docker-compose-train.yml

version: '3.3'

# with help from https://github.com/aganse/docker_mlflow_db/blob/master/docker-compose.yaml

# run local mlflow server
services:
  # use local s3 AWS based bucket for first tries to store artifacts
  # not required if you are using remote AWS bucket
  #localstack:
  #  image: localstack/localstack:latest
  #  container_name: mlflow_s3
  #  env_file:
  #    - ../.env
  #  environment:
  #    - EDGE_PORT=4566
  #    - SERVICES=lambda,s3
  #  ports:
  #    - '4566-4583:4566-4583'
  #  volumes:
  #    - "${TEMPDIR:-/tmp/localstack}:/tmp/localstack"
  #    - "/var/run/docker.sock:/var/run/docker.sock"
  #  networks:
  #    - backend

  #s3:
  #  image:  minio/minio:RELEASE.2021-11-24T23-19-33Z
  #  restart: unless-stopped
  #  container_name: mlflow_s3
  #  ports:
  #    - "9000:9000"
  #    - "9001:9001"
  #  environment:
  #    - MINIO_ROOT_USER=${AWS_ACCESS_KEY_ID}
  #    - MINIO_ROOT_PASSWORD=${AWS_SECRET_ACCESS_KEY}
  #  command: server /data --console-address ":9001"
  #  networks:
  #    - frontend
  #    - backend
  #  volumes:
  #    - minio_volume:/data

 #db:
 #   restart: always
 #   image: postgres:latest
 #   container_name: mlflow_db
 #   expose:
 #       - "5432"
 #   networks:
 #       - backend
 #   environment:
 #       - MUID=$UID
 #       - MGID=$GID
 #       - POSTGRES_DB=${POSTGRES_DATABASE}
 #       - POSTGRES_USER=${POSTGRES_USER}
 #       - POSTGRES_PASSWORD=${POSTGRES_PASSWORD}
 #   volumes:
 #     - db_datapg:/var/lib/postgresql/data

  web:
    restart: always
    build: ./mlflow
    image: mlflow_server
    container_name: mlflow_server
    expose:
      - "5000"
    networks:
      - frontend
      - backend
    env_file:
      - .env
    command: mlflow server --backend-store-uri postgresql://${POSTGRES_USER}:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:5432/${POSTGRES_DATABASE} --default-artifact-root s3://${MLFLOW_BUCKET_NAME} --host 0.0.0.0 -p 5000
  #  depends_on:
   #   - db
     # - create_s3_buckets

  nginx:
    restart: always
    build: ./nginx
    image: mlflow_nginx
    container_name: mlflow_nginx
    ports:
        - "${TRACKING_SERVER_HOST_PORT}:80"
    networks:
        - frontend
    depends_on:
        - web

  #create_s3_buckets:
  #  image: minio/mc
  #  depends_on:
  #    - "s3"
  #  entrypoint: >
  #    /bin/sh -c "
  #    until (/usr/bin/mc alias set minio http://s3:9000 '${AWS_ACCESS_KEY_ID}' '${AWS_SECRET_ACCESS_KEY}') do echo '...waiting...' && sleep 1; done;
  #    /usr/bin/mc mb minio/mlflow;
  #    exit 0;
  #    "
  #  networks:
  #    - backend

networks:
  frontend:
    driver: bridge
  backend:
    driver: bridge

volumes:
  db_datapg: {}
  minio_volume: {}

#  mlflow:
#    restart: always
#    image: mlflow_server:latest
#    container_name: mlflow_server_local
#    env_file:
#      - ../.env
#    environment:
#      - MLFLOW_S3_ENDPOINT_URL=s3://${MLFLOW_BUCKET_NAME}
#    ports:
#      - "5000:5000"
#    volumes:
#      - '../mlflow_data:/app'
#    depends_on:
#      - localstack
#    command: mlflow server --backend-store-uri sqlite:////app/mlflow.db --default-artifact-root s3://${MLFLOW_BUCKET_NAME} --host 0.0.0.0 -p 5000