AiDeploymentResourcePool

class AiDeploymentResourcePool : KotlinCustomResource

'DeploymentResourcePool can be shared by multiple deployed models, whose underlying specification consists of dedicated resources.' To get more information about DeploymentResourcePool, see:

Example Usage

Vertex Ai Deployment Resource Pool

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";
const deploymentResourcePool = new gcp.vertex.AiDeploymentResourcePool("deployment_resource_pool", {
region: "us-central1",
name: "example-deployment-resource-pool",
dedicatedResources: {
machineSpec: {
machineType: "n1-standard-4",
acceleratorType: "NVIDIA_TESLA_K80",
acceleratorCount: 1,
},
minReplicaCount: 1,
maxReplicaCount: 2,
autoscalingMetricSpecs: [{
metricName: "aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle",
target: 60,
}],
},
});
import pulumi
import pulumi_gcp as gcp
deployment_resource_pool = gcp.vertex.AiDeploymentResourcePool("deployment_resource_pool",
region="us-central1",
name="example-deployment-resource-pool",
dedicated_resources={
"machine_spec": {
"machine_type": "n1-standard-4",
"accelerator_type": "NVIDIA_TESLA_K80",
"accelerator_count": 1,
},
"min_replica_count": 1,
"max_replica_count": 2,
"autoscaling_metric_specs": [{
"metric_name": "aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle",
"target": 60,
}],
})
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;
return await Deployment.RunAsync(() =>
{
var deploymentResourcePool = new Gcp.Vertex.AiDeploymentResourcePool("deployment_resource_pool", new()
{
Region = "us-central1",
Name = "example-deployment-resource-pool",
DedicatedResources = new Gcp.Vertex.Inputs.AiDeploymentResourcePoolDedicatedResourcesArgs
{
MachineSpec = new Gcp.Vertex.Inputs.AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs
{
MachineType = "n1-standard-4",
AcceleratorType = "NVIDIA_TESLA_K80",
AcceleratorCount = 1,
},
MinReplicaCount = 1,
MaxReplicaCount = 2,
AutoscalingMetricSpecs = new[]
{
new Gcp.Vertex.Inputs.AiDeploymentResourcePoolDedicatedResourcesAutoscalingMetricSpecArgs
{
MetricName = "aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle",
Target = 60,
},
},
},
});
});
package main
import (
"github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/vertex"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := vertex.NewAiDeploymentResourcePool(ctx, "deployment_resource_pool", &vertex.AiDeploymentResourcePoolArgs{
Region: pulumi.String("us-central1"),
Name: pulumi.String("example-deployment-resource-pool"),
DedicatedResources: &vertex.AiDeploymentResourcePoolDedicatedResourcesArgs{
MachineSpec: &vertex.AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs{
MachineType: pulumi.String("n1-standard-4"),
AcceleratorType: pulumi.String("NVIDIA_TESLA_K80"),
AcceleratorCount: pulumi.Int(1),
},
MinReplicaCount: pulumi.Int(1),
MaxReplicaCount: pulumi.Int(2),
AutoscalingMetricSpecs: vertex.AiDeploymentResourcePoolDedicatedResourcesAutoscalingMetricSpecArray{
&vertex.AiDeploymentResourcePoolDedicatedResourcesAutoscalingMetricSpecArgs{
MetricName: pulumi.String("aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle"),
Target: pulumi.Int(60),
},
},
},
})
if err != nil {
return err
}
return nil
})
}
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiDeploymentResourcePool;
import com.pulumi.gcp.vertex.AiDeploymentResourcePoolArgs;
import com.pulumi.gcp.vertex.inputs.AiDeploymentResourcePoolDedicatedResourcesArgs;
import com.pulumi.gcp.vertex.inputs.AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var deploymentResourcePool = new AiDeploymentResourcePool("deploymentResourcePool", AiDeploymentResourcePoolArgs.builder()
.region("us-central1")
.name("example-deployment-resource-pool")
.dedicatedResources(AiDeploymentResourcePoolDedicatedResourcesArgs.builder()
.machineSpec(AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs.builder()
.machineType("n1-standard-4")
.acceleratorType("NVIDIA_TESLA_K80")
.acceleratorCount(1)
.build())
.minReplicaCount(1)
.maxReplicaCount(2)
.autoscalingMetricSpecs(AiDeploymentResourcePoolDedicatedResourcesAutoscalingMetricSpecArgs.builder()
.metricName("aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle")
.target(60)
.build())
.build())
.build());
}
}
resources:
deploymentResourcePool:
type: gcp:vertex:AiDeploymentResourcePool
name: deployment_resource_pool
properties:
region: us-central1
name: example-deployment-resource-pool
dedicatedResources:
machineSpec:
machineType: n1-standard-4
acceleratorType: NVIDIA_TESLA_K80
acceleratorCount: 1
minReplicaCount: 1
maxReplicaCount: 2
autoscalingMetricSpecs:
- metricName: aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle
target: 60

Import

DeploymentResourcePool can be imported using any of these accepted formats:

  • projects/{{project}}/locations/{{region}}/deploymentResourcePools/{{name}}

  • {{project}}/{{region}}/{{name}}

  • {{region}}/{{name}}

  • {{name}} When using the pulumi import command, DeploymentResourcePool can be imported using one of the formats above. For example:

$ pulumi import gcp:vertex/aiDeploymentResourcePool:AiDeploymentResourcePool default projects/{{project}}/locations/{{region}}/deploymentResourcePools/{{name}}
$ pulumi import gcp:vertex/aiDeploymentResourcePool:AiDeploymentResourcePool default {{project}}/{{region}}/{{name}}
$ pulumi import gcp:vertex/aiDeploymentResourcePool:AiDeploymentResourcePool default {{region}}/{{name}}
$ pulumi import gcp:vertex/aiDeploymentResourcePool:AiDeploymentResourcePool default {{name}}

Properties

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val createTime: Output<String>

A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

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The underlying dedicated resources that the deployment resource pool uses. Structure is documented below.

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val id: Output<String>
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val name: Output<String>

The resource name of deployment resource pool. The maximum length is 63 characters, and valid characters are /^a-z?$/.

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val project: Output<String>

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

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val pulumiChildResources: Set<KotlinResource>
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val region: Output<String>?

The region of deployment resource pool. eg us-central1

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val urn: Output<String>