Cómo usar
- Copia el comando y revisa el paquete antes de instalarlo en tu entorno de agente.
- Consulta las herramientas, credenciales y entornos necesarios en el documento original.
- Describe las entradas y el resultado deseado; contrasta la salida con las fuentes.
npx skills add https://github.com/wshobson/agents --skill distributed-tracingAntes de empezar
- La instalación no incluye suscripción al modelo, cuota API ni permisos sobre tus archivos.
- Las estrellas e instalaciones reflejan actividad, no una prueba independiente de calidad o seguridad.
Documento original del Skill
Contenido del repositorio de origen con títulos, ejemplos, código, tablas, enlaces e imágenes preservados.
Distributed Tracing
Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices.
Purpose
Track requests across distributed systems to understand latency, dependencies, and failure points.
When to Use
- Debug latency issues
- Understand service dependencies
- Identify bottlenecks
- Trace error propagation
- Analyze request paths
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Best Practices
- Sample appropriately (1-10% in production)
- Add meaningful tags (userid, requestid)
- Propagate context across all service boundaries
- Log exceptions in spans
- Use consistent naming for operations
- Monitor tracing overhead (<1% CPU impact)
- Set up alerts for trace errors
- Implement distributed context (baggage)
- Use span events for important milestones
- Document instrumentation standards
Integration with Logging
Correlated Logs
python
import logging
from opentelemetry import trace
logger = logging.getLogger(__name__)
def process_request():
span = trace.get_current_span()
trace_id = span.get_span_context().trace_id
logger.info(
"Processing request",
extra={"trace_id": format(trace_id, '032x')}
)Troubleshooting
No traces appearing:
- Check collector endpoint
- Verify network connectivity
- Check sampling configuration
- Review application logs
High latency overhead:
- Reduce sampling rate
- Use batch span processor
- Check exporter configuration
Related Skills
prometheus-configuration- For metricsgrafana-dashboards- For visualizationslo-implementation- For latency SLOs
