aws.sagemaker.getPrebuiltEcrImage

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AWS v6.71.0 published on Friday, Mar 7, 2025 by Pulumi

NOTE: The AWS provider creates a validly constructed registry_path but does not verify that the registry_path corresponds to an existing image. For example, using a registry_path containing an image_tag that does not correspond to a Docker image in the ECR repository, will result in an error.

Example Usage

Basic usage:

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

const test = aws.sagemaker.getPrebuiltEcrImage({
    repositoryName: "sagemaker-scikit-learn",
    imageTag: "2.2-1.0.11.0",
});

import pulumi
import pulumi_aws as aws

test = aws.sagemaker.get_prebuilt_ecr_image(repository_name="sagemaker-scikit-learn",
    image_tag="2.2-1.0.11.0")

package main

import (
	"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := sagemaker.GetPrebuiltEcrImage(ctx, &sagemaker.GetPrebuiltEcrImageArgs{
			RepositoryName: "sagemaker-scikit-learn",
			ImageTag:       pulumi.StringRef("2.2-1.0.11.0"),
		}, nil)
		if err != nil {
			return err
		}
		return nil
	})
}

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

return await Deployment.RunAsync(() => 
{
    var test = Aws.Sagemaker.GetPrebuiltEcrImage.Invoke(new()
    {
        RepositoryName = "sagemaker-scikit-learn",
        ImageTag = "2.2-1.0.11.0",
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.sagemaker.SagemakerFunctions;
import com.pulumi.aws.sagemaker.inputs.GetPrebuiltEcrImageArgs;
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 test = SagemakerFunctions.getPrebuiltEcrImage(GetPrebuiltEcrImageArgs.builder()
            .repositoryName("sagemaker-scikit-learn")
            .imageTag("2.2-1.0.11.0")
            .build());

    }
}

variables:
  test:
    fn::invoke:
      function: aws:sagemaker:getPrebuiltEcrImage
      arguments:
        repositoryName: sagemaker-scikit-learn
        imageTag: 2.2-1.0.11.0

Using getPrebuiltEcrImage

Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.

function getPrebuiltEcrImage(args: GetPrebuiltEcrImageArgs, opts?: InvokeOptions): Promise<GetPrebuiltEcrImageResult>
function getPrebuiltEcrImageOutput(args: GetPrebuiltEcrImageOutputArgs, opts?: InvokeOptions): Output<GetPrebuiltEcrImageResult>

def get_prebuilt_ecr_image(dns_suffix: Optional[str] = None,
                           image_tag: Optional[str] = None,
                           region: Optional[str] = None,
                           repository_name: Optional[str] = None,
                           opts: Optional[InvokeOptions] = None) -> GetPrebuiltEcrImageResult
def get_prebuilt_ecr_image_output(dns_suffix: Optional[pulumi.Input[str]] = None,
                           image_tag: Optional[pulumi.Input[str]] = None,
                           region: Optional[pulumi.Input[str]] = None,
                           repository_name: Optional[pulumi.Input[str]] = None,
                           opts: Optional[InvokeOptions] = None) -> Output[GetPrebuiltEcrImageResult]

func GetPrebuiltEcrImage(ctx *Context, args *GetPrebuiltEcrImageArgs, opts ...InvokeOption) (*GetPrebuiltEcrImageResult, error)
func GetPrebuiltEcrImageOutput(ctx *Context, args *GetPrebuiltEcrImageOutputArgs, opts ...InvokeOption) GetPrebuiltEcrImageResultOutput

> Note: This function is named GetPrebuiltEcrImage in the Go SDK.

public static class GetPrebuiltEcrImage 
{
    public static Task<GetPrebuiltEcrImageResult> InvokeAsync(GetPrebuiltEcrImageArgs args, InvokeOptions? opts = null)
    public static Output<GetPrebuiltEcrImageResult> Invoke(GetPrebuiltEcrImageInvokeArgs args, InvokeOptions? opts = null)
}

public static CompletableFuture<GetPrebuiltEcrImageResult> getPrebuiltEcrImage(GetPrebuiltEcrImageArgs args, InvokeOptions options)
public static Output<GetPrebuiltEcrImageResult> getPrebuiltEcrImage(GetPrebuiltEcrImageArgs args, InvokeOptions options)

fn::invoke:
  function: aws:sagemaker/getPrebuiltEcrImage:getPrebuiltEcrImage
  arguments:
    # arguments dictionary

The following arguments are supported:

