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gcore 0.19.0 published on Monday, Apr 14, 2025 by g-core
g-core/terraform-provider-gcore

gcore.InferenceDeployment

Explore with Pulumi AI

gcore 0.19.0 published on Monday, Apr 14, 2025 by g-core
g-core/terraform-provider-gcore

Represent inference deployment

Example Usage

Prerequisite
import * as pulumi from "@pulumi/pulumi";
import * as gcore from "@pulumi/gcore";

const project = gcore.getProject({
    name: "Default",
});
const region = gcore.getRegion({
    name: "Luxembourg-2",
});
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import pulumi
import pulumi_gcore as gcore

project = gcore.get_project(name="Default")
region = gcore.get_region(name="Luxembourg-2")
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package main

import (
	"github.com/pulumi/pulumi-terraform-provider/sdks/go/gcore/gcore"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := gcore.GetProject(ctx, &gcore.GetProjectArgs{
			Name: "Default",
		}, nil)
		if err != nil {
			return err
		}
		_, err = gcore.GetRegion(ctx, &gcore.GetRegionArgs{
			Name: "Luxembourg-2",
		}, nil)
		if err != nil {
			return err
		}
		return nil
	})
}
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using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcore = Pulumi.Gcore;

return await Deployment.RunAsync(() => 
{
    var project = Gcore.GetProject.Invoke(new()
    {
        Name = "Default",
    });

    var region = Gcore.GetRegion.Invoke(new()
    {
        Name = "Luxembourg-2",
    });

});
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package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcore.GcoreFunctions;
import com.pulumi.gcore.inputs.GetProjectArgs;
import com.pulumi.gcore.inputs.GetRegionArgs;
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 project = GcoreFunctions.getProject(GetProjectArgs.builder()
            .name("Default")
            .build());

        final var region = GcoreFunctions.getRegion(GetRegionArgs.builder()
            .name("Luxembourg-2")
            .build());

    }
}
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variables:
  project:
    fn::invoke:
      function: gcore:getProject
      arguments:
        name: Default
  region:
    fn::invoke:
      function: gcore:getRegion
      arguments:
        name: Luxembourg-2
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Basic example

Creating inference deployment

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

const inf = new gcore.InferenceDeployment("inf", {
    projectId: data.gcore_project.project.id,
    image: "nginx:latest",
    listeningPort: 80,
    flavorName: "inference-4vcpu-16gib",
    containers: [{
        regionId: data.gcore_region.region.id,
        scaleMin: 2,
        scaleMax: 2,
        triggersCpuThreshold: 80,
    }],
    livenessProbe: {
        enabled: true,
        failureThreshold: 3,
        initialDelaySeconds: 10,
        periodSeconds: 10,
        timeoutSeconds: 1,
        successThreshold: 1,
        httpGetPort: 80,
        httpGetHeaders: {
            "User-Agent": "my user agent",
        },
        httpGetHost: "localhost",
        httpGetPath: "/",
        httpGetSchema: "HTTPS",
    },
    readinessProbe: {
        enabled: false,
    },
    startupProbe: {
        enabled: false,
    },
});
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import pulumi
import pulumi_gcore as gcore

inf = gcore.InferenceDeployment("inf",
    project_id=data["gcore_project"]["project"]["id"],
    image="nginx:latest",
    listening_port=80,
    flavor_name="inference-4vcpu-16gib",
    containers=[{
        "region_id": data["gcore_region"]["region"]["id"],
        "scale_min": 2,
        "scale_max": 2,
        "triggers_cpu_threshold": 80,
    }],
    liveness_probe={
        "enabled": True,
        "failure_threshold": 3,
        "initial_delay_seconds": 10,
        "period_seconds": 10,
        "timeout_seconds": 1,
        "success_threshold": 1,
        "http_get_port": 80,
        "http_get_headers": {
            "User-Agent": "my user agent",
        },
        "http_get_host": "localhost",
        "http_get_path": "/",
        "http_get_schema": "HTTPS",
    },
    readiness_probe={
        "enabled": False,
    },
    startup_probe={
        "enabled": False,
    })
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package main

import (
	"github.com/pulumi/pulumi-terraform-provider/sdks/go/gcore/gcore"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := gcore.NewInferenceDeployment(ctx, "inf", &gcore.InferenceDeploymentArgs{
			ProjectId:     pulumi.Any(data.Gcore_project.Project.Id),
			Image:         pulumi.String("nginx:latest"),
			ListeningPort: pulumi.Float64(80),
			FlavorName:    pulumi.String("inference-4vcpu-16gib"),
			Containers: gcore.InferenceDeploymentContainerArray{
				&gcore.InferenceDeploymentContainerArgs{
					RegionId:             pulumi.Any(data.Gcore_region.Region.Id),
					ScaleMin:             pulumi.Float64(2),
					ScaleMax:             pulumi.Float64(2),
					TriggersCpuThreshold: pulumi.Float64(80),
				},
			},
			LivenessProbe: &gcore.InferenceDeploymentLivenessProbeArgs{
				Enabled:             pulumi.Bool(true),
				FailureThreshold:    pulumi.Float64(3),
				InitialDelaySeconds: pulumi.Float64(10),
				PeriodSeconds:       pulumi.Float64(10),
				TimeoutSeconds:      pulumi.Float64(1),
				SuccessThreshold:    pulumi.Float64(1),
				HttpGetPort:         pulumi.Float64(80),
				HttpGetHeaders: pulumi.StringMap{
					"User-Agent": pulumi.String("my user agent"),
				},
				HttpGetHost:   pulumi.String("localhost"),
				HttpGetPath:   pulumi.String("/"),
				HttpGetSchema: pulumi.String("HTTPS"),
			},
			ReadinessProbe: &gcore.InferenceDeploymentReadinessProbeArgs{
				Enabled: pulumi.Bool(false),
			},
			StartupProbe: &gcore.InferenceDeploymentStartupProbeArgs{
				Enabled: pulumi.Bool(false),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}
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using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcore = Pulumi.Gcore;

return await Deployment.RunAsync(() => 
{
    var inf = new Gcore.InferenceDeployment("inf", new()
    {
        ProjectId = data.Gcore_project.Project.Id,
        Image = "nginx:latest",
        ListeningPort = 80,
        FlavorName = "inference-4vcpu-16gib",
        Containers = new[]
        {
            new Gcore.Inputs.InferenceDeploymentContainerArgs
            {
                RegionId = data.Gcore_region.Region.Id,
                ScaleMin = 2,
                ScaleMax = 2,
                TriggersCpuThreshold = 80,
            },
        },
        LivenessProbe = new Gcore.Inputs.InferenceDeploymentLivenessProbeArgs
        {
            Enabled = true,
            FailureThreshold = 3,
            InitialDelaySeconds = 10,
            PeriodSeconds = 10,
            TimeoutSeconds = 1,
            SuccessThreshold = 1,
            HttpGetPort = 80,
            HttpGetHeaders = 
            {
                { "User-Agent", "my user agent" },
            },
            HttpGetHost = "localhost",
            HttpGetPath = "/",
            HttpGetSchema = "HTTPS",
        },
        ReadinessProbe = new Gcore.Inputs.InferenceDeploymentReadinessProbeArgs
        {
            Enabled = false,
        },
        StartupProbe = new Gcore.Inputs.InferenceDeploymentStartupProbeArgs
        {
            Enabled = false,
        },
    });

});
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package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcore.InferenceDeployment;
import com.pulumi.gcore.InferenceDeploymentArgs;
import com.pulumi.gcore.inputs.InferenceDeploymentContainerArgs;
import com.pulumi.gcore.inputs.InferenceDeploymentLivenessProbeArgs;
import com.pulumi.gcore.inputs.InferenceDeploymentReadinessProbeArgs;
import com.pulumi.gcore.inputs.InferenceDeploymentStartupProbeArgs;
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 inf = new InferenceDeployment("inf", InferenceDeploymentArgs.builder()
            .projectId(data.gcore_project().project().id())
            .image("nginx:latest")
            .listeningPort(80)
            .flavorName("inference-4vcpu-16gib")
            .containers(InferenceDeploymentContainerArgs.builder()
                .regionId(data.gcore_region().region().id())
                .scaleMin(2)
                .scaleMax(2)
                .triggersCpuThreshold(80)
                .build())
            .livenessProbe(InferenceDeploymentLivenessProbeArgs.builder()
                .enabled(true)
                .failureThreshold(3)
                .initialDelaySeconds(10)
                .periodSeconds(10)
                .timeoutSeconds(1)
                .successThreshold(1)
                .httpGetPort(80)
                .httpGetHeaders(Map.of("User-Agent", "my user agent"))
                .httpGetHost("localhost")
                .httpGetPath("/")
                .httpGetSchema("HTTPS")
                .build())
            .readinessProbe(InferenceDeploymentReadinessProbeArgs.builder()
                .enabled(false)
                .build())
            .startupProbe(InferenceDeploymentStartupProbeArgs.builder()
                .enabled(false)
                .build())
            .build());

    }
}
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resources:
  'inf':
    type: gcore:InferenceDeployment
    properties:
      projectId: ${data.gcore_project.project.id}
      image: nginx:latest
      listeningPort: 80
      flavorName: inference-4vcpu-16gib
      containers:
        - regionId: ${data.gcore_region.region.id}
          scaleMin: 2
          scaleMax: 2
          triggersCpuThreshold: 80
      livenessProbe:
        enabled: true
        failureThreshold: 3
        initialDelaySeconds: 10
        periodSeconds: 10
        timeoutSeconds: 1
        successThreshold: 1
        httpGetPort: 80
        httpGetHeaders:
          User-Agent: my user agent
        httpGetHost: localhost
        httpGetPath: /
        httpGetSchema: HTTPS
      readinessProbe:
        enabled: false
      startupProbe:
        enabled: false
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Creating inference deployment with sqs trigger

