# DeepSeekV32-Exp RBG Based PD Deploy ## 0. Prerequisites 1. k8s >=1.26 2. lws installed on k8s. 3. rbg installed on k8s. For RBG installation, please refer to: https://github.com/sgl-project/rbg ## 1. Image Preparation `lmsysorg/sglang:latest` ### 2. All In One manifest file *Note: The NodeSelector section, model location section, and taint toleration section can be adjusted according to your actual deployment environment* rbg-dsv32.yml ```yaml apiVersion: workloads.x-k8s.io/v1alpha1 kind: RoleBasedGroup metadata: name: deepseek-rbg-32exp namespace: default spec: roles: - name: prefill replicas: 1 workload: apiVersion: leaderworkerset.x-k8s.io/v1 kind: LeaderWorkerSet restartPolicy: None leaderWorkerSet: size: 1 patchLeaderTemplate: metadata: labels: role: leader pd_role: prefill spec: containers: - command: - python3 - -m - sglang.launch_server - --model-path - /work/models - --port - "30000" - --trust-remote - --host - 0.0.0.0 - --disaggregation-ib-device - mlx5_0,mlx5_1,mlx5_2,mlx5_3,mlx5_4,mlx5_5,mlx5_6,mlx5_7 - --disable-radix-cache - --chunked-prefill-size - "131072" - --page-size - "64" # - --enable-eplb - --ep-dispatch-algorithm - dynamic - --eplb-algorithm - deepseek - --enable-dp-lm-head - --enable-dp-attention - --dp-size - "8" - --moe-a2a-backend - deepep - --deepep-mode - normal - --disaggregation-mode - prefill - --mem-fraction-static - "0.8" - --max-prefill-tokens - "32768" - --context-length - "32768" - --tp - "8" - --dist-init-addr - $(LWS_LEADER_ADDRESS):20102 - --nnodes - $(LWS_GROUP_SIZE) - --node-rank - $(LWS_WORKER_INDEX) - --trust-remote-code - --ep-num-redundant-experts - "32" - --moe-dense-tp-size - "1" - --max-running-requests - "1024" env: - name: LWS_WORKER_INDEX valueFrom: fieldRef: fieldPath: metadata.labels['leaderworkerset.sigs.k8s.io/worker-index'] livenessProbe: failureThreshold: 3000 httpGet: path: /health port: 30000 initialDelaySeconds: 300 periodSeconds: 60 successThreshold: 1 timeoutSeconds: 10 readinessProbe: failureThreshold: 20 httpGet: path: /health port: 30000 periodSeconds: 30 successThreshold: 1 timeoutSeconds: 10 name: sglang ports: - containerPort: 30000 name: sglang-http protocol: TCP patchWorkerTemplate: {} template: metadata: labels: inference-framework: sglang inference-stack.io/monitoring: "enabled" spec: containers: - name: sglang image: lmsysorg/sglang:latest env: - name: SGLANG_SKIP_SGL_KERNEL_VERSION_CHECK value: "1" - name: CUDA_LAUNCH_BLOCKING value: "0" - name: SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT value: "1000000000" - name: NVSHMEM_IB_TRAFFIC_CLASS value: "16" - name: NVSHMEM_DISABLE_P2P value: "0" - name: ENABLE_METRICS value: "true" - name: NVSHMEM_IB_GID_INDEX value: "3" - name: NVSHMEM_IB_SL value: "5" - name: SGLANG_SET_CPU_AFFINITY value: "true" - name: SGL_ENABLE_JIT_DEEPGEMM value: "1" - name: NCCL_IB_QPS_PER_CONNECTION value: "8" - name: NCCL_IB_SPLIT_DATA_ON_QPS value: "1" - name: NCCL_NET_PLUGIN value: "none" - name: NCCL_IB_TC value: "136" - name: NCCL_IB_SL value: "5" - name: NCCL_IB_TIMEOUT value: "22" - name: NCCL_IB_GID_INDEX value: "3" - name: NCCL_MIN_NCHANNELS value: "4" - name: NCCL_SOCKET_IFNAME value: bond0 - name: GLOO_SOCKET_IFNAME value: bond0 - name: NCCL_IB_HCA value: ^=mlx5_0,mlx5_5,mlx5_6 - name: NVSHMEM_BOOTSTRAP_UID_SOCK_IFNAME value: "bond0" - name: MC_TE_METRIC value: "false" resources: limits: nvidia.com/gpu: "8" securityContext: capabilities: add: - IPC_LOCK privileged: true volumeMounts: - mountPath: /root/.cache name: sgl-cache - mountPath: /dev/shm name: dshm - mountPath: /work/models name: model - mountPath: /dev/infiniband name: ib - mountPath: /sgl-workspace/sglang name: src dnsPolicy: ClusterFirstWithHostNet hostIPC: true hostNetwork: true nodeSelector: pd: "yes" tolerations: - key: pd operator: Exists volumes: - hostPath: