Implements BILLING.md. The architecture was sound -- snapshot-on-Due, dated prices, asymmetric dry-run commands are all kept -- so this fixes the three hardcoded assumptions rather than rewriting. The real defect: grace ran from period_END, so an annual club used the whole unpaid year plus 45 days (~410 days) before anything switched it off. Grace now runs from the period START, and every clock is per-plan. - Tier -> Plan (+ TierPrice -> PlanPrice, and every FK). Migration 0004 is hand-written: run non-interactively, makemigrations emits DeleteModel+CreateModel and drops every price, subscription and due. Its two RemoveConstraints must come first, or SQLite's table-rebuild tries to render a constraint over a just-renamed column. Verified by round-tripping real rows through it. - Plan gains duration_months / renewal_lead_days / grace_days / is_trial, with CheckConstraints and a matching clean() so the form reports an impossible plan instead of 500ing on IntegrityError. - Existing dues keep their stored grace_until. Re-deriving it would put the date in the past for every open annual period and archive the entire paying customer base on the next --commit run. - Trials take their length from the trial plan's own duration_months; start_trial() loses its trial_months argument. - New BillingNotice service drives a club-facing warning: every level on the dashboard, and on every management page once urgent. - send_billing_reminders emails club admins, once per escalation level so a daily cron is not a daily email. SMTP settings are env-driven and provider-agnostic; the backend defaults to console. - Paying does not auto-restore an archived club -- the control panel surfaces a Reactivate prompt instead, since a club can also be archived by hand.
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Deploying RosterChief
One server today, several later, with no code changes in between — only environment variables. This document is the runbook and, more usefully, the list of things that are specific to this app and will bite you if you treat it as a generic Django deploy.
The five things that make this deployment unusual
1. You need a wildcard TLS certificate, and that forces DNS-01.
Tenancy is subdomain-based (ajax.rosterchief.app), so the certificate must cover
*.rosterchief.app. Let's Encrypt will not issue a wildcard over HTTP-01 — only over
DNS-01, which means the TLS terminator needs API access to your DNS zone. That is why
deploy/caddy/Dockerfile builds Caddy with a DNS provider plugin, and why
CLOUDFLARE_API_TOKEN is a required variable rather than a nicety. Swap the plugin
(caddy-dns/route53, caddy-dns/digitalocean, …) if your DNS lives elsewhere.
DNS needs two records, both pointing at the server:
A rosterchief.app -> <server ip>
A *.rosterchief.app -> <server ip>
2. Redis is not optional, even on one server.
waffle caches each feature flag's targeting in the Django cache, and LocMemCache is
private to a single process. Under several gunicorn workers, toggling a feature in the
control panel flushes one worker's cache while the others keep serving the stale flag —
a feature that "sometimes doesn't turn on". A shared cache is the fix.
3. SECURE_PROXY_SSL_HEADER must be set, and Caddy must send the header.
Caddy terminates TLS, so without it Django believes every request is plain HTTP:
request.is_secure() goes false, WebAuthn disagrees with the browser about the origin, and
SECURE_SSL_REDIRECT becomes a redirect loop. Both halves are already wired (settings +
header_up X-Forwarded-Proto); don't remove either.
4. Uploads must move to object storage before the second app server.
Club logos go to MEDIA_ROOT on local disk by default. compose.yaml mounts a media_data
volume, shared read-write with web and read-only with caddy, so uploads both survive a
rebuild and get served by Caddy directly (handle_path /media/* in the Caddyfile) rather than
round-tripping through a gunicorn worker. rosterchief/urls.py still serves /media/* itself
as a fallback whenever AWS_STORAGE_BUCKET_NAME is unset — needed for compose.behind-proxy.yaml
(no bundled Caddy there) and for runserver. On two boxes local disk stops working regardless
of any of this: a logo uploaded to node A is still a 404 on node B, since nothing shares the
volume between them. Setting AWS_STORAGE_BUCKET_NAME switches the default storage to S3 — do
it before you scale, not during.
5. PDF invoices need native libraries. WeasyPrint binds to pango/cairo. The image installs them; a bare-metal deploy would need them too, and a Mac needs Homebrew. This is the main reason to run the container even in development if you touch invoicing.
First deploy
# 1. Configure
cp .env.compose.example .env # read by docker compose
cp .env.production.example .env.production # read by Django
python -c "import secrets; print(secrets.token_urlsafe(64))" # -> DJANGO_SECRET_KEY
# 2. Build and start
docker compose build
docker compose up -d db redis
docker compose run --rm web python manage.py migrate
docker compose run --rm web python manage.py createsuperuser
docker compose up -d
# 3. Verify
curl -fsS https://rosterchief.app/healthz # {"status": "ok", ...}
docker compose run --rm web python manage.py check --deploy
check --deploy is what catches an env file that forgot the HTTPS flags: they default to
off in code, because defaulting them to not DEBUG would redirect every test request to
https and break the suite anywhere DEBUG is unset.
Keep DJANGO_DEBUG=False, even on the test server
A test box is still a deployment: it is behind TLS, on a real domain, with real passkeys.
DEBUG=True there leaks tracebacks and settings to anyone who can reach a 500, and turns off
several of the protections in this document. Use it locally, not on a server.
The app no longer crashes if you set it — django_browser_reload is a dev dependency that
the image installs with --no-dev, so settings guard on the module being importable rather
than assuming DEBUG implies it is there — but the reason to keep it off is not the crash.
One dependency comes from git
django-lucide is our fork ([tool.uv.sources] in pyproject.toml, pinned by uv.lock to a
commit), so uv shells out to git to fetch it. python:*-slim has no git, which is why
the image builds the virtualenv in a separate stage that installs git, and copies the
finished .venv into a runtime stage that does not have it — a build tool has no business in
a production image.
Two consequences worth knowing:
- The build needs network access to GitHub, and the fork must stay reachable. If that ever becomes awkward (a private runner, an air-gapped build), publish the fork to a private index or vendor the wheel, and the git stage disappears.
uv.lockpins the exact commit, so the build is reproducible even though the source is a branch. Don't build with--no-frozen.
The first docker compose up will take a minute or two: Caddy is provisioning the wildcard
certificate over DNS-01, and DNS propagation is not instant. Watch it with
docker compose logs -f caddy.
Migrations
Deliberately not run by the container's entrypoint. With more than one web container they would race, and a starting gunicorn worker is a bad place to discover a failed migration. Run them once, explicitly, as part of the deploy:
docker compose build
docker compose run --rm web python manage.py migrate
docker compose up -d --no-deps web
Scheduled jobs
Four commands need to run on a schedule. Put them on the host, not in a container, and on exactly one node when you have several — three nodes archiving the same club is three emails to the same club.
# Bill: remind club admins about outstanding platform fees. Dry-run by default, same as the
# archive job below — this one mails paying customers, so --commit is opt-in. Reminders go
# once per escalation level, not once per run, so a daily cron is not a daily email.
0 5 * * * cd /srv/rosterchief && docker compose run --rm web python manage.py send_billing_reminders --commit
# Bill: archive clubs unpaid past their grace period.
# Run it WITHOUT --commit for the first week and read the output. The flag exists because
# this switches off paying customers: a bad clock or a bad cron should cost you an email,
# not a morning of angry clubs. Since grace now runs from the period START rather than its
# end (see BILLING.md §3), this job is load-bearing in a way it never used to be — a club
# is archivable ~60 days after being invoiced, not ~410. Re-do the dry-run week.
0 6 * * * cd /srv/rosterchief && docker compose run --rm web python manage.py archive_overdue_clubs --commit
# Events: extend recurring series so the calendar never runs dry.
0 3 * * * cd /srv/rosterchief && docker compose run --rm web python manage.py extend_event_series
# Seasons: generate the next 2 years ahead for every active club. Safe to run repeatedly and
# needs no --commit — unlike archiving or resyncing, creating a future season row is additive
# and idempotent, so a monthly cadence just keeps every club's season list from ever running
# out. --resync exists on the same command for removing seasons that no longer match a club's
# settings, but that can delete rows, so it isn't run unattended here.
0 5 1 * * cd /srv/rosterchief && docker compose run --rm web python manage.py generate_seasons
Maintenance mode
Control panel → Features → Maintenance mode. While it is on:
- every club subdomain serves a 503 maintenance page, in that club's own colours;
- the control panel and the sign-in screens stay open, because closing them would leave you with no way to turn it back off;
/healthzkeeps answering on every host, or the load balancer would take the node out of rotation and the control panel with it;- the scheduled jobs stand down —
archive_overdue_clubs,extend_event_seriesandimport_members_csvrefuse to run.
migrate and collectstatic are deliberately not blocked. Maintenance is usually
declared in order to run them, and a guard that stopped them would mean turning the mode
off to do the work you turned it on for.