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

const aws = new gcore.InferenceSecret("aws", {
    projectId: data.gcore_project.project.id,
    dataAwsAccessKeyId: "my-aws-access-key-id",
    dataAwsSecretAccessKey: "my-aws-access-key",
});
const inf = new gcore.InferenceDeployment("inf", {
    projectId: data.gcore_project.project.id,
    image: "nginx:latest",
    listeningPort: 80,
    flavorName: "inference-4vcpu-16gib",
    timeout: 60,
    containers: [{
        regionId: data.gcore_region.region.id,
        cooldownPeriod: 60,
        pollingInterval: 60,
        scaleMin: 0,
        scaleMax: 2,
        triggersCpuThreshold: 80,
        triggersSqsSecretName: aws.name,
        triggersSqsAwsRegion: "us-west-2",
        triggersSqsQueueUrl: "https://sqs.us-west-2.amazonaws.com/1234567890/my-queue",
        triggersSqsQueueLength: 5,
        triggersSqsActivationQueueLength: 2,
    }],
    livenessProbe: {
        enabled: false,
    },
    readinessProbe: {
        enabled: false,
    },
    startupProbe: {
        enabled: false,
    },
});
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import pulumi
import pulumi_gcore as gcore

aws = gcore.InferenceSecret("aws",
    project_id=data["gcore_project"]["project"]["id"],
    data_aws_access_key_id="my-aws-access-key-id",
    data_aws_secret_access_key="my-aws-access-key")
inf = gcore.InferenceDeployment("inf",
    project_id=data["gcore_project"]["project"]["id"],
    image="nginx:latest",
    listening_port=80,
    flavor_name="inference-4vcpu-16gib",
    timeout=60,
    containers=[{
        "region_id": data["gcore_region"]["region"]["id"],
        "cooldown_period": 60,
        "polling_interval": 60,
        "scale_min": 0,
        "scale_max": 2,
        "triggers_cpu_threshold": 80,
        "triggers_sqs_secret_name": aws.name,
        "triggers_sqs_aws_region": "us-west-2",
        "triggers_sqs_queue_url": "https://sqs.us-west-2.amazonaws.com/1234567890/my-queue",
        "triggers_sqs_queue_length": 5,
        "triggers_sqs_activation_queue_length": 2,
    }],
    liveness_probe={
        "enabled": False,
    },
    readiness_probe={
        "enabled": False,
    },
    startup_probe={
        "enabled": False,
    })
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package main

import (
	"github.com/pulumi/pulumi-terraform-provider/sdks/go/gcore/gcore"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		aws, err := gcore.NewInferenceSecret(ctx, "aws", &gcore.InferenceSecretArgs{
			ProjectId:              pulumi.Any(data.Gcore_project.Project.Id),
			DataAwsAccessKeyId:     pulumi.String("my-aws-access-key-id"),
			DataAwsSecretAccessKey: pulumi.String("my-aws-access-key"),
		})
		if err != nil {
			return err
		}
		_, err = gcore.NewInferenceDeployment(ctx, "inf", &gcore.InferenceDeploymentArgs{
			ProjectId:     pulumi.Any(data.Gcore_project.Project.Id),
			Image:         pulumi.String("nginx:latest"),
			ListeningPort: pulumi.Float64(80),
			FlavorName:    pulumi.String("inference-4vcpu-16gib"),
			Timeout:       pulumi.Float64(60),
			Containers: gcore.InferenceDeploymentContainerArray{
				&gcore.InferenceDeploymentContainerArgs{
					RegionId:                         pulumi.Any(data.Gcore_region.Region.Id),
					CooldownPeriod:                   pulumi.Float64(60),
					PollingInterval:                  pulumi.Float64(60),
					ScaleMin:                         pulumi.Float64(0),
					ScaleMax:                         pulumi.Float64(2),
					TriggersCpuThreshold:             pulumi.Float64(80),
					TriggersSqsSecretName:            aws.Name,
					TriggersSqsAwsRegion:             pulumi.String("us-west-2"),
					TriggersSqsQueueUrl:              pulumi.String("https://sqs.us-west-2.amazonaws.com/1234567890/my-queue"),
					TriggersSqsQueueLength:           pulumi.Float64(5),
					TriggersSqsActivationQueueLength: pulumi.Float64(2),
				},
			},
			LivenessProbe: &gcore.InferenceDeploymentLivenessProbeArgs{
				Enabled: pulumi.Bool(false),
			},
			ReadinessProbe: &gcore.InferenceDeploymentReadinessProbeArgs{
				Enabled: pulumi.Bool(false),
			},
			StartupProbe: &gcore.InferenceDeploymentStartupProbeArgs{
				Enabled: pulumi.Bool(false),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}
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using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcore = Pulumi.Gcore;

return await Deployment.RunAsync(() => 
{
    var aws = new Gcore.InferenceSecret("aws", new()
    {
        ProjectId = data.Gcore_project.Project.Id,
        DataAwsAccessKeyId = "my-aws-access-key-id",
        DataAwsSecretAccessKey = "my-aws-access-key",
    });

    var inf = new Gcore.InferenceDeployment("inf", new()
    {
        ProjectId = data.Gcore_project.Project.Id,
        Image = "nginx:latest",
        ListeningPort = 80,
        FlavorName = "inference-4vcpu-16gib",
        Timeout = 60,
        Containers = new[]
        {
            new Gcore.Inputs.InferenceDeploymentContainerArgs
            {
                RegionId = data.Gcore_region.Region.Id,
                CooldownPeriod = 60,
                PollingInterval = 60,
                ScaleMin = 0,
                ScaleMax = 2,
                TriggersCpuThreshold = 80,
                TriggersSqsSecretName = aws.Name,
                TriggersSqsAwsRegion = "us-west-2",
                TriggersSqsQueueUrl = "https://sqs.us-west-2.amazonaws.com/1234567890/my-queue",
                TriggersSqsQueueLength = 5,
                TriggersSqsActivationQueueLength = 2,
            },
        },
        LivenessProbe = new Gcore.Inputs.InferenceDeploymentLivenessProbeArgs
        {
            Enabled = false,
        },
        ReadinessProbe = new Gcore.Inputs.InferenceDeploymentReadinessProbeArgs
        {
            Enabled = false,
        },
        StartupProbe = new Gcore.Inputs.InferenceDeploymentStartupProbeArgs
        {
            Enabled = false,
        },
    });

});
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package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcore.InferenceSecret;
import com.pulumi.gcore.InferenceSecretArgs;
import com.pulumi.gcore.InferenceDeployment;
import com.pulumi.gcore.InferenceDeploymentArgs;
import com.pulumi.gcore.inputs.InferenceDeploymentContainerArgs;
import com.pulumi.gcore.inputs.InferenceDeploymentLivenessProbeArgs;
import com.pulumi.gcore.inputs.InferenceDeploymentReadinessProbeArgs;
import com.pulumi.gcore.inputs.InferenceDeploymentStartupProbeArgs;
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 aws = new InferenceSecret("aws", InferenceSecretArgs.builder()
            .projectId(data.gcore_project().project().id())
            .dataAwsAccessKeyId("my-aws-access-key-id")
            .dataAwsSecretAccessKey("my-aws-access-key")
            .build());

        var inf = new InferenceDeployment("inf", InferenceDeploymentArgs.builder()
            .projectId(data.gcore_project().project().id())
            .image("nginx:latest")
            .listeningPort(80)
            .flavorName("inference-4vcpu-16gib")
            .timeout(60)
            .containers(InferenceDeploymentContainerArgs.builder()
                .regionId(data.gcore_region().region().id())
                .cooldownPeriod(60)
                .pollingInterval(60)
                .scaleMin(0)
                .scaleMax(2)
                .triggersCpuThreshold(80)
                .triggersSqsSecretName(aws.name())
                .triggersSqsAwsRegion("us-west-2")
                .triggersSqsQueueUrl("https://sqs.us-west-2.amazonaws.com/1234567890/my-queue")
                .triggersSqsQueueLength(5)
                .triggersSqsActivationQueueLength(2)
                .build())
            .livenessProbe(InferenceDeploymentLivenessProbeArgs.builder()
                .enabled(false)
                .build())
            .readinessProbe(InferenceDeploymentReadinessProbeArgs.builder()
                .enabled(false)
                .build())
            .startupProbe(InferenceDeploymentStartupProbeArgs.builder()
                .enabled(false)
                .build())
            .build());

    }
}
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resources:
  aws:
    type: gcore:InferenceSecret
    properties:
      projectId: ${data.gcore_project.project.id}
      dataAwsAccessKeyId: my-aws-access-key-id
      dataAwsSecretAccessKey: my-aws-access-key
  'inf':
    type: gcore:InferenceDeployment
    properties:
      projectId: ${data.gcore_project.project.id}
      image: nginx:latest
      listeningPort: 80
      flavorName: inference-4vcpu-16gib
      timeout: 60
      containers:
        - regionId: ${data.gcore_region.region.id}
          cooldownPeriod: 60
          pollingInterval: 60
          scaleMin: 0
          scaleMax: 2
          triggersCpuThreshold: 80
          triggersSqsSecretName: ${aws.name}
          triggersSqsAwsRegion: us-west-2
          triggersSqsQueueUrl: https://sqs.us-west-2.amazonaws.com/1234567890/my-queue
          triggersSqsQueueLength: 5
          triggersSqsActivationQueueLength: 2
      livenessProbe:
        enabled: false
      readinessProbe:
        enabled: false
      startupProbe:
        enabled: false
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Create InferenceDeployment Resource

Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

Constructor syntax

new InferenceDeployment(name: string, args: InferenceDeploymentArgs, opts?: CustomResourceOptions);
@overload
def InferenceDeployment(resource_name: str,
                        args: InferenceDeploymentArgs,
                        opts: Optional[ResourceOptions] = None)

@overload
def InferenceDeployment(resource_name: str,
                        opts: Optional[ResourceOptions] = None,
                        flavor_name: Optional[str] = None,
                        listening_port: Optional[float] = None,
                        containers: Optional[Sequence[InferenceDeploymentContainerArgs]] = None,
                        image: Optional[str] = None,
                        inference_deployment_id: Optional[str] = None,
                        logging: Optional[InferenceDeploymentLoggingArgs] = None,
                        description: Optional[str] = None,
                        credentials_name: Optional[str] = None,
                        auth_enabled: Optional[bool] = None,
                        command: Optional[str] = None,
                        liveness_probe: Optional[InferenceDeploymentLivenessProbeArgs] = None,
                        envs: Optional[Mapping[str, str]] = None,
                        name: Optional[str] = None,
                        project_id: Optional[float] = None,
                        project_name: Optional[str] = None,
                        readiness_probe: Optional[InferenceDeploymentReadinessProbeArgs] = None,
                        startup_probe: Optional[InferenceDeploymentStartupProbeArgs] = None,
                        timeout: Optional[float] = None)
func NewInferenceDeployment(ctx *Context, name string, args InferenceDeploymentArgs, opts ...ResourceOption) (*InferenceDeployment, error)
public InferenceDeployment(string name, InferenceDeploymentArgs args, CustomResourceOptions? opts = null)
public InferenceDeployment(String name, InferenceDeploymentArgs args)
public InferenceDeployment(String name, InferenceDeploymentArgs args, CustomResourceOptions options)

type: gcore:InferenceDeployment
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name This property is required. string
The unique name of the resource.
args This property is required. InferenceDeploymentArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
resource_name This property is required. str
The unique name of the resource.
args This property is required. InferenceDeploymentArgs
The arguments to resource properties.
opts ResourceOptions
Bag of options to control resource's behavior.
ctx Context
Context object for the current deployment.
name This property is required. string
The unique name of the resource.
args This property is required. InferenceDeploymentArgs
The arguments to resource properties.
opts ResourceOption
Bag of options to control resource's behavior.
name This property is required. string
The unique name of the resource.
args This property is required. InferenceDeploymentArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
name This property is required. String
The unique name of the resource.
args This property is required. InferenceDeploymentArgs
The arguments to resource properties.
options CustomResourceOptions
Bag of options to control resource's behavior.

Constructor example

The following reference example uses placeholder values for all input properties.

