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docker-compose.yml
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87 lines (80 loc) · 1.92 KB
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services:
app:
build: ./backend
container_name: oculus_backend
command: uvicorn app.main:app --host 0.0.0.0 --port 8000
ports:
- "8000:8000"
volumes:
- data_volume:/data
env_file:
- .env
depends_on:
- redis
- mongo
- gjtiff
celery-worker:
container_name: oculus_celery-worker
build: ./backend
command: celery -A app.infrastructure.celery.celery_app.celery worker -l info
volumes:
- data_volume:/data
env_file:
- .env
depends_on:
- redis
- mongo
restart: always
celery-worker-processing:
build: ./backend
container_name: oculus_celery-worker-processing
command: celery -A app.infrastructure.celery.celery_app.celery worker -Q process_task_queue --concurrency=1 -l info
volumes:
- data_volume:/data
- /var/run/docker.sock:/var/run/docker.sock
env_file:
- .env
depends_on:
- redis
- mongo
restart: always
celery-beat:
build: ./backend
container_name: oculus_celery-beat
command: celery -A app.infrastructure.celery.celery_app.celery beat --loglevel=info
volumes:
- data_volume:/data
depends_on:
- redis
- mongo
env_file:
- .env
restart: always
redis:
image: redis:7
container_name: oculus_redis
ports:
- "6379:6379"
restart: always
mongo:
image: mongo:6
container_name: oculus_mongo
ports:
- "27017:27017"
restart: always
gjtiff:
build: ./gjtiff
container_name: oculus_gjtiff # !!! This container must be named 'oculus_gjtiff' as GJTIFFProcessor Python class is hardcoded to this name !!!
command: [ "sleep", "infinity" ]
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [ gpu ]
volumes:
- ./gjtiff:/gjtiff
- data_volume:/data
volumes:
data_volume: