distributed-tracing

name	distributed-tracing
description	Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices.
category	Document Processing
source	antigravity
tags	["python","javascript","node","api","ai","agent","template","document","image","docker"]
url	https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/distributed-tracing

Distributed Tracing

Implement distributed tracing with Jaeger and Tempo for request flow visibility across microservices.

Do not use this skill when

• The task is unrelated to distributed tracing
• You need a different domain or tool outside this scope

Instructions

• Clarify goals, constraints, and required inputs.
• Apply relevant best practices and validate outcomes.
• Provide actionable steps and verification.
• If detailed examples are required, open resources/implementation-playbook.md.

Purpose

Track requests across distributed systems to understand latency, dependencies, and failure points.

Use this skill when

• Debug latency issues
• Understand service dependencies
• Identify bottlenecks
• Trace error propagation
• Analyze request paths

Distributed Tracing Concepts

Trace Structure

Trace (Request ID: abc123)
  ↓
Span (frontend) [100ms]
  ↓
Span (api-gateway) [80ms]
  ├→ Span (auth-service) [10ms]
  └→ Span (user-service) [60ms]
      └→ Span (database) [40ms]

Key Components

• Trace - End-to-end request journey
• Span - Single operation within a trace
• Context - Metadata propagated between services
• Tags - Key-value pairs for filtering
• Logs - Timestamped events within a span

Jaeger Setup

Kubernetes Deployment

# Deploy Jaeger Operator
kubectl create namespace observability
kubectl create -f https://github.com/jaegertracing/jaeger-operator/releases/download/v1.51.0/jaeger-operator.yaml -n observability

# Deploy Jaeger instance
kubectl apply -f - <<EOF
apiVersion: jaegertracing.io/v1
kind: Jaeger
metadata:
  name: jaeger
  namespace: observability
spec:
  strategy: production
  storage:
    type: elasticsearch
    options:
      es:
        server-urls: http://elasticsearch:9200
  ingress:
    enabled: true
EOF

Docker Compose

version: '3.8'
services:
  jaeger:
    image: jaegertracing/all-in-one:latest
    ports:
      - "5775:5775/udp"
      - "6831:6831/udp"
      - "6832:6832/udp"
      - "5778:5778"
      - "16686:16686"  # UI
      - "14268:14268"  # Collector
      - "14250:14250"  # gRPC
      - "9411:9411"    # Zipkin
    environment:
      - COLLECTOR_ZIPKIN_HOST_PORT=:9411

Reference: See references/jaeger-setup.md

Application Instrumentation

OpenTelemetry (Recommended)

Python (Flask)

from opentelemetry import trace
from opentelemetry.exporter.jaeger.thrift import JaegerExporter
from opentelemetry.sdk.resources import SERVICE_NAME, Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.instrumentation.flask import FlaskInstrumentor
from flask import Flask

# Initialize tracer
resource = Resource(attributes={SERVICE_NAME: "my-service"})
provider = TracerProvider(resource=resource)
processor = BatchSpanProcessor(JaegerExporter(
    agent_host_name="jaeger",
    agent_port=6831,
))
provider.add_span_processor(processor)
trace.set_tracer_provider(provider)

# Instrument Flask
app = Flask(__name__)
FlaskInstrumentor().instrument_app(app)

@app.route('/api/users')
def get_users():
    tracer = trace.get_tracer(__name__)

    with tracer.start_as_current_span("get_users") as span:
        span.set_attribute("user.count", 100)
        # Business logic
        users = fetch_users_from_db()
        return {"users": users}

def fetch_users_from_db():
    tracer = trace.get_tracer(__name__)

    with tracer.start_as_current_span("database_query") as span:
        span.set_attribute("db.system", "postgresql")
        span.set_attribute("db.statement", )
        
         query_database()

Node.js (Express)

const { NodeTracerProvider } = require('@opentelemetry/sdk-trace-node');
const { JaegerExporter } = require('@opentelemetry/exporter-jaeger');
const { BatchSpanProcessor } = require('@opentelemetry/sdk-trace-base');
const { registerInstrumentations } = require('@opentelemetry/instrumentation');
const { HttpInstrumentation } = require('@opentelemetry/instrumentation-http');
const { ExpressInstrumentation } = require('@opentelemetry/instrumentation-express');

// Initialize tracer
const provider = new NodeTracerProvider({
  resource: { attributes: { 'service.name': 'my-service' } }
});

const exporter = new JaegerExporter({
  endpoint: 'http://jaeger:14268/api/traces'
});

provider.addSpanProcessor(new BatchSpanProcessor(exporter));
provider.register();

// Instrument libraries
registerInstrumentations({
  instrumentations: [
    new HttpInstrumentation(),
    new ExpressInstrumentation(),
  ],
});

 express = ();
 app = ();

app.(,  (req, res) => {
   tracer = trace.();
   span = tracer.();

   {
     users =  ();
    span.({ : users. });
    res.({ users })