使用 Karpenter 自動擴展來建立和設定 HyperPod 叢集

載入您的環境組態，並從 CloudFormation 堆疊中擷取值。

source .env
SUBNET1=$(cfn-output $VPC_STACK_NAME PrivateSubnet1)
SUBNET2=$(cfn-output $VPC_STACK_NAME PrivateSubnet2)
SUBNET3=$(cfn-output $VPC_STACK_NAME PrivateSubnet3)
SECURITY_GROUP=$(cfn-output $VPC_STACK_NAME NoIngressSecurityGroup)
EKS_CLUSTER_ARN=$(cfn-output $EKS_STACK_NAME ClusterArn)
EXECUTION_ROLE=$(cfn-output $SAGEMAKER_STACK_NAME ExecutionRole)
SERVICE_ROLE=$(cfn-output $SAGEMAKER_STACK_NAME ServiceRole)
BUCKET_NAME=$(cfn-output $SAGEMAKER_STACK_NAME Bucket)
HP_CLUSTER_NAME="hyperpod-eks-test-$(date +%s)"
EKS_CLUSTER_NAME=$(cfn-output $EKS_STACK_NAME ClusterName)
HP_CLUSTER_ROLE=$(cfn-output $SAGEMAKER_STACK_NAME ClusterRole)

將節點初始化指令碼上傳至您的 Amazon S3 儲存貯體。

aws s3 cp lifecyclescripts/on_create_noop.sh s3://$BUCKET_NAME

使用您的環境變數建立叢集組態檔案。

cat > cluster_config.json << EOF
{
    "ClusterName": "$HP_CLUSTER_NAME",
    "InstanceGroups": [
        {
            "InstanceCount": 1,
            "InstanceGroupName": "system",
            "InstanceType": "ml.c5.xlarge",
            "LifeCycleConfig": {
                "SourceS3Uri": "s3://$BUCKET_NAME",
                "OnCreate": "on_create_noop.sh"
            },
            "ExecutionRole": "$EXECUTION_ROLE"
        },
        {
            "InstanceCount": 0,
            "InstanceGroupName": "auto-c5-az1",
            "InstanceType": "ml.c5.xlarge",
            "LifeCycleConfig": {
                "SourceS3Uri": "s3://$BUCKET_NAME",
                "OnCreate": "on_create_noop.sh"
            },
            "ExecutionRole": "$EXECUTION_ROLE"
        },
        {
            "InstanceCount": 0,
            "InstanceGroupName": "auto-c5-4xaz2",
            "InstanceType": "ml.c5.4xlarge",
            "LifeCycleConfig": {
                "SourceS3Uri": "s3://$BUCKET_NAME",
                "OnCreate": "on_create_noop.sh"
            },
            "ExecutionRole": "$EXECUTION_ROLE",
            "OverrideVpcConfig": {
                "SecurityGroupIds": [
                    "$SECURITY_GROUP"
                ],
                "Subnets": [
                    "$SUBNET2"
                ]
            }
        },
        {
            "InstanceCount": 0,
            "InstanceGroupName": "auto-g5-az3",
            "InstanceType": "ml.g5.xlarge",
            "LifeCycleConfig": {
                "SourceS3Uri": "s3://$BUCKET_NAME",
                "OnCreate": "on_create_noop.sh"
            },
            "ExecutionRole": "$EXECUTION_ROLE",
            "OverrideVpcConfig": {
                "SecurityGroupIds": [
                    "$SECURITY_GROUP"
                ],
                "Subnets": [
                    "$SUBNET3"
                ]
            }
        }
    ],
    "VpcConfig": {
        "SecurityGroupIds": [
            "$SECURITY_GROUP"
        ],
        "Subnets": [
            "$SUBNET1"
        ]
    },
    "Orchestrator": {
        "Eks": {
            "ClusterArn": "$EKS_CLUSTER_ARN"
        }
    },
    "ClusterRole": "$HP_CLUSTER_ROLE",
    "AutoScaling": {
        "Mode": "Enable",
        "AutoScalerType": "Karpenter"
    },
    "NodeProvisioningMode": "Continuous"
}
EOF

執行下列命令以建立您的 HyperPod 叢集。

aws sagemaker create-cluster --cli-input-json file://./cluster_config.json

叢集建立程序約需 20 分鐘的時間。監控叢集狀態，直到 ClusterStatus 和 AutoScaling.Status 都顯示 InService。

儲存叢集 ARN 以進行後續操作。

HP_CLUSTER_ARN=$(aws sagemaker describe-cluster --cluster-name $HP_CLUSTER_NAME \
   --output text --query ClusterArn)

執行下列命令，在具有連續節點佈建模式的任何預先存在叢集上啟用 Karpenter 型自動擴展。

aws sagemaker update-cluster \
    --cluster-name $HP_CLUSTER_NAME \
    --auto-scaling Mode=Enable,AutoScalerType=Karpenter \
    --cluster-role $HP_CLUSTER_ROLE

驗證是否已成功啟用 Karpenter：

aws sagemaker describe-cluster --cluster-name $HP_CLUSTER_NAME --query 'AutoScaling'

預期的輸出結果：

{
    "Mode": "Enable",
    "AutoScalerType": "Karpenter",
    "Status": "InService"
}