mitzo/docker-compose.yml at main · dimakis/mitzo · GitHub

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# Local observability stack: Jaeger (traces) + Loki (logs) + Grafana (UI) + MLflow (experiments).
# Jaeger only:  npm run tracing:up / tracing:down
# Full stack:   npm run observability:up / observability:down
# Jaeger UI: http://localhost:16686
# Grafana:   http://localhost:3002 (no login required)
# Loki API:  http://localhost:3200
# MLflow UI: http://localhost:5050
services:
  jaeger:
    image: jaegertracing/jaeger:2.19.0
    restart: always
    ports:
      - '4318:4318' # OTLP HTTP receiver (server + browser)
      - '16686:16686' # Jaeger UI
    command: ['--config', '/etc/jaeger/config.yaml']
    volumes:
      - ./infra/jaeger-v2-config.yaml:/etc/jaeger/config.yaml:ro
      - ./.jaeger-data:/badger

  loki:
    image: grafana/loki:3.4.2
    restart: always
    ports:
      - '3200:3100' # 3200 externally — 3100 conflicts with Mitzo server
    volumes:
      - ./infra/loki-config.yaml:/etc/loki/local-config.yaml
      - ./.loki-data:/loki
    command: -config.file=/etc/loki/local-config.yaml

  grafana:
    image: grafana/grafana:12.4.1
    restart: always
    ports:
      - '3002:3000'
    environment:
      GF_AUTH_ANONYMOUS_ENABLED: 'true'
      GF_AUTH_ANONYMOUS_ORG_ROLE: Admin
    volumes:
      - ./infra/grafana/provisioning:/etc/grafana/provisioning
      - ./.grafana-data:/var/lib/grafana
    depends_on:
      - loki
      - jaeger

  # Experiment tracking for knowledge space V-learning and prompt tuning.
  # Uses SQLite backend (single-writer, adequate for local dev).
  mlflow:
    image: ghcr.io/mlflow/mlflow:v2.22.0
    restart: always
    ports:
      - '5050:5000' # 5050 externally — 5000 conflicts with macOS AirPlay
    command:
      - mlflow
      - server
      - --host
      - '0.0.0.0'
      - --backend-store-uri
      - sqlite:///mlflow/mlflow.db
      - --default-artifact-root
      - /mlflow/artifacts
    volumes:
      - ./.mlflow-data:/mlflow