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Layout on 4x Tesla V100 32GB (PCIe, no NVLink), all TP=1: GPU0+1 vLLM DeepSeek-R1-Distill-Qwen-32B bnb-nf4 (2 replicas) GPU2 Ollama ornith:35b + qwen2.5:3b-instruct (co-resident) GPU3 vLLM Qwen2.5-Math-PRM-7B (reward model) CPU TEI nomic-embed-text-v2-moe, bge-reranker-base Volta constraints, each verified against live output rather than config: - vLLM pinned v0.11.0: sm_70 dropped from CUDA_SUPPORTED_ARCHS at v0.11.1. - AWQ hard-rejected (needs sm_75). GPTQ passes vLLM's min_capability=60 gate but is NUMERICALLY WRONG on sm_70 — emits garbage logits. Proven by an fp16 control run producing correct text on an identical backend. bitsandbytes nf4 verified correct by output. - flashinfer's check_cuda_arch() crashes on any sm_7x (calls .isdigit() on an int) -> VLLM_USE_FLASHINFER_SAMPLER=0. - xformers has no sm_70 kernel for V1's paged-attention bias, and V0 was removed in v0.11.0 -> TRITON_ATTN. - Ornith is Qwen3.5-MoE hybrid-attention; vLLM added that arch after dropping Volta, so no build has both -> Ollama, which also multiplexes a second model on the same card for free. Cluster prereqs that were absent: - RuntimeClass nvidia: the Talos toolkit extension registers the containerd handler but not the k8s object; without it every pod is rejected at admission. - gpu-system pinned to privileged PSA: a device plugin cannot satisfy the cluster-default baseline, it must mount hostPath. - device-plugin affinity=null: the chart requires NFD labels that do not exist here, so it matched zero nodes and reported desiredNumberScheduled=0 silently. - Recreate strategy on GPU services: with GPUs allocated exactly 4/4, a RollingUpdate surge pod has no card and deadlocks the rollout. - longhorn-llm-local SC (1 replica, strict-local, disk tag llm): the default 3-replica class could not place the volume at all (every control-plane disk was at its over-provisioning ceiling), and this keeps ~60GB of weights on worker-1's own NVMe instead of reading them over the network. deploy-gpu-serving.sh sequences ArgoCD syncs (or helm/kubectl in --manual mode) and never applies a manifest absent from git; doctor/unstick/teardown stages exist so this is diagnosable without ad-hoc kubectl archaeology.
44 lines
1.4 KiB
YAML
44 lines
1.4 KiB
YAML
# Default-deny ingress for the serving pods.
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#
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# This is a real compensating control, not hygiene: vLLM is pinned to v0.11.0
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# (forced — last release with Volta kernels), which sits below the patch line on
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# several advisories that will never be backported to that branch, incl.
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# CVE-2026-54234 (remote DoS) and GHSA-7m6h-x95x-82q5 (cross-user data leak).
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# Those are all remote/unauthenticated attack surface, so keeping the engines
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# reachable only from opted-in in-cluster clients is what keeps exposure low.
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#
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# Consumers opt in with label `llm-client: "true"`. Do NOT expose these via
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# Ingress.
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apiVersion: networking.k8s.io/v1
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kind: NetworkPolicy
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metadata:
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name: llm-serving-default-deny
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spec:
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podSelector:
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matchLabels:
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app.kubernetes.io/part-of: llm-serving
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policyTypes:
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- Ingress
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ingress:
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- from:
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# Any pod, any namespace, that explicitly opts in as an LLM client.
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- namespaceSelector: {}
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podSelector:
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matchLabels:
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llm-client: "true"
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# Sibling engines (harness may chain calls between them).
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- podSelector:
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matchLabels:
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app.kubernetes.io/part-of: llm-serving
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ports:
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- protocol: TCP
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port: 8080
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- from:
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# Prometheus scraping /metrics.
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- namespaceSelector:
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matchLabels:
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kubernetes.io/metadata.name: monitoring
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ports:
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- protocol: TCP
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port: 8080
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