var inferenceDeploymentResource = new Gcore.InferenceDeployment("inferenceDeploymentResource", new()
{
    FlavorName = "string",
    ListeningPort = 0,
    Containers = new[]
    {
        new Gcore.Inputs.InferenceDeploymentContainerArgs
        {
            ScaleMax = 0,
            CooldownPeriod = 0,
            ScaleMin = 0,
            RegionId = 0,
            TriggersHttpRate = 0,
            TriggersSqsActivationQueueLength = 0,
            TotalContainers = 0,
            TriggersCpuThreshold = 0,
            TriggersGpuMemoryThreshold = 0,
            TriggersGpuUtilizationThreshold = 0,
            PollingInterval = 0,
            TriggersHttpWindow = 0,
            TriggersMemoryThreshold = 0,
            ReadyContainers = 0,
            TriggersSqsAwsEndpoint = "string",
            TriggersSqsAwsRegion = "string",
            TriggersSqsQueueLength = 0,
            TriggersSqsQueueUrl = "string",
            TriggersSqsScaleOnDelayed = false,
            TriggersSqsScaleOnFlight = false,
            TriggersSqsSecretName = "string",
        },
    },
    Image = "string",
    InferenceDeploymentId = "string",
    Logging = new Gcore.Inputs.InferenceDeploymentLoggingArgs
    {
        DestinationRegionId = 0,
        Enabled = false,
        RetentionPolicyPeriod = 0,
        TopicName = "string",
    },
    Description = "string",
    CredentialsName = "string",
    AuthEnabled = false,
    Command = "string",
    LivenessProbe = new Gcore.Inputs.InferenceDeploymentLivenessProbeArgs
    {
        Enabled = false,
        ExecCommand = "string",
        FailureThreshold = 0,
        HttpGetHeaders = 
        {
            { "string", "string" },
        },
        HttpGetHost = "string",
        HttpGetPath = "string",
        HttpGetPort = 0,
        HttpGetSchema = "string",
        InitialDelaySeconds = 0,
        PeriodSeconds = 0,
        SuccessThreshold = 0,
        TcpSocketPort = 0,
        TimeoutSeconds = 0,
    },
    Envs = 
    {
        { "string", "string" },
    },
    Name = "string",
    ProjectId = 0,
    ProjectName = "string",
    ReadinessProbe = new Gcore.Inputs.InferenceDeploymentReadinessProbeArgs
    {
        Enabled = false,
        ExecCommand = "string",
        FailureThreshold = 0,
        HttpGetHeaders = 
        {
            { "string", "string" },
        },
        HttpGetHost = "string",
        HttpGetPath = "string",
        HttpGetPort = 0,
        HttpGetSchema = "string",
        InitialDelaySeconds = 0,
        PeriodSeconds = 0,
        SuccessThreshold = 0,
        TcpSocketPort = 0,
        TimeoutSeconds = 0,
    },
    StartupProbe = new Gcore.Inputs.InferenceDeploymentStartupProbeArgs
    {
        Enabled = false,
        ExecCommand = "string",
        FailureThreshold = 0,
        HttpGetHeaders = 
        {
            { "string", "string" },
        },
        HttpGetHost = "string",
        HttpGetPath = "string",
        HttpGetPort = 0,
        HttpGetSchema = "string",
        InitialDelaySeconds = 0,
        PeriodSeconds = 0,
        SuccessThreshold = 0,
        TcpSocketPort = 0,
        TimeoutSeconds = 0,
    },
    Timeout = 0,
});
Copy
example, err := gcore.NewInferenceDeployment(ctx, "inferenceDeploymentResource", &gcore.InferenceDeploymentArgs{
FlavorName: pulumi.String("string"),
ListeningPort: pulumi.Float64(0),
Containers: .InferenceDeploymentContainerArray{
&.InferenceDeploymentContainerArgs{
ScaleMax: pulumi.Float64(0),
CooldownPeriod: pulumi.Float64(0),
ScaleMin: pulumi.Float64(0),
RegionId: pulumi.Float64(0),
TriggersHttpRate: pulumi.Float64(0),
TriggersSqsActivationQueueLength: pulumi.Float64(0),
TotalContainers: pulumi.Float64(0),
TriggersCpuThreshold: pulumi.Float64(0),
TriggersGpuMemoryThreshold: pulumi.Float64(0),
TriggersGpuUtilizationThreshold: pulumi.Float64(0),
PollingInterval: pulumi.Float64(0),
TriggersHttpWindow: pulumi.Float64(0),
TriggersMemoryThreshold: pulumi.Float64(0),
ReadyContainers: pulumi.Float64(0),
TriggersSqsAwsEndpoint: pulumi.String("string"),
TriggersSqsAwsRegion: pulumi.String("string"),
TriggersSqsQueueLength: pulumi.Float64(0),
TriggersSqsQueueUrl: pulumi.String("string"),
TriggersSqsScaleOnDelayed: pulumi.Bool(false),
TriggersSqsScaleOnFlight: pulumi.Bool(false),
TriggersSqsSecretName: pulumi.String("string"),
},
},
Image: pulumi.String("string"),
InferenceDeploymentId: pulumi.String("string"),
Logging: &.InferenceDeploymentLoggingArgs{
DestinationRegionId: pulumi.Float64(0),
Enabled: pulumi.Bool(false),
RetentionPolicyPeriod: pulumi.Float64(0),
TopicName: pulumi.String("string"),
},
Description: pulumi.String("string"),
CredentialsName: pulumi.String("string"),
AuthEnabled: pulumi.Bool(false),
Command: pulumi.String("string"),
LivenessProbe: &.InferenceDeploymentLivenessProbeArgs{
Enabled: pulumi.Bool(false),
ExecCommand: pulumi.String("string"),
FailureThreshold: pulumi.Float64(0),
HttpGetHeaders: pulumi.StringMap{
"string": pulumi.String("string"),
},
HttpGetHost: pulumi.String("string"),
HttpGetPath: pulumi.String("string"),
HttpGetPort: pulumi.Float64(0),
HttpGetSchema: pulumi.String("string"),
InitialDelaySeconds: pulumi.Float64(0),
PeriodSeconds: pulumi.Float64(0),
SuccessThreshold: pulumi.Float64(0),
TcpSocketPort: pulumi.Float64(0),
TimeoutSeconds: pulumi.Float64(0),
},
Envs: pulumi.StringMap{
"string": pulumi.String("string"),
},
Name: pulumi.String("string"),
ProjectId: pulumi.Float64(0),
ProjectName: pulumi.String("string"),
ReadinessProbe: &.InferenceDeploymentReadinessProbeArgs{
Enabled: pulumi.Bool(false),
ExecCommand: pulumi.String("string"),
FailureThreshold: pulumi.Float64(0),
HttpGetHeaders: pulumi.StringMap{
"string": pulumi.String("string"),
},
HttpGetHost: pulumi.String("string"),
HttpGetPath: pulumi.String("string"),
HttpGetPort: pulumi.Float64(0),
HttpGetSchema: pulumi.String("string"),
InitialDelaySeconds: pulumi.Float64(0),
PeriodSeconds: pulumi.Float64(0),
SuccessThreshold: pulumi.Float64(0),
TcpSocketPort: pulumi.Float64(0),
TimeoutSeconds: pulumi.Float64(0),
},
StartupProbe: &.InferenceDeploymentStartupProbeArgs{
Enabled: pulumi.Bool(false),
ExecCommand: pulumi.String("string"),
FailureThreshold: pulumi.Float64(0),
HttpGetHeaders: pulumi.StringMap{
"string": pulumi.String("string"),
},
HttpGetHost: pulumi.String("string"),
HttpGetPath: pulumi.String("string"),
HttpGetPort: pulumi.Float64(0),
HttpGetSchema: pulumi.String("string"),
InitialDelaySeconds: pulumi.Float64(0),
PeriodSeconds: pulumi.Float64(0),
SuccessThreshold: pulumi.Float64(0),
TcpSocketPort: pulumi.Float64(0),
TimeoutSeconds: pulumi.Float64(0),
},
Timeout: pulumi.Float64(0),
})
Copy
var inferenceDeploymentResource = new InferenceDeployment("inferenceDeploymentResource", InferenceDeploymentArgs.builder()
    .flavorName("string")
    .listeningPort(0)
    .containers(InferenceDeploymentContainerArgs.builder()
        .scaleMax(0)
        .cooldownPeriod(0)
        .scaleMin(0)
        .regionId(0)
        .triggersHttpRate(0)
        .triggersSqsActivationQueueLength(0)
        .totalContainers(0)
        .triggersCpuThreshold(0)
        .triggersGpuMemoryThreshold(0)
        .triggersGpuUtilizationThreshold(0)
        .pollingInterval(0)
        .triggersHttpWindow(0)
        .triggersMemoryThreshold(0)
        .readyContainers(0)
        .triggersSqsAwsEndpoint("string")
        .triggersSqsAwsRegion("string")
        .triggersSqsQueueLength(0)
        .triggersSqsQueueUrl("string")
        .triggersSqsScaleOnDelayed(false)
        .triggersSqsScaleOnFlight(false)
        .triggersSqsSecretName("string")
        .build())
    .image("string")
    .inferenceDeploymentId("string")
    .logging(InferenceDeploymentLoggingArgs.builder()
        .destinationRegionId(0)
        .enabled(false)
        .retentionPolicyPeriod(0)
        .topicName("string")
        .build())
    .description("string")
    .credentialsName("string")
    .authEnabled(false)
    .command("string")
    .livenessProbe(InferenceDeploymentLivenessProbeArgs.builder()
        .enabled(false)
        .execCommand("string")
        .failureThreshold(0)
        .httpGetHeaders(Map.of("string", "string"))
        .httpGetHost("string")
        .httpGetPath("string")
        .httpGetPort(0)
        .httpGetSchema("string")
        .initialDelaySeconds(0)
        .periodSeconds(0)
        .successThreshold(0)
        .tcpSocketPort(0)
        .timeoutSeconds(0)
        .build())
    .envs(Map.of("string", "string"))
    .name("string")
    .projectId(0)
    .projectName("string")
    .readinessProbe(InferenceDeploymentReadinessProbeArgs.builder()
        .enabled(false)
        .execCommand("string")
        .failureThreshold(0)
        .httpGetHeaders(Map.of("string", "string"))
        .httpGetHost("string")
        .httpGetPath("string")
        .httpGetPort(0)
        .httpGetSchema("string")
        .initialDelaySeconds(0)
        .periodSeconds(0)
        .successThreshold(0)
        .tcpSocketPort(0)
        .timeoutSeconds(0)
        .build())
    .startupProbe(InferenceDeploymentStartupProbeArgs.builder()
        .enabled(false)
        .execCommand("string")
        .failureThreshold(0)
        .httpGetHeaders(Map.of("string", "string"))
        .httpGetHost("string")
        .httpGetPath("string")
        .httpGetPort(0)
        .httpGetSchema("string")
        .initialDelaySeconds(0)
        .periodSeconds(0)
        .successThreshold(0)
        .tcpSocketPort(0)
        .timeoutSeconds(0)
        .build())
    .timeout(0)
    .build());
Copy
inference_deployment_resource = gcore.InferenceDeployment("inferenceDeploymentResource",
    flavor_name="string",
    listening_port=0,
    containers=[{
        "scale_max": 0,
        "cooldown_period": 0,
        "scale_min": 0,
        "region_id": 0,
        "triggers_http_rate": 0,
        "triggers_sqs_activation_queue_length": 0,
        "total_containers": 0,
        "triggers_cpu_threshold": 0,
        "triggers_gpu_memory_threshold": 0,
        "triggers_gpu_utilization_threshold": 0,
        "polling_interval": 0,
        "triggers_http_window": 0,
        "triggers_memory_threshold": 0,
        "ready_containers": 0,
        "triggers_sqs_aws_endpoint": "string",
        "triggers_sqs_aws_region": "string",
        "triggers_sqs_queue_length": 0,
        "triggers_sqs_queue_url": "string",
        "triggers_sqs_scale_on_delayed": False,
        "triggers_sqs_scale_on_flight": False,
        "triggers_sqs_secret_name": "string",
    }],
    image="string",
    inference_deployment_id="string",
    logging={
        "destination_region_id": 0,
        "enabled": False,
        "retention_policy_period": 0,
        "topic_name": "string",
    },
    description="string",
    credentials_name="string",
    auth_enabled=False,
    command="string",
    liveness_probe={
        "enabled": False,
        "exec_command": "string",
        "failure_threshold": 0,
        "http_get_headers": {
            "string": "string",
        },
        "http_get_host": "string",
        "http_get_path": "string",
        "http_get_port": 0,
        "http_get_schema": "string",
        "initial_delay_seconds": 0,
        "period_seconds": 0,
        "success_threshold": 0,
        "tcp_socket_port": 0,
        "timeout_seconds": 0,
    },
    envs={
        "string": "string",
    },
    name="string",
    project_id=0,
    project_name="string",
    readiness_probe={
        "enabled": False,
        "exec_command": "string",
        "failure_threshold": 0,
        "http_get_headers": {
            "string": "string",
        },
        "http_get_host": "string",
        "http_get_path": "string",
        "http_get_port": 0,
        "http_get_schema": "string",
        "initial_delay_seconds": 0,
        "period_seconds": 0,
        "success_threshold": 0,
        "tcp_socket_port": 0,
        "timeout_seconds": 0,
    },
    startup_probe={
        "enabled": False,
        "exec_command": "string",
        "failure_threshold": 0,
        "http_get_headers": {
            "string": "string",
        },
        "http_get_host": "string",
        "http_get_path": "string",
        "http_get_port": 0,
        "http_get_schema": "string",
        "initial_delay_seconds": 0,
        "period_seconds": 0,
        "success_threshold": 0,
        "tcp_socket_port": 0,
        "timeout_seconds": 0,
    },
    timeout=0)
Copy
const inferenceDeploymentResource = new gcore.InferenceDeployment("inferenceDeploymentResource", {
    flavorName: "string",
    listeningPort: 0,
    containers: [{
        scaleMax: 0,
        cooldownPeriod: 0,
        scaleMin: 0,
        regionId: 0,
        triggersHttpRate: 0,
        triggersSqsActivationQueueLength: 0,
        totalContainers: 0,
        triggersCpuThreshold: 0,
        triggersGpuMemoryThreshold: 0,
        triggersGpuUtilizationThreshold: 0,
        pollingInterval: 0,
        triggersHttpWindow: 0,
        triggersMemoryThreshold: 0,
        readyContainers: 0,
        triggersSqsAwsEndpoint: "string",
        triggersSqsAwsRegion: "string",
        triggersSqsQueueLength: 0,
        triggersSqsQueueUrl: "string",
        triggersSqsScaleOnDelayed: false,
        triggersSqsScaleOnFlight: false,
        triggersSqsSecretName: "string",
    }],
    image: "string",
    inferenceDeploymentId: "string",
    logging: {
        destinationRegionId: 0,
        enabled: false,
        retentionPolicyPeriod: 0,
        topicName: "string",
    },
    description: "string",
    credentialsName: "string",
    authEnabled: false,
    command: "string",
    livenessProbe: {
        enabled: false,
        execCommand: "string",
        failureThreshold: 0,
        httpGetHeaders: {
            string: "string",
        },
        httpGetHost: "string",
        httpGetPath: "string",
        httpGetPort: 0,
        httpGetSchema: "string",
        initialDelaySeconds: 0,
        periodSeconds: 0,
        successThreshold: 0,
        tcpSocketPort: 0,
        timeoutSeconds: 0,
    },
    envs: {
        string: "string",
    },
    name: "string",
    projectId: 0,
    projectName: "string",
    readinessProbe: {
        enabled: false,
        execCommand: "string",
        failureThreshold: 0,
        httpGetHeaders: {
            string: "string",
        },
        httpGetHost: "string",
        httpGetPath: "string",
        httpGetPort: 0,
        httpGetSchema: "string",
        initialDelaySeconds: 0,
        periodSeconds: 0,
        successThreshold: 0,
        tcpSocketPort: 0,
        timeoutSeconds: 0,
    },
    startupProbe: {
        enabled: false,
        execCommand: "string",
        failureThreshold: 0,
        httpGetHeaders: {
            string: "string",
        },
        httpGetHost: "string",
        httpGetPath: "string",
        httpGetPort: 0,
        httpGetSchema: "string",
        initialDelaySeconds: 0,
        periodSeconds: 0,
        successThreshold: 0,
        tcpSocketPort: 0,
        timeoutSeconds: 0,
    },
    timeout: 0,
});
Copy
type: gcore:InferenceDeployment
properties:
    authEnabled: false
    command: string
    containers:
        - cooldownPeriod: 0
          pollingInterval: 0
          readyContainers: 0
          regionId: 0
          scaleMax: 0
          scaleMin: 0
          totalContainers: 0
          triggersCpuThreshold: 0
          triggersGpuMemoryThreshold: 0
          triggersGpuUtilizationThreshold: 0
          triggersHttpRate: 0
          triggersHttpWindow: 0
          triggersMemoryThreshold: 0
          triggersSqsActivationQueueLength: 0
          triggersSqsAwsEndpoint: string
          triggersSqsAwsRegion: string
          triggersSqsQueueLength: 0
          triggersSqsQueueUrl: string
          triggersSqsScaleOnDelayed: false
          triggersSqsScaleOnFlight: false
          triggersSqsSecretName: string
    credentialsName: string
    description: string
    envs:
        string: string
    flavorName: string
    image: string
    inferenceDeploymentId: string
    listeningPort: 0
    livenessProbe:
        enabled: false
        execCommand: string
        failureThreshold: 0
        httpGetHeaders:
            string: string
        httpGetHost: string
        httpGetPath: string
        httpGetPort: 0
        httpGetSchema: string
        initialDelaySeconds: 0
        periodSeconds: 0
        successThreshold: 0
        tcpSocketPort: 0
        timeoutSeconds: 0
    logging:
        destinationRegionId: 0
        enabled: false
        retentionPolicyPeriod: 0
        topicName: string
    name: string
    projectId: 0
    projectName: string
    readinessProbe:
        enabled: false
        execCommand: string
        failureThreshold: 0
        httpGetHeaders:
            string: string
        httpGetHost: string
        httpGetPath: string
        httpGetPort: 0
        httpGetSchema: string
        initialDelaySeconds: 0
        periodSeconds: 0
        successThreshold: 0
        tcpSocketPort: 0
        timeoutSeconds: 0
    startupProbe:
        enabled: false
        execCommand: string
        failureThreshold: 0
        httpGetHeaders:
            string: string
        httpGetHost: string
        httpGetPath: string
        httpGetPort: 0
        httpGetSchema: string
        initialDelaySeconds: 0
        periodSeconds: 0
        successThreshold: 0
        tcpSocketPort: 0
        timeoutSeconds: 0
    timeout: 0
Copy

