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docker-compose.yml
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287 lines (275 loc) · 8.92 KB
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name: openprocessor
services:
triton-server:
image: davidamacey/openprocessor-triton:latest
build:
context: .
dockerfile: Dockerfile.triton
container_name: triton-server
restart: always
ports:
- 4600:8000 # HTTP
- 4601:8001 # gRPC
- 4602:8002 # Metrics
volumes:
- ./models:/models
command:
- tritonserver
- --model-store=/models
- --backend-config=default-max-batch-size=128
- --strict-model-config=false
- --model-control-mode=explicit
# ===================================================================
# Visual Search Models
# ===================================================================
- --load-model=yolov11_small_trt_end2end
- --load-model=scrfd_10g_bnkps
- --load-model=arcface_w600k_r50
- --load-model=mobileclip2_s2_image_encoder
- --load-model=mobileclip2_s2_text_encoder
- --load-model=paddleocr_det_trt
- --load-model=paddleocr_rec_trt
- --load-model=ocr_pipeline
# ===================================================================
- --log-verbose=1
- --log-info=true
shm_size: 8g
ulimits:
memlock: -1
stack: 67108864
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids: [ '0' ]
capabilities:
- gpu
networks:
- triton_net
yolo-api:
image: davidamacey/openprocessor:latest
container_name: yolo-api
restart: always
build:
context: .
dockerfile: Dockerfile
volumes:
- ./src:/app/src
- ./export:/app/export
- ./scripts:/app/scripts
- ./tests:/app/tests
- ./benchmarks:/app/benchmarks
- ./models:/app/models
- ./pytorch_models:/app/pytorch_models
- ./test_images:/app/test_images
- ./VERSION:/app/VERSION:ro
- ./cache/huggingface:/home/appuser/.cache/huggingface # HuggingFace tokenizers (appuser)
environment:
# Triton gRPC endpoint (Docker service name)
- TRITON_URL=triton-server:8001
# HuggingFace cache configuration (appuser home directory)
- HF_HOME=/home/appuser/.cache/huggingface
- HF_HUB_CACHE=/home/appuser/.cache/huggingface/hub
shm_size: 8g
stdin_open: true # Keep stdin open
tty: true # Allocate a pseudo-TTY
command:
- uvicorn
- src.main:app
- --host=0.0.0.0
- --port=8000
# ===================================================================
# Worker Configuration (Performance Tuning)
# Production: 64 workers for dual-GPU throughput
# Benchmark: 4 workers to match TRT instance count for fair comparison
# ===================================================================
- --workers=32 # Increased for higher face pipeline throughput
- --limit-max-requests=10000 # Recycle workers every 10k requests (prevents memory leaks)
# ===================================================================
# Event Loop & HTTP Protocol (Already Optimized)
# ===================================================================
- --loop=uvloop # 2-3x faster than asyncio default loop
- --http=httptools # Faster HTTP parsing than h11
# ===================================================================
# Connection & Concurrency Settings
# ===================================================================
- --backlog=4096 # Socket connection queue size
- --limit-concurrency=512 # Max concurrent requests (prevents overload)
- --timeout-keep-alive=75 # Keep connections alive for reuse
- --timeout-graceful-shutdown=30 # Clean shutdown (drain connections)
# ===================================================================
# Logging
# ===================================================================
- --access-log
- --log-level=info
ports:
- 4603:8000 # FastAPI
ulimits:
memlock: -1
stack: 67108864
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids: [ '0' ]
capabilities:
- gpu
depends_on:
- triton-server
networks:
- triton_net
triton-sdk:
image: nvcr.io/nvidia/tritonserver:25.10-py3-sdk
container_name: triton-sdk