RepositoryName string: Name of the repository, which is generally the algorithm or library. Values include autogluon-inference, autogluon-training, blazingtext, djl-inference, factorization-machines, forecasting-deepar, huggingface-pytorch-inference, huggingface-pytorch-inference-neuron, huggingface-pytorch-inference-neuronx, huggingface-pytorch-tgi-inference, huggingface-pytorch-training, huggingface-pytorch-training-neuronx, huggingface-pytorch-trcomp-training, huggingface-tensorflow-inference, huggingface-tensorflow-training, huggingface-tensorflow-trcomp-training, image-classification, image-classification-neo, ipinsights, kmeans, knn, lda, linear-learner, mxnet-inference, mxnet-inference-eia, mxnet-training, ntm, object-detection, object2vec, pca, pytorch-inference, pytorch-inference-eia, pytorch-inference-graviton, pytorch-inference-neuronx, pytorch-training, pytorch-training-neuronx, pytorch-trcomp-training, randomcutforest, sagemaker-base-python, sagemaker-chainer, sagemaker-clarify-processing, sagemaker-data-wrangler-container, sagemaker-debugger-rules, sagemaker-geospatial-v1-0, sagemaker-inference-mxnet, sagemaker-inference-pytorch, sagemaker-inference-tensorflow, sagemaker-model-monitor-analyzer, sagemaker-mxnet, sagemaker-mxnet-eia, sagemaker-mxnet-serving, sagemaker-mxnet-serving-eia, sagemaker-neo-mxnet, sagemaker-neo-pytorch, sagemaker-neo-tensorflow, sagemaker-pytorch, sagemaker-rl-coach-container, sagemaker-rl-mxnet, sagemaker-rl-ray-container, sagemaker-rl-tensorflow, sagemaker-rl-vw-container, sagemaker-scikit-learn, sagemaker-spark-processing, sagemaker-sparkml-serving, sagemaker-tensorflow, sagemaker-tensorflow-eia, sagemaker-tensorflow-scriptmode, sagemaker-tensorflow-serving, sagemaker-tensorflow-serving-eia, sagemaker-tritonserver, sagemaker-xgboost, semantic-segmentation, seq2seq, stabilityai-pytorch-inference, tei, tei-cpu, tensorflow-inference, tensorflow-inference-eia, tensorflow-inference-graviton, tensorflow-training, and xgboost-neo.
DnsSuffix string: DNS suffix to use in the registry path. If not specified, the AWS provider sets it to the DNS suffix for the current region.
ImageTag string: Image tag for the Docker image. If not specified, the AWS provider sets the value to 1, which for many repositories indicates the latest version. Some repositories, such as XGBoost, do not support 1 or latest and specific version must be used.
Region string: Region to use in the registry path. If not specified, the AWS provider sets it to the current region.

RepositoryName string: Name of the repository, which is generally the algorithm or library. Values include autogluon-inference, autogluon-training, blazingtext, djl-inference, factorization-machines, forecasting-deepar, huggingface-pytorch-inference, huggingface-pytorch-inference-neuron, huggingface-pytorch-inference-neuronx, huggingface-pytorch-tgi-inference, huggingface-pytorch-training, huggingface-pytorch-training-neuronx, huggingface-pytorch-trcomp-training, huggingface-tensorflow-inference, huggingface-tensorflow-training, huggingface-tensorflow-trcomp-training, image-classification, image-classification-neo, ipinsights, kmeans, knn, lda, linear-learner, mxnet-inference, mxnet-inference-eia, mxnet-training, ntm, object-detection, object2vec, pca, pytorch-inference, pytorch-inference-eia, pytorch-inference-graviton, pytorch-inference-neuronx, pytorch-training, pytorch-training-neuronx, pytorch-trcomp-training, randomcutforest, sagemaker-base-python, sagemaker-chainer, sagemaker-clarify-processing, sagemaker-data-wrangler-container, sagemaker-debugger-rules, sagemaker-geospatial-v1-0, sagemaker-inference-mxnet, sagemaker-inference-pytorch, sagemaker-inference-tensorflow, sagemaker-model-monitor-analyzer, sagemaker-mxnet, sagemaker-mxnet-eia, sagemaker-mxnet-serving, sagemaker-mxnet-serving-eia, sagemaker-neo-mxnet, sagemaker-neo-pytorch, sagemaker-neo-tensorflow, sagemaker-pytorch, sagemaker-rl-coach-container, sagemaker-rl-mxnet, sagemaker-rl-ray-container, sagemaker-rl-tensorflow, sagemaker-rl-vw-container, sagemaker-scikit-learn, sagemaker-spark-processing, sagemaker-sparkml-serving, sagemaker-tensorflow, sagemaker-tensorflow-eia, sagemaker-tensorflow-scriptmode, sagemaker-tensorflow-serving, sagemaker-tensorflow-serving-eia, sagemaker-tritonserver, sagemaker-xgboost, semantic-segmentation, seq2seq, stabilityai-pytorch-inference, tei, tei-cpu, tensorflow-inference, tensorflow-inference-eia, tensorflow-inference-graviton, tensorflow-training, and xgboost-neo.
DnsSuffix string: DNS suffix to use in the registry path. If not specified, the AWS provider sets it to the DNS suffix for the current region.
ImageTag string: Image tag for the Docker image. If not specified, the AWS provider sets the value to 1, which for many repositories indicates the latest version. Some repositories, such as XGBoost, do not support 1 or latest and specific version must be used.
Region string: Region to use in the registry path. If not specified, the AWS provider sets it to the current region.

