# One server. The same image and the same environment variables run a multi-server # deployment: point DJANGO_DATABASE_URL / DJANGO_REDIS_URL at your central services, set a # bucket, drop the `db` and `redis` services, and run several `web` containers behind a load # balancer. Nothing in the code changes. name: rosterchief services: caddy: build: context: ./deploy/caddy restart: unless-stopped ports: - "80:80" - "443:443" - "443:443/udp" environment: # A wildcard certificate for *.rosterchief.app cannot be issued over HTTP-01 — Let's # Encrypt only does wildcards via DNS-01. That is why Caddy needs a DNS API token, and # why this image is built with the provider's DNS plugin rather than pulled as-is. ROSTERCHIEF_BASE_DOMAIN: ${ROSTERCHIEF_BASE_DOMAIN:?set the base domain, e.g. rosterchief.app} ACME_EMAIL: ${ACME_EMAIL:?set an email for Let's Encrypt} CLOUDFLARE_API_TOKEN: ${CLOUDFLARE_API_TOKEN:?DNS-01 needs an API token with DNS:Edit on the zone} volumes: - ./deploy/caddy/Caddyfile:/etc/caddy/Caddyfile:ro - caddy_data:/data - caddy_config:/config # Read-only: Caddy serves club logos straight off disk instead of round-tripping every # image request through a gunicorn worker. Same volume `web` writes uploads into. - media_data:/srv/media:ro depends_on: - web web: build: . restart: unless-stopped env_file: .env.production volumes: # Uploaded club logos, while storage is local disk (see rosterchief/urls.py). Without # this, a rebuild or recreate wipes MEDIA_ROOT even though the container itself keeps # running fine in between. - media_data:/app/media # Private uploads (e.g. a member's medical certificate -- see rosterchief/storage.py). # Deliberately NOT mounted into `caddy` below, unlike media_data: nothing should be able # to serve this except the authenticated Django view that reads it. - private_media_data:/app/private_media depends_on: db: condition: service_healthy redis: condition: service_started healthcheck: test: ["CMD", "curl", "-fsS", "http://localhost:8000/healthz"] interval: 30s timeout: 5s retries: 3 start_period: 20s worker: build: . restart: unless-stopped env_file: .env.production # The scheduled platform jobs (see billing/tasks.py, club/tasks.py, events/tasks.py) run # here, dispatched by `beat` below over the same Redis `web` uses as a cache — see # rosterchief/settings.py's "Task queue (Celery)" section. Several of these are safe to # scale; `beat` is not (see its own comment). command: ["celery", "-A", "rosterchief", "worker", "--loglevel=info", "--concurrency=2"] volumes: - media_data:/app/media depends_on: db: condition: service_healthy redis: condition: service_started beat: build: . restart: unless-stopped env_file: .env.production # The scheduler -- decides *when* each task in CELERY_BEAT_SCHEDULE fires and hands it to # a worker. Run exactly ONE of these: two beats would each independently decide it's time # and every job runs twice (two archive_overdue_clubs runs is two emails to the same club, # same reasoning as the old crontab's "exactly one node" -- see DEPLOYMENT.md). command: ["celery", "-A", "rosterchief", "beat", "--loglevel=info"] depends_on: db: condition: service_healthy redis: condition: service_started db: image: postgres:17-alpine restart: unless-stopped environment: POSTGRES_DB: ${POSTGRES_DB:-rosterchief} POSTGRES_USER: ${POSTGRES_USER:-rosterchief} POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?set a database password} # shared_buffers/max_connections default to 128MB / 100 — sized for a much bigger database # than this app's (DEPLOYMENT.md: ~0.2GB after 5 years). 20 connections is comfortably above # 2 gunicorn workers x 4 threads plus the odd `manage.py` one-off; trimmed both for the box, # not for the data. command: ["postgres", "-c", "shared_buffers=64MB", "-c", "max_connections=20"] volumes: - pgdata:/var/lib/postgresql/data healthcheck: test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-rosterchief}"] interval: 10s timeout: 5s retries: 5 redis: image: redis:7-alpine restart: unless-stopped # Doubles as the Celery broker/result backend for `worker`/`beat` (see rosterchief/settings.py) # as well as the cache. maxmemory-policy allkeys-lru is right for a cache — evict rather than # grow unbounded — but it means a queued task message COULD be evicted under memory pressure # before a worker consumes it, same as a Redis restart drops anything queued (--save "", # --appendonly no: nothing here persists by design). Acceptable at this job volume (five # scheduled tasks a day; a missed one runs at its next scheduled time regardless, per # CELERY_BEAT_SCHEDULE); if that stops being true, give Celery its own Redis instance rather # than changing this cache's eviction policy to suit it. command: ["redis-server", "--save", "", "--appendonly", "no", "--maxmemory", "32mb", "--maxmemory-policy", "allkeys-lru"] volumes: pgdata: caddy_data: caddy_config: media_data: private_media_data: