Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.
npxskills add wshobson/agents--skill distributed-tracingLoading…
Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices.
Track requests across distributed systems to understand latency, dependencies, and failure points.
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
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')}
)
No traces appearing:
High latency overhead:
prometheus-configuration - For metricsgrafana-dashboards - For visualizationslo-implementation - For latency SLOs
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