repositoryName String: Name of the repository, which is generally the algorithm or library. Values include autogluon-inference, autogluon-training, blazingtext, djl-inference, factorization-machines, forecasting-deepar, huggingface-pytorch-inference, huggingface-pytorch-inference-neuron, huggingface-pytorch-inference-neuronx, huggingface-pytorch-tgi-inference, huggingface-pytorch-training, huggingface-pytorch-training-neuronx, huggingface-pytorch-trcomp-training, huggingface-tensorflow-inference, huggingface-tensorflow-training, huggingface-tensorflow-trcomp-training, image-classification, image-classification-neo, ipinsights, kmeans, knn, lda, linear-learner, mxnet-inference, mxnet-inference-eia, mxnet-training, ntm, object-detection, object2vec, pca, pytorch-inference, pytorch-inference-eia, pytorch-inference-graviton, pytorch-inference-neuronx, pytorch-training, pytorch-training-neuronx, pytorch-trcomp-training, randomcutforest, sagemaker-base-python, sagemaker-chainer, sagemaker-clarify-processing, sagemaker-data-wrangler-container, sagemaker-debugger-rules, sagemaker-geospatial-v1-0, sagemaker-inference-mxnet, sagemaker-inference-pytorch, sagemaker-inference-tensorflow, sagemaker-model-monitor-analyzer, sagemaker-mxnet, sagemaker-mxnet-eia, sagemaker-mxnet-serving, sagemaker-mxnet-serving-eia, sagemaker-neo-mxnet, sagemaker-neo-pytorch, sagemaker-neo-tensorflow, sagemaker-pytorch, sagemaker-rl-coach-container, sagemaker-rl-mxnet, sagemaker-rl-ray-container, sagemaker-rl-tensorflow, sagemaker-rl-vw-container, sagemaker-scikit-learn, sagemaker-spark-processing, sagemaker-sparkml-serving, sagemaker-tensorflow, sagemaker-tensorflow-eia, sagemaker-tensorflow-scriptmode, sagemaker-tensorflow-serving, sagemaker-tensorflow-serving-eia, sagemaker-tritonserver, sagemaker-xgboost, semantic-segmentation, seq2seq, stabilityai-pytorch-inference, tei, tei-cpu, tensorflow-inference, tensorflow-inference-eia, tensorflow-inference-graviton, tensorflow-training, and xgboost-neo.
dnsSuffix String: DNS suffix to use in the registry path. If not specified, the AWS provider sets it to the DNS suffix for the current region.
imageTag String: Image tag for the Docker image. If not specified, the AWS provider sets the value to 1, which for many repositories indicates the latest version. Some repositories, such as XGBoost, do not support 1 or latest and specific version must be used.
region String: Region to use in the registry path. If not specified, the AWS provider sets it to the current region.

