deploy: Dockerfile, Compose pro Rolle, LiteLLM, Prometheus/Alertmanager, Canary-Prober, n8n-Workflows

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-12 00:51:31 +02:00
parent 4cbe313c62
commit cb5a413169
28 changed files with 1731 additions and 9 deletions
@@ -0,0 +1,8 @@
+LLAMACPP_REF=b6000
+CUDA_VERSION=12.4.0
+CUDA_DOCKER_ARCH=52;61
+MODELS_DIR=/srv/models
+EMBED_GGUF=Qwen3-Embedding-0.6B-Q8_0.gguf
+EMBED_POOLING=last
+RERANK_GGUF=bge-reranker-v2-m3-Q8_0.gguf
+CHAT_GGUF=Qwen3-4B-Q4_K_M.gguf
@@ -0,0 +1,86 @@
+# Rollen "gpu-embed" und "gpu-small" (VMs mit Quadro P2000 / M4000): llama.cpp-Server.
+# Maxwell (sm_52) und Pascal (sm_61) brauchen CUDA 12.x – daher eigener Build mit festen Architekturen.
+# Profile: embed (Embedding + Rerank), chat (Verifier/Signatur), z. B. `docker compose --profile embed up -d`
+name: knaster-gpu-llamacpp
+
+x-llamacpp: &llamacpp
+  build:
+    context: https://github.com/ggml-org/llama.cpp.git#${LLAMACPP_REF:-b6000}
+    dockerfile: .devops/cuda.Dockerfile
+    target: server
+    args:
+      CUDA_VERSION: ${CUDA_VERSION:-12.4.0}
+      CUDA_DOCKER_ARCH: ${CUDA_DOCKER_ARCH:-52;61}
+  image: knaster/llamacpp-server:${LLAMACPP_REF:-b6000}-cu12
+  restart: unless-stopped
+  labels: {autoheal: "true"}
+  volumes:
+    - ${MODELS_DIR:-/srv/models}:/models:ro
+  deploy:
+    resources:
+      reservations:
+        devices: [{driver: nvidia, count: 1, capabilities: [gpu]}]
+
+services:
+  llamacpp-embed:
+    <<: *llamacpp
+    container_name: llamacpp-embed
+    profiles: ["embed"]
+    command: ["-m", "/models/${EMBED_GGUF:-Qwen3-Embedding-0.6B-Q8_0.gguf}", "--embedding",
+              "--pooling", "${EMBED_POOLING:-last}", "-c", "8192", "-ub", "8192", "-ngl", "99",
+              "--alias", "embed-default", "--metrics", "--host", "0.0.0.0", "--port", "8081"]
+    ports: ["8081:8081"]
+    healthcheck: &hc
+      test: ["CMD", "curl", "-fsS", "http://127.0.0.1:8081/health"]
+      interval: 30s
+      timeout: 5s
+      retries: 3
+      start_period: 60s
+
+  llamacpp-rerank:
+    <<: *llamacpp
+    container_name: llamacpp-rerank
+    profiles: ["embed"]
+    command: ["-m", "/models/${RERANK_GGUF:-bge-reranker-v2-m3-Q8_0.gguf}", "--reranking", "-c", "8192",
+              "-ub", "8192", "-ngl", "99", "--alias", "rerank-default", "--metrics", "--host", "0.0.0.0",
+              "--port", "8082"]
+    ports: ["8082:8082"]
+    healthcheck:
+      <<: *hc
+      test: ["CMD", "curl", "-fsS", "http://127.0.0.1:8082/health"]
+
+  llamacpp-chat:
+    <<: *llamacpp
+    container_name: llamacpp-chat
+    profiles: ["chat"]
+    command: ["-m", "/models/${CHAT_GGUF:-Qwen3-4B-Q4_K_M.gguf}", "-c", "8192", "-ngl", "99",
+              "--alias", "verifier-small", "--metrics", "--host", "0.0.0.0", "--port", "8080"]
+    ports: ["8080:8080"]
+    healthcheck:
+      <<: *hc
+      test: ["CMD", "curl", "-fsS", "http://127.0.0.1:8080/health"]
+
+  gpu-exporter:
+    image: utkuozdemir/nvidia_gpu_exporter:1.2.1
+    restart: unless-stopped
+    ports: ["9835:9835"]
+    deploy:
+      resources:
+        reservations:
+          devices: [{driver: nvidia, count: all, capabilities: [gpu, utility]}]
+
+  node-exporter:
+    image: prom/node-exporter:v1.8.1
+    restart: unless-stopped
