disagg_8b_tp2.yaml

# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0

apiVersion: nvidia.com/v1alpha1
kind: DynamoGraphDeployment
metadata:
  name: vllm-disagg
spec:
  services:
    Frontend:
      dynamoNamespace: vllm-disagg
      componentType: main
      replicas: 1
      livenessProbe:
        httpGet:
          path: /health
          port: 8000
        initialDelaySeconds: 20
        periodSeconds: 5
        timeoutSeconds: 5
        failureThreshold: 3
      readinessProbe:
        exec:
          command:
            - /bin/sh
            - -c
            - 'curl -s http://localhost:8000/health | jq -e ".status == \"healthy\""'
        initialDelaySeconds: 60
        periodSeconds: 60
        timeoutSeconds: 30
        failureThreshold: 10
      resources:
        requests:
          cpu: "16"
          memory: "10Gi"
        limits:
          cpu: "128"
          memory: "100Gi"
      extraPodSpec:
        mainContainer:
          image: my-registry/vllm-runtime:my-tag
          workingDir: /workspace/components/backends/vllm
          command:
            - /bin/sh
            - -c
          args:
            - "python3 -m dynamo.frontend --http-port 8000 --kv-cache-block-size 128"
    VllmDecodeWorker:
      dynamoNamespace: vllm-disagg
      envFromSecret: hf-token-secret
      componentType: worker
      replicas: 1
      livenessProbe:
        httpGet:
          path: /live
          port: 9090
        periodSeconds: 5
        timeoutSeconds: 30
        failureThreshold: 1
      readinessProbe:
        httpGet:
          path: /health
          port: 9090
        periodSeconds: 10
        timeoutSeconds: 30
        failureThreshold: 60
      resources:
        requests:
          cpu: "16"
          memory: "50Gi"
          gpu: "2"
        limits:
          cpu: "128"
          memory: "100Gi"
          gpu: "2"
      envs:
        - name: DYN_SYSTEM_ENABLED
          value: "true"
        - name: DYN_SYSTEM_USE_ENDPOINT_HEALTH_STATUS
          value: "[\"generate\"]"
        - name: DYN_SYSTEM_PORT
          value: "9090"
      extraPodSpec:
        mainContainer:
          startupProbe:
            httpGet:
              path: /health
              port: 9090
            periodSeconds: 10
            failureThreshold: 60
          image: my-registry/vllm-runtime:my-tag
          workingDir: /workspace/components/backends/vllm
          command:
            - /bin/sh
            - -c
          args:
            - "python3 -m dynamo.vllm --model nvidia/Llama-3.1-8B-Instruct-FP8 --no-enable-prefix-caching --block-size 128 --tensor-parallel-size 2 2>&1 | tee /tmp/vllm.log"
    VllmPrefillWorker:
      dynamoNamespace: vllm-disagg
      envFromSecret: hf-token-secret
      componentType: worker
      replicas: 1
      livenessProbe:
        httpGet:
          path: /live
          port: 9090
        periodSeconds: 5
        timeoutSeconds: 30
        failureThreshold: 1
      readinessProbe:
        httpGet:
          path: /health
          port: 9090
        periodSeconds: 10
        timeoutSeconds: 30
        failureThreshold: 60
      resources:
        requests:
          cpu: "16"
          memory: "50Gi"
          gpu: "2"
        limits:
          cpu: "128"
          memory: "100Gi"
          gpu: "2"
      envs:
        - name: DYN_SYSTEM_ENABLED
          value: "true"
        - name: DYN_SYSTEM_USE_ENDPOINT_HEALTH_STATUS
          value: "[\"generate\"]"
        - name: DYN_SYSTEM_PORT
          value: "9090"
      extraPodSpec:
        mainContainer:
          startupProbe:
            httpGet:
              path: /health
              port: 9090
            periodSeconds: 10
            failureThreshold: 60
          image: my-registry/vllm-runtime:my-tag
          workingDir: /workspace/components/backends/vllm
          command:
            - /bin/sh
            - -c
          args:
            - "python3 -m dynamo.vllm --model nvidia/Llama-3.1-8B-Instruct-FP8 --is-prefill-worker --no-enable-prefix-caching --block-size 128 --tensor-parallel-size 2 2>&1 | tee /tmp/vllm.log"