docker-compose.yaml

version: "3"
services:
  notebook: # Notebook
    build:
      context: ./notebook
    image: swiri021/openkbc_msproject:notebookcontainer1
    volumes:
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/notebook/notebook_lib:/home/jovyan/work/notebook_lib
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/notebook/notebook_utils:/home/jovyan/work/notebook_utils
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/notebook/notebook_archive:/home/jovyan/work/notebook_archive
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/notebook/resultFiles:/home/jovyan/work/resultFiles
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/data:/home/jovyan/MainData
    ports:
      - 8888:8888
    container_name: notebookContainer

  pipelines: # Pipelines
    build:
      context: ./pipelines
    image: swiri021/openkbc_msproject:pipelinecontainer1
    volumes:
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/pipelines:/pipelines
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/data:/MainData
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/notebook/resultFiles:/Output
      -  $HOME/.aws/credentials:/root/.aws/credentials:ro
    ports:
      - 80:5000
    depends_on:
      - redis
    container_name: pipelineContainer
    working_dir: /pipelines/pipeline_controller
    command: conda run -n pipeline_controller_base gunicorn --bind 0.0.0.0:5000 --workers 2 --threads 4 --worker-class gthread connector:app

  redis: # redis
    image: redis:alpine
    command: redis-server
    ports:
      - 6379:6379
    container_name: redisServer

  celery: # celery
    build:
      context: ./pipelines
    image: swiri021/openkbc_msproject:celerycontainer1
    deploy:
      resources:
        limits:
          memory: 8000m
    volumes:
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/pipelines:/pipelines
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/data:/MainData
      - /Users/junheeyun/OpenKBC/multiple_sclerosis_proj/notebook/resultFiles:/Output
      -  $HOME/.aws/credentials:/root/.aws/credentials:ro
    working_dir: /pipelines/pipeline_controller/
    command: conda run -n pipeline_controller_base celery -A app.celery worker --loglevel=info
    depends_on:
      - redis
      - pipelines
    container_name: celeryContainer