Google Cloud Classic v6.66.0, Sep 18 23

Google Cloud Classic v6.66.0 published on Monday, Sep 18, 2023 by Pulumi

gcp.compute.Autoscaler

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Google Cloud Classic v6.66.0 published on Monday, Sep 18, 2023 by Pulumi

pulumi/pulumi-gcp

Example Usage

Autoscaler Single Instance

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var debian9 = Gcp.Compute.GetImage.Invoke(new()
    {
        Family = "debian-11",
        Project = "debian-cloud",
    });

    var defaultInstanceTemplate = new Gcp.Compute.InstanceTemplate("defaultInstanceTemplate", new()
    {
        MachineType = "e2-medium",
        CanIpForward = false,
        Tags = new[]
        {
            "foo",
            "bar",
        },
        Disks = new[]
        {
            new Gcp.Compute.Inputs.InstanceTemplateDiskArgs
            {
                SourceImage = debian9.Apply(getImageResult => getImageResult.Id),
            },
        },
        NetworkInterfaces = new[]
        {
            new Gcp.Compute.Inputs.InstanceTemplateNetworkInterfaceArgs
            {
                Network = "default",
            },
        },
        Metadata = 
        {
            { "foo", "bar" },
        },
        ServiceAccount = new Gcp.Compute.Inputs.InstanceTemplateServiceAccountArgs
        {
            Scopes = new[]
            {
                "userinfo-email",
                "compute-ro",
                "storage-ro",
            },
        },
    }, new CustomResourceOptions
    {
        Provider = google_beta,
    });

    var defaultTargetPool = new Gcp.Compute.TargetPool("defaultTargetPool", new()
    {
    }, new CustomResourceOptions
    {
        Provider = google_beta,
    });

    var defaultInstanceGroupManager = new Gcp.Compute.InstanceGroupManager("defaultInstanceGroupManager", new()
    {
        Zone = "us-central1-f",
        Versions = new[]
        {
            new Gcp.Compute.Inputs.InstanceGroupManagerVersionArgs
            {
                InstanceTemplate = defaultInstanceTemplate.Id,
                Name = "primary",
            },
        },
        TargetPools = new[]
        {
            defaultTargetPool.Id,
        },
        BaseInstanceName = "autoscaler-sample",
    }, new CustomResourceOptions
    {
        Provider = google_beta,
    });

    var defaultAutoscaler = new Gcp.Compute.Autoscaler("defaultAutoscaler", new()
    {
        Zone = "us-central1-f",
        Target = defaultInstanceGroupManager.Id,
        AutoscalingPolicy = new Gcp.Compute.Inputs.AutoscalerAutoscalingPolicyArgs
        {
            MaxReplicas = 5,
            MinReplicas = 1,
            CooldownPeriod = 60,
            Metrics = new[]
            {
                new Gcp.Compute.Inputs.AutoscalerAutoscalingPolicyMetricArgs
                {
                    Name = "pubsub.googleapis.com/subscription/num_undelivered_messages",
                    Filter = "resource.type = pubsub_subscription AND resource.label.subscription_id = our-subscription",
                    SingleInstanceAssignment = 65535,
                },
            },
        },
    }, new CustomResourceOptions
    {
        Provider = google_beta,
    });

});

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v6/go/gcp/compute"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		debian9, err := compute.LookupImage(ctx, &compute.LookupImageArgs{
			Family:  pulumi.StringRef("debian-11"),
			Project: pulumi.StringRef("debian-cloud"),
		}, nil)
		if err != nil {
			return err
		}
		defaultInstanceTemplate, err := compute.NewInstanceTemplate(ctx, "defaultInstanceTemplate", &compute.InstanceTemplateArgs{
			MachineType:  pulumi.String("e2-medium"),
			CanIpForward: pulumi.Bool(false),
			Tags: pulumi.StringArray{
				pulumi.String("foo"),
				pulumi.String("bar"),
			},
			Disks: compute.InstanceTemplateDiskArray{
				&compute.InstanceTemplateDiskArgs{
					SourceImage: *pulumi.String(debian9.Id),
				},
			},
			NetworkInterfaces: compute.InstanceTemplateNetworkInterfaceArray{
				&compute.InstanceTemplateNetworkInterfaceArgs{
					Network: pulumi.String("default"),
				},
			},
			Metadata: pulumi.AnyMap{
				"foo": pulumi.Any("bar"),
			},
			ServiceAccount: &compute.InstanceTemplateServiceAccountArgs{
				Scopes: pulumi.StringArray{
					pulumi.String("userinfo-email"),
					pulumi.String("compute-ro"),
					pulumi.String("storage-ro"),
				},
			},
		}, pulumi.Provider(google_beta))
		if err != nil {
			return err
		}
		defaultTargetPool, err := compute.NewTargetPool(ctx, "defaultTargetPool", nil, pulumi.Provider(google_beta))
		if err != nil {
			return err
		}
		defaultInstanceGroupManager, err := compute.NewInstanceGroupManager(ctx, "defaultInstanceGroupManager", &compute.InstanceGroupManagerArgs{
			Zone: pulumi.String("us-central1-f"),
			Versions: compute.InstanceGroupManagerVersionArray{
				&compute.InstanceGroupManagerVersionArgs{
					InstanceTemplate: defaultInstanceTemplate.ID(),
					Name:             pulumi.String("primary"),
				},
			},
			TargetPools: pulumi.StringArray{
				defaultTargetPool.ID(),
			},
			BaseInstanceName: pulumi.String("autoscaler-sample"),
		}, pulumi.Provider(google_beta))
		if err != nil {
			return err
		}
		_, err = compute.NewAutoscaler(ctx, "defaultAutoscaler", &compute.AutoscalerArgs{
			Zone:   pulumi.String("us-central1-f"),
			Target: defaultInstanceGroupManager.ID(),
			AutoscalingPolicy: &compute.AutoscalerAutoscalingPolicyArgs{
				MaxReplicas:    pulumi.Int(5),
				MinReplicas:    pulumi.Int(1),
				CooldownPeriod: pulumi.Int(60),
				Metrics: compute.AutoscalerAutoscalingPolicyMetricArray{
					&compute.AutoscalerAutoscalingPolicyMetricArgs{
						Name:                     pulumi.String("pubsub.googleapis.com/subscription/num_undelivered_messages"),
						Filter:                   pulumi.String("resource.type = pubsub_subscription AND resource.label.subscription_id = our-subscription"),
						SingleInstanceAssignment: pulumi.Float64(65535),
					},
				},
			},
		}, pulumi.Provider(google_beta))
		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.compute.ComputeFunctions;
import com.pulumi.gcp.compute.inputs.GetImageArgs;
import com.pulumi.gcp.compute.InstanceTemplate;
import com.pulumi.gcp.compute.InstanceTemplateArgs;
import com.pulumi.gcp.compute.inputs.InstanceTemplateDiskArgs;
import com.pulumi.gcp.compute.inputs.InstanceTemplateNetworkInterfaceArgs;
import com.pulumi.gcp.compute.inputs.InstanceTemplateServiceAccountArgs;
import com.pulumi.gcp.compute.TargetPool;
import com.pulumi.gcp.compute.TargetPoolArgs;
import com.pulumi.gcp.compute.InstanceGroupManager;
import com.pulumi.gcp.compute.InstanceGroupManagerArgs;
import com.pulumi.gcp.compute.inputs.InstanceGroupManagerVersionArgs;
import com.pulumi.gcp.compute.Autoscaler;
import com.pulumi.gcp.compute.AutoscalerArgs;
import com.pulumi.gcp.compute.inputs.AutoscalerAutoscalingPolicyArgs;
import com.pulumi.resources.CustomResourceOptions;
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) {
        final var debian9 = ComputeFunctions.getImage(GetImageArgs.builder()
            .family("debian-11")
            .project("debian-cloud")
            .build());