repositoryName string: Name of the repository, which is generally the algorithm or library. Values include autogluon-inference, autogluon-training, blazingtext, djl-inference, factorization-machines, forecasting-deepar, huggingface-pytorch-inference, huggingface-pytorch-inference-neuron, huggingface-pytorch-inference-neuronx, huggingface-pytorch-tgi-inference, huggingface-pytorch-training, huggingface-pytorch-training-neuronx, huggingface-pytorch-trcomp-training, huggingface-tensorflow-inference, huggingface-tensorflow-training, huggingface-tensorflow-trcomp-training, image-classification, image-classification-neo, ipinsights, kmeans, knn, lda, linear-learner, mxnet-inference, mxnet-inference-eia, mxnet-training, ntm, object-detection, object2vec, pca, pytorch-inference, pytorch-inference-eia, pytorch-inference-graviton, pytorch-inference-neuronx, pytorch-training, pytorch-training-neuronx, pytorch-trcomp-training, randomcutforest, sagemaker-base-python, sagemaker-chainer, sagemaker-clarify-processing, sagemaker-data-wrangler-container, sagemaker-debugger-rules, sagemaker-geospatial-v1-0, sagemaker-inference-mxnet, sagemaker-inference-pytorch, sagemaker-inference-tensorflow, sagemaker-model-monitor-analyzer, sagemaker-mxnet, sagemaker-mxnet-eia, sagemaker-mxnet-serving, sagemaker-mxnet-serving-eia, sagemaker-neo-mxnet, sagemaker-neo-pytorch, sagemaker-neo-tensorflow, sagemaker-pytorch, sagemaker-rl-coach-container, sagemaker-rl-mxnet, sagemaker-rl-ray-container, sagemaker-rl-tensorflow, sagemaker-rl-vw-container, sagemaker-scikit-learn, sagemaker-spark-processing, sagemaker-sparkml-serving, sagemaker-tensorflow, sagemaker-tensorflow-eia, sagemaker-tensorflow-scriptmode, sagemaker-tensorflow-serving, sagemaker-tensorflow-serving-eia, sagemaker-tritonserver, sagemaker-xgboost, semantic-segmentation, seq2seq, stabilityai-pytorch-inference, tei, tei-cpu, tensorflow-inference, tensorflow-inference-eia, tensorflow-inference-graviton, tensorflow-training, and xgboost-neo.
dnsSuffix string: DNS suffix to use in the registry path. If not specified, the AWS provider sets it to the DNS suffix for the current region.
imageTag string: Image tag for the Docker image. If not specified, the AWS provider sets the value to 1, which for many repositories indicates the latest version. Some repositories, such as XGBoost, do not support 1 or latest and specific version must be used.
region string: Region to use in the registry path. If not specified, the AWS provider sets it to the current region.

repository_name str: Name of the repository, which is generally the algorithm or library. Values include autogluon-inference, autogluon-training, blazingtext, djl-inference, factorization-machines, forecasting-deepar, huggingface-pytorch-inference, huggingface-pytorch-inference-neuron, huggingface-pytorch-inference-neuronx, huggingface-pytorch-tgi-inference, huggingface-pytorch-training, huggingface-pytorch-training-neuronx, huggingface-pytorch-trcomp-training, huggingface-tensorflow-inference, huggingface-tensorflow-training, huggingface-tensorflow-trcomp-training, image-classification, image-classification-neo, ipinsights, kmeans, knn, lda, linear-learner, mxnet-inference, mxnet-inference-eia, mxnet-training, ntm, object-detection, object2vec, pca, pytorch-inference, pytorch-inference-eia, pytorch-inference-graviton, pytorch-inference-neuronx, pytorch-training, pytorch-training-neuronx, pytorch-trcomp-training, randomcutforest, sagemaker-base-python, sagemaker-chainer, sagemaker-clarify-processing, sagemaker-data-wrangler-container, sagemaker-debugger-rules, sagemaker-geospatial-v1-0, sagemaker-inference-mxnet, sagemaker-inference-pytorch, sagemaker-inference-tensorflow, sagemaker-model-monitor-analyzer, sagemaker-mxnet, sagemaker-mxnet-eia, sagemaker-mxnet-serving, sagemaker-mxnet-serving-eia, sagemaker-neo-mxnet, sagemaker-neo-pytorch, sagemaker-neo-tensorflow, sagemaker-pytorch, sagemaker-rl-coach-container, sagemaker-rl-mxnet, sagemaker-rl-ray-container, sagemaker-rl-tensorflow, sagemaker-rl-vw-container, sagemaker-scikit-learn, sagemaker-spark-processing, sagemaker-sparkml-serving, sagemaker-tensorflow, sagemaker-tensorflow-eia, sagemaker-tensorflow-scriptmode, sagemaker-tensorflow-serving, sagemaker-tensorflow-serving-eia, sagemaker-tritonserver, sagemaker-xgboost, semantic-segmentation, seq2seq, stabilityai-pytorch-inference, tei, tei-cpu, tensorflow-inference, tensorflow-inference-eia, tensorflow-inference-graviton, tensorflow-training, and xgboost-neo.
dns_suffix str: DNS suffix to use in the registry path. If not specified, the AWS provider sets it to the DNS suffix for the current region.
image_tag str: Image tag for the Docker image. If not specified, the AWS provider sets the value to 1, which for many repositories indicates the latest version. Some repositories, such as XGBoost, do not support 1 or latest and specific version must be used.
region str: Region to use in the registry path. If not specified, the AWS provider sets it to the current region.