InferenceDeployment Resource Properties

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

Inputs

In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

The InferenceDeployment resource accepts the following input properties:

Containers This property is required. List<InferenceDeploymentContainer>
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
FlavorName This property is required. string
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
Image This property is required. string
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
ListeningPort This property is required. double
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
AuthEnabled bool
Set to true to enable API key authentication for the inference instance.
Command string
Command to be executed when running a container from an image.
CredentialsName string
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
Description string
Envs Dictionary<string, string>
Environment variables for the inference instance.
InferenceDeploymentId string
The ID of this resource.
LivenessProbe InferenceDeploymentLivenessProbe
Logging InferenceDeploymentLogging
Name string
The name of the deployment. This should be unique within the scope of the project.
ProjectId double
ProjectName string
ReadinessProbe InferenceDeploymentReadinessProbe
StartupProbe InferenceDeploymentStartupProbe
Timeout double
Containers This property is required. []InferenceDeploymentContainerArgs
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
FlavorName This property is required. string
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
Image This property is required. string
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
ListeningPort This property is required. float64
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
AuthEnabled bool
Set to true to enable API key authentication for the inference instance.
Command string
Command to be executed when running a container from an image.
CredentialsName string
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
Description string
Envs map[string]string
Environment variables for the inference instance.
InferenceDeploymentId string
The ID of this resource.
LivenessProbe InferenceDeploymentLivenessProbeArgs
Logging InferenceDeploymentLoggingArgs
Name string
The name of the deployment. This should be unique within the scope of the project.
ProjectId float64
ProjectName string
ReadinessProbe InferenceDeploymentReadinessProbeArgs
StartupProbe InferenceDeploymentStartupProbeArgs
Timeout float64
containers This property is required. List<InferenceDeploymentContainer>
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
flavorName This property is required. String
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
image This property is required. String
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
listeningPort This property is required. Double
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
authEnabled Boolean
Set to true to enable API key authentication for the inference instance.
command String
Command to be executed when running a container from an image.
credentialsName String
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
description String
envs Map<String,String>
Environment variables for the inference instance.
inferenceDeploymentId String
The ID of this resource.
livenessProbe InferenceDeploymentLivenessProbe
logging InferenceDeploymentLogging
name String
The name of the deployment. This should be unique within the scope of the project.
projectId Double
projectName String
readinessProbe InferenceDeploymentReadinessProbe
startupProbe InferenceDeploymentStartupProbe
timeout Double
containers This property is required. InferenceDeploymentContainer[]
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
flavorName This property is required. string
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
image This property is required. string
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
listeningPort This property is required. number
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
authEnabled boolean
Set to true to enable API key authentication for the inference instance.
command string
Command to be executed when running a container from an image.
credentialsName string
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
description string
envs {[key: string]: string}
Environment variables for the inference instance.
inferenceDeploymentId string
The ID of this resource.
livenessProbe InferenceDeploymentLivenessProbe
logging InferenceDeploymentLogging
name string
The name of the deployment. This should be unique within the scope of the project.
projectId number
projectName string
readinessProbe InferenceDeploymentReadinessProbe
startupProbe InferenceDeploymentStartupProbe
timeout number
containers This property is required. Sequence[InferenceDeploymentContainerArgs]
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
flavor_name This property is required. str
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
image This property is required. str
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
listening_port This property is required. float
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
auth_enabled bool
Set to true to enable API key authentication for the inference instance.
command str
Command to be executed when running a container from an image.
credentials_name str
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
description str
envs Mapping[str, str]
Environment variables for the inference instance.
inference_deployment_id str
The ID of this resource.
liveness_probe InferenceDeploymentLivenessProbeArgs
logging InferenceDeploymentLoggingArgs
name str
The name of the deployment. This should be unique within the scope of the project.
project_id float
project_name str
readiness_probe InferenceDeploymentReadinessProbeArgs
startup_probe InferenceDeploymentStartupProbeArgs
timeout float
containers This property is required. List<Property Map>
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
flavorName This property is required. String
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
image This property is required. String
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
listeningPort This property is required. Number
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
authEnabled Boolean
Set to true to enable API key authentication for the inference instance.
command String
Command to be executed when running a container from an image.
credentialsName String
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
description String
envs Map<String>
Environment variables for the inference instance.
inferenceDeploymentId String
The ID of this resource.
livenessProbe Property Map
logging Property Map
name String
The name of the deployment. This should be unique within the scope of the project.
projectId Number
projectName String
readinessProbe Property Map
startupProbe Property Map
timeout Number

Outputs

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

Address string
CreatedAt string
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
Id string
The provider-assigned unique ID for this managed resource.
Status string
Address string
CreatedAt string
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
Id string
The provider-assigned unique ID for this managed resource.
Status string
address String
createdAt String
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
id String
The provider-assigned unique ID for this managed resource.
status String
address string
createdAt string
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
id string
The provider-assigned unique ID for this managed resource.
status string
address str
created_at str
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
id str
The provider-assigned unique ID for this managed resource.
status str
address String
createdAt String
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
id String
The provider-assigned unique ID for this managed resource.
status String