The scheduled jobs exit non-zero while the platform is closed, so cron will mail you.
That is intended: a job that silently skips itself is how a month of billing goes missing. If
you genuinely mean to run one during a window, pass --ignore-maintenance.
So a migration-heavy deploy looks like:
# 1. Close the platform in the control panel (or from a shell):
docker compose run --rm web python manage.py shell -c \
"from features.models import Maintenance; Maintenance.start(message='Upgrading. Back by 21:00.')"
# 2. Do the work — migrate is not blocked.
docker compose build
docker compose run --rm web python manage.py migrate
docker compose up -d --no-deps web
# 3. Reopen from the control panel.
The state lives in Redis as well as the database, so it takes effect on every worker and every server at once — a per-process cache would leave some workers still serving clubs.
Behind an existing Caddy (dev / test server)
If the box already runs Caddy on :80 and :443 — a test server sharing a host with other sites — do not run ours: two Caddies cannot both hold port 80. Run the app only, publish it on the loopback, and add a site block to the Caddy that is already there.
docker compose -f compose.behind-proxy.yaml up -d # web + db + redis, no caddy
web publishes on 127.0.0.1:8001 (override with WEB_PORT). Loopback, not 0.0.0.0 —
bound to all interfaces, a test instance is reachable at http://<server-ip>:8001 with no
TLS, bypassing the proxy and every security header with it.
Then add a site block to the host's Caddyfile. Caddy serves any number of domains on the same ports — TLS is chosen per connection by SNI — so a second (or tenth) site is just another block.
If that Caddy already does Cloudflare DNS-01
Which is the usual case: the box has a domain on Cloudflare and Caddy already has the DNS
plugin. Then set the challenge once, globally, and every site inherits it — no tls
block per site, and wildcards simply work:
{
email you@example.com
# Applies DNS-01 to every site below.
acme_dns cloudflare {env.CLOUDFLARE_API_TOKEN}
}
# --- whatever the box already serves --------------------------------------
existing-thing.example.com {
reverse_proxy 127.0.0.1:3000
}
# --- RosterChief test instance --------------------------------------------
# The bare host AND the wildcard, on one certificate.
test.rosterchief.app, *.test.rosterchief.app {
encode zstd gzip
reverse_proxy 127.0.0.1:8001 {
header_up X-Forwarded-Proto {scheme}
header_up X-Real-IP {remote_host}
}
}
If the two domains need different tokens
Different Cloudflare accounts, or tokens scoped per zone. Drop acme_dns and give each site
its own tls; a snippet keeps it short:
{
email you@example.com
}
(cf) {
tls {
dns cloudflare {args[0]}
}
}
existing-thing.example.com {
import cf {env.CF_TOKEN_EXAMPLE}
reverse_proxy 127.0.0.1:3000
}
test.rosterchief.app, *.test.rosterchief.app {
import cf {env.CF_TOKEN_ROSTERCHIEF}
reverse_proxy 127.0.0.1:8001 {
header_up X-Forwarded-Proto {scheme}
}
}
What actually goes wrong
-
The token must cover the new zone. A Cloudflare token is scoped to named zones, and an existing one almost certainly grants
Zone:DNS:Editon the domain it was made for and nothing else. The new site then fails its DNS-01 challenge on a permissions error whose text does not say so. Widen the token, or mint a second one and use the snippet form. -
Both hostnames must be listed.
*.test.rosterchief.appdoes not matchtest.rosterchief.app— a wildcard covers exactly one label. Leave the bare host out and the club subdomains have a certificate while the control panel does not. Hence the comma. (Wildcards are also only one level deep:ajax.test.…yes,a.b.test.…no.) -
Caddy must have the DNS plugin. Stock
caddycannot answer a DNS-01 challenge at all.caddy add-package github.com/caddy-dns/cloudflare, or run a Caddy built likedeploy/caddy/Dockerfile. (If DNS-01 already works on the box, you have it.) -
The token must be in Caddy's environment, not your shell's —
{env.…}reads the process it runs in:# /etc/systemd/system/caddy.service.d/override.conf [Service] EnvironmentFile=/etc/caddy/caddy.env # CLOUDFLARE_API_TOKEN=...Then
systemctl daemon-reload && systemctl restart caddy. -
header_up X-Forwarded-Protois not optional, exactly as in the bundled Caddyfile: without it Django believes the request behind the proxy is plain HTTP. -
Give the test instance its own subdomain tree and set
ROSTERCHIEF_BASE_DOMAIN=test.rosterchief.app. That variable drives tenant resolution, the shared session cookie and the WebAuthn RP ID — point it at the production domain and test passkeys start colliding with real ones.
