disagg_8b_planner.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-planner
spec:
  envs:
    - name: DYNAMO_SERVICE_CONFIG
      value: '{"Prometheus":{"global":{"scrape_interval":"5s"},"scrape_configs":[{"job_name":"prometheus","static_configs":[{"targets":["localhost:8000"]}]},{"job_name":"frontend","static_configs":[{"targets":["vllm-disagg-planner-frontend:8000"]}]}]}}'
    - name: DYNAMO_NAMESPACE
      value: "vllm-disagg-planner"
  services:
    Frontend:
      dynamoNamespace: vllm-disagg-planner
      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 --router-mode kv --kv-overlap-score-weight 0.0 --router-temperature 0.0 --no-kv-events"
    Planner:
      dynamoNamespace: vllm-disagg-planner
      envFromSecret: hf-token-secret
      componentType: planner
      replicas: 1
      envs:
        - name: PROMETHEUS_PORT
          value: "8000"
      livenessProbe:
        exec:
          command:
            - /bin/sh
            - -c
            - "exit 0"
        periodSeconds: 60
        timeoutSeconds: 30
        failureThreshold: 10
      readinessProbe:
        exec:
          command:
            - /bin/sh
            - -c
            - "exit 0"
        initialDelaySeconds: 60
        periodSeconds: 60
        timeoutSeconds: 30
        failureThreshold: 10
      extraPodSpec:
        mainContainer:
          image: my-registry/vllm-runtime:my-tag
          workingDir: /workspace/components/planner/src/dynamo/planner
          ports:
            - name: metrics
              containerPort: 9085
          command:
            - /bin/sh
            - -c
          args:
            - >-
              python3 -m planner_sla
              --environment=kubernetes
              --backend=vllm
              --ttft 0.2
              --itl 0.01
              --profile-results-dir /workspace/tests/planner/profiling_results/H200_TP1P_TP1D/
              --adjustment-interval=60
              --prometheus-port=9085
              --no-correction
    Prometheus:
      dynamoNamespace: vllm-disagg-planner
      componentType: main
      replicas: 1
      envs:
        - name: PYTHONPATH
          value: "/workspace/components/planner/src"
        - name: PROMETHEUS_PORT
          value: "8000"
      livenessProbe:
        exec:
          command:
            - /bin/sh
            - -c
            - "exit 0"
        periodSeconds: 60
        timeoutSeconds: 30
        failureThreshold: 10
      readinessProbe:
        exec:
          command:
            - /bin/sh
            - -c
            - "exit 0"
        initialDelaySeconds: 30
        periodSeconds: 60
        timeoutSeconds: 30
        failureThreshold: 10
      extraPodSpec:
        mainContainer:
          image: my-registry/vllm-runtime:my-tag
          workingDir: /workspace/components/backends/vllm
          command:
            - /bin/sh
            - -c
          args:
            - "python3 -m dynamo.planner.prometheus"
    VllmDecodeWorker:
      dynamoNamespace: vllm-disagg-planner
      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: "20Gi"
          gpu: "1"
        limits:
          cpu: "128"
          memory: "100Gi"
          gpu: "1"
      envs:
        - name: DYN_SYSTEM_ENABLED
          value: "true"
        - name: DYN_SYSTEM_USE_ENDPOINT_HEALTH_STATUS
          value: "[\"generate\"]"
        - name: DYN_SYSTEM_PORT
          value: "9090"
      extraPodSpec:
        terminationGracePeriodSeconds: 600
        mainContainer:
          startupProbe:
            httpGet:
              path: /health
              port: 9090
            periodSeconds: 10
            failureThreshold: 60
          image: my-registry/vllm-runtime:my-tag
          workingDir: /workspace/components/backends/vllm
          command:
            - python3
          args:
            - -m
            - dynamo.vllm
            - --model
            - nvidia/Llama-3.1-8B-Instruct-FP8
            - --no-enable-prefix-caching
            - --block-size
            - "128"
    VllmPrefillWorker:
      dynamoNamespace: vllm-disagg-planner
      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: "20Gi"
          gpu: "1"
        limits:
          cpu: "128"
          memory: "100Gi"
          gpu: "1"
      envs:
        - name: DYN_SYSTEM_ENABLED
          value: "true"
        - name: DYN_SYSTEM_USE_ENDPOINT_HEALTH_STATUS
          value: "[\"generate\"]"
        - name: DYN_SYSTEM_PORT
          value: "9090"
      extraPodSpec:
        terminationGracePeriodSeconds: 600
        mainContainer:
          startupProbe:
            httpGet:
              path: /health
              port: 9090
            periodSeconds: 10
            failureThreshold: 60
          image: my-registry/vllm-runtime:my-tag
          workingDir: /workspace/components/backends/vllm
          command:
            - python3
          args:
            - -m
            - dynamo.vllm
            - --model
            - nvidia/Llama-3.1-8B-Instruct-FP8
            - --is-prefill-worker
            - --no-enable-prefix-caching
            - --block-size
            - "128"