+    command: ["--path.rootfs=/host", "--collector.textfile.directory=/textfile"]
+    pid: host
+    volumes:
+      - /:/host:ro,rslave
+      - /var/lib/node_exporter/textfile:/textfile:ro
+    ports: ["9100:9100"]
+
+  autoheal:
+    image: willfarrell/autoheal:1.2.0
+    restart: unless-stopped
+    environment: {AUTOHEAL_CONTAINER_LABEL: autoheal}
+    volumes: ["/var/run/docker.sock:/var/run/docker.sock"]
@@ -0,0 +1,9 @@
+SLOT_ALIAS=tier1-general
+VLLM_MODEL=Qwen/Qwen3-14B-AWQ
+MAX_MODEL_LEN=32768
+GPU_MEM_UTIL=0.90
+MAX_LORAS=4
+MAX_LORA_RANK=64
+MODELS_DIR=/srv/models
+ADAPTERS_DIR=/srv/adapters
+HF_TOKEN=
@@ -0,0 +1,62 @@
+# Rolle "gpu-main" / "gpu-flex" (VM mit durchgereichter RTX 4000 Ada): vLLM mit Multi-LoRA.
+name: knaster-gpu-vllm
+
+services:
+  vllm:
+    image: vllm/vllm-openai:${VLLM_TAG:-v0.10.0}   # Engine-Updates laufen als Lifecycle-Kandidat
+    container_name: vllm
+    restart: unless-stopped
+    labels: {autoheal: "true"}
+    ipc: host
+    env_file: .env
+    environment:
+      VLLM_ALLOW_RUNTIME_LORA_UPDATING: "True"   # Adapter per /v1/load_lora_adapter nachladen
+    command:
+      - --model=${VLLM_MODEL:?VLLM_MODEL fehlt}
+      - --served-model-name=${SLOT_ALIAS:?SLOT_ALIAS fehlt}
+      - --max-model-len=${MAX_MODEL_LEN:-32768}
+      - --gpu-memory-utilization=${GPU_MEM_UTIL:-0.90}
+      - --enable-lora
+      - --max-loras=${MAX_LORAS:-4}
+      - --max-lora-rank=${MAX_LORA_RANK:-64}
+      - --host=0.0.0.0
+      - --port=8000
+    volumes:
+      - ${MODELS_DIR:-/srv/models}:/root/.cache/huggingface
+      - ${ADAPTERS_DIR:-/srv/adapters}:/adapters:ro
+    ports: ["8000:8000"]
+    deploy:
+      resources:
+        reservations:
+          devices: [{driver: nvidia, count: 1, capabilities: [gpu]}]
+    healthcheck:
+      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health', timeout=4)"]
+      interval: 30s
+      timeout: 5s
+      retries: 3
+      start_period: 300s   # Laden großer Modelle
+
+  gpu-exporter:
+    image: utkuozdemir/nvidia_gpu_exporter:1.2.1
+    restart: unless-stopped
+    ports: ["9835:9835"]
+    deploy:
+      resources:
+        reservations:
+          devices: [{driver: nvidia, count: all, capabilities: [gpu, utility]}]
+
+  node-exporter:
+    image: prom/node-exporter:v1.8.1
+    restart: unless-stopped
+    command: ["--path.rootfs=/host", "--collector.textfile.directory=/textfile"]
+    pid: host
+    volumes:
+      - /:/host:ro,rslave
+      - /var/lib/node_exporter/textfile:/textfile:ro
+    ports: ["9100:9100"]
+
+  autoheal:
+    image: willfarrell/autoheal:1.2.0
+    restart: unless-stopped
+    environment: {AUTOHEAL_CONTAINER_LABEL: autoheal, AUTOHEAL_START_PERIOD: "300"}
+    volumes: ["/var/run/docker.sock:/var/run/docker.sock"]
@@ -0,0 +1,18 @@
+KNASTER_VERSION=dev
+KNASTER_SITE=knaster
+KNASTER_API_TOKEN=change-me
+KNASTER_DRY_RUN=true
+KNASTER_CANARY_INTERVAL=60
+POSTGRES_PASSWORD=change-me
+LITELLM_API_KEY=change-me
+LITELLM_MASTER_KEY=change-me
+OPENROUTER_API_KEY=
+RERANK_URL=http://gpu-embed-1:8082
+NOTIFY_WEBHOOK_URL=
+KNASTER_JOB_WEBHOOK_URL=
+PORTAINER_HOST=
+PORTAINER_KEY=
+PROXMOX_URL=
+PROXMOX_TOKEN_ID=
+PROXMOX_TOKEN_SECRET=
+KNASTER_WEBHOOK_AUTH=Bearer change-me
@@ -0,0 +1,104 @@
+# Rolle "infra" (LXC/VM auf einem i7-Node): Router, LiteLLM, Postgres, Monitoring.
