vllm - ✅(Solved) Fix [Bug]: Editing `values.labels` in `chart-helm` breaks Service selector and leaves Endpoints empty [2 pull requests, 1 participants]

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vllm-project/vllm#37942Fetched 2026-04-08 01:22:30
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Fix Action

Fix / Workaround

============================== CPU Info

Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 45 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 16 On-line CPU(s) list: 0-15 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Platinum 8268 CPU @ 2.90GHz CPU family: 6 Model: 85 Thread(s) per core: 1 Core(s) per socket: 1 Socket(s): 16 Stepping: 7 BogoMIPS: 5786.40 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon nopl xtopology tsc_reliable nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 invpcid avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat pku ospke avx512_vnni md_clear flush_l1d arch_capabilities ibpb_exit_to_user L1d cache: 512 KiB (16 instances) L1i cache: 512 KiB (16 instances) L2 cache: 16 MiB (16 instances) L3 cache: 572 MiB (16 instances) NUMA node(s): 1 NUMA node0 CPU(s): 0-15 Vulnerability Gather data sampling: Vulnerable: No microcode Vulnerability Itlb multihit: KVM: Mitigation: VMX unsupported Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Vulnerable: Clear CPU buffers attempted, no microcode; SMT disabled Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Mitigation; Enhanced IBRS Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

PR fix notes

PR #37959: [Bugfix] Fix Helm chart Deployment using hardcoded labels instead of chart.labels

Description (problem / solution / changelog)

Essential Changes

The Deployment template in examples/online_serving/chart-helm had hardcoded selector.matchLabels and template.metadata.labels:

selector:
  matchLabels:
    environment: "test"
    release: "test"
template:
  metadata:
    labels:
      environment: "test"
      release: "test"

Meanwhile, the Service template already uses the chart.labels helper (which reads from values.labels). When users customize labels in values.yaml, the Service selector no longer matches the Deployment pod labels, leaving Service endpoints empty.

This PR replaces the hardcoded labels with {{ include "chart.labels" . }} to keep the Deployment selector/labels consistent with the Service selector.

Fixes #37942

Testing

  • Verified helm template output before and after: selector and pod labels now match Service selector when values.labels is customized.
  • Confirmed default values.yaml labels (environment: test, release: test) still work correctly.

Changed files

  • DAILY_LEARNINGS.md (added, +974/-0)
  • dgx_spark_issues.md (added, +423/-0)
  • examples/online_serving/chart-helm/templates/deployment.yaml (modified, +3/-5)

PR #38340: [Doc] fix selector/label mismatch in helm chart

Description (problem / solution / changelog)

Purpose

Fixes #37942

This fixes label/selector consistency in examples/online_serving/chart-helm by:

  • introducing stable selector labels (app.kubernetes.io/name, app.kubernetes.io/instance) for Deployment/Service selectors,
  • applying common chart labels across resources
  • and updating values.schema.json so .Values.labels supports arbitrary string key/value pairs instead of only environment/release.

Breaking change note:

  • Deployment.spec.selector.matchLabels changed from hardcoded environment/release to app.kubernetes.io/name/app.kubernetes.io/instance.
  • Existing releases may require recreation (or equivalent force-replace flow) when upgrading because Deployment selectors are immutable in Kubernetes.

Test Plan

  • helm lint examples/online_serving/chart-helm
  • helm template test examples/online_serving/chart-helm
  • helm unittest examples/online_serving/chart-helm

