Kubernetes instance pass own request resource and ingnore InstantceType configuration
まだ誰も着手していません。
評価
- 難易度
- 4/5
- 見積もり時間
- 3〜5日
- 初心者へのやさしさ
- 25/100
- issue の種類
- バグ
- 明瞭さ
- おおむね明確
- 活発さ
- 停滞
- 技術スタック
- azure, kubernetes
調査の方向性
まず、提供された InstanceType YAML を使用して AKS デプロイメントを再現し、生成された Pod マニフェストを調査します。特に inference-server のリソースを確認してください。設定された requests と、結果として設定される 100m CPU および 512Mi メモリの値を比較します。デプロイメントの Pod が InstanceType の request 値を使用し、表示されている limits と node selector を維持していれば完了です。
索引モデルが issue の本文から書いたものです。
説明
I am creating instance type configuration in AKS cluster.
Enable autoscale for nodepools gpuproc2 and cpuproc2.
When deployment is creating configuration spec.resources.requests from defined Instance type is ignored and pod are created with other values.
Values are seeing like hardcoded values cpu 100m and memory 512Mi.
Until this will working properly I can't allocate pods on different nodes from same nodepool group.
---
apiVersion: amlarc.azureml.com/v1alpha1
kind: InstanceType
metadata:
name: standard-nc4
spec:
nodeSelector:
agentpool: gpuproc2
resources:
limits:
cpu: "1"
memory: "20Gi"
requests:
cpu: "700m"
memory: "1900Mi"
---
apiVersion: amlarc.azureml.com/v1alpha1
kind: InstanceType
metadata:
name: standard-cpuproc
spec:
nodeSelector:
agentpool: cpuproc2
resources:
limits:
cpu: "3"
memory: "15Gi"
requests:
cpu: "1100m"
memory: "1500Mi"
Pod created by azure workspace deployment:
apiVersion: v1
kind: Pod
metadata:
creationTimestamp: "2023-04-19T04:06:00Z"
generateName: deployname-134205-model-name-79c786f5c-
labels:
azuremlappname: deployname-134205-model-name
isazuremlapp: "true"
ml.azure.com/compute: aksnemlflowprod
ml.azure.com/deployment-name: deployname-134205
ml.azure.com/endpoint-name: model-name
ml.azure.com/identity: deployname-134205-model-name
ml.azure.com/resource-group: smarteye-ml-ne-prod
ml.azure.com/scrape-metrics: "true"
ml.azure.com/subscription-id: 89f996fd-5276-46d1-87c6-64544e672483
ml.azure.com/workspace: ne-mlflow-prod
pod-template-hash: 79c786f5c
name: deployname-134205-model-name-79c786f5c-sd2ch
namespace: default
ownerReferences:
- apiVersion: apps/v1
blockOwnerDeletion: true
controller: true
kind: ReplicaSet
name: deployname-134205-model-name-79c786f5c
uid: b72dae92-2086-44fa-899b-9aadedc0a1ec
resourceVersion: "29057046"
uid: c6ff4522-57a9-4cb9-963e-f8064a9daac8
spec:
automountServiceAccountToken: true
containers:
- command:
- runsvdir
- /var/runit
env:
- name: AML_APP_ROOT
value: /var/azureml-app/product-detection
- name: AZUREML_ENTRY_SCRIPT
value: azureml_score.py
- name: AZUREML_MODEL_DIR
value: /var/azureml-app/azureml-models/model_name/5
- name: AZURE_STORAGE_CONNECTION_STRING
value: SharedAccessSignature=;BlobEndpoint=https://account.blob.core.windows.net/;
- name: CELERY_WORKER_QUEUE
value: queue_name
- name: CLASSIFICATION_MODEL_NAME
value: model_name
- name: CLASSIFICATION_MODEL_ROOT
value: /opt/project/models
- name: DEFAULT_CONSUMER
value: InferenceDetector
- name: DEFAULT_CONSUMER_MODULE
value: model_extractor.queue_consumer
- name: DETECTOR_MODEL_NAME
value: name_of_package
- name: DETECTOR_MODEL_PACKAGE
value: https://url.tld/file
- name: DETECTOR_MODEL_ROOT
value: /opt/project/models
- name: GPU_MEMORY_LIMIT
value: "4096"
- name: MLFLOW_MODEL_FOLDER
value: /var/azureml-app/azureml-models
- name: PREDICT_BATCH_SIZE
value: "4"
- name: SERVICE_NAME
value: model-name
