disagg_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: sglang-disagg-planner
  annotations:
    nvidia.com/enable-grove: "false" # temporarily disable grove because current k8s connector does not work with grove
spec:
  envs:
    - name: DYNAMO_SERVICE_CONFIG
      value: '{"Prometheus":{"global":{"scrape_interval":"5s"},"scrape_configs":[{"job_name":"prometheus","static_configs":[{"targets":["localhost:9090"]}]},{"job_name":"frontend","static_configs":[{"targets":["sglang-disagg-planner-frontend:8000"]}]}]}}'
    - name: DYNAMO_NAMESPACE
      value: "dynamo"
  services:
    Frontend:
      dynamoNamespace: dynamo
      componentType: frontend
      replicas: 1
      resources:
        requests:
          cpu: "10"
          memory: "10Gi"
        limits:
          cpu: "32"
          memory: "40Gi"
      extraPodSpec:
        mainContainer:
          image: nvcr.io/nvidian/nim-llm-dev/sglang-runtime:hzhou-0811-1
          workingDir: /workspace/components/backends/sglang
          command: ["sh", "-c"]
          args:
            - "python3 -m dynamo.sglang.utils.clear_namespace --namespace sglang-disagg && python3 -m dynamo.frontend --http-port=8000"
    Planner:
      dynamoNamespace: dynamo
      envFromSecret: hf-token-secret
      componentType: planner
      replicas: 1
      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
      resources:
        requests:
          cpu: "2"
          memory: "2Gi"
        limits:
          cpu: "8"
          memory: "16Gi"
      pvc:
        create: false
        name: profiling-pvc # Must be pre-created before deployment and SLA profiler must have been run
        mountPoint: /workspace/profiling_results
      extraPodSpec:
        mainContainer:
          image: nvcr.io/nvidian/nim-llm-dev/sglang-runtime:hzhou-0811-1
          workingDir: /workspace/components/planner/src/dynamo/planner
          command:
            - /bin/sh
            - -c
          args:
            - >-
              python3 -m planner_sla
              --environment=kubernetes
              --backend=sglang
              --adjustment-interval=60
              --profile-results-dir=/workspace/profiling_results
    Prometheus: # NOTE: this is set on Prometheus to ensure a service is created for the Prometheus component. This is a workaround and should be managed differently.
      dynamoNamespace: dynamo
      componentType: frontend
      replicas: 1
      envs:
        - name: PYTHONPATH
          value: "/workspace/components/planner/src"
      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
      resources:
        requests:
          cpu: "2"
          memory: "2Gi"
        limits:
          cpu: "8"
          memory: "16Gi"
      extraPodSpec:
        mainContainer:
          image: nvcr.io/nvidian/nim-llm-dev/sglang-runtime:hzhou-0811-1
          workingDir: /workspace/components/backends/sglang
          command:
            - /bin/sh
            - -c
          args:
            - "python3 -m dynamo.planner.prometheus"
    SGLangDecodeWorker:
      dynamoNamespace: dynamo
      envFromSecret: hf-token-secret
      componentType: worker
      replicas: 2
      resources:
        requests:
          cpu: "10"
          memory: "20Gi"
          gpu: "1"
        limits:
          cpu: "32"
          memory: "80Gi"
          gpu: "1"
      extraPodSpec:
        mainContainer:
          image: nvcr.io/nvidian/nim-llm-dev/sglang-runtime:hzhou-0811-1
          workingDir: /workspace/components/backends/sglang
          command:
            - /bin/sh
            - -c
          args:
            - >-
              python3 -m dynamo.sglang.decode_worker
              --model-path deepseek-ai/DeepSeek-R1-Distill-Llama-8B
              --served-model-name deepseek-ai/DeepSeek-R1-Distill-Llama-8B
              --page-size 16
              --tp 1
              --trust-remote-code
              --skip-tokenizer-init
              --disaggregation-mode decode
              --disaggregation-transfer-backend nixl
    SGLangPrefillWorker:
      dynamoNamespace: dynamo
      envFromSecret: hf-token-secret
      componentType: worker
      replicas: 2
      resources:
        requests:
          cpu: "10"
          memory: "20Gi"
          gpu: "1"
        limits:
          cpu: "32"
          memory: "80Gi"
          gpu: "1"
      extraPodSpec:
        mainContainer:
          image: nvcr.io/nvidian/nim-llm-dev/sglang-runtime:hzhou-0811-1
          workingDir: /workspace/components/backends/sglang
          command:
            - /bin/sh
            - -c
          args:
            - >-
              python3 -m dynamo.sglang.worker
              --model-path deepseek-ai/DeepSeek-R1-Distill-Llama-8B
              --served-model-name deepseek-ai/DeepSeek-R1-Distill-Llama-8B
              --page-size 16
              --tp 1
              --trust-remote-code
              --skip-tokenizer-init
              --disaggregation-mode prefill
              --disaggregation-transfer-backend nixl