        var defaultInstanceTemplate = new InstanceTemplate("defaultInstanceTemplate", InstanceTemplateArgs.builder()        
            .machineType("e2-medium")
            .canIpForward(false)
            .tags(            
                "foo",
                "bar")
            .disks(InstanceTemplateDiskArgs.builder()
                .sourceImage(debian9.applyValue(getImageResult -> getImageResult.id()))
                .build())
            .networkInterfaces(InstanceTemplateNetworkInterfaceArgs.builder()
                .network("default")
                .build())
            .metadata(Map.of("foo", "bar"))
            .serviceAccount(InstanceTemplateServiceAccountArgs.builder()
                .scopes(                
                    "userinfo-email",
                    "compute-ro",
                    "storage-ro")
                .build())
            .build(), CustomResourceOptions.builder()
                .provider(google_beta)
                .build());

        var defaultTargetPool = new TargetPool("defaultTargetPool", TargetPoolArgs.Empty, CustomResourceOptions.builder()
            .provider(google_beta)
            .build());

        var defaultInstanceGroupManager = new InstanceGroupManager("defaultInstanceGroupManager", InstanceGroupManagerArgs.builder()        
            .zone("us-central1-f")
            .versions(InstanceGroupManagerVersionArgs.builder()
                .instanceTemplate(defaultInstanceTemplate.id())
                .name("primary")
                .build())
            .targetPools(defaultTargetPool.id())
            .baseInstanceName("autoscaler-sample")
            .build(), CustomResourceOptions.builder()
                .provider(google_beta)
                .build());

        var defaultAutoscaler = new Autoscaler("defaultAutoscaler", AutoscalerArgs.builder()        
            .zone("us-central1-f")
            .target(defaultInstanceGroupManager.id())
            .autoscalingPolicy(AutoscalerAutoscalingPolicyArgs.builder()
                .maxReplicas(5)
                .minReplicas(1)
                .cooldownPeriod(60)
                .metrics(AutoscalerAutoscalingPolicyMetricArgs.builder()
                    .name("pubsub.googleapis.com/subscription/num_undelivered_messages")
                    .filter("resource.type = pubsub_subscription AND resource.label.subscription_id = our-subscription")
                    .singleInstanceAssignment(65535)
                    .build())
                .build())
            .build(), CustomResourceOptions.builder()
                .provider(google_beta)
                .build());

    }
}

import pulumi
import pulumi_gcp as gcp

debian9 = gcp.compute.get_image(family="debian-11",
    project="debian-cloud")
default_instance_template = gcp.compute.InstanceTemplate("defaultInstanceTemplate",
    machine_type="e2-medium",
    can_ip_forward=False,
    tags=[
        "foo",
        "bar",
    ],
    disks=[gcp.compute.InstanceTemplateDiskArgs(
        source_image=debian9.id,
    )],
    network_interfaces=[gcp.compute.InstanceTemplateNetworkInterfaceArgs(
        network="default",
    )],
    metadata={
        "foo": "bar",
    },
    service_account=gcp.compute.InstanceTemplateServiceAccountArgs(
        scopes=[
            "userinfo-email",
            "compute-ro",
            "storage-ro",
        ],
    ),
    opts=pulumi.ResourceOptions(provider=google_beta))
default_target_pool = gcp.compute.TargetPool("defaultTargetPool", opts=pulumi.ResourceOptions(provider=google_beta))
default_instance_group_manager = gcp.compute.InstanceGroupManager("defaultInstanceGroupManager",
    zone="us-central1-f",
    versions=[gcp.compute.InstanceGroupManagerVersionArgs(
        instance_template=default_instance_template.id,
        name="primary",
    )],
    target_pools=[default_target_pool.id],
    base_instance_name="autoscaler-sample",
    opts=pulumi.ResourceOptions(provider=google_beta))
default_autoscaler = gcp.compute.Autoscaler("defaultAutoscaler",
    zone="us-central1-f",
    target=default_instance_group_manager.id,
    autoscaling_policy=gcp.compute.AutoscalerAutoscalingPolicyArgs(
        max_replicas=5,
        min_replicas=1,
        cooldown_period=60,
        metrics=[gcp.compute.AutoscalerAutoscalingPolicyMetricArgs(
            name="pubsub.googleapis.com/subscription/num_undelivered_messages",
            filter="resource.type = pubsub_subscription AND resource.label.subscription_id = our-subscription",
            single_instance_assignment=65535,
        )],
    ),
    opts=pulumi.ResourceOptions(provider=google_beta))

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const debian9 = gcp.compute.getImage({
    family: "debian-11",
    project: "debian-cloud",
});
const defaultInstanceTemplate = new gcp.compute.InstanceTemplate("defaultInstanceTemplate", {
    machineType: "e2-medium",
    canIpForward: false,
    tags: [
        "foo",
        "bar",
    ],
    disks: [{
        sourceImage: debian9.then(debian9 => debian9.id),
    }],
    networkInterfaces: [{
        network: "default",
    }],
    metadata: {
        foo: "bar",
    },
    serviceAccount: {
        scopes: [
            "userinfo-email",
            "compute-ro",
            "storage-ro",
        ],
    },
}, {
    provider: google_beta,
});
const defaultTargetPool = new gcp.compute.TargetPool("defaultTargetPool", {}, {
    provider: google_beta,
});
const defaultInstanceGroupManager = new gcp.compute.InstanceGroupManager("defaultInstanceGroupManager", {
    zone: "us-central1-f",
    versions: [{
        instanceTemplate: defaultInstanceTemplate.id,
        name: "primary",
    }],
    targetPools: [defaultTargetPool.id],
    baseInstanceName: "autoscaler-sample",
}, {
    provider: google_beta,
});
const defaultAutoscaler = new gcp.compute.Autoscaler("defaultAutoscaler", {
    zone: "us-central1-f",
    target: defaultInstanceGroupManager.id,
    autoscalingPolicy: {
        maxReplicas: 5,
        minReplicas: 1,
        cooldownPeriod: 60,
        metrics: [{
            name: "pubsub.googleapis.com/subscription/num_undelivered_messages",
            filter: "resource.type = pubsub_subscription AND resource.label.subscription_id = our-subscription",
            singleInstanceAssignment: 65535,
        }],
    },
}, {
    provider: google_beta,
});

resources:
  defaultAutoscaler:
    type: gcp:compute:Autoscaler
    properties:
      zone: us-central1-f
      target: ${defaultInstanceGroupManager.id}
      autoscalingPolicy:
        maxReplicas: 5
        minReplicas: 1
        cooldownPeriod: 60
        metrics:
          - name: pubsub.googleapis.com/subscription/num_undelivered_messages
            filter: resource.type = pubsub_subscription AND resource.label.subscription_id = our-subscription
            singleInstanceAssignment: 65535
    options:
      provider: ${["google-beta"]}
  defaultInstanceTemplate:
    type: gcp:compute:InstanceTemplate
    properties:
      machineType: e2-medium
      canIpForward: false
      tags:
        - foo
        - bar
      disks:
        - sourceImage: ${debian9.id}
      networkInterfaces:
        - network: default
      metadata:
        foo: bar
      serviceAccount:
        scopes:
          - userinfo-email
          - compute-ro
          - storage-ro
    options:
      provider: ${["google-beta"]}
  defaultTargetPool:
    type: gcp:compute:TargetPool
    options:
      provider: ${["google-beta"]}
  defaultInstanceGroupManager:
    type: gcp:compute:InstanceGroupManager
    properties:
      zone: us-central1-f
      versions:
        - instanceTemplate: ${defaultInstanceTemplate.id}
          name: primary
      targetPools:
        - ${defaultTargetPool.id}
      baseInstanceName: autoscaler-sample
    options:
      provider: ${["google-beta"]}
variables:
  debian9:
    fn::invoke:
      Function: gcp:compute:getImage
      Arguments:
        family: debian-11
        project: debian-cloud

