error).message);
    throw e;
  } finally {
    span.end();
  }
}

Application spans appear as children of the auto-generated actor.receive span — your custom logic sits naturally inside the actor’s processing.

MDC integration

The framework does not automatically merge traceId / spanId into the LogContext — log lines are not stamped with the active span’s IDs out of the box. The MDC fields you set yourself (e.g. correlationId) still flow into every log line as usual; the trace IDs simply aren’t among them unless you add them.

To share IDs between logs and traces, copy them from the active span into the MDC yourself:

const span = tracer.activeSpan();
if (span) {
  const { traceId, spanId } = span.context();
  LogContext.with({ traceId, spanId }, () => {
    // log lines emitted in here now carry traceId + spanId
  });
}

With the IDs in the MDC, your logs and traces share them — you can pivot from a slow trace in Honeycomb to the matching log lines in Loki.

Performance

When tracing is disabled (NoopTracer), the auto-instrumentation is zero overhead — the framework’s hot paths short-circuit without allocating spans or doing async-storage lookups.

When enabled, each message processed adds:

• One span allocation (small object).
• A few attribute writes.
• One AsyncLocalStorage scope.

Total cost per message: ~5-10 microseconds. Significant for million-msg-per-second systems; negligible otherwise.

Trace volume in high-throughput systems

// 100,000 messages/sec × 1 span each = 100K spans/sec

At this rate, always sample. See the OTel adapter’s sampling section for the typical 1-10 % production rate.

Span attributes from message contents

// The framework includes actor.message.type by default
// It does NOT auto-include message field values

This is by design — message contents may contain PII or large payloads. Add custom attributes manually where it’s safe and useful.

`pipeTo` doesn't propagate active span

pipeTo(externalCall(), target);
// Target's onReceive doesn't see this caller's active span

Manual workaround:

const context = tracer.injectContext();
pipeTo(externalCall(), target, { sender: this.self });
// Then target reads its own carrier from message metadata if needed

This is a known limitation; spans don’t auto-chain through pipeTo currently.

Where to next

• Tracer API — the underlying interface.
• OTel adapter — pipe to your tracing backend.
• Recording tracer — for test assertions.
• Logging — LogContext — the MDC you can stamp with trace IDs yourself.