Distributed Tracing

TL;DR

Explanation

A trace represents one request journey. Each service adds a span (operation + timing). Spans link via trace ID + parent span ID propagated in headers (W3C Trace Context: traceparent header). Tools: Jaeger, Zipkin, Datadog APM, AWS X-Ray, Honeycomb. OpenTelemetry: the standard SDK for instrumentation. PHP: opentelemetry-php SDK, Laravel/Symfony integration. Key use: find where in a multi-service request the latency is — which service is slow, which DB query takes 2s. Without tracing, cross-service debugging requires correlating logs by timestamp — fragile and slow.

Common Misconception

Why It Matters

Common Mistakes

• Not propagating trace headers between services — breaks the trace chain.
• 100% sampling in production — high volume, high cost. Use sampling.
• Not adding custom attributes to spans — spans without context are hard to use.

Code Examples

// No trace propagation — broken traces:
$response = $httpClient->post('/api/orders', $data);
// No traceparent header passed — downstream sees a new root trace

// Propagate W3C trace context:
$response = $httpClient->post('/api/orders', $data, [
    'headers' => [
        'traceparent' => $tracer->getCurrentSpan()->getContext()->getTraceId(),
    ]
]);

// OpenTelemetry PHP:
$span = $tracer->spanBuilder('processOrder')->startSpan();
$span->setAttribute('order.id', $orderId);
try { processOrder(); }
finally { $span->end(); }

References

• ↗ https://opentelemetry.io/docs/concepts/signals/traces/

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