Autoscaler Basic

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var debian9 = Gcp.Compute.GetImage.Invoke(new()
    {
        Family = "debian-11",
        Project = "debian-cloud",
    });

    var foobarInstanceTemplate = new Gcp.Compute.InstanceTemplate("foobarInstanceTemplate", new()
    {
        MachineType = "e2-medium",
        CanIpForward = false,
        Tags = new[]
        {
            "foo",
            "bar",
        },
        Disks = new[]
        {
            new Gcp.Compute.Inputs.InstanceTemplateDiskArgs
            {
                SourceImage = debian9.Apply(getImageResult => getImageResult.Id),
            },
        },
        NetworkInterfaces = new[]
        {
            new Gcp.Compute.Inputs.InstanceTemplateNetworkInterfaceArgs
            {
                Network = "default",
            },
        },
        Metadata = 
        {
            { "foo", "bar" },
        },
        ServiceAccount = new Gcp.Compute.Inputs.InstanceTemplateServiceAccountArgs
        {
            Scopes = new[]
            {
                "userinfo-email",
                "compute-ro",
                "storage-ro",
            },
        },
    });

    var foobarTargetPool = new Gcp.Compute.TargetPool("foobarTargetPool");

    var foobarInstanceGroupManager = new Gcp.Compute.InstanceGroupManager("foobarInstanceGroupManager", new()
    {
        Zone = "us-central1-f",
        Versions = new[]
        {
            new Gcp.Compute.Inputs.InstanceGroupManagerVersionArgs
            {
                InstanceTemplate = foobarInstanceTemplate.Id,
                Name = "primary",
            },
        },
        TargetPools = new[]
        {
            foobarTargetPool.Id,
        },
        BaseInstanceName = "foobar",
    });

    var foobarAutoscaler = new Gcp.Compute.Autoscaler("foobarAutoscaler", new()
    {
        Zone = "us-central1-f",
        Target = foobarInstanceGroupManager.Id,
        AutoscalingPolicy = new Gcp.Compute.Inputs.AutoscalerAutoscalingPolicyArgs
        {
            MaxReplicas = 5,
            MinReplicas = 1,
            CooldownPeriod = 60,
            CpuUtilization = new Gcp.Compute.Inputs.AutoscalerAutoscalingPolicyCpuUtilizationArgs
            {
                Target = 0.5,
            },
        },
    });

});

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v6/go/gcp/compute"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		debian9, err := compute.LookupImage(ctx, &compute.LookupImageArgs{
			Family:  pulumi.StringRef("debian-11"),
			Project: pulumi.StringRef("debian-cloud"),
		}, nil)
		if err != nil {
			return err
		}
		foobarInstanceTemplate, err := compute.NewInstanceTemplate(ctx, "foobarInstanceTemplate", &compute.InstanceTemplateArgs{
			MachineType:  pulumi.String("e2-medium"),
			CanIpForward: pulumi.Bool(false),
			Tags: pulumi.StringArray{
				pulumi.String("foo"),
				pulumi.String("bar"),
			},
			Disks: compute.InstanceTemplateDiskArray{
				&compute.InstanceTemplateDiskArgs{
					SourceImage: *pulumi.String(debian9.Id),
				},
			},
			NetworkInterfaces: compute.InstanceTemplateNetworkInterfaceArray{
				&compute.InstanceTemplateNetworkInterfaceArgs{
					Network: pulumi.String("default"),
				},
			},
			Metadata: pulumi.AnyMap{
				"foo": pulumi.Any("bar"),
			},
			ServiceAccount: &compute.InstanceTemplateServiceAccountArgs{
				Scopes: pulumi.StringArray{
					pulumi.String("userinfo-email"),
					pulumi.String("compute-ro"),
					pulumi.String("storage-ro"),
				},
			},
		})
		if err != nil {
			return err
		}
		foobarTargetPool, err := compute.NewTargetPool(ctx, "foobarTargetPool", nil)
		if err != nil {
			return err
		}
		foobarInstanceGroupManager, err := compute.NewInstanceGroupManager(ctx, "foobarInstanceGroupManager", &compute.InstanceGroupManagerArgs{
			Zone: pulumi.String("us-central1-f"),
			Versions: compute.InstanceGroupManagerVersionArray{
				&compute.InstanceGroupManagerVersionArgs{
					InstanceTemplate: foobarInstanceTemplate.ID(),
					Name:             pulumi.String("primary"),
				},
			},
			TargetPools: pulumi.StringArray{
				foobarTargetPool.ID(),
			},
			BaseInstanceName: pulumi.String("foobar"),
		})
		if err != nil {
			return err
		}
		_, err = compute.NewAutoscaler(ctx, "foobarAutoscaler", &compute.AutoscalerArgs{
			Zone:   pulumi.String("us-central1-f"),
			Target: foobarInstanceGroupManager.ID(),
			AutoscalingPolicy: &compute.AutoscalerAutoscalingPolicyArgs{
				MaxReplicas:    pulumi.Int(5),
				MinReplicas:    pulumi.Int(1),
				CooldownPeriod: pulumi.Int(60),
				CpuUtilization: &compute.AutoscalerAutoscalingPolicyCpuUtilizationArgs{
					Target: pulumi.Float64(0.5),
				},
			},
		})
		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.compute.ComputeFunctions;
import com.pulumi.gcp.compute.inputs.GetImageArgs;
import com.pulumi.gcp.compute.InstanceTemplate;
import com.pulumi.gcp.compute.InstanceTemplateArgs;
import com.pulumi.gcp.compute.inputs.InstanceTemplateDiskArgs;
import com.pulumi.gcp.compute.inputs.InstanceTemplateNetworkInterfaceArgs;
import com.pulumi.gcp.compute.inputs.InstanceTemplateServiceAccountArgs;
import com.pulumi.gcp.compute.TargetPool;
import com.pulumi.gcp.compute.InstanceGroupManager;
import com.pulumi.gcp.compute.InstanceGroupManagerArgs;
import com.pulumi.gcp.compute.inputs.InstanceGroupManagerVersionArgs;
import com.pulumi.gcp.compute.Autoscaler;
import com.pulumi.gcp.compute.AutoscalerArgs;
import com.pulumi.gcp.compute.inputs.AutoscalerAutoscalingPolicyArgs;
import com.pulumi.gcp.compute.inputs.AutoscalerAutoscalingPolicyCpuUtilizationArgs;
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) {
        final var debian9 = ComputeFunctions.getImage(GetImageArgs.builder()
            .family("debian-11")
            .project("debian-cloud")
            .build());

        var foobarInstanceTemplate = new InstanceTemplate("foobarInstanceTemplate", InstanceTemplateArgs.builder()        
            .machineType("e2-medium")
            .canIpForward(false)
            .tags(            
                "foo",
                "bar")
            .disks(InstanceTemplateDiskArgs.builder()
                .sourceImage(debian9.applyValue(getImageResult -> getImageResult.id()))
                .build())
            .networkInterfaces(InstanceTemplateNetworkInterfaceArgs.builder()
                .network("default")
                .build())
            .metadata(Map.of("foo", "bar"))
            .serviceAccount(InstanceTemplateServiceAccountArgs.builder()
                .scopes(                
                    "userinfo-email",
                    "compute-ro",
                    "storage-ro")
                .build())
            .build());

        var foobarTargetPool = new TargetPool("foobarTargetPool");

        var foobarInstanceGroupManager = new InstanceGroupManager("foobarInstanceGroupManager", InstanceGroupManagerArgs.builder()        
            .zone("us-central1-f")
            .versions(InstanceGroupManagerVersionArgs.builder()
                .instanceTemplate(foobarInstanceTemplate.id())
                .name("primary")
                .build())
            .targetPools(foobarTargetPool.id())
            .baseInstanceName("foobar")
            .build());

        var foobarAutoscaler = new Autoscaler("foobarAutoscaler", AutoscalerArgs.builder()        
            .zone("us-central1-f")
            .target(foobarInstanceGroupManager.id())
            .autoscalingPolicy(AutoscalerAutoscalingPolicyArgs.builder()
                .maxReplicas(5)
                .minReplicas(1)
                .cooldownPeriod(60)
                .cpuUtilization(AutoscalerAutoscalingPolicyCpuUtilizationArgs.builder()
                    .target(0.5)
                    .build())
                .build())
            .build());

