c1948ea198
T-2: Extract getJobStatusColor() into utils/jobStatusMessages.ts; StatusBadge now uses the
shared helper (single source of truth for badge colors).
PR-7: GET /admin/production/queue-stats — returns Celery queue depths via Redis LLEN.
Production dashboard shows a live panel (10s refresh) with per-queue task counts.
PR-8: POST /admin/production/jobs/{id}/upload-final-vtt — Production/Admin can upload a
hand-crafted VTT to bypass AI, writing to GCS and advancing the job to PENDING_QC.
Upload modal added to FailuresList with language + type (captions/ad) selectors.
docker-compose.optical-dev.yml: enable USE_CELERY_FALLBACK=true, set worker replicas=1
for all pipeline workers (ffmpeg/tts/whisper) with WORKER_CONCURRENCY=2 so the full
pipeline runs on the 2-CPU optical-dev server until Cloud Run VPC Connector is ready.
Fix: remove unused effectiveMs variable in TimelinePreview (TS6133).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
99 lines
2.5 KiB
YAML
99 lines
2.5 KiB
YAML
# =============================================================================
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# optical-dev overrides — 2 CPU / ~8 GB RAM server
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#
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# Cloud Run Jobs (va-worker) are NOT yet reachable from this server
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# (VPC Connector pending). Until then USE_CELERY_FALLBACK=true routes all
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# heavy tasks through local Celery workers constrained to WORKER_CONCURRENCY=2
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# so they fit in 2 CPU without OOM on large videos.
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#
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# Usage:
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# docker compose -f docker-compose.yml \
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# -f docker-compose.prod.yml \
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# -f docker-compose.optical-dev.yml \
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# --env-file .env.production up -d
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# =============================================================================
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services:
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# ── Keep on this server, resource limits fit in 2 CPU ──────────────────────
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mongodb:
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deploy:
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resources:
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limits:
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memory: 1G
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cpus: '0.5'
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reservations:
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memory: 512M
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cpus: '0.25'
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redis:
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deploy:
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resources:
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limits:
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memory: 512M
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cpus: '0.25'
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reservations:
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memory: 256M
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cpus: '0.1'
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api:
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deploy:
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resources:
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limits:
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memory: 2G
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cpus: '1.0'
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reservations:
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memory: 1G
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cpus: '0.5'
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environment:
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APP_ENV: prod
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# Fallback mode: bypass Cloud Run, dispatch heavy tasks to local workers
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USE_CELERY_FALLBACK: "true"
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WORKER_CONCURRENCY: "2"
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# Full worker: handles ALL queues in fallback mode
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worker:
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deploy:
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replicas: 1
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resources:
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limits:
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memory: 2G
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cpus: '0.75'
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reservations:
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memory: 1G
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cpus: '0.25'
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environment:
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APP_ENV: prod
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WORKER_CONCURRENCY: "2"
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command: >
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celery -A app.tasks worker
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--loglevel=info
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--queues=default,ingest,tts,render,ffmpeg,whisper,notify,embed
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--concurrency=2
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--hostname=full-worker@%h
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# ── Pipeline workers — enabled in fallback mode ────────────────────────────
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ffmpeg-worker:
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deploy:
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replicas: 1
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resources:
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limits:
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memory: 1G
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cpus: '0.5'
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tts-worker:
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deploy:
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replicas: 1
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resources:
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limits:
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memory: 512M
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cpus: '0.25'
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whisper-worker:
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deploy:
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replicas: 1
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resources:
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limits:
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memory: 2G
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cpus: '0.5'
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