- name: SERVICE_PATH_PREFIX
value: api/v1/endpoint/model-name
- name: TF_GPU_ALLOCATOR
value: cuda_malloc_async
- name: MSI_SECRET
valueFrom:
secretKeyRef:
key: secret
name: deployname-134205-model-name-sidecar
- name: IDENTITY_HEADER
valueFrom:
secretKeyRef:
key: secret
name: deployname-134205-model-name-sidecar
- name: MSI_ENDPOINT
value: http://localhost:9999/token
- name: IDENTITY_ENDPOINT
value: http://localhost:9999/token
image: registry.azurecr.io/image/path:v3.6.2
imagePullPolicy: IfNotPresent
livenessProbe:
failureThreshold: 30
httpGet:
path: /
port: 5001
scheme: HTTP
initialDelaySeconds: 10
periodSeconds: 10
successThreshold: 1
timeoutSeconds: 180
name: inference-server
ports:
- containerPort: 5001
protocol: TCP
readinessProbe:
failureThreshold: 30
httpGet:
path: /
port: 5001
scheme: HTTP
initialDelaySeconds: 10
periodSeconds: 10
successThreshold: 1
timeoutSeconds: 2
resources:
limits:
cpu: "1"
memory: 20Gi
requests:
cpu: 100m
memory: 512Mi
securityContext:
privileged: false
terminationMessagePath: /dev/termination-log
terminationMessagePolicy: File
volumeMounts:
- mountPath: /var/azureml-app
name: model-mount-0
readOnly: true
- mountPath: /var/run/secrets/kubernetes.io/serviceaccount
name: kube-api-access-wjf8j
readOnly: true
- args:
- --identity
- /identity/identity_secret.json
- --token
- /identity/sidecar_token
- --ca
- /identity/ca.crt
- --remote-host
- https://amlarc-identity-proxy-service.azureml.svc.cluster.local
- --port
- "9999"
- --path
- /token
- --remote-path
- /token
env:
- name: MSI_SECRET
valueFrom:
secretKeyRef:
key: secret
name: deployname-134205-model-name-sidecar
image: mcr.microsoft.com/azureml/amlarc/docker/identity-sidecar:1.1.25
imagePullPolicy: IfNotPresent
name: identity-sidecar
resources:
limits:
cpu: 100m
memory: 50Mi
requests:
cpu: 100m
memory: 50Mi
terminationMessagePath: /dev/termination-log
terminationMessagePolicy: File
volumeMounts:
- mountPath: /identity
name: identity-secret-volume
readOnly: true
- mountPath: /var/run/secrets/kubernetes.io/serviceaccount
name: kube-api-access-wjf8j
readOnly: true
dnsPolicy: ClusterFirst
enableServiceLinks: true
imagePullSecrets:
- name: deployname-134205-model-name-registry.azurecr.io
initContainers:
- env:
- name: STORAGE_MANIFEST_URL
value: https://account.blob.core.windows.net/azureml/model-name_deployname-134205-model-name_model_config_map.json_f455169bb7e34736bc0c618741641388
- name: STORAGE_DOWNLOAD_PATH
value: /var/azureml-app
- name: STORAGE_CREDENTIAL_CLIENTID
value: uuid
- name: STORAGE_CREDENTIAL_TYPE
value: Amlarc
- name: STORAGE_CREDENTIAL_ENDPOINT
value: https://amlarc-identity-proxy-service.azureml.svc.cluster.local/token
- name: STORAGE_CREDENTIAL_TOKENFILE
value: /identity/sidecar_token
image: mcr.microsoft.com/mir/mir-storageinitializer:46571814.1631244300887
imagePullPolicy: IfNotPresent
name: storageinitializer-modeldata
resources:
limits:
cpu: 100m
memory: 500Mi
requests:
cpu: 100m
memory: 500Mi
terminationMessagePath: /dev/termination-log
terminationMessagePolicy: File
volumeMounts:
- mountPath: /var/azureml-app
name: model-mount-0
- mountPath: /var/run/secrets/kubernetes.io/serviceaccount
name: kube-api-access-wjf8j
readOnly: true
- mountPath: /identity
name: identity-secret-volume
readOnly: true
nodeName: aks-gpuproc2-28077253-vmss00000n
nodeSelector:
agentpool: gpuproc2
preemptionPolicy: PreemptLowerPriority
priority: 0
restartPolicy: Always