    }
}

import pulumi
import pulumi_gcp as gcp

debian9 = gcp.compute.get_image(family="debian-11",
    project="debian-cloud")
foobar_instance_template = gcp.compute.InstanceTemplate("foobarInstanceTemplate",
    machine_type="e2-medium",
    can_ip_forward=False,
    tags=[
        "foo",
        "bar",
    ],
    disks=[gcp.compute.InstanceTemplateDiskArgs(
        source_image=debian9.id,
    )],
    network_interfaces=[gcp.compute.InstanceTemplateNetworkInterfaceArgs(
        network="default",
    )],
    metadata={
        "foo": "bar",
    },
    service_account=gcp.compute.InstanceTemplateServiceAccountArgs(
        scopes=[
            "userinfo-email",
            "compute-ro",
            "storage-ro",
        ],
    ))
foobar_target_pool = gcp.compute.TargetPool("foobarTargetPool")
foobar_instance_group_manager = gcp.compute.InstanceGroupManager("foobarInstanceGroupManager",
    zone="us-central1-f",
    versions=[gcp.compute.InstanceGroupManagerVersionArgs(
        instance_template=foobar_instance_template.id,
        name="primary",
    )],
    target_pools=[foobar_target_pool.id],
    base_instance_name="foobar")
foobar_autoscaler = gcp.compute.Autoscaler("foobarAutoscaler",
    zone="us-central1-f",
    target=foobar_instance_group_manager.id,
    autoscaling_policy=gcp.compute.AutoscalerAutoscalingPolicyArgs(
        max_replicas=5,
        min_replicas=1,
        cooldown_period=60,
        cpu_utilization=gcp.compute.AutoscalerAutoscalingPolicyCpuUtilizationArgs(
            target=0.5,
        ),
    ))

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const debian9 = gcp.compute.getImage({
    family: "debian-11",
    project: "debian-cloud",
});
const foobarInstanceTemplate = new gcp.compute.InstanceTemplate("foobarInstanceTemplate", {
    machineType: "e2-medium",
    canIpForward: false,
    tags: [
        "foo",
        "bar",
    ],
    disks: [{
        sourceImage: debian9.then(debian9 => debian9.id),
    }],
    networkInterfaces: [{
        network: "default",
    }],
    metadata: {
        foo: "bar",
    },
    serviceAccount: {
        scopes: [
            "userinfo-email",
            "compute-ro",
            "storage-ro",
        ],
    },
});
const foobarTargetPool = new gcp.compute.TargetPool("foobarTargetPool", {});
const foobarInstanceGroupManager = new gcp.compute.InstanceGroupManager("foobarInstanceGroupManager", {
    zone: "us-central1-f",
    versions: [{
        instanceTemplate: foobarInstanceTemplate.id,
        name: "primary",
    }],
    targetPools: [foobarTargetPool.id],
    baseInstanceName: "foobar",
});
const foobarAutoscaler = new gcp.compute.Autoscaler("foobarAutoscaler", {
    zone: "us-central1-f",
    target: foobarInstanceGroupManager.id,
    autoscalingPolicy: {
        maxReplicas: 5,
        minReplicas: 1,
        cooldownPeriod: 60,
        cpuUtilization: {
            target: 0.5,
        },
    },
});

resources:
  foobarAutoscaler:
    type: gcp:compute:Autoscaler
    properties:
      zone: us-central1-f
      target: ${foobarInstanceGroupManager.id}
      autoscalingPolicy:
        maxReplicas: 5
        minReplicas: 1
        cooldownPeriod: 60
        cpuUtilization:
          target: 0.5
  foobarInstanceTemplate:
    type: gcp:compute:InstanceTemplate
    properties:
      machineType: e2-medium
      canIpForward: false
      tags:
        - foo
        - bar
      disks:
        - sourceImage: ${debian9.id}
      networkInterfaces:
        - network: default
      metadata:
        foo: bar
      serviceAccount:
        scopes:
          - userinfo-email
          - compute-ro
          - storage-ro
  foobarTargetPool:
    type: gcp:compute:TargetPool
  foobarInstanceGroupManager:
    type: gcp:compute:InstanceGroupManager
    properties:
      zone: us-central1-f
      versions:
        - instanceTemplate: ${foobarInstanceTemplate.id}
          name: primary
      targetPools:
        - ${foobarTargetPool.id}
      baseInstanceName: foobar
variables:
  debian9:
    fn::invoke:
      Function: gcp:compute:getImage
      Arguments:
        family: debian-11
        project: debian-cloud

Create Autoscaler Resource

new Autoscaler(name: string, args: AutoscalerArgs, opts?: CustomResourceOptions);

@overload
def Autoscaler(resource_name: str,
               opts: Optional[ResourceOptions] = None,
               autoscaling_policy: Optional[AutoscalerAutoscalingPolicyArgs] = None,
               description: Optional[str] = None,
               name: Optional[str] = None,
               project: Optional[str] = None,
               target: Optional[str] = None,
               zone: Optional[str] = None)
@overload
def Autoscaler(resource_name: str,
               args: AutoscalerArgs,
               opts: Optional[ResourceOptions] = None)

func NewAutoscaler(ctx *Context, name string, args AutoscalerArgs, opts ...ResourceOption) (*Autoscaler, error)

public Autoscaler(string name, AutoscalerArgs args, CustomResourceOptions? opts = null)

public Autoscaler(String name, AutoscalerArgs args)
public Autoscaler(String name, AutoscalerArgs args, CustomResourceOptions options)

type: gcp:compute:Autoscaler
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

name string: The unique name of the resource.
args AutoscalerArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
args AutoscalerArgs: The arguments to resource properties.
opts ResourceOptions: Bag of options to control resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args AutoscalerArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args AutoscalerArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args AutoscalerArgs: The arguments to resource properties.
options CustomResourceOptions: Bag of options to control resource's behavior.

Autoscaler Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

The Autoscaler resource accepts the following input properties:

AutoscalingPolicy AutoscalerAutoscalingPolicy

The configuration parameters for the autoscaling algorithm. You can define one or more of the policies for an autoscaler: cpuUtilization, customMetricUtilizations, and loadBalancingUtilization. If none of these are specified, the default will be to autoscale based on cpuUtilization to 0.6 or 60%. Structure is documented below.

Target string

URL of the managed instance group that this autoscaler will scale.

Description string

A description of a scaling schedule.

(Optional) An optional description of this resource.

Name string

Name of the resource. The name must be 1-63 characters long and match the regular expression a-z? which means the first character must be a lowercase letter, and all following characters must be a dash, lowercase letter, or digit, except the last character, which cannot be a dash.

Project string

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

Zone string

URL of the zone where the instance group resides.

AutoscalingPolicy AutoscalerAutoscalingPolicyArgs

Target string

URL of the managed instance group that this autoscaler will scale.

Description string

A description of a scaling schedule.

(Optional) An optional description of this resource.

Name string

Project string

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

Zone string

URL of the zone where the instance group resides.

autoscalingPolicy AutoscalerAutoscalingPolicy

target String

URL of the managed instance group that this autoscaler will scale.

description String

A description of a scaling schedule.