Applying and checking it
caddy validate --config /etc/caddy/Caddyfile # syntax and modules
systemctl reload caddy # zero downtime; existing certs untouched
journalctl -u caddy -f # watch the DNS-01 challenge
curl -I https://test.rosterchief.app/healthz
curl -I https://any-club-slug.test.rosterchief.app/ # proves the WILDCARD, not just the host
Reloading provisions only what is new, so the existing site's certificate is not reissued. Allow 30–60s for the DNS record to propagate before the challenge completes.
DNS needs both records, pointing at the test box:
A test.rosterchief.app -> <server ip>
A *.test.rosterchief.app -> <server ip>
The compose project is named rosterchief-test, so its containers and volumes never collide
with a production stack on the same host.
Deploying with one command
Once the server has the repo cloned at /home/bernard/RosterChief and its two env files in
place, deploy/deploy-dev.sh does a full deploy over SSH:
deploy/deploy-dev.sh # deploy the current branch
BRANCH=main deploy/deploy-dev.sh
deploy/deploy-dev.sh --push # push the branch first, then deploy
It runs from your machine and does the work on the server in one SSH session: fetch the pushed
branch (a hard reset to origin/<branch>, since a deploy target only receives deploys), build
the image, run migrations explicitly, restart only web, and wait for /healthz.
It refuses to deploy a branch whose local commits are not pushed — the server pulls from git,
so unpushed work would ship stale code silently. Override the host, user, directory or branch
with the SSH_HOST / SSH_USER / REMOTE_DIR / BRANCH environment variables.
First-time setup on the server, once:
git clone git@git.siebens.org:bernard/RosterChief.git /home/bernard/RosterChief
cd /home/bernard/RosterChief
cp .env.compose.example .env # fill in POSTGRES_PASSWORD etc.
cp .env.production.example .env.production
# then add the reverse_proxy site block to the host's Caddy (see above)
Automated backups
deploy/backup.sh dumps the database, tars the uploads while they are still on local disk,
prunes anything older than KEEP_DAYS, and — if you set BACKUP_REMOTE — copies the lot off
the box with rclone.
deploy/backup.sh /var/backups/rosterchief
It writes to a .part file and only moves it into place once gzip -t says the archive is
readable and non-empty. A truncated dump that looks like a backup is the failure mode worth
engineering against, because you only discover it on the day you need it.
Schedule it as root on the host (single server; on several, run it on the database node):
# Nightly at 02:30, before the billing and event jobs.
30 2 * * * cd /srv/rosterchief && BACKUP_REMOTE=b2:rosterchief-backups KEEP_DAYS=14 deploy/backup.sh /var/backups/rosterchief
# Weekly restore rehearsal into a throwaway database. This is the only line here that proves
# the others work.
0 4 * * 0 cd /srv/rosterchief && deploy/restore-check.sh
Cron mails you on non-zero exit, and the script uses set -Eeuo pipefail so it does exit
non-zero. A backup script that fails quietly is worse than none, because you will believe you
have backups.
Offsite matters more than frequency. A dump sitting on the same disk as the database
survives a bad migration but not the server. BACKUP_REMOTE takes any rclone remote (S3,
Backblaze, a second box).
Once uploads move to S3 (AWS_STORAGE_BUCKET_NAME), the script skips the media tarball:
the bucket's own versioning is the backup. Turn versioning on when you create it.
Restoring
gunzip -c /var/backups/rosterchief/db-2026-07-14-0230.sql.gz \
| docker compose exec -T db psql -U rosterchief rosterchief
The dump is taken with --clean --if-exists, so it drops and recreates rather than colliding
with what is there. Rehearse it once, now, against a scratch database — not the first time you
need it.
Backups (manual)
Two things carry state: Postgres and the uploads.