Look up Existing InferenceDeployment Resource

Get an existing InferenceDeployment 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?: InferenceDeploymentState, opts?: CustomResourceOptions): InferenceDeployment
@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        address: Optional[str] = None,
        auth_enabled: Optional[bool] = None,
        command: Optional[str] = None,
        containers: Optional[Sequence[InferenceDeploymentContainerArgs]] = None,
        created_at: Optional[str] = None,
        credentials_name: Optional[str] = None,
        description: Optional[str] = None,
        envs: Optional[Mapping[str, str]] = None,
        flavor_name: Optional[str] = None,
        image: Optional[str] = None,
        inference_deployment_id: Optional[str] = None,
        listening_port: Optional[float] = None,
        liveness_probe: Optional[InferenceDeploymentLivenessProbeArgs] = None,
        logging: Optional[InferenceDeploymentLoggingArgs] = None,
        name: Optional[str] = None,
        project_id: Optional[float] = None,
        project_name: Optional[str] = None,
        readiness_probe: Optional[InferenceDeploymentReadinessProbeArgs] = None,
        startup_probe: Optional[InferenceDeploymentStartupProbeArgs] = None,
        status: Optional[str] = None,
        timeout: Optional[float] = None) -> InferenceDeployment
func GetInferenceDeployment(ctx *Context, name string, id IDInput, state *InferenceDeploymentState, opts ...ResourceOption) (*InferenceDeployment, error)
public static InferenceDeployment Get(string name, Input<string> id, InferenceDeploymentState? state, CustomResourceOptions? opts = null)
public static InferenceDeployment get(String name, Output<String> id, InferenceDeploymentState state, CustomResourceOptions options)
resources:  _:    type: gcore:InferenceDeployment    get:      id: ${id}
name This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
The unique provider ID of the resource to lookup.
name This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
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:
Address string
AuthEnabled bool
Set to true to enable API key authentication for the inference instance.
Command string
Command to be executed when running a container from an image.
Containers List<InferenceDeploymentContainer>
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
CreatedAt string
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
CredentialsName string
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
Description string
Envs Dictionary<string, string>
Environment variables for the inference instance.
FlavorName string
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
Image string
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
InferenceDeploymentId string
The ID of this resource.
ListeningPort double
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
LivenessProbe InferenceDeploymentLivenessProbe
Logging InferenceDeploymentLogging
Name string
The name of the deployment. This should be unique within the scope of the project.
ProjectId double
ProjectName string
ReadinessProbe InferenceDeploymentReadinessProbe
StartupProbe InferenceDeploymentStartupProbe
Status string
Timeout double
Address string
AuthEnabled bool
Set to true to enable API key authentication for the inference instance.
Command string
Command to be executed when running a container from an image.
Containers []InferenceDeploymentContainerArgs
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
CreatedAt string
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
CredentialsName string
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
Description string
Envs map[string]string
Environment variables for the inference instance.
FlavorName string
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
Image string
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
InferenceDeploymentId string
The ID of this resource.
ListeningPort float64
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
LivenessProbe InferenceDeploymentLivenessProbeArgs
Logging InferenceDeploymentLoggingArgs
Name string
The name of the deployment. This should be unique within the scope of the project.
ProjectId float64
ProjectName string
ReadinessProbe InferenceDeploymentReadinessProbeArgs
StartupProbe InferenceDeploymentStartupProbeArgs
Status string
Timeout float64
address String
authEnabled Boolean
Set to true to enable API key authentication for the inference instance.
command String
Command to be executed when running a container from an image.
containers List<InferenceDeploymentContainer>
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
createdAt String
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
credentialsName String
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
description String
envs Map<String,String>
Environment variables for the inference instance.
flavorName String
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
image String
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
inferenceDeploymentId String
The ID of this resource.
listeningPort Double
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
livenessProbe InferenceDeploymentLivenessProbe
logging InferenceDeploymentLogging
name String
The name of the deployment. This should be unique within the scope of the project.
projectId Double
projectName String
readinessProbe InferenceDeploymentReadinessProbe
startupProbe InferenceDeploymentStartupProbe
status String
timeout Double
address string
authEnabled boolean
Set to true to enable API key authentication for the inference instance.
command string
Command to be executed when running a container from an image.
containers InferenceDeploymentContainer[]
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
createdAt string
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
credentialsName string
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
description string
envs {[key: string]: string}
Environment variables for the inference instance.
flavorName string
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
image string
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
inferenceDeploymentId string
The ID of this resource.
listeningPort number
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
livenessProbe InferenceDeploymentLivenessProbe
logging InferenceDeploymentLogging
name string
The name of the deployment. This should be unique within the scope of the project.
projectId number
projectName string
readinessProbe InferenceDeploymentReadinessProbe
startupProbe InferenceDeploymentStartupProbe
status string
timeout number
address str
auth_enabled bool
Set to true to enable API key authentication for the inference instance.
command str
Command to be executed when running a container from an image.
containers Sequence[InferenceDeploymentContainerArgs]
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
created_at str
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
credentials_name str
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
description str
envs Mapping[str, str]
Environment variables for the inference instance.
flavor_name str
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
image str
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
inference_deployment_id str
The ID of this resource.
listening_port float
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
liveness_probe InferenceDeploymentLivenessProbeArgs
logging InferenceDeploymentLoggingArgs
name str
The name of the deployment. This should be unique within the scope of the project.
project_id float
project_name str
readiness_probe InferenceDeploymentReadinessProbeArgs
startup_probe InferenceDeploymentStartupProbeArgs
status str
timeout float
address String
authEnabled Boolean
Set to true to enable API key authentication for the inference instance.
command String
Command to be executed when running a container from an image.
containers List<Property Map>
A required list of container definitions. Each entry represents a container configuration, and at least one container must be specified. See the nested schema below for further details.
createdAt String
Datetime when the inference deployment was created. The format is 2025-12-28T19:14:44.180394
credentialsName String
Required if using a private image registry. Specifies the name of the credentials to authenticate with the registry where the container image is stored.
description String
envs Map<String>
Environment variables for the inference instance.
flavorName String
Specifies the resource flavor for the container, determining its allocated CPU, memory, and potentially GPU resources.
image String
The container image to be used for deployment. This should be a valid image reference, such as a public or private Docker image (registry.example.com/my-image:latest). Note: If the image is hosted in a private registry, you must specify credentials_name to provide authentication details.
inferenceDeploymentId String
The ID of this resource.
listeningPort Number
The port on which the container will accept incoming traffic. This should match the port your application is configured to listen on within the container.
livenessProbe Property Map
logging Property Map
name String
The name of the deployment. This should be unique within the scope of the project.
projectId Number
projectName String
readinessProbe Property Map
startupProbe Property Map
status String
timeout Number