Test Result

  • helm lint passes
  • helm template renders expected selectors/labels
  • helm unittest passes
<details> <summary> Test Result Details </summary> <pre><code> $ helm lint examples/online_serving/chart-helm ==> Linting examples/online_serving/chart-helm [INFO] Chart.yaml: icon is recommended 1 chart(s) linted, 0 chart(s) failed </code></pre> <pre><code> $ helm template test examples/online_serving/chart-helm --- # Source: chart-vllm/templates/poddisruptionbudget.yaml apiVersion: policy/v1 kind: PodDisruptionBudget metadata: name: "test-pdb" namespace: default labels: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test helm.sh/chart: chart-vllm-0.0.1 app.kubernetes.io/managed-by: Helm spec: maxUnavailable: 1 --- # Source: chart-vllm/templates/secrets.yaml apiVersion: v1 kind: Secret metadata: name: "test-secrets" namespace: default labels: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test helm.sh/chart: chart-vllm-0.0.1 app.kubernetes.io/managed-by: Helm type: Opaque data: --- # Source: chart-vllm/templates/pvc.yaml apiVersion: v1 kind: PersistentVolumeClaim metadata: name: "test-storage-claim" namespace: default labels: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test helm.sh/chart: chart-vllm-0.0.1 app.kubernetes.io/managed-by: Helm spec: accessModes: - ReadWriteOnce resources: requests: storage: 1Gi --- # Source: chart-vllm/templates/service.yaml apiVersion: v1 kind: Service metadata: name: "test-service" namespace: default labels: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test helm.sh/chart: chart-vllm-0.0.1 app.kubernetes.io/managed-by: Helm spec: type: ClusterIP ports: - name: "service-port" port: 80 targetPort: "container-port" protocol: TCP selector: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test --- # Source: chart-vllm/templates/deployment.yaml apiVersion: apps/v1 kind: Deployment metadata: name: "test-deployment-vllm" namespace: default labels: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test helm.sh/chart: chart-vllm-0.0.1 app.kubernetes.io/managed-by: Helm spec: replicas: 1 strategy: rollingUpdate: maxSurge: 100% maxUnavailable: 0 selector: matchLabels: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test progressDeadlineSeconds: 1200 template: metadata: labels: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test helm.sh/chart: chart-vllm-0.0.1 app.kubernetes.io/managed-by: Helm spec: containers: - name: "vllm" image: "vllm/vllm-openai:latest" command : - vllm - serve - /data/ - --served-model-name - opt-125m - --enforce-eager - --dtype - bfloat16 - --block-size - "16" - --host - 0.0.0.0 - --port - "8000" securityContext: runAsNonRoot: false imagePullPolicy: IfNotPresent env: [] ports: - name: "container-port" containerPort: 8000 readinessProbe: failureThreshold: 3 httpGet: path: /health port: 8000 initialDelaySeconds: 5 periodSeconds: 5 livenessProbe: failureThreshold: 3 httpGet: path: /health port: 8000 initialDelaySeconds: 15 periodSeconds: 10 resources: requests: memory: "16Gi" cpu: "4" nvidia.com/gpu: "1" limits: memory: "16Gi" cpu: "4" nvidia.com/gpu: "1" volumeMounts: - name: test-storage mountPath: /data initContainers: - name: wait-download-model image: amazon/aws-cli:2.6.4 imagePullPolicy: IfNotPresent command: ["/bin/bash"] args: - -eucx - while aws --endpoint-url $S3_ENDPOINT_URL s3 sync --dryrun s3://$S3_BUCKET_NAME/$S3_PATH /data | grep -q download; do sleep 10; done env: - name: S3_ENDPOINT_URL valueFrom: secretKeyRef: name: test-secrets key: s3endpoint - name: S3_BUCKET_NAME valueFrom: secretKeyRef: name: test-secrets key: s3bucketname - name: AWS_ACCESS_KEY_ID valueFrom: secretKeyRef: name: test-secrets key: s3accesskeyid - name: AWS_SECRET_ACCESS_KEY valueFrom: secretKeyRef: name: test-secrets key: s3accesskey - name: S3_PATH value: "relative_s3_model_path/opt-125m" - name: AWS_EC2_METADATA_DISABLED value: "true" resources: requests: cpu: 200m memory: 1Gi limits: cpu: 500m memory: 2Gi volumeMounts: - name: test-storage mountPath: /data volumes: - name: test-storage persistentVolumeClaim: claimName: test-storage-claim runtimeClassName: nvidia affinity: nodeAffinity: requiredDuringSchedulingIgnoredDuringExecution: nodeSelectorTerms: - matchExpressions: - key: nvidia.com/gpu.product operator: In values: - TYPE_GPU_USED --- # Source: chart-vllm/templates/job.yaml apiVersion: batch/v1 kind: Job metadata: name: "test-init-vllm" namespace: default labels: app.kubernetes.io/name: chart-vllm app.kubernetes.io/instance: test helm.sh/chart: chart-vllm-0.0.1 app.kubernetes.io/managed-by: Helm spec: ttlSecondsAfterFinished: 100 template: metadata: name: init-vllm spec: containers: - name: job-download-model image: amazon/aws-cli:2.6.4 imagePullPolicy: IfNotPresent command: ["/bin/bash"] args: - -eucx - aws --endpoint-url $S3_ENDPOINT_URL s3 sync s3://$S3_BUCKET_NAME/$S3_PATH /data env: - name: S3_ENDPOINT_URL valueFrom: secretKeyRef: name: test-secrets key: s3endpoint - name: S3_BUCKET_NAME valueFrom: secretKeyRef: name: test-secrets key: s3bucketname - name: AWS_ACCESS_KEY_ID valueFrom: secretKeyRef: name: test-secrets key: s3accesskeyid - name: AWS_SECRET_ACCESS_KEY valueFrom: secretKeyRef: name: test-secrets key: s3accesskey - name: S3_PATH value: "relative_s3_model_path/opt-125m" - name: AWS_EC2_METADATA_DISABLED value: "true" volumeMounts: - name: test-storage mountPath: /data resources: requests: cpu: 200m memory: 1Gi limits: cpu: 500m memory: 2Gi restartPolicy: OnFailure volumes: - name: test-storage persistentVolumeClaim: claimName: "test-storage-claim" </code></pre> <pre><code> $ helm unittest examples/online_serving/chart-helm ### Chart [ chart-vllm ] examples/online_serving/chart-helm PASS test deployment examples/online_serving/chart-helm/tests/deployment_test.yaml PASS test job examples/online_serving/chart-helm/tests/job_test.yaml PASS test pvc examples/online_serving/chart-helm/tests/pvc_test.yaml Charts: 1 passed, 1 total Test Suites: 3 passed, 3 total Tests: 6 passed, 6 total Snapshot: 0 passed, 0 total Time: 44.598564ms </code></pre> </details>
<details> <summary> Essential Elements of an Effective PR Description Checklist </summary>
  • The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
  • The test plan, such as providing test command.
  • The test results, such as pasting the results comparison before and after, or e2e results
  • (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.
  • (Optional) Release notes update. If your change is user facing, please update the release notes draft in the Google Doc.
</details>