# Database
docker compose exec -T db pg_dump -U rosterchief rosterchief | gzip > rosterchief-$(date +%F).sql.gz
# Uploads — until they are on S3, in which case the bucket's own versioning is the backup.
docker compose cp web:/app/media ./media-backup
Restore is gunzip -c dump.sql.gz | docker compose exec -T db psql -U rosterchief rosterchief.
Test it once, now, rather than the first time you need it.
Sizing the server
For 1–5 clubs, ~1000 members, ~10 events per club per week.
The short answer: 2 vCPU, 4 GB RAM, 40 GB SSD — a €4–6/month VPS (Hetzner CX22 or equivalent). The interesting part is why, because the data is not what sizes this box.
The data is negligible
Row counts for that workload, from the actual schema (attendance dominates: every event invites a squad, so one event is ~20 rows):
| table | rows/year | MB/year |
|---|---|---|
events.Attendance |
52,000 | 16 |
events.Event |
2,600 | 2 |
formbuilder answers |
10,000 | 3 |
shop orders + lines |
3,000 | 1 |
| members, memberships, rosters | ~3,000 | 1 |
| total, with WAL and bloat | ~40 MB/year |
That is 0.2 GB after five years. Uploads are club logos — a handful of files. Invoices are rendered on demand and never stored. Nothing here grows into a problem.
So do not size for the data. Size for the processes.
What actually consumes the box
Measured, running this app under gunicorn with DEBUG=False, before the tuning below —
--workers 3, no --preload, Postgres and Redis on their image defaults:
| memory | |
|---|---|
| gunicorn master + 3 workers | ~270 MB (~54 MB per worker) |
PostgreSQL (default shared_buffers) |
~200–400 MB |
| Redis (cache only) | < 50 MB |
| Caddy | ~30 MB |
| OS + Docker daemon | ~400 MB |
| steady state | ~1.0–1.2 GB |
Since then, Dockerfile/compose.yaml were tuned for smaller boxes: --workers 2 --preload
(one fewer duplicated Django process, and --preload shares immutable memory across workers
via copy-on-write instead of each worker importing Django independently), plus trimmed Postgres
shared_buffers/max_connections and a Redis --maxmemory cap. Expect the gunicorn and
Postgres rows to come in lower than above — not yet re-measured, so treat the table as the
shape of where memory goes rather than exact numbers on the current config.
2 GB would run it. 4 GB is the recommendation for three reasons, all of which are the kind of thing that bites at the worst moment:
docker compose buildis the memory spike, not serving. npm, uv andcollectstatictogether will OOM a 2 GB box that is also running Postgres. Either take the 4 GB, or build the image elsewhere and pull it.- Rendering an invoice loads WeasyPrint. It is imported lazily (which is why the workers measure 54 MB and not 150), so pango and its fonts land in whichever worker renders a PDF — expect that worker to grow by ~50–100 MB the first time someone downloads an invoice.
- Headroom is Postgres's page cache. With 200 MB of data and 4 GB of RAM, the entire database lives in cache and the disk is never touched for reads.
Disk
| Docker images (app ~1 GB with pango, postgres, redis, caddy) | ~1.5 GB |
| Build cache | 2–4 GB |
| Database, 5 years | < 0.5 GB |
| Backups: 14 daily compressed dumps | < 0.5 GB |
| Logs | ~1 GB |
| 40 GB is roomy; 20 GB works |
CPU and concurrency
2 vCPU. Three workers × four threads is twelve concurrent requests, against a peak of "the whole club checks the Saturday line-up at 09:00" — perhaps a few hundred requests over a few minutes. This workload is not CPU-bound; the one CPU-heavy operation is PDF rendering, which happens a handful of times a month.
When to grow
Not at "more members" — at these:
- Uploads become real content (photo galleries, documents). Media, not rows, is what makes storage grow, and it is also the trigger for moving to S3.
- Attendance passes a few million rows (~20 clubs at this rate, i.e. several years out). Add an index before adding a server.
- You want zero-downtime deploys. That is a second app node, not a bigger one.
For fun: three nodes on AWS
Wildly over-engineered for 1000 members, but here is what it looks like — and what it costs.