(Optional) An optional description of this resource.

name String

project String

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

zone String

URL of the zone where the instance group resides.

autoscalingPolicy AutoscalerAutoscalingPolicy

target string

URL of the managed instance group that this autoscaler will scale.

description string

A description of a scaling schedule.

(Optional) An optional description of this resource.

name string

project string

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

zone string

URL of the zone where the instance group resides.

autoscaling_policy AutoscalerAutoscalingPolicyArgs

target str

URL of the managed instance group that this autoscaler will scale.

description str

A description of a scaling schedule.

(Optional) An optional description of this resource.

name str

project str

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

zone str

URL of the zone where the instance group resides.

autoscalingPolicy Property Map

target String

URL of the managed instance group that this autoscaler will scale.

description String

A description of a scaling schedule.

(Optional) An optional description of this resource.

name String

project String

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

zone String

URL of the zone where the instance group resides.

Outputs

All input properties are implicitly available as output properties. Additionally, the Autoscaler resource produces the following output properties:

CreationTimestamp string: Creation timestamp in RFC3339 text format.
Id string: The provider-assigned unique ID for this managed resource.
SelfLink string: The URI of the created resource.

CreationTimestamp string: Creation timestamp in RFC3339 text format.
Id string: The provider-assigned unique ID for this managed resource.
SelfLink string: The URI of the created resource.

creationTimestamp String: Creation timestamp in RFC3339 text format.
id String: The provider-assigned unique ID for this managed resource.
selfLink String: The URI of the created resource.

creationTimestamp string: Creation timestamp in RFC3339 text format.
id string: The provider-assigned unique ID for this managed resource.
selfLink string: The URI of the created resource.

creation_timestamp str: Creation timestamp in RFC3339 text format.
id str: The provider-assigned unique ID for this managed resource.
self_link str: The URI of the created resource.

creationTimestamp String: Creation timestamp in RFC3339 text format.
id String: The provider-assigned unique ID for this managed resource.
selfLink String: The URI of the created resource.

Look up Existing Autoscaler Resource

Get an existing Autoscaler resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

public static get(name: string, id: Input<ID>, state?: AutoscalerState, opts?: CustomResourceOptions): Autoscaler

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        autoscaling_policy: Optional[AutoscalerAutoscalingPolicyArgs] = None,
        creation_timestamp: Optional[str] = None,
        description: Optional[str] = None,
        name: Optional[str] = None,
        project: Optional[str] = None,
        self_link: Optional[str] = None,
        target: Optional[str] = None,
        zone: Optional[str] = None) -> Autoscaler

func GetAutoscaler(ctx *Context, name string, id IDInput, state *AutoscalerState, opts ...ResourceOption) (*Autoscaler, error)

public static Autoscaler Get(string name, Input<string> id, AutoscalerState? state, CustomResourceOptions? opts = null)

public static Autoscaler get(String name, Output<String> id, AutoscalerState state, CustomResourceOptions options)

Resource lookup is not supported in YAML

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

resource_name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

The following state arguments are supported:

AutoscalingPolicy AutoscalerAutoscalingPolicy

CreationTimestamp string

Creation timestamp in RFC3339 text format.

Description string

A description of a scaling schedule.

(Optional) An optional description of this resource.

Name string

Project string

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

SelfLink string

The URI of the created resource.

Target string

URL of the managed instance group that this autoscaler will scale.

Zone string

URL of the zone where the instance group resides.

AutoscalingPolicy AutoscalerAutoscalingPolicyArgs

CreationTimestamp string

Creation timestamp in RFC3339 text format.

Description string

A description of a scaling schedule.

(Optional) An optional description of this resource.

Name string

Project string

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

SelfLink string

The URI of the created resource.

Target string

URL of the managed instance group that this autoscaler will scale.

Zone string

URL of the zone where the instance group resides.

autoscalingPolicy AutoscalerAutoscalingPolicy

creationTimestamp String

Creation timestamp in RFC3339 text format.

description String

A description of a scaling schedule.

(Optional) An optional description of this resource.

name String

project String

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

selfLink String

The URI of the created resource.

target String

URL of the managed instance group that this autoscaler will scale.

zone String

URL of the zone where the instance group resides.

autoscalingPolicy AutoscalerAutoscalingPolicy

creationTimestamp string

Creation timestamp in RFC3339 text format.

description string

A description of a scaling schedule.

(Optional) An optional description of this resource.

name string

project string

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

selfLink string

The URI of the created resource.

target string

URL of the managed instance group that this autoscaler will scale.

zone string

URL of the zone where the instance group resides.

autoscaling_policy AutoscalerAutoscalingPolicyArgs

creation_timestamp str

Creation timestamp in RFC3339 text format.

description str

A description of a scaling schedule.

(Optional) An optional description of this resource.

name str

project str

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

self_link str

The URI of the created resource.

target str

URL of the managed instance group that this autoscaler will scale.

zone str

URL of the zone where the instance group resides.

autoscalingPolicy Property Map

creationTimestamp String

Creation timestamp in RFC3339 text format.

description String

A description of a scaling schedule.

(Optional) An optional description of this resource.

name String

project String

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

selfLink String

The URI of the created resource.

target String

URL of the managed instance group that this autoscaler will scale.

zone String

URL of the zone where the instance group resides.

Supporting Types

AutoscalerAutoscalingPolicy, AutoscalerAutoscalingPolicyArgs

MaxReplicas int: The maximum number of instances that the autoscaler can scale up to. This is required when creating or updating an autoscaler. The maximum number of replicas should not be lower than minimal number of replicas.
MinReplicas int: The minimum number of replicas that the autoscaler can scale down to. This cannot be less than 0. If not provided, autoscaler will choose a default value depending on maximum number of instances allowed.
CooldownPeriod int: The number of seconds that the autoscaler should wait before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
CpuUtilization AutoscalerAutoscalingPolicyCpuUtilization: Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group. Structure is documented below.
LoadBalancingUtilization AutoscalerAutoscalingPolicyLoadBalancingUtilization: Configuration parameters of autoscaling based on a load balancer. Structure is documented below.
Metrics List<AutoscalerAutoscalingPolicyMetric>: Configuration parameters of autoscaling based on a custom metric. Structure is documented below.
Mode string: Defines operating mode for this policy. Default value is ON. Possible values are: OFF, ONLY_UP, ON.
ScaleDownControl AutoscalerAutoscalingPolicyScaleDownControl: Defines scale down controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
ScaleInControl AutoscalerAutoscalingPolicyScaleInControl: Defines scale in controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
ScalingSchedules List<AutoscalerAutoscalingPolicyScalingSchedule>: Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler and they can overlap. Structure is documented below.