profiles:
- benchmark
command: sleep infinity
volumes:
- ./benchmarks:/workspace/benchmarks
- ./models:/models
networks:
- triton_net
node-exporter:
image: prom/node-exporter:latest
container_name: triton-node-exporter
restart: always
command:
- '--path.rootfs=/host'
pid: host
volumes:
- '/:/host:ro,rslave'
networks:
- triton_net
prometheus:
image: prom/prometheus:latest
container_name: triton-prometheus
restart: always
ports:
- 4604:9090 # Prometheus
volumes:
- ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml
- ./monitoring/alerts:/etc/prometheus/alerts
- prometheus_data:/prometheus
command:
- '--config.file=/etc/prometheus/prometheus.yml'
- '--storage.tsdb.path=/prometheus'
- '--web.console.libraries=/usr/share/prometheus/console_libraries'
- '--web.console.templates=/usr/share/prometheus/consoles'
networks:
- triton_net
depends_on:
- triton-server
- node-exporter
grafana:
image: grafana/grafana:latest
container_name: triton-grafana
restart: always
ports:
- 4605:3000 # Grafana
volumes:
- grafana_data:/var/lib/grafana
- ./monitoring/grafana-datasources.yml:/etc/grafana/provisioning/datasources/datasources.yml
- ./monitoring/grafana-dashboards.yml:/etc/grafana/provisioning/dashboards/dashboards.yml
- ./monitoring/grafana-alerting.yml:/etc/grafana/provisioning/alerting/alerting.yml
- ./monitoring/dashboards:/etc/grafana/dashboards
environment:
- GF_SECURITY_ADMIN_USER=admin
- GF_SECURITY_ADMIN_PASSWORD=admin
- GF_USERS_ALLOW_SIGN_UP=false
# Enable unified alerting (Grafana 8+)
- GF_UNIFIED_ALERTING_ENABLED=true
- GF_ALERTING_ENABLED=false
networks:
- triton_net
depends_on:
- prometheus
- loki
loki:
image: grafana/loki:latest
container_name: triton-loki
restart: always
user: "0" # Run as root to avoid permission issues
ports:
- 4606:3100 # Loki
volumes:
- ./monitoring/loki-config.yml:/etc/loki/local-config.yaml
- loki_data:/loki
command: -config.file=/etc/loki/local-config.yaml
networks:
- triton_net
promtail:
image: grafana/promtail:latest
container_name: triton-promtail
restart: always
volumes:
- ./monitoring/promtail-config.yml:/etc/promtail/config.yml
- /var/run/docker.sock:/var/run/docker.sock
- /var/lib/docker/containers:/var/lib/docker/containers:ro
command: -config.file=/etc/promtail/config.yml
networks:
- triton_net
depends_on:
- loki
# ===================================================================
# OpenSearch for Visual Search (Vector Database)
# OpenSearch 3.x with k-NN plugin for vector similarity search
# ===================================================================
opensearch:
image: opensearchproject/opensearch:3.3.1
container_name: triton-opensearch
restart: always
environment:
- discovery.type=single-node
- bootstrap.memory_lock=true
- "OPENSEARCH_JAVA_OPTS=-Xms2g -Xmx2g" # Heap size (adjust based on RAM)
- DISABLE_SECURITY_PLUGIN=true # Disable security for dev (enable in production)
ulimits:
memlock:
soft: -1
hard: -1
nofile:
soft: 65536
hard: 65536
volumes:
- opensearch_data:/usr/share/opensearch/data
ports:
- 4607:9200 # REST API
healthcheck:
test: ["CMD-SHELL", "curl -sS http://localhost:9200 || exit 1"]
interval: 5s
timeout: 10s
retries: 20
networks:
- triton_net
opensearch-dashboards:
image: opensearchproject/opensearch-dashboards:3.3.0
container_name: triton-opensearch-dashboards
restart: always
environment:
- OPENSEARCH_HOSTS=["http://opensearch:9200"]
- DISABLE_SECURITY_DASHBOARDS_PLUGIN=true # Must match OpenSearch security setting
ports:
- 4608:5601 # OpenSearch Dashboards
volumes:
- opensearch_dashboards_data:/usr/share/opensearch-dashboards/data
healthcheck:
test: ["CMD-SHELL", "curl -sS http://localhost:5601 || exit 1"]
interval: 10s
timeout: 10s
retries: 20
networks:
- triton_net
depends_on:
opensearch:
condition: service_healthy
networks:
triton_net:
driver: bridge
volumes:
prometheus_data:
grafana_data:
loki_data:
opensearch_data:
opensearch_dashboards_data: