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Exemples de Traçage Distribué
Exemples complets de traçage distribué utilisant Jaeger, OpenTelemetry et outils d'observabilité modernes
Exemples
Entrées de cette collection
Configuration de Traçage Distribué Jaeger
Configuration complète Jaeger avec collecteurs, agents et UI pour traçage distribué
Difficulté
6/10
Temps estimé
20 min
Étiquettes
jaeger, collector, agent, deployment, sampling, storage
# Jaeger Configuration File
# Complete setup for production distributed tracing
version: '3.8'
services:
# Jaeger Collector
jaeger-collector:
image: jaegertracing/jaeger-collector:1.45
environment:
- SPAN_STORAGE_TYPE=elasticsearch
- ES_SERVER_URLS=http://elasticsearch:9200
- ES_USERNAME=elastic
- ES_PASSWORD=changeme
- ES_INDEX_PREFIX=jaeger
- COLLECTOR_ZIPKIN_HOST_PORT=:9411
- COLLECTOR_OTLP_ENABLED=true
ports:
- "14269:14269"
- "14268:14268"
- "14250:14250"
- "9411:9411"
depends_on:
- elasticsearch
# Jaeger Agent
jaeger-agent:
image: jaegertracing/jaeger-agent:1.45
command: ["--reporter.grpc.host-port=jaeger-collector:14250"]
ports:
- "6831:6831/udp"
- "6832:6832/udp"
depends_on:
- jaeger-collector
# Jaeger Query Service
jaeger-query:
image: jaegertracing/jaeger-query:1.45
environment:
- SPAN_STORAGE_TYPE=elasticsearch
- ES_SERVER_URLS=http://elasticsearch:9200
- ES_USERNAME=elastic
- ES_PASSWORD=changeme
- ES_INDEX_PREFIX=jaeger
- JAEGER_UI_CONFIG_JSON=/etc/jaeger-ui-config.json
ports:
- "16686:16686"
- "16687:16687"
volumes:
- ./jaeger-ui-config.json:/etc/jaeger-ui-config.json
depends_on:
- elasticsearch
# Elasticsearch Backend
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:8.8.0
environment:
- discovery.type=single-node
- ES_JAVA_OPTS=-Xms1g -Xmx1g
- xpack.security.enabled=false
ports:
- "9200:9200"
volumes:
- elasticsearch_data:/usr/share/elasticsearch/data
volumes:
elasticsearch_data:- format
- YAML
- version
- 1.x
- components
- ["collector","agent","query-service","ui"]
- storage
- elasticsearch
- features
- ["sampling","compression","batch-processing"]
Instrumentation Automatique OpenTelemetry
Configuration d'instrumentation automatique pour plusieurs langages avec spans personnalisés
Difficulté
7/10
Temps estimé
25 min
Étiquettes
opentelemetry, instrumentation, auto-instrument, telemetry, metrics, tracing
# OpenTelemetry Auto-Instrumentation Configuration
# Example configuration for Java applications
# Environment Variables
export OTEL_SERVICE_NAME=my-service
export OTEL_RESOURCE_ATTRIBUTES=service.name=my-service,service.version=1.0.0
export OTEL_EXPORTER_OTLP_ENDPOINT=http://otel-collector:4317
export OTEL_TRACES_SAMPLER=traceidratio
export OTEL_TRACES_SAMPLER_ARG=1.0
# Java Agent Configuration
-javaagent:/app/opentelemetry-javaagent.jar -Dotel.service.name=my-service -Dotel.resource.attributes=service.name=my-service,service.version=1.0.0 -Dotel.exporter.otlp.endpoint=http://otel-collector:4317 -Dotel.traces.sampler=traceidratio -Dotel.traces.sampler.arg=1.0 -Dotel.javaagent.extensions=io.opentelemetry.extension.noopapi.NoOpApiExtension
# Custom Span Creation (Java Example)
import io.opentelemetry.api.OpenTelemetry;
import io.opentelemetry.api.trace.Span;
import io.opentelemetry.api.trace.Tracer;
Tracer tracer = OpenTelemetry.getGlobalTracer("my-service");
Span span = tracer.spanBuilder("custom-operation")
.setAttribute("user.id", "12345")
.setAttribute("operation.type", "business")
.startSpan();
// Do work here...