MaxReplicas int: The maximum number of instances that the autoscaler can scale up to. This is required when creating or updating an autoscaler. The maximum number of replicas should not be lower than minimal number of replicas.
MinReplicas int: The minimum number of replicas that the autoscaler can scale down to. This cannot be less than 0. If not provided, autoscaler will choose a default value depending on maximum number of instances allowed.
CooldownPeriod int: The number of seconds that the autoscaler should wait before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
CpuUtilization AutoscalerAutoscalingPolicyCpuUtilization: Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group. Structure is documented below.
LoadBalancingUtilization AutoscalerAutoscalingPolicyLoadBalancingUtilization: Configuration parameters of autoscaling based on a load balancer. Structure is documented below.
Metrics []AutoscalerAutoscalingPolicyMetric: Configuration parameters of autoscaling based on a custom metric. Structure is documented below.
Mode string: Defines operating mode for this policy. Default value is ON. Possible values are: OFF, ONLY_UP, ON.
ScaleDownControl AutoscalerAutoscalingPolicyScaleDownControl: Defines scale down controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
ScaleInControl AutoscalerAutoscalingPolicyScaleInControl: Defines scale in controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
ScalingSchedules []AutoscalerAutoscalingPolicyScalingSchedule: Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler and they can overlap. Structure is documented below.

maxReplicas Integer: The maximum number of instances that the autoscaler can scale up to. This is required when creating or updating an autoscaler. The maximum number of replicas should not be lower than minimal number of replicas.
minReplicas Integer: The minimum number of replicas that the autoscaler can scale down to. This cannot be less than 0. If not provided, autoscaler will choose a default value depending on maximum number of instances allowed.
cooldownPeriod Integer: The number of seconds that the autoscaler should wait before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
cpuUtilization AutoscalerAutoscalingPolicyCpuUtilization: Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group. Structure is documented below.
loadBalancingUtilization AutoscalerAutoscalingPolicyLoadBalancingUtilization: Configuration parameters of autoscaling based on a load balancer. Structure is documented below.
metrics List<AutoscalerAutoscalingPolicyMetric>: Configuration parameters of autoscaling based on a custom metric. Structure is documented below.
mode String: Defines operating mode for this policy. Default value is ON. Possible values are: OFF, ONLY_UP, ON.
scaleDownControl AutoscalerAutoscalingPolicyScaleDownControl: Defines scale down controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
scaleInControl AutoscalerAutoscalingPolicyScaleInControl: Defines scale in controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
scalingSchedules List<AutoscalerAutoscalingPolicyScalingSchedule>: Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler and they can overlap. Structure is documented below.

maxReplicas number: The maximum number of instances that the autoscaler can scale up to. This is required when creating or updating an autoscaler. The maximum number of replicas should not be lower than minimal number of replicas.
minReplicas number: The minimum number of replicas that the autoscaler can scale down to. This cannot be less than 0. If not provided, autoscaler will choose a default value depending on maximum number of instances allowed.
cooldownPeriod number: The number of seconds that the autoscaler should wait before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
cpuUtilization AutoscalerAutoscalingPolicyCpuUtilization: Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group. Structure is documented below.
loadBalancingUtilization AutoscalerAutoscalingPolicyLoadBalancingUtilization: Configuration parameters of autoscaling based on a load balancer. Structure is documented below.
metrics AutoscalerAutoscalingPolicyMetric[]: Configuration parameters of autoscaling based on a custom metric. Structure is documented below.
mode string: Defines operating mode for this policy. Default value is ON. Possible values are: OFF, ONLY_UP, ON.
scaleDownControl AutoscalerAutoscalingPolicyScaleDownControl: Defines scale down controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
scaleInControl AutoscalerAutoscalingPolicyScaleInControl: Defines scale in controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
scalingSchedules AutoscalerAutoscalingPolicyScalingSchedule[]: Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler and they can overlap. Structure is documented below.

max_replicas int: The maximum number of instances that the autoscaler can scale up to. This is required when creating or updating an autoscaler. The maximum number of replicas should not be lower than minimal number of replicas.
min_replicas int: The minimum number of replicas that the autoscaler can scale down to. This cannot be less than 0. If not provided, autoscaler will choose a default value depending on maximum number of instances allowed.
cooldown_period int: The number of seconds that the autoscaler should wait before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
cpu_utilization AutoscalerAutoscalingPolicyCpuUtilization: Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group. Structure is documented below.
load_balancing_utilization AutoscalerAutoscalingPolicyLoadBalancingUtilization: Configuration parameters of autoscaling based on a load balancer. Structure is documented below.
metrics Sequence[AutoscalerAutoscalingPolicyMetric]: Configuration parameters of autoscaling based on a custom metric. Structure is documented below.
mode str: Defines operating mode for this policy. Default value is ON. Possible values are: OFF, ONLY_UP, ON.
scale_down_control AutoscalerAutoscalingPolicyScaleDownControl: Defines scale down controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
scale_in_control AutoscalerAutoscalingPolicyScaleInControl: Defines scale in controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
scaling_schedules Sequence[AutoscalerAutoscalingPolicyScalingSchedule]: Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler and they can overlap. Structure is documented below.

maxReplicas Number: The maximum number of instances that the autoscaler can scale up to. This is required when creating or updating an autoscaler. The maximum number of replicas should not be lower than minimal number of replicas.
minReplicas Number: The minimum number of replicas that the autoscaler can scale down to. This cannot be less than 0. If not provided, autoscaler will choose a default value depending on maximum number of instances allowed.
cooldownPeriod Number: The number of seconds that the autoscaler should wait before it starts collecting information from a new instance. This prevents the autoscaler from collecting information when the instance is initializing, during which the collected usage would not be reliable. The default time autoscaler waits is 60 seconds. Virtual machine initialization times might vary because of numerous factors. We recommend that you test how long an instance may take to initialize. To do this, create an instance and time the startup process.
cpuUtilization Property Map: Defines the CPU utilization policy that allows the autoscaler to scale based on the average CPU utilization of a managed instance group. Structure is documented below.
loadBalancingUtilization Property Map: Configuration parameters of autoscaling based on a load balancer. Structure is documented below.
metrics List<Property Map>: Configuration parameters of autoscaling based on a custom metric. Structure is documented below.
mode String: Defines operating mode for this policy. Default value is ON. Possible values are: OFF, ONLY_UP, ON.
scaleDownControl Property Map: Defines scale down controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
scaleInControl Property Map: Defines scale in controls to reduce the risk of response latency and outages due to abrupt scale-in events Structure is documented below.
scalingSchedules List<Property Map>: Scaling schedules defined for an autoscaler. Multiple schedules can be set on an autoscaler and they can overlap. Structure is documented below.

AutoscalerAutoscalingPolicyCpuUtilization, AutoscalerAutoscalingPolicyCpuUtilizationArgs

Target double

The target CPU utilization that the autoscaler should maintain. Must be a float value in the range (0, 1]. If not specified, the default is 0.6. If the CPU level is below the target utilization, the autoscaler scales down the number of instances until it reaches the minimum number of instances you specified or until the average CPU of your instances reaches the target utilization. If the average CPU is above the target utilization, the autoscaler scales up until it reaches the maximum number of instances you specified or until the average utilization reaches the target utilization.

PredictiveMethod string

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:

NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

Target float64

PredictiveMethod string

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:

NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

target Double

predictiveMethod String

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:

NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

target number

predictiveMethod string

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:

NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

target float

predictive_method str

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:

NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

target Number

predictiveMethod String

Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:

NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.

AutoscalerAutoscalingPolicyLoadBalancingUtilization, AutoscalerAutoscalingPolicyLoadBalancingUtilizationArgs

Target double: Fraction of backend capacity utilization (set in HTTP(s) load balancing configuration) that autoscaler should maintain. Must be a positive float value. If not defined, the default is 0.8.

Target float64: Fraction of backend capacity utilization (set in HTTP(s) load balancing configuration) that autoscaler should maintain. Must be a positive float value. If not defined, the default is 0.8.

target Double: Fraction of backend capacity utilization (set in HTTP(s) load balancing configuration) that autoscaler should maintain. Must be a positive float value. If not defined, the default is 0.8.

target number: Fraction of backend capacity utilization (set in HTTP(s) load balancing configuration) that autoscaler should maintain. Must be a positive float value. If not defined, the default is 0.8.

target float: Fraction of backend capacity utilization (set in HTTP(s) load balancing configuration) that autoscaler should maintain. Must be a positive float value. If not defined, the default is 0.8.

target Number: Fraction of backend capacity utilization (set in HTTP(s) load balancing configuration) that autoscaler should maintain. Must be a positive float value. If not defined, the default is 0.8.