The layout
Route 53 (rosterchief.app + *.rosterchief.app)
|
ACM certificate (wildcard, free)
|
Application Load Balancer (TLS terminates here)
|
+----+----+----+
| | |
ECS task task task 3 × Fargate, one per AZ, same image
| | |
+----+----+----+
|
+----+---------------+----------------+
| | |
RDS PostgreSQL ElastiCache Redis S3 (media)
(Multi-AZ) (cache.t4g.micro) + CloudFront (optional)
The one genuinely nice thing AWS gives you here: ACM issues the wildcard certificate for free, with DNS validation in Route 53. The whole DNS-01 dance disappears — no Caddy plugin, no API token, no renewal. The ALB terminates TLS and forwards to the tasks. That is the single biggest simplification versus the VPS.
What changes in the app
Nothing in the code. Only environment:
DJANGO_DATABASE_URL |
the RDS endpoint |
DJANGO_REDIS_URL |
the ElastiCache endpoint |
AWS_STORAGE_BUCKET_NAME |
the media bucket — required now, three nodes cannot share a disk |
SECURE_PROXY_SSL_HEADER |
already set; the ALB sends X-Forwarded-Proto |
| health check | point the target group at /healthz — that is what it is for |
Sessions are database-backed, so no sticky sessions: any task can serve any request.
Scheduled jobs get better here. EventBridge Scheduler firing a one-off ECS task solves the "run it on exactly one node" problem properly — no cron on three boxes racing each other:
EventBridge (cron: 0 6 * * ? *) -> ECS RunTask -> archive_overdue_clubs --commit
Backups become RDS automated snapshots + PITR, and deploy/backup.sh retires — though the
restore rehearsal does not. Snapshots you have never restored are still a hypothesis.
Monthly cost (eu-central-1, on-demand, indicative)
| $/month | ||
|---|---|---|
| ALB | fixed + a little LCU | ~22 |
| ECS Fargate | 3 × (0.5 vCPU, 1 GB) | ~54 |
| RDS PostgreSQL | db.t4g.micro, 20 GB gp3, single-AZ |
~17 |
| ElastiCache | cache.t4g.micro |
~12 |
| S3 + CloudFront | a few GB, low traffic | ~2 |
| Route 53 | hosted zone + queries | ~1 |
| ECR, CloudWatch logs | small | ~3 |
| single-AZ total | ~110 | |
| RDS Multi-AZ | doubles the database | +17 |
| highly-available total | ~130 |
Watch the NAT Gateway. If the tasks sit in private subnets and reach the internet through a NAT Gateway, add ~$32/month per AZ plus data charges — for three AZs that is more than the compute. Either put the tasks in public subnets with tight security groups, or use VPC endpoints for ECR/S3/CloudWatch. It is the single most common surprise on an AWS bill of this shape.
Prices are indicative and move; check the calculator before committing.
The honest comparison
| Hetzner CX22 | 2 vCPU, 4 GB, 40 GB | ~€5/month |
| AWS, three nodes | as above | ~$110–130/month |
Roughly 25×, for a workload whose database is 200 MB after five years. What the money buys is real — managed Postgres with PITR, three AZs, no box to patch, free wildcard certificates — but it is bought for resilience, not for capacity. At 1000 members you are paying for the insurance, not the compute.
A reasonable middle: one VPS now, and move Postgres to a managed service (RDS, or a €15/month managed Postgres) the day the data starts to matter more than the uptime. That is the change that is painful to do late, and everything else in this document is already designed for it.
Going multi-server
Nothing in the code changes. What changes is where the services live:
| one server | several | |
|---|---|---|
| Postgres | db container |
DJANGO_DATABASE_URL → your central Postgres |
| Cache / flags | redis container |
managed Redis (or your existing one) |
| Uploads | local disk | S3 bucket (AWS_STORAGE_BUCKET_NAME) |
| Static files | WhiteNoise, in the image | unchanged — that is why WhiteNoise is there |
| Cron | host crontab | one node only |
| TLS | Caddy on the box | load balancer, or Caddy on each node |
Drop db and redis from compose.yaml, point the URLs at the central services, and run
web on as many nodes as you like behind a load balancer pointed at /healthz.
The health check tests the database and a cache round trip, not just that the process is listening — a node that cannot reach Postgres, or whose cache silently swallows writes, is not healthy, and a load balancer must not keep feeding it traffic.
Rollback
Images are the unit of rollback. Tag on build, keep the last few, and:
docker compose up -d --no-deps web # with the previous image tag
Migrations are the exception: they don't roll back with the image. Prefer additive migrations (add a column, deploy, backfill, then stop writing the old one) so that yesterday's image still runs against today's schema.