path: /var/run/sys-topology name: topo - hostPath: path: /data1/sgl_cache4 type: DirectoryOrCreate name: sgl-cache - emptyDir: medium: Memory name: dshm - hostPath: path: /data/DeepSeek-V3.2-Exp name: model - hostPath: path: /dev/infiniband name: ib - hostPath: path: /data/src/sglang type: DirectoryOrCreate name: src - name: decode replicas: 1 workload: apiVersion: leaderworkerset.x-k8s.io/v1 kind: LeaderWorkerSet leaderWorkerSet: size: 1 patchLeaderTemplate: metadata: labels: role: leader pd_role: decode spec: containers: - command: - python3 - -m - sglang.launch_server - --model-path - /work/models - --port - "30000" - --trust-remote - --host - 0.0.0.0 - --disaggregation-ib-device - mlx5_0,mlx5_1,mlx5_2,mlx5_3,mlx5_4,mlx5_5,mlx5_6,mlx5_7 - --chunked-prefill-size - "131072" - --eplb-rebalance-layers-per-chunk - "29" - --page-size - "64" - --enable-dp-attention - --enable-dp-lm-head - --dp-size - "8" - --moe-a2a-backend - deepep - --deepep-mode - low_latency - --disaggregation-mode - decode - --mem-fraction-static - "0.8" - --context-length - "32768" - --max-running-requests - "2048" - --tp-size - "8" # Size of Tensor Parallelism - --cuda-graph-max-bs - "16" - --dist-init-addr - $(LWS_LEADER_ADDRESS):20102 - --nnodes - $(LWS_GROUP_SIZE) - --node-rank - $(LWS_WORKER_INDEX) - --trust-remote-code - --ep-num-redundant-experts - "32" - --moe-dense-tp-size - "1" env: - name: LWS_WORKER_INDEX valueFrom: fieldRef: fieldPath: metadata.labels['leaderworkerset.sigs.k8s.io/worker-index'] livenessProbe: failureThreshold: 30000 httpGet: path: /health port: 30000 initialDelaySeconds: 300 periodSeconds: 60 successThreshold: 1 timeoutSeconds: 10 name: sglang readinessProbe: failureThreshold: 20 httpGet: path: /health port: 30000 periodSeconds: 30 successThreshold: 1 timeoutSeconds: 10 patchWorkerTemplate: spec: containers: - command: - python3 - -m - sglang.launch_server - --model-path - /work/models - --crash-dump-folder - /log - --chunked-prefill-size - "262144" - --eplb-rebalance-layers-per-chunk - "29" - --page-size - "64" - --enable-dp-attention - --enable-dp-lm-head - --dp-size - "32" - --moe-a2a-backend - "deepep" - --deepep-mode - low_latency - --disaggregation-mode - decode - --mem-fraction-static - "0.849" - --context-length - "32768" - --disaggregation-ib-device - mlx5_0,mlx5_1,mlx5_2,mlx5_3,mlx5_4,mlx5_5,mlx5_6,mlx5_7 - --max-running-requests - "4096" - --cuda-graph-max-bs - "16" - --tp-size - "8" # Size of Tensor Parallelism - --dist-init-addr - $(LWS_LEADER_ADDRESS):20102 - --nnodes - $(LWS_GROUP_SIZE) - --node-rank - $(LWS_WORKER_INDEX) - --trust-remote-code - --ep-num-redundant-experts - "32" - --moe-dense-tp-size - "1" env: - name: LWS_WORKER_INDEX valueFrom: fieldRef: fieldPath: metadata.labels['leaderworkerset.sigs.k8s.io/worker-index'] name: sglang template: metadata: labels: inference-framework: sglang-unuse inference-stack.io/monitoring: "enabled" spec: containers: - image: lmsysorg/sglang:latest name: sglang resources: limits: nvidia.com/gpu: "8" securityContext: capabilities: add: - IPC_LOCK privileged: true volumeMounts: - mountPath: /root/.cache name: sgl-cache - mountPath: /dev/shm name: dshm - mountPath: /work/models name: model - mountPath: /dev/infiniband name: ib - mountPath: /sgl-workspace/sglang name: src env: - name: SGLANG_SKIP_SGL_KERNEL_VERSION_CHECK value: "1" - name: SGLANG_DISAGGREGATION_WAITING_TIMEOUT value: "100000000" - name: NVSHMEM_DISABLE_P2P value: "0" - name: NVSHMEM_IB_TRAFFIC_CLASS value: "16" - name: NVSHMEM_IB_SL value: "5" - name: ENABLE_METRICS value: "true" - name: CUDA_LAUNCH_BLOCKING value: "0" - name: NVSHMEM_IB_GID_INDEX value: "3" - name: NCCL_IB_QPS_PER_CONNECTION value: "8" - name: NCCL_IB_SPLIT_DATA_ON_QPS value: "1" - name: NCCL_NET_PLUGIN value: "none" - name: NCCL_IB_TC value: "136" - name: NCCL_IB_SL value: "5" - name: NCCL_IB_TIMEOUT value: "22" - name: NCCL_IB_GID_INDEX value: "3" - name: NCCL_MIN_NCHANNELS value: "4" - name: NCCL_SOCKET_IFNAME value: bond0 - name: GLOO_SOCKET_IFNAME value: bond0 - name: NVSHMEM_BOOTSTRAP_UID_SOCK_IFNAME value: "bond0" - name: NCCL_IB_HCA value: ^=mlx5_0,mlx5_5,mlx5_6 - name: MC_TE_METRIC value: "false" - name: SGL_ENABLE_JIT_DEEPGEMM value: "1" dnsPolicy: ClusterFirstWithHostNet hostIPC: true hostNetwork: true nodeSelector: pd: "yes" tolerations: - key: pd operator: Exists volumes: - hostPath: path: /var/run/sys-topology name: topo - hostPath: path: /data1/sgl_cache4 type: DirectoryOrCreate name: sgl-cache - hostPath: path: /data/src/sglang type: DirectoryOrCreate name: src - emptyDir: medium: Memory name: dshm - hostPath: path: /data/DeepSeek-V3.2-Exp name: model - hostPath: path: /dev/infiniband name: ib - name: router replicas: 1 dependencies: [ "decode", "prefill" ] template: spec: containers: - name: scheduler image: lmsysorg/sglang:latest command: - sh - -c - > python3 -m sglang_router.launch_router --host 0.0.0.0 --port 8080 --pd-disaggregation --policy random --service-discovery --service-discovery-namespace ${NAMESPACE} --service-discovery-port 30000 --prefill-selector pd_role=prefill --decode-selector pd_role=decode --max-payload-size 2147483648 --worker-startup-timeout-secs 1200 env: - name: NAMESPACE valueFrom: fieldRef: apiVersion: v1 fieldPath: metadata.namespace --- apiVersion: v1 kind: Service metadata: labels: app: deepseek-rbg-32exp name: deepseek-rbg-32exp namespace: default spec: ports: - name: http port: 8080 protocol: TCP targetPort: 8080 nodePort: 30080 selector: rolebasedgroup.workloads.x-k8s.io/name: deepseek-rbg-32exp rolebasedgroup.workloads.x-k8s.io/role: router type: NodePort ``` ```bash [root@ecs-001]# kubectl get po -n default deepseek-rbg-32exp-decode-main-0 1/1 Running 0 74m deepseek-rbg-32exp-decode-0-1 1/1 Running 0 74m deepseek-rbg-32exp-router-9c5dbfc57 1/1 Running 0 22m deepseek-rbg-32exp-prefill-0 1/1 Running 0 74m [root@ecs-cbm-x1-pd-cpu-001 main_doc]# kubectl get svc |grep dee deepseek-rbg-32exp-decode ClusterIP None 97m deepseek-rbg-32exp-router-service NodePort 172.16.242.169 8000:30800/TCP 22m deepseek-rbg-32exp-prefill ClusterIP None 97m ``` At this point, select a nodePort:30800 to access: ```bash [root@ecs-001]# curl -X POST "http://{nodePort}:30800/v1/chat/completions" \ > -H "Content-Type: application/json" \ > -H "Authorization: Bearer None" \ > -d '{ > "rid":"ccccdd", > "model": "dsv32", > "messages": [ > {"role": "system", "content": "0: You are a helpful AI assistant"}, > {"role": "user", "content": "你是谁？."} > ], > "max_tokens":221 > }' {"id":"ccccdd","object":"chat.completion","created":1750252498,"model":"qwen2","choices":[{"index":0,"message":{"role":"assistant","content":"\n嗯，用户问了一个很基础的自我介绍问题"你是谁？"。这可能是第一次互动时的常规开场白，也可能是想确认我的身份和功能范围。\n\n用户没有提供任何背景信息，语气简洁中性。这种场景下新用户的可能性较高，需要给出清晰友好的自我介绍，同时突出实用价值来降低陌生感。\n\n考虑到中文用户，应该用简体中文回复。重点要说明三点：身份归属（深度求索）、功能定位（AI助手）、服务范围（学习/工作/生活）。结尾用开放性问题引导对话很关键——既能了解需求，又能避免让用户面对空白输入框时不知所措。\n\n用波浪线结尾可以软化语气，那个笑脸表情😊刚好能中和AI的机械感。不过要控制表情符号数量，避免显得轻浮。\n\n你好呀！我是你的AI助手，由深度求索公司（DeepSeek）开发的语言模型，名字叫 **DeepSeek-V32**。你可以把我当成一个知识丰富、随叫随到的小帮手～😊\n\n我的任务就是陪你聊天、解答问题、","reasoning_content":null,"tool_calls":null},"logprobs":null,"finish_reason":"length","matched_stop":null}],"usage":{"prompt_tokens":14,"total_tokens":235,"completion_tokens":221,"prompt_tokens_details":null}} ``` ## FAQ 1. The current deployment startup parameters may not be fully compatible with all RDMA scenarios. Different RDMA NCCL-related environment configurations may be needed in different network environments. 2. Please ensure that the sglang code in the image has incorporated the changes from [PR #10912](https://github.com/sgl-project/sglang/pull/10912).