+# Start: cp .env.example .env && docker compose up -d
+name: knaster-infra
+
+x-restart: &restart
+  restart: unless-stopped
+  labels: {autoheal: "true"}
+
+services:
+  router:
+    <<: *restart
+    build:
+      context: ../../..
+      dockerfile: deploy/docker/router.Dockerfile
+    image: knaster/router:${KNASTER_VERSION:-dev}
+    env_file: .env
+    environment:
+      KNASTER_DB_URL: postgresql+psycopg://knaster:${POSTGRES_PASSWORD:?POSTGRES_PASSWORD fehlt}@postgres:5432/knaster
+      KNASTER_SITE_DIR: /app/sites/${KNASTER_SITE:-knaster}
+      LITELLM_BASE_URL: http://litellm:4000
+    ports: ["8080:8080"]
+    depends_on:
+      postgres: {condition: service_healthy}
+      litellm: {condition: service_started}
+
+  litellm:
+    <<: *restart
+    image: ghcr.io/berriai/litellm:${LITELLM_TAG:-main-stable}   # vor Deployment auf feste Version pinnen
+    command: ["--config", "/app/config.yaml", "--port", "4000"]
+    env_file: .env
+    volumes:
+      - ../../litellm/config.yaml:/app/config.yaml:ro
+    ports: ["4000:4000"]
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://127.0.0.1:4000/health/liveliness', timeout=4)"]
+      interval: 30s
+      timeout: 5s
+      retries: 3
+
+  postgres:
+    <<: *restart
+    image: pgvector/pgvector:pg16
+    environment:
+      POSTGRES_USER: knaster
+      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?POSTGRES_PASSWORD fehlt}
+      POSTGRES_DB: knaster
+    volumes:
+      - postgres:/var/lib/postgresql/data
+    healthcheck:
+      test: ["CMD-SHELL", "pg_isready -U knaster -d knaster"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
+
+  prometheus:
+    <<: *restart
+    image: prom/prometheus:v2.53.0
+    command:
+      - --config.file=/etc/prometheus/prometheus.yml
+      - --storage.tsdb.retention.time=15d
+      - --web.enable-lifecycle
+    volumes:
+      - ../../prometheus:/etc/prometheus:ro
+      - prometheus:/prometheus
+    ports: ["9090:9090"]
+
+  alertmanager:
+    <<: *restart
+    image: prom/alertmanager:v0.27.0
+    command: ["--config.file=/etc/alertmanager/alertmanager.yml"]
+    volumes:
+      - ../../alertmanager/alertmanager.yml:/etc/alertmanager/alertmanager.yml:ro
+      - ./secrets/router_token:/etc/alertmanager/router_token:ro
+    ports: ["9093:9093"]
+
+  grafana:
+    <<: *restart
+    image: grafana/grafana:11.1.0
+    profiles: ["dashboards"]
+    volumes:
+      - grafana:/var/lib/grafana
+    ports: ["3000:3000"]
+
+  pve-exporter:
+    <<: *restart
+    image: prompve/prometheus-pve-exporter:${PVE_EXPORTER_TAG:-latest}   # vor Deployment pinnen
+    profiles: ["proxmox"]
+    volumes:
+      - ./secrets/pve.yml:/etc/prometheus/pve.yml:ro
+    ports: ["9221:9221"]
+
+  autoheal:
+    restart: unless-stopped
+    image: willfarrell/autoheal:1.2.0
+    environment:
+      AUTOHEAL_CONTAINER_LABEL: autoheal
+      AUTOHEAL_INTERVAL: "15"
+    volumes:
+      - /var/run/docker.sock:/var/run/docker.sock
+
+volumes:
+  postgres: {}
+  prometheus: {}
+  grafana: {}