技能版本 1.0.0
distributed-tracing
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.
价格
免费
- 安装:免费
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如何使用
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技能说明
- 名称
- distributed-tracing
- 说明
- 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.
仅指令
技能包内没有脚本文件:这个技能是供模型阅读的文本。
SKILL.md 节选
# 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
## 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
```bash
# 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
```yaml
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)
```python
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", "SELECT * FROM users")
# Database query
return query_database()
```
#### Node.js (Express)
```javascript
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'
});SKILL.md 不止这些内容,安装后可阅读全文。
技能包内容
共 1 个文件,合计 10.0 KiB
- SKILL.md10.0 KiB
来源与审核
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