span.end();- format
- JSON
- specification
- OpenTelemetry
- languages
- ["java","python","nodejs","go","dotnet"]
- features
- ["auto-instrumentation","custom-spans","baggage","propagation"]
Flux de Requêtes Microservices
Exemple de trace distribuée montrant le flux à travers plusieurs microservices
Difficulté
5/10
Temps estimé
10 min
Étiquettes
microservices, request-flow, correlation, context-propagation, span-tree
{
"trace_id": "550e8400-e29b-41d4-a716-446655440000",
"spans": [
{
"trace_id": "550e8400-e29b-41d4-a716-446655440000",
"span_id": "550e8400-e29b-41d4-a716-446655440001",
"parent_span_id": null,
"operation_name": "HTTP GET /api/orders",
"service_name": "api-gateway",
"start_time": 1701954645123000000,
"end_time": 1701954645156000000,
"duration_ms": 33,
"tags": {
"http.method": "GET",
"http.url": "/api/orders",
"http.status_code": "200",
"component": "netty"
},
"logs": [
{
"timestamp": 1701954645140000000,
"level": "info",
"message": "Request authenticated successfully"
}
]
},
{
"trace_id": "550e8400-e29b-41d4-a716-446655440000",
"span_id": "550e8400-e29b-41d4-a716-446655440002",
"parent_span_id": "550e8400-e29b-41d4-a716-446655440001",
"operation_name": "UserService.GetUser",
"service_name": "user-service",
"start_time": 1701954645130000000,
"end_time": 1701954645145000000,
"duration_ms": 15,
"tags": {
"user.id": "12345",
"db.system": "postgresql",
"operation.type": "query"
}
},
{
"trace_id": "550e8400-e29b-41d4-a716-446655440000",
"span_id": "550e8400-e29b-41d4-a716-446655440003",
"parent_span_id": "550e8400-e29b-41d4-a716-446655440001",
"operation_name": "OrderService.GetOrders",
"service_name": "order-service",
"start_time": 1701954645132000000,
"end_time": 1701954645152000000,
"duration_ms": 20,
"tags": {
"user.id": "12345",
"operation.type": "business"
}
}
]
}- format
- JSON
- services
- ["api-gateway","user-service","order-service","payment-service","notification-service"]
- spanTypes
- ["http","database","cache","message-queue"]
- complexity
- multi-service
Détection de Goulots d'Étranglement de Performance
Configuration avancée pour identifier les goulots avec attributs détaillés
Difficulté
8/10
Temps estimé
30 min
Étiquettes
performance, bottleneck, analysis, optimization, error-tracking, metrics
# Performance Analysis Configuration
# Example setup for performance bottleneck detection
# Custom Span Attributes
attributes:
- database.query.duration
- cache.hit_ratio
- memory.usage
- cpu.utilization
# Performance Thresholds
thresholds:
slow_query: 100ms
high_memory: 80%
high_cpu: 90%
# Alert Configuration
alerts:
- name: Slow Database Queries
condition: span.duration > 100ms
severity: warning- format
- YAML
- features
- ["span-attributes","error-tracking","slow-queries","memory-usage","cpu-profiling"]
- alerts
- ["threshold-based","anomaly-detection"]
- integrations
- ["prometheus","grafana"]
Pipeline OpenTelemetry Collector
Configuration pour traiter et exporter les traces vers plusieurs backends
Difficulté
7/10
Temps estimé
25 min
Étiquettes
otel-collector, pipeline, processors, exporters, receivers
# OpenTelemetry Collector Configuration
receivers:
otlp:
protocols:
grpc:
http:
processors:
memory_limiter:
check_interval: 5s
limit_mib: 512
batch:
timeout: 5s
send_batch_size: 1024
attributes:
actions:
- key: environment
value: production
action: insert
exporters:
otlp/jaeger:
endpoint: jaeger-collector:4317
tls:
insecure: true
logging:
loglevel: info
service:
pipelines:
traces:
receivers: [otlp]
processors: [memory_limiter, batch, attributes]
exporters: [otlp/jaeger, logging]- format
- YAML
- version
- 0.x
- components
- ["receivers","processors","exporters","extensions"]
- backends
- ["jaeger","zipkin","prometheus","elasticsearch"]
- features
- ["batch-processing","sampling","filtering","transformation"]
Propagation de Contexte Inter-Services
Exemple d'implémentation de propagation de contexte entre microservices
Difficulté
6/10
Temps estimé
15 min
Étiquettes
context-propagation, headers, cross-service, correlation, baggage
// Context propagation across services (Node.js + OpenTelemetry)
import { context, propagation, trace } from '@opentelemetry/api'
const tracer = trace.getTracer('orders-service')
export async function handleIncomingRequest(req, res) {
// Extract trace context from inbound HTTP headers
const parentContext = propagation.extract(context.active(), req.headers)
await context.with(parentContext, async () => {
const span = tracer.startSpan('handle-order-request')
try {
span.setAttribute('http.route', req.url)
span.setAttribute('service.name', 'orders-service')
// Inject context when calling downstream service
const headers = {}
const spanContext = trace.setSpan(context.active(), span)
propagation.inject(spanContext, headers)
const response = await fetch('http://inventory-service/check', {
method: 'POST',
headers: {
...headers,
'content-type': 'application/json'
},
body: JSON.stringify({ sku: req.body.sku, quantity: req.body.quantity })
})
if (!response.ok) {
span.setAttribute('error', true)
span.setAttribute('http.status_code', response.status)
}
res.status(200).json({ ok: true })
} catch (error) {
span.recordException(error)
span.setAttribute('error', true)
res.status(500).json({ ok: false })
} finally {
span.end()
}
})
}- format
- JavaScript
- apis
- ["@opentelemetry/api","@opentelemetry/sdk-node"]
- concepts
- ["context","baggage","propagators","extract","inject"]
- protocols
- ["http","grpc","messaging"]
Outils
Outils souvent utilisés avec cet exemple
Associé