vh
39da1d4a97
The board mixed tools with endpoints. A vLLM seat whose href is a /docs page
sat in the same band as ComfyUI; the MQTT broker and the RustDesk relay, which
have no page at all, sat in Apps; and `Service Networking` was thirteen members
spanning three AdGuards, five Dockges, two Traefiks and four headless agents.
Every group is now one of two kinds and they never mix. TOOLS are expanded and
sit at the top of their tab. ENDPOINTS — an API, a broker, a background agent,
an href that is /docs or /ping or nothing — carry `initiallyCollapsed: true`
and sit at the bottom. Collapsed is not hidden: the eyebrow and its rule still
render, so the tab still says the thing exists and one click expands it.
A second rule fell out of the same pass and now shapes the group boundaries: a
group's members should all carry a widget or none should. A stat strip makes a
card ~50px taller, so one widget card in a row of plain ones opens a void under
the plain ones. That is why AdGuard and Traefik get their own groups rather
than sharing one with Dockge, and it is most of why the old Service Networking
band looked broken. AdGuard (ANA) was the last short card in its row and now
carries the same query/blocked/latency strip as its two siblings — one
infra-ops AdGuard login authenticates against all three instances, verified
against each; it lives in that stack's .env on the host and is vaulted.
The sixteen GPU-backed model seats were deliberately NOT relabelled.
`homepage.group` is read at container creation, so clearer names for
`AI - Inference` and friends would have cost a recreate on six vLLM seats, four
eval seats and four TTS engines — multi-minute model reloads on endpoints peers
reach through the gateway. Order plus `initiallyCollapsed` buys the same
separation for nothing, so those names stay as they are on purpose.
28 containers that ARE cheap to bounce were relabelled, across five hosts, via
rerunnable elway playbooks. Their label steps are gated on the old value still
being present, so a second run reports skipped rather than churning. Two verify
steps were wrong on first contact and are fixed with the reason recorded: the
traefik check raced its own recreate, and asserting a model seat is "running"
cannot answer "did I bounce it" when a seat may be legitimately stopped —
container age can, and now does.
The canonical stacks/ tree was synced to the deployed labels afterwards, so
intent and reality agree again on all fourteen tracked stacks.
Also documents the real nature of the post-recreate blank dashboard, which cost
~25 minutes here and an hour on 2026-08-19. `initialSettings":{}` in the served
HTML is the catch branch of the page's data loader, not a warm-up and not a
cache — and the error can vanish entirely, because the logger is assigned inside
the same try and the catch only logs if the logger exists. Ruled out by
measurement this time: all four API routes return 200 with correct content while
the page serves {}, and the previous known-good settings.yaml reproduces it
identically. The README now carries the one-command test and the next lead.
Before/after, all four tabs: http://10.100.10.50:8090/b/homepage-relayout/
100 lines
4.5 KiB
YAML
100 lines
4.5 KiB
YAML
# waterland-studio — watercolour render service on irv-ml1, port 8410.
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#
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# FastAPI + vanilla-JS SPA fronting the waterland CLI: upload an image, get a
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# watercolour plate and a painted-in reveal animation. Every job shells out to
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# the CLI, which runs a fluid simulation on the A6000.
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#
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# Handed over by waterland-dev 2026-08-19, replacing a bare `nohup` that would
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# not have survived a reboot.
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#
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# ⚠️ THE BUILD CONTEXT LIVES OUTSIDE THIS DIRECTORY, DELIBERATELY.
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# /opt/waterland-studio/src is a checkout of vh/waterland @ main.
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# `deploy-stack.sh` rsyncs this stack dir with --delete, so a checkout kept
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# in here would be destroyed on the next deploy. Refresh it with ./update.sh.
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#
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# ⚠️ SERIAL BY DESIGN — ONE REPLICA, ONE CARD. A render is 20-45s of near-full
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# GPU and the app runs a single worker thread. Two of these on the same A6000
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# would OOM or thrash. Throughput is a conversation about hardware, not about
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# replica count (waterland-dev, explicitly).
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#
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# ⚠️ NO AUTHENTICATION, AND IT ACCEPTS ARBITRARY FILE UPLOADS. It must stay
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# inside the LAN / WireGuard boundary. Do NOT paper over this by putting it
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# behind a proxy with a password — waterland-dev has offered to add a real
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# auth layer if it ever needs wider reach. Ask, don't improvise.
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name: waterland-studio
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services:
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waterland-studio:
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build:
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# Absolute paths: the context is the source checkout, the Dockerfile is
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# this version-controlled one, and the two live in different trees.
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context: /opt/waterland-studio/src
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dockerfile: /opt/docker/compose/waterland-studio/Dockerfile
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image: waterland-studio:local
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container_name: ${WLS_CONTAINER:-waterland-studio}
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restart: unless-stopped
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ports:
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- "${WLS_PORT:-8410}:8410"
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volumes:
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# Job store: uploaded sources plus rendered plates and animations.
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# ~12 MB per job with an animation; the app self-evicts at 40 retained
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# jobs (RETAIN in studio/jobs.py), so steady state is bounded ~500 MB.
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# That bound holds ACROSS restarts only as of b72425b, which rehydrates
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# the job index from this volume at startup; before that, eviction was
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# blind to anything a restart had orphaned. See the README.
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# Scratch output, not source-of-truth — losing it costs a re-render.
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- waterland_studio_data:/data
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# cupy JIT kernel cache. Not optional for good behaviour: cupy compiles
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# its kernels through NVRTC on first use, and measured on this host that
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# cold compile costs ~17s — the first 256^2 render after a fresh
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# container took 23.3s against 6.1s warm. Without this volume every
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# restart makes the next user wait 4x, and it looks like the service is
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# slow rather than warming up.
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- waterland_studio_kernels:/root/.cupy
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environment:
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- WATERLAND_STUDIO_DATA=/data
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- WATERLAND_STUDIO_REPO=/app
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- WATERLAND_STUDIO_BACKEND=${WLS_BACKEND:-cupy}
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# 0, not 1 — see the Dockerfile. Exactly one GPU is exposed below, so
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# inside this container the A6000 is index 0 under PCI_BUS_ID ordering.
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- CUDA_VISIBLE_DEVICES_TARGET=${WLS_CUDA_TARGET:-0}
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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# "1" is the A6000 in DOCKER's device ordering, matching the
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# comfyui stack on this host. Device 0 is the 3090, which hosts
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# the TTS zoo and must not be touched.
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device_ids: ["${WLS_GPU_ID:-1}"]
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capabilities: [gpu]
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healthcheck:
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# /api/health touches no GPU and is safe to poll. The interval is
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# deliberately loose: a render holds the GPU for 20-45s and the app's own
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# job timeout is 480s, so an aggressive probe would be measuring queue
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# depth rather than liveness.
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test: ["CMD-SHELL", "python -c \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:8410/api/health', timeout=5).status==200 else 1)\""]
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interval: 60s
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timeout: 10s
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retries: 3
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start_period: 30s
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networks:
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- tnet
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labels:
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- homepage.group=AI - Studios
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- homepage.name=Waterland Studio
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- homepage.icon=mdi-watercolor
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- homepage.description=Watercolour plate + reveal animation renderer (irv-ml1, A6000)
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- homepage.href=http://10.100.79.3:${WLS_PORT:-8410}/
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- homepage.siteMonitor=http://10.100.79.3:${WLS_PORT:-8410}/api/health
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volumes:
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waterland_studio_data: {}
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waterland_studio_kernels: {}
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networks:
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tnet:
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name: traefik-net
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external: true
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