How to Deploy OpenTelemetry, Grafana Tempo, and Jaeger with Docker Compose for End-to-End Tracing

Tempo Overview

Grafana Tempo is an open‑source distributed tracing backend that stores and queries trace data at low cost. It is compatible with Jaeger, Zipkin and OpenTelemetry protocols, so existing instrumentation does not need changes.

Official docs: https://grafana.com/docs/tempo/latest/

Deployment

Docker‑Compose definition

Create a docker-compose.yaml that runs Grafana, Tempo, an OpenTelemetry Collector and a Jaeger Hot‑Rod example on a common trace network.

services:
  grafana:
    container_name: grafana
    image: grafana/grafana-oss:12.2.0-17142428006
    restart: always
    ports:
      - "3000:3000"
    volumes:
      - ./grafana/data:/var/lib/grafana
    environment:
      GF_SERVER_ROOT_URL: http://localhost:3000/
    networks:
      - trace

  tempo:
    image: grafana/tempo:r224-3f5070b
    container_name: tempo
    restart: unless-stopped
    ports:
      - "3200:3200"
    volumes:
      - ./tempo/tempo-config.yml:/etc/tempo/config.yml
      - ./tempo/tempo-data:/tmp/tempo
    command: ["-config.file=/etc/tempo/config.yml"]
    networks:
      - trace

  otel-collector:
    image: otel/opentelemetry-collector-contrib:0.136.0
    container_name: otel-collector
    restart: always
    ports:
      - "4317:4317"   # OTLP gRPC
      - "4318:4318"   # OTLP HTTP
    volumes:
      - ./otel/otel-collector-config.yml:/etc/otelcol-contrib/config.yaml
    networks:
      - trace

  jaeger-example-hotrod:
    image: jaegertracing/example-hotrod:1.72.0
    container_name: jaeger-example-hotrod
    restart: always
    command: ["all", "--otel-exporter=otlp"]
    ports:
      - "18080-18083:8080-8083"
    environment:
      - OTEL_EXPORTER_OTLP_ENDPOINT=http://otel-collector:4318
    depends_on:
      - otel-collector
    networks:
      - trace

networks:
  trace:
    driver: bridge
    driver_opts:
      com.docker.network.enable_ipv6: "false"

Tempo configuration (tempo-config.yml)

server:
  http_listen_port: 3200

distributor:
  receivers:
    otlp:
      protocols:
        http:
          endpoint: 0.0.0.0:4318
        grpc:
          endpoint: 0.0.0.0:4317

storage:
  trace:
    backend: local
    local:
      path: /tmp/tempo
    block:
      retention: 72h

OpenTelemetry Collector configuration (otel-collector-config.yml)

receivers:
  otlp:
    protocols:
      grpc:
        endpoint: "0.0.0.0:4317"
      http:
        endpoint: "0.0.0.0:4318"

processors:
  resource:
    attributes:
      - key: env
        value: "dev"
        action: upsert

exporters:
  otlphttp:
    endpoint: "http://tempo:4318"
    tls:
      insecure: true

service:
  pipelines:
    traces:
      receivers: [otlp]
      processors: [resource]
      exporters: [otlphttp]

Running the stack

Start all services in detached mode:

docker compose up -d

Grafana is reachable at http://localhost:3000 (default credentials admin/admin). Add a new data source of type Tempo with URL http://tempo:3200. Save and test the connection.

Observing traces

The Jaeger Hot‑Rod example generates trace data that is sent to the collector, forwarded to Tempo, and visualised in Grafana’s “Drill‑down” view. Open the Hot‑Rod UI at http://localhost:18080, interact with the sample endpoints, then switch to Grafana → Explore → Tempo to query traces by service name or trace ID.

Notes

Tempo uses local storage in this example; for production replace backend: local with an object store such as S3 or MinIO.

The collector disables TLS ( insecure: true) for simplicity; enable proper certificates in a secure environment.

All containers share the trace Docker bridge network, ensuring name‑based service discovery (e.g., tempo, otel-collector).