Changed files

  • docs/deployment/frameworks/helm.md (modified, +1/-1)
  • examples/online_serving/chart-helm/templates/_helpers.tpl (modified, +21/-3)
  • examples/online_serving/chart-helm/templates/configmap.yaml (modified, +3/-1)
  • examples/online_serving/chart-helm/templates/deployment.yaml (modified, +4/-6)
  • examples/online_serving/chart-helm/templates/hpa.yaml (modified, +3/-1)
  • examples/online_serving/chart-helm/templates/job.yaml (modified, +3/-1)
  • examples/online_serving/chart-helm/templates/poddisruptionbudget.yaml (modified, +3/-1)
  • examples/online_serving/chart-helm/templates/pvc.yaml (modified, +3/-1)
  • examples/online_serving/chart-helm/templates/secrets.yaml (modified, +3/-1)
  • examples/online_serving/chart-helm/templates/service.yaml (modified, +3/-1)
  • examples/online_serving/chart-helm/tests/labels_test.yaml (added, +107/-0)
  • examples/online_serving/chart-helm/values.schema.json (modified, +4/-13)
  • examples/online_serving/chart-helm/values.yaml (modified, +2/-3)

Code Example

==============================
        System Info
==============================
OS                           : Ubuntu 24.04 LTS (x86_64)
GCC version                  : (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version                : Could not collect
CMake version                : Could not collect
Libc version                 : glibc-2.39

==============================
       PyTorch Info
==============================
PyTorch version              : 2.10.0+cu128
Is debug build               : False
CUDA used to build PyTorch   : 12.8
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.3 (main, Nov  6 2025, 13:44:16) [GCC 13.3.0] (64-bit runtime)
Python platform              : Linux-6.8.0-90-generic-x86_64-with-glibc2.39

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : Could not collect
CUDA_MODULE_LOADING set to   :
GPU models and configuration : GPU 0: NVIDIA A100-PCIE-40GB
Nvidia driver version        : 570.195.03
cuDNN version                : Could not collect
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        45 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               16
On-line CPU(s) list:                  0-15
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Platinum 8268 CPU @ 2.90GHz
CPU family:                           6
Model:                                85
Thread(s) per core:                   1
Core(s) per socket:                   1
Socket(s):                            16
Stepping:                             7
BogoMIPS:                             5786.40
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon nopl xtopology tsc_reliable nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 invpcid avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat pku ospke avx512_vnni md_clear flush_l1d arch_capabilities ibpb_exit_to_user
L1d cache:                            512 KiB (16 instances)
L1i cache:                            512 KiB (16 instances)
L2 cache:                             16 MiB (16 instances)
L3 cache:                             572 MiB (16 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-15
Vulnerability Gather data sampling:   Vulnerable: No microcode
Vulnerability Itlb multihit:          KVM: Mitigation: VMX unsupported
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Vulnerable: Clear CPU buffers attempted, no microcode; SMT disabled
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected
Vulnerability Vmscape:                Mitigation; IBPB before exit to userspace

