deploy: mermaid flow diagram, single page with tabs, section rework

Collapse the deploy sub-pages back into one deploy.md (tabs, not separate
pages), add a working mermaid flow diagram, and rework the top per feedback.

- Mermaid: enable via superfences fence_div_format (the fence_code_format
  <pre><code> wrapper broke mermaid's render — div format fixes it); vendor
  mermaid.min.js locally (no CDN dependency for a self-hosted site) + a small
  init that renders each block once and survives instant-nav.
- Content tabs Compose / Dockerfile / Secrets hold the three pieces together
  on one page (inline comments in the code, no annotation +).
- 'What can run here' tip moved above the flow; section renamed
  'Preparing for Deploy' with the 'you don't run deploy commands' point folded
  sparsely into the intro (standalone note removed); 'svc never changes'
  called out.
- Flow diagram (below the tabs): build group now includes our libraries; git
  -> staging shown as develop-if-gitflow (dotted); deployment (no MR-to-main)
  -> docker image built + run on the fleet.
- Revert inbound links to deploy.md.

Verified in-browser: diagram renders with all nodes, tabs switch, section
order correct; mkdocs build --strict clean.

Signed-off-by: disqualifier <dev@disqualifier.me>
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2026-07-01 02:53:02 -04:00
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# Deployment Guide
> How a project gets onto **rethink-net** — our Ubuntu 26.x servers. Get your
> container to follow a few consistent rules and deploying is mostly handing us a
> `compose.yaml`.
!!! tip "What can run here"
APIs, websites, applets, bots, monitors.
## Preparing for Deploy
Get these three right and your repo is deployable — you don't run any deploy commands
yourself, the ops tooling takes it from git. Each tab is one piece.
!!! danger "Your compose names nothing repo-specific"
**No `container_name`. No hardcoded names, workspace, or `/srv` paths.** The
deploy layer injects identity and host paths at deploy time — your compose stays
generic so it can't collide with any other service on the fleet.
- the service key is **always `svc`** — it never changes, in any repo
- named volumes use **bare names** (`cache`, not `myapp_cache`)
- host paths come from **`${LOGS_DIR}` / `${CONFIG_DIR}`**
Naming things after your repo used to cause **container-name collisions** at
fleet scale — two repos shipping the same name clashed. The generic compose in
the **Compose** tab fixes that.
=== "Compose"
The `compose.yaml` your repo ships. Copy it verbatim — it names nothing
repo-specific, so the deploy layer can inject identity and host paths without
collisions.
```yaml
services:
svc: # generic service key — ALWAYS svc, no container_name
build: .
user: "1337:1337" # the shared services account (required)
restart: unless-stopped # required — host unit is oneshot; this recovers crashes
environment:
HOME: /tmp
volumes:
- ${LOGS_DIR:-./logs}:/app/logs # output — host log dir, injected at deploy
- ${CONFIG_DIR:-./config}:/app/config # input — host config dir, injected at deploy
# - ${MOUNTS_DIR:-./mounts}:/app/data # optional — arbitrary host data (opt-in)
- cache:/app/cache # your data — ephemeral named volume
volumes:
cache: # bare name — deploy auto-prefixes it per service
```
**The rules:**
- **Service key is always `svc`** — never a repo-specific name, never a
`container_name`. The ops tooling keys off `svc`; this is what makes services
collision-proof on the fleet.
- **`user: "1337:1337"` and `restart: unless-stopped` are required** — the shared
`services` account (uid/gid 1337, fixed fleet-wide), and Docker's restart policy
recovering a crashed container (the host unit is oneshot).
- **Host paths come from `${...}` variables, never hardcoded.** Write to
`${LOGS_DIR}` and `${CONFIG_DIR}`; `${MOUNTS_DIR}` is optional.
- **Named volumes use bare names** (`cache`, not `myapp_cache`) — deploy
auto-prefixes them per service so they can't collide.
!!! tip "The container path is where your code reads and writes"
`WORKDIR` is `/app`, so the **right-hand side** of each volume line is the path
your code targets. If your app writes to `./cache` (i.e. `/app/cache`), that's
the `cache` mount; logs go to `/app/logs`, config is read from `/app/config`.
**Three tiers of storage:**
- **`logs`** (output) and **`config`** (input you edit) — **we handle these**:
injected and managed at deploy time.
- **`mounts`** (optional) — a host dir for arbitrary read/write data. The deploy
layer **injects `MOUNTS_DIR` and auto-creates the dir**, but the mount line is