repositoryName String: Name of the repository, which is generally the algorithm or library. Values include autogluon-inference, autogluon-training, blazingtext, djl-inference, factorization-machines, forecasting-deepar, huggingface-pytorch-inference, huggingface-pytorch-inference-neuron, huggingface-pytorch-inference-neuronx, huggingface-pytorch-tgi-inference, huggingface-pytorch-training, huggingface-pytorch-training-neuronx, huggingface-pytorch-trcomp-training, huggingface-tensorflow-inference, huggingface-tensorflow-training, huggingface-tensorflow-trcomp-training, image-classification, image-classification-neo, ipinsights, kmeans, knn, lda, linear-learner, mxnet-inference, mxnet-inference-eia, mxnet-training, ntm, object-detection, object2vec, pca, pytorch-inference, pytorch-inference-eia, pytorch-inference-graviton, pytorch-inference-neuronx, pytorch-training, pytorch-training-neuronx, pytorch-trcomp-training, randomcutforest, sagemaker-base-python, sagemaker-chainer, sagemaker-clarify-processing, sagemaker-data-wrangler-container, sagemaker-debugger-rules, sagemaker-geospatial-v1-0, sagemaker-inference-mxnet, sagemaker-inference-pytorch, sagemaker-inference-tensorflow, sagemaker-model-monitor-analyzer, sagemaker-mxnet, sagemaker-mxnet-eia, sagemaker-mxnet-serving, sagemaker-mxnet-serving-eia, sagemaker-neo-mxnet, sagemaker-neo-pytorch, sagemaker-neo-tensorflow, sagemaker-pytorch, sagemaker-rl-coach-container, sagemaker-rl-mxnet, sagemaker-rl-ray-container, sagemaker-rl-tensorflow, sagemaker-rl-vw-container, sagemaker-scikit-learn, sagemaker-spark-processing, sagemaker-sparkml-serving, sagemaker-tensorflow, sagemaker-tensorflow-eia, sagemaker-tensorflow-scriptmode, sagemaker-tensorflow-serving, sagemaker-tensorflow-serving-eia, sagemaker-tritonserver, sagemaker-xgboost, semantic-segmentation, seq2seq, stabilityai-pytorch-inference, tei, tei-cpu, tensorflow-inference, tensorflow-inference-eia, tensorflow-inference-graviton, tensorflow-training, and xgboost-neo.
dnsSuffix String: DNS suffix to use in the registry path. If not specified, the AWS provider sets it to the DNS suffix for the current region.
imageTag String: Image tag for the Docker image. If not specified, the AWS provider sets the value to 1, which for many repositories indicates the latest version. Some repositories, such as XGBoost, do not support 1 or latest and specific version must be used.
region String: Region to use in the registry path. If not specified, the AWS provider sets it to the current region.

getPrebuiltEcrImage Result

The following output properties are available:

Id string: The provider-assigned unique ID for this managed resource.
RegistryId string: Account ID containing the image. For example, 469771592824.
RegistryPath string: Docker image URL. For example, 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:2.4.
RepositoryName string
DnsSuffix string
ImageTag string
Region string

Id string: The provider-assigned unique ID for this managed resource.
RegistryId string: Account ID containing the image. For example, 469771592824.
RegistryPath string: Docker image URL. For example, 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:2.4.
RepositoryName string
DnsSuffix string
ImageTag string
Region string

id String: The provider-assigned unique ID for this managed resource.
registryId String: Account ID containing the image. For example, 469771592824.
registryPath String: Docker image URL. For example, 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:2.4.
repositoryName String
dnsSuffix String
imageTag String
region String

id string: The provider-assigned unique ID for this managed resource.
registryId string: Account ID containing the image. For example, 469771592824.
registryPath string: Docker image URL. For example, 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:2.4.
repositoryName string
dnsSuffix string
imageTag string
region string

id str: The provider-assigned unique ID for this managed resource.
registry_id str: Account ID containing the image. For example, 469771592824.
registry_path str: Docker image URL. For example, 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:2.4.
repository_name str
dns_suffix str
image_tag str
region str

id String: The provider-assigned unique ID for this managed resource.
registryId String: Account ID containing the image. For example, 469771592824.
registryPath String: Docker image URL. For example, 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:2.4.
repositoryName String
dnsSuffix String
imageTag String
region String

Package Details

Repository: AWS Classic pulumi/pulumi-aws
License: Apache-2.0
Notes: This Pulumi package is based on the aws Terraform Provider.

AWS v6.71.0 published on Friday, Mar 7, 2025 by Pulumi

pulumi/pulumi-aws

aws.sagemaker.getPrebuiltEcrImage

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Example Usage

Using getPrebuiltEcrImage

getPrebuiltEcrImage Result

Package Details

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