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.6
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-frontend==1.18.0
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-cufile-cu12==1.13.1.3
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.4.2
[pip3] nvidia-cutlass-dsl-libs-base==4.4.2
[pip3] nvidia-ml-py==13.595.45
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvshmem-cu12==3.4.5
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] pyzmq==27.1.0
[pip3] torch==2.10.0
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.10.0
[pip3] torchvision==0.25.0
[pip3] transformers==4.57.6
[pip3] triton==3.6.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.18.0
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
        GPU0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      0-15    0               N/A

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

==============================
     Environment Variables
==============================
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_<user>

---

labels:
  environment: "dev"
  release: "my-release"

---

helm install <release name> ./examples/online_serving/chart-helm -f ./examples/online_serving/chart-helm/values.yaml

---

kubectl get pod -owide -n <namespace>
kubectl get endpointslice -n <namespace>

---

labels:
  environment: "cl-nagoya-ruri-v3-310m"
  release: "cl-nagoya-ruri-v3-310m"

---

labels:
  environment: "quanttrio-qwen3-vl-30b-a3b-instruct-awq"
  release: "quanttrio-qwen3-vl-30b-a3b-instruct-awq"

---

$ kubectl get pod -owide -n models
NAME                                                              READY   STATUS    RESTARTS   AGE   IP                NODE            NOMINATED NODE   READINESS GATES
cl-nagoya-ruri-v3-310m-deployment-vllm-6bcc6756f7-rm8vn           1/1     Running   0          68m   192.168.128.132   utsumi-llmops   <none>           <none>
quanttrio-qwen3-vl-30b-a3b-instruct-awq-deployment-vllm-69r8bx8   1/1     Running   0          75m   192.168.128.130   utsumi-llmops   <none>           <none>

---

$ kubectl get endpointslice -n models
NAME                                                    ADDRESSTYPE   PORTS     ENDPOINTS   AGE
cl-nagoya-ruri-v3-310m-service-7rtvt                    IPv4          <unset>   <unset>     71m
quanttrio-qwen3-vl-30b-a3b-instruct-awq-service-pp7tr   IPv4          <unset>   <unset>     78m
RAW_BUFFERClick to expand / collapse

Your current environment

<details> <summary>The output of <code>python collect_env.py</code></summary>
==============================
        System Info
==============================
OS                           : Ubuntu 24.04 LTS (x86_64)
GCC version                  : (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version                : Could not collect
CMake version                : Could not collect
Libc version                 : glibc-2.39

==============================
       PyTorch Info
==============================
PyTorch version              : 2.10.0+cu128
Is debug build               : False
CUDA used to build PyTorch   : 12.8
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.3 (main, Nov  6 2025, 13:44:16) [GCC 13.3.0] (64-bit runtime)
Python platform              : Linux-6.8.0-90-generic-x86_64-with-glibc2.39

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : Could not collect
CUDA_MODULE_LOADING set to   :
GPU models and configuration : GPU 0: NVIDIA A100-PCIE-40GB
Nvidia driver version        : 570.195.03
cuDNN version                : Could not collect
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        45 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               16
On-line CPU(s) list:                  0-15
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Platinum 8268 CPU @ 2.90GHz
CPU family:                           6
Model:                                85
Thread(s) per core:                   1
Core(s) per socket:                   1
Socket(s):                            16
Stepping:                             7
BogoMIPS:                             5786.40
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon nopl xtopology tsc_reliable nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 invpcid avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat pku ospke avx512_vnni md_clear flush_l1d arch_capabilities ibpb_exit_to_user
L1d cache:                            512 KiB (16 instances)
L1i cache:                            512 KiB (16 instances)
L2 cache:                             16 MiB (16 instances)
L3 cache:                             572 MiB (16 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-15
Vulnerability Gather data sampling:   Vulnerable: No microcode
Vulnerability Itlb multihit:          KVM: Mitigation: VMX unsupported
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Vulnerable: Clear CPU buffers attempted, no microcode; SMT disabled
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected
Vulnerability Vmscape:                Mitigation; IBPB before exit to userspace

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.6
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-frontend==1.18.0
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-cufile-cu12==1.13.1.3
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.4.2
[pip3] nvidia-cutlass-dsl-libs-base==4.4.2
[pip3] nvidia-ml-py==13.595.45
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvshmem-cu12==3.4.5
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] pyzmq==27.1.0
[pip3] torch==2.10.0
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.10.0
[pip3] torchvision==0.25.0
[pip3] transformers==4.57.6
[pip3] triton==3.6.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.18.0
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
        GPU0    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      0-15    0               N/A

Legend:

  X    = Self
  SYS  = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
  NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
  PHB  = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
  PXB  = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
  PIX  = Connection traversing at most a single PCIe bridge
  NV#  = Connection traversing a bonded set of # NVLinks

==============================
     Environment Variables
==============================
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_<user>
</details>

🐛 Describe the bug

This issue is about chart-helm.

