OpenTelemetry Go 技术栈：Tempo Prometheus Loki

为 Go 部署 OpenTelemetry 栈：追踪、指标和日志

Go 应用的 OpenTelemetry 栈将追踪数据收集到 Tempo 中，指标收集到 Prometheus 中，日志收集到 Loki 中。客户端 app-1 通过 otel-collector 向服务器 app-2 发送请求。Grafana 可视化所有数据。整个栈使用 docker-compose 和最小配置运行。

Docker Compose 配置

关键服务：两个 Go 应用、otel-collector 作为遥测接收器、后端 Tempo/Prometheus/Loki 和 Grafana。可观测性网络隔离流量。

关键端口：

• app-2: 8080
• otel-collector: 4317 (gRPC), 4318 (HTTP), 8889 (metrics)
• Prometheus: 9090
• Tempo: 3200
• Loki: 3100
• Grafana: 3000

services:
  app-1:
    build: ./app_1
    depends_on:
      otel-collector:
        condition: service_started
    networks:
      - observability
  app-2:
    build: ./app_2
    ports:
      - "8080:8080"
    networks:
      - observability
  otel-collector:
    image: otel/opentelemetry-collector-contrib:latest
    ports:
      - "4318:4318"
      - "4317:4317"
      - "8889:8889"
    volumes:
      - ./configs/otel-collector-config.yaml:/etc/otelcol/config.yaml:ro
    networks:
      - observability
  prometheus:
    image: prom/prometheus:latest
    ports:
      - "9090:9090"
    volumes:
      - ./configs/prometheus.yml:/etc/prometheus/prometheus.yml:ro
    networks:
      - observability
  tempo:
    image: grafana/tempo:2.7.0
    ports:
      - "3200:3200"
    volumes:
      - ./configs/tempo-config.yaml:/etc/tempo/tempo.yaml
    networks:
      - observability
  loki:
    image: grafana/loki:3.3.2
    ports:
      - "3100:3100"
    volumes:
      - ./configs/loki-config.yaml:/etc/loki/local-config.yaml:ro
    networks:
      - observability
  grafana:
    image: grafana/grafana:latest
    ports:
      - "3000:3000"
    volumes:
      - ./configs/grafana/datasources.yaml:/etc/grafana/provisioning/datasources/datasources.yaml:ro
    networks:
      - observability
networks:
  observability:
    driver: bridge

用于追踪的 Tempo 配置

Tempo 通过 gRPC (4317) 和 HTTP (4318) 接收 OTLP。追踪块使用 30m 保留期进行压缩。trace_idle_period 为 5s 确保在用户界面中快速可见。

server:
  http_listen_port: 3200
  grpc_listen_port: 9095
distributor:
  receivers:
    otlp:
      protocols:
        grpc:
          endpoint: "0.0.0.0:4317"
ingester:
  trace_idle_period: 5s
  max_block_duration: 30m
storage:
  trace:
    backend: local
    local:
      path: /var/tempo/traces
compactor:
  compaction:
    block_retention: 30m

Prometheus 和告警规则

指标每 60s 从 otel-collector:8889 抓取。告警规则跟踪 P95 延迟 > 2000ms 和错误率 > 5%。

global:
  scrape_interval: 60s
scrape_configs:
  - job_name: "otel-collector"
    static_configs:
      - targets: ["otel-collector:8889"]

示例规则：

groups:
  - name: app1-service-alerts
    rules:
      - alert: App1LatencyHigh
        expr: histogram_quantile(0.95, sum by (le) (rate(app_1_requests_latency_ms_bucket[5m]))) > 2000
        for: 3m
        labels:
          severity: warning
  - name: app2-service-alerts
    rules:
      - alert: App2HighErrorRate
        expr: rate(app_2_requests_total{status="failed"}[5m]) / rate(app_2_requests_total[5m]) > 0.05
        for: 2m
        labels:
          severity: critical

用于日志的 Loki 配置

日志存储在文件系统中，使用 TSDB schema v13。按 24h 周期索引。启用结构化元数据。

auth_enabled: false
server:
  http_listen_port: 3100
common:
  path_prefix: /tmp/loki
  storage:
    filesystem:
      chunks_directory: /tmp/loki/chunks
schema_config:
  configs:
    - from: 2020-10-24
      store: tsdb
      schema: v13
      index:
        period: 24h
limits_config:
  allow_structured_metadata: true

Grafana 中的集成

数据源链接指标→追踪→日志：

• Prometheus exemplarTraceIdDestinations
• Loki derivedFields by traceID
• Tempo serviceMap and tracesToLogsV2

在 Go 客户端中初始化 OTel

InitOTel 函数为所有信号创建提供者，并带有资源属性。追踪采样率为 10%，导出时进行批处理。

func InitOTel(ctx context.Context, serviceName string) (*log.LoggerProvider, func(context.Context) error) {
    ctx, cancel := context.WithTimeout(ctx, 10*time.Second)
    defer cancel()

    res := resource.NewWithAttributes(
       semconv.SchemaURL,
       semconv.ServiceName(serviceName),
       semconv.ServiceVersion("1.0.0"),
    )

    // Tracing
    traceExp, err := otlptracegrpc.New(ctx,
       otlptracegrpc.WithEndpoint("otel-collector:4317"),
       otlptracegrpc.WithInsecure(),
    )
    tracerProvider := sdktrace.NewTracerProvider(
       sdktrace.WithSampler(sdktrace.ParentBased(sdktrace.TraceIDRatioBased(0.1))),
       sdktrace.WithBatcher(traceExp),
       sdktrace.WithResource(res),
    )
    otel.SetTracerProvider(tracerProvider)

    // Metrics
    metricExp, err := otlpmetricgrpc.New(ctx,
       otlpmetricgrpc.WithEndpoint("otel-collector:4317"),
       otlpmetricgrpc.WithInsecure(),
    )
    meterProvider := sdkmetric.NewMeterProvider(
       sdkmetric.WithReader(sdkmetric.NewPeriodicReader(metricExp, sdkmetric.WithInterval(10*time.Second))),
       sdkmetric.WithResource(res),
    )
    otel.SetMeterProvider(meterProvider)

    // Logs
    logExp, _ := otlploggrpc.New(ctx,
       otlploggrpc.WithEndpoint("otel-collector:4317"),
       otlploggrpc.WithInsecure(),
    )
    logProvider := log.NewLoggerProvider(
       log.WithProcessor(log.NewBatchProcessor(logExp)),
       log.WithResource(res),
    )

    return logProvider, func(ctx context.Context) error {
       // shutdown logic
       return nil
    }
}

关键点

• 完整的 OTel 栈：通过 otel-collector 集成追踪 (Tempo)、指标 (Prometheus)、日志 (Loki)
• Go 插桩：otelhttp.Transport、otelslog.Handler、counter/histogram 指标
• 原生 Grafana 集成：通过 traceID 从指标→追踪→日志转换
• 性能：trace_idle_period 5s、10% 采样、10s 周期读取器
• 告警：P95 延迟 > 2000ms、错误率 > 5%

— Editorial Team