Supporting Types

InferenceDeploymentContainer
, InferenceDeploymentContainerArgs

CooldownPeriod This property is required. double
Cooldown period between scaling actions in seconds
RegionId This property is required. double
Region id for the container
ScaleMax This property is required. double
Maximum scale for the container
ScaleMin This property is required. double
Minimum scale for the container. It can be set to 0, in which case the container will be downscaled to 0 when there is no load.
PollingInterval double
Polling interval for scaling triggers in seconds
ReadyContainers double
Status of the containers deployment. Number of ready instances
TotalContainers double
Status of the containers deployment. Total number of instances
TriggersCpuThreshold double
CPU trigger threshold configuration
TriggersGpuMemoryThreshold double
GPU memory trigger threshold configuration. Calculated by DCGMFIDEVMEMCOPY_UTIL metric
TriggersGpuUtilizationThreshold double
GPU utilization trigger threshold configuration. Calculated by DCGMFIDEVGPUUTIL metric
TriggersHttpRate double
Request count per 'window' seconds for the http trigger. Required if you use http trigger
TriggersHttpWindow double
Time window for rate calculation in seconds. Required if you use http trigger
TriggersMemoryThreshold double
Memory trigger threshold configuration
TriggersSqsActivationQueueLength double
Number of messages for activation
TriggersSqsAwsEndpoint string
Custom AWS endpoint, left empty to use default aws endpoint
TriggersSqsAwsRegion string
AWS region. Required if you use SQS trigger
TriggersSqsQueueLength double
Number of messages for one replica
TriggersSqsQueueUrl string
URL of the SQS queue. Required if you use SQS trigger
TriggersSqsScaleOnDelayed bool
Scale on delayed messages
TriggersSqsScaleOnFlight bool
Scale on in-flight messages
TriggersSqsSecretName string
Name of the secret with AWS credentials. Required if you use SQS trigger
CooldownPeriod This property is required. float64
Cooldown period between scaling actions in seconds
RegionId This property is required. float64
Region id for the container
ScaleMax This property is required. float64
Maximum scale for the container
ScaleMin This property is required. float64
Minimum scale for the container. It can be set to 0, in which case the container will be downscaled to 0 when there is no load.
PollingInterval float64
Polling interval for scaling triggers in seconds
ReadyContainers float64
Status of the containers deployment. Number of ready instances
TotalContainers float64
Status of the containers deployment. Total number of instances
TriggersCpuThreshold float64
CPU trigger threshold configuration
TriggersGpuMemoryThreshold float64
GPU memory trigger threshold configuration. Calculated by DCGMFIDEVMEMCOPY_UTIL metric
TriggersGpuUtilizationThreshold float64
GPU utilization trigger threshold configuration. Calculated by DCGMFIDEVGPUUTIL metric
TriggersHttpRate float64
Request count per 'window' seconds for the http trigger. Required if you use http trigger
TriggersHttpWindow float64
Time window for rate calculation in seconds. Required if you use http trigger
TriggersMemoryThreshold float64
Memory trigger threshold configuration
TriggersSqsActivationQueueLength float64
Number of messages for activation
TriggersSqsAwsEndpoint string
Custom AWS endpoint, left empty to use default aws endpoint
TriggersSqsAwsRegion string
AWS region. Required if you use SQS trigger
TriggersSqsQueueLength float64
Number of messages for one replica
TriggersSqsQueueUrl string
URL of the SQS queue. Required if you use SQS trigger
TriggersSqsScaleOnDelayed bool
Scale on delayed messages
TriggersSqsScaleOnFlight bool
Scale on in-flight messages
TriggersSqsSecretName string
Name of the secret with AWS credentials. Required if you use SQS trigger
cooldownPeriod This property is required. Double
Cooldown period between scaling actions in seconds
regionId This property is required. Double
Region id for the container
scaleMax This property is required. Double
Maximum scale for the container
scaleMin This property is required. Double
Minimum scale for the container. It can be set to 0, in which case the container will be downscaled to 0 when there is no load.
pollingInterval Double
Polling interval for scaling triggers in seconds
readyContainers Double
Status of the containers deployment. Number of ready instances
totalContainers Double
Status of the containers deployment. Total number of instances
triggersCpuThreshold Double
CPU trigger threshold configuration
triggersGpuMemoryThreshold Double
GPU memory trigger threshold configuration. Calculated by DCGMFIDEVMEMCOPY_UTIL metric
triggersGpuUtilizationThreshold Double
GPU utilization trigger threshold configuration. Calculated by DCGMFIDEVGPUUTIL metric
triggersHttpRate Double
Request count per 'window' seconds for the http trigger. Required if you use http trigger
triggersHttpWindow Double
Time window for rate calculation in seconds. Required if you use http trigger
triggersMemoryThreshold Double
Memory trigger threshold configuration
triggersSqsActivationQueueLength Double
Number of messages for activation
triggersSqsAwsEndpoint String
Custom AWS endpoint, left empty to use default aws endpoint
triggersSqsAwsRegion String
AWS region. Required if you use SQS trigger
triggersSqsQueueLength Double
Number of messages for one replica
triggersSqsQueueUrl String
URL of the SQS queue. Required if you use SQS trigger
triggersSqsScaleOnDelayed Boolean
Scale on delayed messages
triggersSqsScaleOnFlight Boolean
Scale on in-flight messages
triggersSqsSecretName String
Name of the secret with AWS credentials. Required if you use SQS trigger
cooldownPeriod This property is required. number
Cooldown period between scaling actions in seconds
regionId This property is required. number
Region id for the container
scaleMax This property is required. number
Maximum scale for the container
scaleMin This property is required. number
Minimum scale for the container. It can be set to 0, in which case the container will be downscaled to 0 when there is no load.
pollingInterval number
Polling interval for scaling triggers in seconds
readyContainers number
Status of the containers deployment. Number of ready instances
totalContainers number
Status of the containers deployment. Total number of instances
triggersCpuThreshold number
CPU trigger threshold configuration
triggersGpuMemoryThreshold number
GPU memory trigger threshold configuration. Calculated by DCGMFIDEVMEMCOPY_UTIL metric
triggersGpuUtilizationThreshold number
GPU utilization trigger threshold configuration. Calculated by DCGMFIDEVGPUUTIL metric
triggersHttpRate number
Request count per 'window' seconds for the http trigger. Required if you use http trigger
triggersHttpWindow number
Time window for rate calculation in seconds. Required if you use http trigger
triggersMemoryThreshold number
Memory trigger threshold configuration
triggersSqsActivationQueueLength number
Number of messages for activation
triggersSqsAwsEndpoint string
Custom AWS endpoint, left empty to use default aws endpoint
triggersSqsAwsRegion string
AWS region. Required if you use SQS trigger
triggersSqsQueueLength number
Number of messages for one replica
triggersSqsQueueUrl string
URL of the SQS queue. Required if you use SQS trigger
triggersSqsScaleOnDelayed boolean
Scale on delayed messages
triggersSqsScaleOnFlight boolean
Scale on in-flight messages
triggersSqsSecretName string
Name of the secret with AWS credentials. Required if you use SQS trigger
cooldown_period This property is required. float
Cooldown period between scaling actions in seconds
region_id This property is required. float
Region id for the container
scale_max This property is required. float
Maximum scale for the container
scale_min This property is required. float
Minimum scale for the container. It can be set to 0, in which case the container will be downscaled to 0 when there is no load.
polling_interval float
Polling interval for scaling triggers in seconds
ready_containers float
Status of the containers deployment. Number of ready instances
total_containers float
Status of the containers deployment. Total number of instances
triggers_cpu_threshold float
CPU trigger threshold configuration
triggers_gpu_memory_threshold float
GPU memory trigger threshold configuration. Calculated by DCGMFIDEVMEMCOPY_UTIL metric
triggers_gpu_utilization_threshold float
GPU utilization trigger threshold configuration. Calculated by DCGMFIDEVGPUUTIL metric
triggers_http_rate float
Request count per 'window' seconds for the http trigger. Required if you use http trigger
triggers_http_window float
Time window for rate calculation in seconds. Required if you use http trigger
triggers_memory_threshold float
Memory trigger threshold configuration
triggers_sqs_activation_queue_length float
Number of messages for activation
triggers_sqs_aws_endpoint str
Custom AWS endpoint, left empty to use default aws endpoint
triggers_sqs_aws_region str
AWS region. Required if you use SQS trigger
triggers_sqs_queue_length float
Number of messages for one replica
triggers_sqs_queue_url str
URL of the SQS queue. Required if you use SQS trigger
triggers_sqs_scale_on_delayed bool
Scale on delayed messages
triggers_sqs_scale_on_flight bool
Scale on in-flight messages
triggers_sqs_secret_name str
Name of the secret with AWS credentials. Required if you use SQS trigger
cooldownPeriod This property is required. Number
Cooldown period between scaling actions in seconds
regionId This property is required. Number
Region id for the container
scaleMax This property is required. Number
Maximum scale for the container
scaleMin This property is required. Number
Minimum scale for the container. It can be set to 0, in which case the container will be downscaled to 0 when there is no load.
pollingInterval Number
Polling interval for scaling triggers in seconds
readyContainers Number
Status of the containers deployment. Number of ready instances
totalContainers Number
Status of the containers deployment. Total number of instances
triggersCpuThreshold Number
CPU trigger threshold configuration
triggersGpuMemoryThreshold Number
GPU memory trigger threshold configuration. Calculated by DCGMFIDEVMEMCOPY_UTIL metric
triggersGpuUtilizationThreshold Number
GPU utilization trigger threshold configuration. Calculated by DCGMFIDEVGPUUTIL metric
triggersHttpRate Number
Request count per 'window' seconds for the http trigger. Required if you use http trigger
triggersHttpWindow Number
Time window for rate calculation in seconds. Required if you use http trigger
triggersMemoryThreshold Number
Memory trigger threshold configuration
triggersSqsActivationQueueLength Number
Number of messages for activation
triggersSqsAwsEndpoint String
Custom AWS endpoint, left empty to use default aws endpoint
triggersSqsAwsRegion String
AWS region. Required if you use SQS trigger
triggersSqsQueueLength Number
Number of messages for one replica
triggersSqsQueueUrl String
URL of the SQS queue. Required if you use SQS trigger
triggersSqsScaleOnDelayed Boolean
Scale on delayed messages
triggersSqsScaleOnFlight Boolean
Scale on in-flight messages
triggersSqsSecretName String
Name of the secret with AWS credentials. Required if you use SQS trigger

InferenceDeploymentLivenessProbe
, InferenceDeploymentLivenessProbeArgs

Enabled This property is required. bool
Enable or disable probe
ExecCommand string
Command to execute in the container to determine the health
FailureThreshold double
Number of failed probes before the container is considered unhealthy
HttpGetHeaders Dictionary<string, string>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
HttpGetHost string
Host name to connect to, valid only for HTTP probes
HttpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
HttpGetPort double
Number of the port to access on the HTTP server, valid only for HTTP probes
HttpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
InitialDelaySeconds double
Number of seconds after the container has started before liveness probes are initiated
PeriodSeconds double
How often (in seconds) to perform the probe
SuccessThreshold double
Minimum consecutive successes for the probe to be considered successful after having failed
TcpSocketPort double
Port to connect to
TimeoutSeconds double
Number of seconds after which the probe times out
Enabled This property is required. bool
Enable or disable probe
ExecCommand string
Command to execute in the container to determine the health
FailureThreshold float64
Number of failed probes before the container is considered unhealthy
HttpGetHeaders map[string]string
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
HttpGetHost string
Host name to connect to, valid only for HTTP probes
HttpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
HttpGetPort float64
Number of the port to access on the HTTP server, valid only for HTTP probes
HttpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
InitialDelaySeconds float64
Number of seconds after the container has started before liveness probes are initiated
PeriodSeconds float64
How often (in seconds) to perform the probe
SuccessThreshold float64
Minimum consecutive successes for the probe to be considered successful after having failed
TcpSocketPort float64
Port to connect to
TimeoutSeconds float64
Number of seconds after which the probe times out
enabled This property is required. Boolean
Enable or disable probe
execCommand String
Command to execute in the container to determine the health
failureThreshold Double
Number of failed probes before the container is considered unhealthy
httpGetHeaders Map<String,String>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost String
Host name to connect to, valid only for HTTP probes
httpGetPath String
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort Double
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema String
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds Double
Number of seconds after the container has started before liveness probes are initiated
periodSeconds Double
How often (in seconds) to perform the probe
successThreshold Double
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort Double
Port to connect to
timeoutSeconds Double
Number of seconds after which the probe times out
enabled This property is required. boolean
Enable or disable probe
execCommand string
Command to execute in the container to determine the health
failureThreshold number
Number of failed probes before the container is considered unhealthy
httpGetHeaders {[key: string]: string}
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost string
Host name to connect to, valid only for HTTP probes
httpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort number
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds number
Number of seconds after the container has started before liveness probes are initiated
periodSeconds number
How often (in seconds) to perform the probe
successThreshold number
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort number
Port to connect to
timeoutSeconds number
Number of seconds after which the probe times out
enabled This property is required. bool
Enable or disable probe
exec_command str
Command to execute in the container to determine the health
failure_threshold float
Number of failed probes before the container is considered unhealthy
http_get_headers Mapping[str, str]
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
http_get_host str
Host name to connect to, valid only for HTTP probes
http_get_path str
Path to access on the HTTP server, valid only for HTTP probes
http_get_port float
Number of the port to access on the HTTP server, valid only for HTTP probes
http_get_schema str
Scheme to use for connecting to the host, valid only for HTTP probes
initial_delay_seconds float
Number of seconds after the container has started before liveness probes are initiated
period_seconds float
How often (in seconds) to perform the probe
success_threshold float
Minimum consecutive successes for the probe to be considered successful after having failed
tcp_socket_port float
Port to connect to
timeout_seconds float
Number of seconds after which the probe times out
enabled This property is required. Boolean
Enable or disable probe
execCommand String
Command to execute in the container to determine the health
failureThreshold Number
Number of failed probes before the container is considered unhealthy
httpGetHeaders Map<String>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost String
Host name to connect to, valid only for HTTP probes
httpGetPath String
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort Number
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema String
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds Number
Number of seconds after the container has started before liveness probes are initiated
periodSeconds Number
How often (in seconds) to perform the probe
successThreshold Number
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort Number
Port to connect to
timeoutSeconds Number
Number of seconds after which the probe times out