schedulerName: default-scheduler
securityContext: {}
serviceAccount: deployname-134205-model-name
serviceAccountName: deployname-134205-model-name
terminationGracePeriodSeconds: 30
tolerations:
- key: ml.azure.com/amlarc
operator: Equal
value: "true"
- key: ml.azure.com/amlarc-workload
operator: Equal
value: "true"
- key: ml.azure.com/resource-group
operator: Equal
value: smarteye-ml-ne-prod
- key: ml.azure.com/workspace
operator: Equal
value: ne-mlflow-prod
- key: ml.azure.com/compute
operator: Equal
value: aksnemlflowprod
- effect: NoExecute
key: node.kubernetes.io/not-ready
operator: Exists
tolerationSeconds: 300
- effect: NoExecute
key: node.kubernetes.io/unreachable
operator: Exists
tolerationSeconds: 300
- effect: NoSchedule
key: node.kubernetes.io/memory-pressure
operator: Exists
volumes:
- emptyDir: {}
name: model-mount-0
- name: kube-api-access-wjf8j
projected:
defaultMode: 420
sources:
- serviceAccountToken:
expirationSeconds: 3607
path: token
- configMap:
items:
- key: ca.crt
path: ca.crt
name: kube-root-ca.crt
- downwardAPI:
items:
- fieldRef:
apiVersion: v1
fieldPath: metadata.namespace
path: namespace
- name: identity-secret-volume
secret:
defaultMode: 420
items:
- key: identityStore
path: identity_secret.json
- key: token
path: sidecar_token
- key: ca
path: ca.crt
secretName: deployname-134205-model-name-sidecar
status:
conditions:
- lastProbeTime: null
lastTransitionTime: "2023-04-19T04:06:16Z"
status: "True"
type: Initialized
- lastProbeTime: null
lastTransitionTime: "2023-04-19T04:06:41Z"
status: "True"
type: Ready
- lastProbeTime: null
lastTransitionTime: "2023-04-19T04:06:41Z"
status: "True"
type: ContainersReady
- lastProbeTime: null
lastTransitionTime: "2023-04-19T04:06:00Z"
status: "True"
type: PodScheduled
containerStatuses:
- containerID: containerd://c6cc35cc482f7bdab5a6a5c1e5a2fb46ac14e82eac9a4e2684626cc05e175139
image: mcr.microsoft.com/azureml/amlarc/docker/identity-sidecar:1.1.25
imageID: mcr.microsoft.com/azureml/amlarc/docker/identity-sidecar@sha256:2aaae7af6e0bd3e5847c55feca123cf50d968fee52616f7e412b0a76b51ce035
lastState: {}
name: identity-sidecar
ready: true
restartCount: 0
started: true
state:
running:
startedAt: "2023-04-19T04:06:16Z"
- containerID: containerd://8dc55c77556ee15f64321dd0c2967eef6002fdbbb92eccf1c0c9d76fc168f5a9
image: registry.azurecr.io/image/path:v3.6.2
imageID: registry.azurecr.io/image/path@sha256:8736a082e2f7698e6c6e5a055e9a17585d15bac3f57b833d889977d5dd2142e3
lastState: {}
name: inference-server
ready: true
restartCount: 0
started: true
state:
running:
startedAt: "2023-04-19T04:06:16Z"
hostIP: 10.224.0.4
initContainerStatuses:
- containerID: containerd://4bfced7cb46a4f6e855cd613dbe87f54d226bff8871f6a3295b76dd49b116afb
image: mcr.microsoft.com/mir/mir-storageinitializer:46571814.1631244300887
imageID: mcr.microsoft.com/mir/mir-storageinitializer@sha256:c5dc758e64d7cf4a571c3877f9195eabd97e752f23ab01965e7c40abac95b83e
lastState: {}
name: storageinitializer-modeldata
ready: true
restartCount: 0
state:
terminated:
containerID: containerd://4bfced7cb46a4f6e855cd613dbe87f54d226bff8871f6a3295b76dd49b116afb
exitCode: 0
finishedAt: "2023-04-19T04:06:16Z"
reason: Completed
startedAt: "2023-04-19T04:06:01Z"
phase: Running
podIP: 10.244.0.17
podIPs:
- ip: 10.244.0.17
qosClass: Burstable
startTime: "2023-04-19T04:06:00Z"
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