AutoscalerAutoscalingPolicyMetric, AutoscalerAutoscalingPolicyMetricArgs

Name string: The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.
Filter string: A filter string to be used as the filter string for a Stackdriver Monitoring TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. You can only use the AND operator for joining selectors. You can only use direct equality comparison operator (=) without any functions for each selector. You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. You should provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.
SingleInstanceAssignment double: If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. The autoscaler will keep the number of instances proportional to the value of this metric, the metric itself should not change value due to group resizing. For example, a good metric to use with the target is pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.
Target double: The target value of the metric that autoscaler should maintain. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilizationTarget is www.googleapis.com/compute/instance/network/received_bytes_count. The autoscaler will work to keep this value constant for each of the instances.
Type string: Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Possible values are: GAUGE, DELTA_PER_SECOND, DELTA_PER_MINUTE.

Name string: The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.
Filter string: A filter string to be used as the filter string for a Stackdriver Monitoring TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. You can only use the AND operator for joining selectors. You can only use direct equality comparison operator (=) without any functions for each selector. You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. You should provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.
SingleInstanceAssignment float64: If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. The autoscaler will keep the number of instances proportional to the value of this metric, the metric itself should not change value due to group resizing. For example, a good metric to use with the target is pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.
Target float64: The target value of the metric that autoscaler should maintain. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilizationTarget is www.googleapis.com/compute/instance/network/received_bytes_count. The autoscaler will work to keep this value constant for each of the instances.
Type string: Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Possible values are: GAUGE, DELTA_PER_SECOND, DELTA_PER_MINUTE.

name String: The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.
filter String: A filter string to be used as the filter string for a Stackdriver Monitoring TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. You can only use the AND operator for joining selectors. You can only use direct equality comparison operator (=) without any functions for each selector. You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. You should provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.
singleInstanceAssignment Double: If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. The autoscaler will keep the number of instances proportional to the value of this metric, the metric itself should not change value due to group resizing. For example, a good metric to use with the target is pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.
target Double: The target value of the metric that autoscaler should maintain. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilizationTarget is www.googleapis.com/compute/instance/network/received_bytes_count. The autoscaler will work to keep this value constant for each of the instances.
type String: Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Possible values are: GAUGE, DELTA_PER_SECOND, DELTA_PER_MINUTE.

name string: The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.
filter string: A filter string to be used as the filter string for a Stackdriver Monitoring TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. You can only use the AND operator for joining selectors. You can only use direct equality comparison operator (=) without any functions for each selector. You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. You should provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.
singleInstanceAssignment number: If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. The autoscaler will keep the number of instances proportional to the value of this metric, the metric itself should not change value due to group resizing. For example, a good metric to use with the target is pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.
target number: The target value of the metric that autoscaler should maintain. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilizationTarget is www.googleapis.com/compute/instance/network/received_bytes_count. The autoscaler will work to keep this value constant for each of the instances.
type string: Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Possible values are: GAUGE, DELTA_PER_SECOND, DELTA_PER_MINUTE.

name str: The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.
filter str: A filter string to be used as the filter string for a Stackdriver Monitoring TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. You can only use the AND operator for joining selectors. You can only use direct equality comparison operator (=) without any functions for each selector. You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. You should provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.
single_instance_assignment float: If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. The autoscaler will keep the number of instances proportional to the value of this metric, the metric itself should not change value due to group resizing. For example, a good metric to use with the target is pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.
target float: The target value of the metric that autoscaler should maintain. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilizationTarget is www.googleapis.com/compute/instance/network/received_bytes_count. The autoscaler will work to keep this value constant for each of the instances.
type str: Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Possible values are: GAUGE, DELTA_PER_SECOND, DELTA_PER_MINUTE.

name String: The identifier (type) of the Stackdriver Monitoring metric. The metric cannot have negative values. The metric must have a value type of INT64 or DOUBLE.
filter String: A filter string to be used as the filter string for a Stackdriver Monitoring TimeSeries.list API call. This filter is used to select a specific TimeSeries for the purpose of autoscaling and to determine whether the metric is exporting per-instance or per-group data. You can only use the AND operator for joining selectors. You can only use direct equality comparison operator (=) without any functions for each selector. You can specify the metric in both the filter string and in the metric field. However, if specified in both places, the metric must be identical. The monitored resource type determines what kind of values are expected for the metric. If it is a gce_instance, the autoscaler expects the metric to include a separate TimeSeries for each instance in a group. In such a case, you cannot filter on resource labels. If the resource type is any other value, the autoscaler expects this metric to contain values that apply to the entire autoscaled instance group and resource label filtering can be performed to point autoscaler at the correct TimeSeries to scale upon. This is called a per-group metric for the purpose of autoscaling. If not specified, the type defaults to gce_instance. You should provide a filter that is selective enough to pick just one TimeSeries for the autoscaled group or for each of the instances (if you are using gce_instance resource type). If multiple TimeSeries are returned upon the query execution, the autoscaler will sum their respective values to obtain its scaling value.
singleInstanceAssignment Number: If scaling is based on a per-group metric value that represents the total amount of work to be done or resource usage, set this value to an amount assigned for a single instance of the scaled group. The autoscaler will keep the number of instances proportional to the value of this metric, the metric itself should not change value due to group resizing. For example, a good metric to use with the target is pubsub.googleapis.com/subscription/num_undelivered_messages or a custom metric exporting the total number of requests coming to your instances. A bad example would be a metric exporting an average or median latency, since this value can't include a chunk assignable to a single instance, it could be better used with utilization_target instead.
target Number: The target value of the metric that autoscaler should maintain. This must be a positive value. A utilization metric scales number of virtual machines handling requests to increase or decrease proportionally to the metric. For example, a good metric to use as a utilizationTarget is www.googleapis.com/compute/instance/network/received_bytes_count. The autoscaler will work to keep this value constant for each of the instances.
type String: Defines how target utilization value is expressed for a Stackdriver Monitoring metric. Possible values are: GAUGE, DELTA_PER_SECOND, DELTA_PER_MINUTE.

AutoscalerAutoscalingPolicyScaleDownControl, AutoscalerAutoscalingPolicyScaleDownControlArgs

MaxScaledDownReplicas AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicas: A nested object resource Structure is documented below.
TimeWindowSec int: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

MaxScaledDownReplicas AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicas: A nested object resource Structure is documented below.
TimeWindowSec int: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

maxScaledDownReplicas AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicas: A nested object resource Structure is documented below.
timeWindowSec Integer: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

maxScaledDownReplicas AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicas: A nested object resource Structure is documented below.
timeWindowSec number: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

max_scaled_down_replicas AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicas: A nested object resource Structure is documented below.
time_window_sec int: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

maxScaledDownReplicas Property Map: A nested object resource Structure is documented below.
timeWindowSec Number: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicas, AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicasArgs

Fixed int: Specifies a fixed number of VM instances. This must be a positive integer.
Percent int: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

Fixed int: Specifies a fixed number of VM instances. This must be a positive integer.
Percent int: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

fixed Integer: Specifies a fixed number of VM instances. This must be a positive integer.
percent Integer: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

fixed number: Specifies a fixed number of VM instances. This must be a positive integer.
percent number: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

fixed int: Specifies a fixed number of VM instances. This must be a positive integer.
percent int: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

fixed Number: Specifies a fixed number of VM instances. This must be a positive integer.
percent Number: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

AutoscalerAutoscalingPolicyScaleInControl, AutoscalerAutoscalingPolicyScaleInControlArgs

MaxScaledInReplicas AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicas: A nested object resource Structure is documented below.
TimeWindowSec int: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

MaxScaledInReplicas AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicas: A nested object resource Structure is documented below.
TimeWindowSec int: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

maxScaledInReplicas AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicas: A nested object resource Structure is documented below.
timeWindowSec Integer: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

maxScaledInReplicas AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicas: A nested object resource Structure is documented below.
timeWindowSec number: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

max_scaled_in_replicas AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicas: A nested object resource Structure is documented below.
time_window_sec int: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

maxScaledInReplicas Property Map: A nested object resource Structure is documented below.
timeWindowSec Number: How long back autoscaling should look when computing recommendations to include directives regarding slower scale down, as described above.

AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicas, AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicasArgs

Fixed int: Specifies a fixed number of VM instances. This must be a positive integer.
Percent int: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

Fixed int: Specifies a fixed number of VM instances. This must be a positive integer.
Percent int: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

fixed Integer: Specifies a fixed number of VM instances. This must be a positive integer.
percent Integer: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

fixed number: Specifies a fixed number of VM instances. This must be a positive integer.
percent number: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

fixed int: Specifies a fixed number of VM instances. This must be a positive integer.
percent int: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

fixed Number: Specifies a fixed number of VM instances. This must be a positive integer.
percent Number: Specifies a percentage of instances between 0 to 100%, inclusive. For example, specify 80 for 80%.

AutoscalerAutoscalingPolicyScalingSchedule, AutoscalerAutoscalingPolicyScalingScheduleArgs

DurationSec int: The duration of time intervals (in seconds) for which this scaling schedule will be running. The minimum allowed value is 300.
MinRequiredReplicas int: Minimum number of VM instances that autoscaler will recommend in time intervals starting according to schedule.
Name string: The identifier for this object. Format specified above.
Schedule string: The start timestamps of time intervals when this scaling schedule should provide a scaling signal. This field uses the extended cron format (with an optional year field).
Description string: An optional description of this resource.
Disabled bool: A boolean value that specifies if a scaling schedule can influence autoscaler recommendations. If set to true, then a scaling schedule has no effect.
TimeZone string: The time zone to be used when interpreting the schedule. The value of this field must be a time zone name from the tz database: http://en.wikipedia.org/wiki/Tz_database.

DurationSec int: The duration of time intervals (in seconds) for which this scaling schedule will be running. The minimum allowed value is 300.
MinRequiredReplicas int: Minimum number of VM instances that autoscaler will recommend in time intervals starting according to schedule.
Name string: The identifier for this object. Format specified above.
Schedule string: The start timestamps of time intervals when this scaling schedule should provide a scaling signal. This field uses the extended cron format (with an optional year field).
Description string: An optional description of this resource.
Disabled bool: A boolean value that specifies if a scaling schedule can influence autoscaler recommendations. If set to true, then a scaling schedule has no effect.
TimeZone string: The time zone to be used when interpreting the schedule. The value of this field must be a time zone name from the tz database: http://en.wikipedia.org/wiki/Tz_database.

durationSec Integer: The duration of time intervals (in seconds) for which this scaling schedule will be running. The minimum allowed value is 300.
minRequiredReplicas Integer: Minimum number of VM instances that autoscaler will recommend in time intervals starting according to schedule.
name String: The identifier for this object. Format specified above.
schedule String: The start timestamps of time intervals when this scaling schedule should provide a scaling signal. This field uses the extended cron format (with an optional year field).
description String: An optional description of this resource.
disabled Boolean: A boolean value that specifies if a scaling schedule can influence autoscaler recommendations. If set to true, then a scaling schedule has no effect.
timeZone String: The time zone to be used when interpreting the schedule. The value of this field must be a time zone name from the tz database: http://en.wikipedia.org/wiki/Tz_database.

durationSec number: The duration of time intervals (in seconds) for which this scaling schedule will be running. The minimum allowed value is 300.
minRequiredReplicas number: Minimum number of VM instances that autoscaler will recommend in time intervals starting according to schedule.
name string: The identifier for this object. Format specified above.
schedule string: The start timestamps of time intervals when this scaling schedule should provide a scaling signal. This field uses the extended cron format (with an optional year field).
description string: An optional description of this resource.
disabled boolean: A boolean value that specifies if a scaling schedule can influence autoscaler recommendations. If set to true, then a scaling schedule has no effect.
timeZone string: The time zone to be used when interpreting the schedule. The value of this field must be a time zone name from the tz database: http://en.wikipedia.org/wiki/Tz_database.

duration_sec int: The duration of time intervals (in seconds) for which this scaling schedule will be running. The minimum allowed value is 300.
min_required_replicas int: Minimum number of VM instances that autoscaler will recommend in time intervals starting according to schedule.
name str: The identifier for this object. Format specified above.
schedule str: The start timestamps of time intervals when this scaling schedule should provide a scaling signal. This field uses the extended cron format (with an optional year field).
description str: An optional description of this resource.
disabled bool: A boolean value that specifies if a scaling schedule can influence autoscaler recommendations. If set to true, then a scaling schedule has no effect.
time_zone str: The time zone to be used when interpreting the schedule. The value of this field must be a time zone name from the tz database: http://en.wikipedia.org/wiki/Tz_database.

durationSec Number: The duration of time intervals (in seconds) for which this scaling schedule will be running. The minimum allowed value is 300.
minRequiredReplicas Number: Minimum number of VM instances that autoscaler will recommend in time intervals starting according to schedule.
name String: The identifier for this object. Format specified above.
schedule String: The start timestamps of time intervals when this scaling schedule should provide a scaling signal. This field uses the extended cron format (with an optional year field).
description String: An optional description of this resource.
disabled Boolean: A boolean value that specifies if a scaling schedule can influence autoscaler recommendations. If set to true, then a scaling schedule has no effect.
timeZone String: The time zone to be used when interpreting the schedule. The value of this field must be a time zone name from the tz database: http://en.wikipedia.org/wiki/Tz_database.

Import

Autoscaler can be imported using any of these accepted formats

 $ pulumi import gcp:compute/autoscaler:Autoscaler default projects/{{project}}/zones/{{zone}}/autoscalers/{{name}}

 $ pulumi import gcp:compute/autoscaler:Autoscaler default {{project}}/{{zone}}/{{name}}

 $ pulumi import gcp:compute/autoscaler:Autoscaler default {{zone}}/{{name}}

 $ pulumi import gcp:compute/autoscaler:Autoscaler default {{name}}

Package Details

Repository: Google Cloud (GCP) Classic pulumi/pulumi-gcp
License: Apache-2.0
Notes: This Pulumi package is based on the google-beta Terraform Provider.

Google Cloud Classic v6.66.0 published on Monday, Sep 18, 2023 by Pulumi

pulumi/pulumi-gcp

gcp.compute.Autoscaler

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Example Usage

Autoscaler Single Instance

Autoscaler Basic

Create Autoscaler Resource

Autoscaler Resource Properties

Inputs

Outputs

Look up Existing Autoscaler Resource

Supporting Types

AutoscalerAutoscalingPolicy, AutoscalerAutoscalingPolicyArgs

AutoscalerAutoscalingPolicyCpuUtilization, AutoscalerAutoscalingPolicyCpuUtilizationArgs

AutoscalerAutoscalingPolicyLoadBalancingUtilization, AutoscalerAutoscalingPolicyLoadBalancingUtilizationArgs

AutoscalerAutoscalingPolicyMetric, AutoscalerAutoscalingPolicyMetricArgs

AutoscalerAutoscalingPolicyScaleDownControl, AutoscalerAutoscalingPolicyScaleDownControlArgs

AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicas, AutoscalerAutoscalingPolicyScaleDownControlMaxScaledDownReplicasArgs

AutoscalerAutoscalingPolicyScaleInControl, AutoscalerAutoscalingPolicyScaleInControlArgs

AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicas, AutoscalerAutoscalingPolicyScaleInControlMaxScaledInReplicasArgs

AutoscalerAutoscalingPolicyScalingSchedule, AutoscalerAutoscalingPolicyScalingScheduleArgs

Import

Package Details

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