Editing labels in values.yaml breaks Service selector and leaves Endpoint empty.

Steps to reproduce:

  1. Edit labels in values.yaml, for example:
labels:
  environment: "dev"
  release: "my-release"
  1. Install the chart:
helm install <release name> ./examples/online_serving/chart-helm -f ./examples/online_serving/chart-helm/values.yaml
  1. Check the resources:
kubectl get pod -owide -n <namespace>
kubectl get endpointslice -n <namespace>

Actual behavior

The Service does not select the Pods, and the Service endpoints remain empty.

In my environment, I deployed two models by executing helm install command respectively. The labels are as follows:

labels:
  environment: "cl-nagoya-ruri-v3-310m"
  release: "cl-nagoya-ruri-v3-310m"
labels:
  environment: "quanttrio-qwen3-vl-30b-a3b-instruct-awq"
  release: "quanttrio-qwen3-vl-30b-a3b-instruct-awq"

The Pods are as follows:

$ kubectl get pod -owide -n models
NAME                                                              READY   STATUS    RESTARTS   AGE   IP                NODE            NOMINATED NODE   READINESS GATES
cl-nagoya-ruri-v3-310m-deployment-vllm-6bcc6756f7-rm8vn           1/1     Running   0          68m   192.168.128.132   utsumi-llmops   <none>           <none>
quanttrio-qwen3-vl-30b-a3b-instruct-awq-deployment-vllm-69r8bx8   1/1     Running   0          75m   192.168.128.130   utsumi-llmops   <none>           <none>

The Endpoints are as follows:

$ kubectl get endpointslice -n models
NAME                                                    ADDRESSTYPE   PORTS     ENDPOINTS   AGE
cl-nagoya-ruri-v3-310m-service-7rtvt                    IPv4          <unset>   <unset>     71m
quanttrio-qwen3-vl-30b-a3b-instruct-awq-service-pp7tr   IPv4          <unset>   <unset>     78m

The above ENDPOINTS and PORTS are <unset>. This indicates that the Services are not connected to the Pods.

It looks like the Service selector uses the edited labels, while the Pod labels in the Deployment remain fixed, causing the mismatch.

Issue #26932 also mentions that the Deployment selector labels are hardcoded to environment: test and release: test.

Expected behavior

Changing labels in values.yaml should not break the Service selector. The Service selector and Pod labels should remain consistent.

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extent analysis

Fix Plan

To resolve the issue, we need to ensure that the Service selector labels match the Pod labels in the Deployment.

Here are the steps to fix the issue:

  • Update the labels in the Deployment to match the labels in values.yaml.
  • Alternatively, update the Service selector to use the hardcoded labels environment: test and release: test if they are intended to be fixed.

Code Changes

We can update the deployment.yaml file in the chart to use the labels from values.yaml.

# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: {{ include "chart-helm.fullname" . }}
spec:
  selector:
    matchLabels:
      environment: {{ .Values.labels.environment }}
      release: {{ .Values.labels.release }}
  template:
    metadata:
      labels:
        environment: {{ .Values.labels.environment }}
        release: {{ .Values.labels.release }}
# service.yaml
apiVersion: v1
kind: Service
metadata:
  name: {{ include "chart-helm.fullname" . }}
spec:
  selector:
    environment: {{ .Values.labels.environment }}
    release: {{ .Values.labels.release }}

Verification

After applying the changes, verify that the Service selector labels match the Pod labels in the Deployment.

kubectl get deployment -n <namespace> -o yaml
kubectl get service -n <namespace> -o yaml
kubectl get pod -n <namespace> -o yaml

Check the labels and selector fields in the output to ensure they match.

Extra Tips

  • Make sure to update the values.yaml file with the correct labels for each environment.
  • Consider using a consistent naming convention for the labels across all environments.
  • If you are using a CI/CD pipeline, update the pipeline to reflect the changes in the chart.

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FAQ

Expected behavior

Changing labels in values.yaml should not break the Service selector. The Service selector and Pod labels should remain consistent.

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vllm - ✅(Solved) Fix [Bug]: Editing `values.labels` in `chart-helm` breaks Service selector and leaves Endpoints empty [2 pull requests, 1 participants]