InferenceDeploymentLogging
, InferenceDeploymentLoggingArgs

InferenceDeploymentReadinessProbe
, InferenceDeploymentReadinessProbeArgs

Enabled This property is required. bool
Enable or disable probe
ExecCommand string
Command to execute in the container to determine the health
FailureThreshold double
Number of failed probes before the container is considered unhealthy
HttpGetHeaders Dictionary<string, string>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
HttpGetHost string
Host name to connect to, valid only for HTTP probes
HttpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
HttpGetPort double
Number of the port to access on the HTTP server, valid only for HTTP probes
HttpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
InitialDelaySeconds double
Number of seconds after the container has started before liveness probes are initiated
PeriodSeconds double
How often (in seconds) to perform the probe
SuccessThreshold double
Minimum consecutive successes for the probe to be considered successful after having failed
TcpSocketPort double
Port to connect to
TimeoutSeconds double
Number of seconds after which the probe times out
Enabled This property is required. bool
Enable or disable probe
ExecCommand string
Command to execute in the container to determine the health
FailureThreshold float64
Number of failed probes before the container is considered unhealthy
HttpGetHeaders map[string]string
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
HttpGetHost string
Host name to connect to, valid only for HTTP probes
HttpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
HttpGetPort float64
Number of the port to access on the HTTP server, valid only for HTTP probes
HttpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
InitialDelaySeconds float64
Number of seconds after the container has started before liveness probes are initiated
PeriodSeconds float64
How often (in seconds) to perform the probe
SuccessThreshold float64
Minimum consecutive successes for the probe to be considered successful after having failed
TcpSocketPort float64
Port to connect to
TimeoutSeconds float64
Number of seconds after which the probe times out
enabled This property is required. Boolean
Enable or disable probe
execCommand String
Command to execute in the container to determine the health
failureThreshold Double
Number of failed probes before the container is considered unhealthy
httpGetHeaders Map<String,String>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost String
Host name to connect to, valid only for HTTP probes
httpGetPath String
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort Double
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema String
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds Double
Number of seconds after the container has started before liveness probes are initiated
periodSeconds Double
How often (in seconds) to perform the probe
successThreshold Double
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort Double
Port to connect to
timeoutSeconds Double
Number of seconds after which the probe times out
enabled This property is required. boolean
Enable or disable probe
execCommand string
Command to execute in the container to determine the health
failureThreshold number
Number of failed probes before the container is considered unhealthy
httpGetHeaders {[key: string]: string}
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost string
Host name to connect to, valid only for HTTP probes
httpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort number
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds number
Number of seconds after the container has started before liveness probes are initiated
periodSeconds number
How often (in seconds) to perform the probe
successThreshold number
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort number
Port to connect to
timeoutSeconds number
Number of seconds after which the probe times out
enabled This property is required. bool
Enable or disable probe
exec_command str
Command to execute in the container to determine the health
failure_threshold float
Number of failed probes before the container is considered unhealthy
http_get_headers Mapping[str, str]
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
http_get_host str
Host name to connect to, valid only for HTTP probes
http_get_path str
Path to access on the HTTP server, valid only for HTTP probes
http_get_port float
Number of the port to access on the HTTP server, valid only for HTTP probes
http_get_schema str
Scheme to use for connecting to the host, valid only for HTTP probes
initial_delay_seconds float
Number of seconds after the container has started before liveness probes are initiated
period_seconds float
How often (in seconds) to perform the probe
success_threshold float
Minimum consecutive successes for the probe to be considered successful after having failed
tcp_socket_port float
Port to connect to
timeout_seconds float
Number of seconds after which the probe times out
enabled This property is required. Boolean
Enable or disable probe
execCommand String
Command to execute in the container to determine the health
failureThreshold Number
Number of failed probes before the container is considered unhealthy
httpGetHeaders Map<String>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost String
Host name to connect to, valid only for HTTP probes
httpGetPath String
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort Number
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema String
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds Number
Number of seconds after the container has started before liveness probes are initiated
periodSeconds Number
How often (in seconds) to perform the probe
successThreshold Number
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort Number
Port to connect to
timeoutSeconds Number
Number of seconds after which the probe times out

InferenceDeploymentStartupProbe
, InferenceDeploymentStartupProbeArgs

Enabled This property is required. bool
Enable or disable probe
ExecCommand string
Command to execute in the container to determine the health
FailureThreshold double
Number of failed probes before the container is considered unhealthy
HttpGetHeaders Dictionary<string, string>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
HttpGetHost string
Host name to connect to, valid only for HTTP probes
HttpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
HttpGetPort double
Number of the port to access on the HTTP server, valid only for HTTP probes
HttpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
InitialDelaySeconds double
Number of seconds after the container has started before liveness probes are initiated
PeriodSeconds double
How often (in seconds) to perform the probe
SuccessThreshold double
Minimum consecutive successes for the probe to be considered successful after having failed
TcpSocketPort double
Port to connect to
TimeoutSeconds double
Number of seconds after which the probe times out
Enabled This property is required. bool
Enable or disable probe
ExecCommand string
Command to execute in the container to determine the health
FailureThreshold float64
Number of failed probes before the container is considered unhealthy
HttpGetHeaders map[string]string
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
HttpGetHost string
Host name to connect to, valid only for HTTP probes
HttpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
HttpGetPort float64
Number of the port to access on the HTTP server, valid only for HTTP probes
HttpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
InitialDelaySeconds float64
Number of seconds after the container has started before liveness probes are initiated
PeriodSeconds float64
How often (in seconds) to perform the probe
SuccessThreshold float64
Minimum consecutive successes for the probe to be considered successful after having failed
TcpSocketPort float64
Port to connect to
TimeoutSeconds float64
Number of seconds after which the probe times out
enabled This property is required. Boolean
Enable or disable probe
execCommand String
Command to execute in the container to determine the health
failureThreshold Double
Number of failed probes before the container is considered unhealthy
httpGetHeaders Map<String,String>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost String
Host name to connect to, valid only for HTTP probes
httpGetPath String
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort Double
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema String
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds Double
Number of seconds after the container has started before liveness probes are initiated
periodSeconds Double
How often (in seconds) to perform the probe
successThreshold Double
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort Double
Port to connect to
timeoutSeconds Double
Number of seconds after which the probe times out
enabled This property is required. boolean
Enable or disable probe
execCommand string
Command to execute in the container to determine the health
failureThreshold number
Number of failed probes before the container is considered unhealthy
httpGetHeaders {[key: string]: string}
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost string
Host name to connect to, valid only for HTTP probes
httpGetPath string
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort number
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema string
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds number
Number of seconds after the container has started before liveness probes are initiated
periodSeconds number
How often (in seconds) to perform the probe
successThreshold number
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort number
Port to connect to
timeoutSeconds number
Number of seconds after which the probe times out
enabled This property is required. bool
Enable or disable probe
exec_command str
Command to execute in the container to determine the health
failure_threshold float
Number of failed probes before the container is considered unhealthy
http_get_headers Mapping[str, str]
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
http_get_host str
Host name to connect to, valid only for HTTP probes
http_get_path str
Path to access on the HTTP server, valid only for HTTP probes
http_get_port float
Number of the port to access on the HTTP server, valid only for HTTP probes
http_get_schema str
Scheme to use for connecting to the host, valid only for HTTP probes
initial_delay_seconds float
Number of seconds after the container has started before liveness probes are initiated
period_seconds float
How often (in seconds) to perform the probe
success_threshold float
Minimum consecutive successes for the probe to be considered successful after having failed
tcp_socket_port float
Port to connect to
timeout_seconds float
Number of seconds after which the probe times out
enabled This property is required. Boolean
Enable or disable probe
execCommand String
Command to execute in the container to determine the health
failureThreshold Number
Number of failed probes before the container is considered unhealthy
httpGetHeaders Map<String>
HTTP headers to use when sending a HTTP GET request, valid only for HTTP probes
httpGetHost String
Host name to connect to, valid only for HTTP probes
httpGetPath String
Path to access on the HTTP server, valid only for HTTP probes
httpGetPort Number
Number of the port to access on the HTTP server, valid only for HTTP probes
httpGetSchema String
Scheme to use for connecting to the host, valid only for HTTP probes
initialDelaySeconds Number
Number of seconds after the container has started before liveness probes are initiated
periodSeconds Number
How often (in seconds) to perform the probe
successThreshold Number
Minimum consecutive successes for the probe to be considered successful after having failed
tcpSocketPort Number
Port to connect to
timeoutSeconds Number
Number of seconds after which the probe times out

Import

import using <project_id>:<inference_deployment_name> format

$ pulumi import gcore:index/inferenceDeployment:InferenceDeployment inf1 1:my-first-inference
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To learn more about importing existing cloud resources, see Importing resources.

Package Details

Repository
gcore g-core/terraform-provider-gcore
License
Notes
This Pulumi package is based on the gcore Terraform Provider.
gcore 0.19.0 published on Monday, Apr 14, 2025 by g-core
g-core/terraform-provider-gcore