**opt-in**: uncomment it and choose the container path yourself (it's
app-specific, so it can't be auto-mounted).
- **Named volumes** (`cache`, …) — **yours**: anything else your service persists.
Docker owns them, no host paths to manage.
Locally, `docker compose up` needs nothing set — the `${VAR:-./default}` fallbacks
use `./logs`, `./config` (and `./mounts` if you enable it). When deployed, the ops
tooling sets the real values, so the same file works both places.
**Subprocess and browser workloads** (bots that spawn Chrome, Xvfb, ffmpeg) need
three extra knobs:
```yaml
services:
svc:
build: .
user: "1337:1337"
restart: unless-stopped
init: true # tini as PID 1 — reaps zombie subprocesses, forwards signals
shm_size: "2gb" # Chrome/headless browsers crash on Docker's default 64 MB /dev/shm
mem_limit: "4g" # bound memory — raise as worker/browser count grows
```
!!! warning "The PID-1 gotcha with shell-wrapper CMDs"
If your `CMD` is a shell-script wrapper (e.g. `xvfb-run ...`), it must **not**
be PID 1, or the real process dies on startup. `init: true` fixes this — tini
takes PID 1, your wrapper runs as a normal child.
=== "Dockerfile"
Every service runs containerized as the shared **`services`** account: **uid/gid
1337**, fixed fleet-wide. Build the image to be **uid-agnostic** so it runs cleanly
as that account.
```dockerfile
FROM python:3.12-slim
ENV HOME=/tmp # services account has no home dir; $HOME must be writable
WORKDIR /app
RUN apt-get update \
&& apt-get install -y --no-install-recommends git \
&& rm -rf /var/lib/apt/lists/* # include git ONLY if the container itself needs it
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt # deps before code — layer caching
COPY . .
RUN chmod -R a+rwX /app # writable by any uid — this is "uid-agnostic"
CMD ["python", "-m", "yourapp"]
```
**Layer caching:** copy the deps file and install **before** `COPY . .` — Docker
caches layers in order, so deps only reinstall when the deps file changes, not on
every code edit.
**Getting files in:** `COPY . .` grabs the whole repo; be explicit about anything
that needs its own place. In `COPY <src> <dest>`, `<src>` is relative to the build
context (your repo), `<dest>` is a path in the image.
```dockerfile
COPY ./config.toml /app/config.toml # a single file into a specific path
COPY ./assets /app/assets # a whole directory (tree mirrors ./assets/)
```
!!! tip "Faster builds with uv (optional)"
[uv](https://docs.astral.sh/uv/) is a drop-in for pip that reads the same
`pyproject.toml` — no lockfile needed in the image. Add `UV_COMPILE_BYTECODE`
so containers don't pay the first-import `.pyc` compile cost:
```dockerfile
FROM python:3.12-slim
COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/ # pull the uv binary from its image
ENV HOME=/tmp
ENV UV_COMPILE_BYTECODE=1 # compile bytecode at build, not cold start
WORKDIR /app
COPY pyproject.toml .
RUN uv pip install --system . # into the image's Python, no venv/lock
COPY . .
RUN chmod -R a+rwX /app
CMD ["python", "-m", "yourapp"]
```
=== "Secrets"
!!! warning "Secrets never go in the image"
We do **not** commit secrets (usually, lol). They stay **gitignored** and live
on the host in your config dir, reaching your container read-only via
`${CONFIG_DIR}`. Add them to `.dockerignore` so a `COPY . .` can't sweep them
into a layer.
- Secrets live on the **host**, in your config dir — never in git, never in the
image.
- They reach the container **read-only** via the injected `${CONFIG_DIR}` mount.
- Keep them out of the build context: list them in `.dockerignore` so a blanket
`COPY . .` can't pull them into a layer.
**Rotating a secret** is a host-side edit — update the file and the service picks
it up on restart. No rebuild, and nothing you run: flag it and we handle the
restart.
## The path to deploy
You build and test locally — leaning on our libraries, AI, and this handbook — then
push to git. From there it's staging (if you're running gitflow) and, once it's good,
deployment: the ops tooling builds the Docker image and starts it on the fleet.
```mermaid
flowchart LR
subgraph build ["you build"]
direction TB
local["local testing"]
libs["our libraries<br/>(rethink-public)"]
ai["AI-assisted<br/>(Claude Code)"]
docs["reading the<br/>handbook"]
local --- libs
libs --- ai
ai --- docs
docs --- local
end
build -->|push| git["git<br/>(Gitea)"]
git -.->|develop, if gitflow| stage["staging"]
git --> deploy["deployment<br/>(ops tooling)"]
stage --> deploy
deploy --> docker["docker<br/>(image built + run on the fleet)"]
classDef ship fill:#061541,stroke:#569bcc,color:#eef1f6;
classDef work fill:#0e1530,stroke:#294274,color:#eef1f6;
class git,stage,deploy,docker ship;
class local,libs,ai,docs work;
```