SageMaker Stacks

Create, inspect, and use SageMaker-backed stacks with S3 storage

A SageMaker stack runs each Kitaru execution as a managed SageMaker job and stores checkpoint outputs in S3.

Use this page when your team wants AWS-managed job execution instead of running an execution cluster yourself. If you want the broader stack model first, start with Stacks.

Prerequisites

Before creating the stack, make sure these resources already exist:

• a Kitaru server you are connected to with kitaru login ...

• an S3 bucket or prefix for artifacts, for example s3://my-bucket/kitaru

• an ECR repository that can store the execution image, for example 123456789012.dkr.ecr.eu-west-1.amazonaws.com/kitaru

• a SageMaker execution role ARN

• AWS credentials available to the Kitaru server / stack setup path

• an AWS region, for example eu-west-1

Kitaru creates the stack definition and component records. It does not create your S3 bucket, ECR repository, IAM role, or SageMaker account setup for you.

Create the stack

kitaru stack create prod-sagemaker \
  --type sagemaker \
  --artifact-store s3://my-bucket/kitaru \
  --container-registry 123456789012.dkr.ecr.eu-west-1.amazonaws.com/kitaru \
  --region eu-west-1 \
  --execution-role arn:aws:iam::123456789012:role/SageMakerExecutionRole

The required SageMaker fields are:

Field	Meaning
--artifact-store	S3 URI where Kitaru writes checkpoint outputs and saved artifacts
--container-registry	ECR repository where Kitaru pushes the run image
--region	AWS region for SageMaker jobs
--execution-role	IAM role used by SageMaker jobs at runtime

You can add an optional credentials reference with --credentials when your server setup uses named cloud credentials.

Set advanced SageMaker defaults

Named flags cover the common setup. Use --extra for lower-level component fields that Kitaru does not expose as first-class flags.

For example, write the asynchronous runner default explicitly with --extra:

kitaru stack create prod-sagemaker \
  --type sagemaker \
  --artifact-store s3://my-bucket/kitaru \
  --container-registry 123456789012.dkr.ecr.eu-west-1.amazonaws.com/kitaru \
  --region eu-west-1 \
  --execution-role arn:aws:iam::123456789012:role/SageMakerExecutionRole \
  --extra orchestrator.synchronous=false

--async is shorthand for that same orchestrator.synchronous=false setting. If you provide both, the explicit --extra value wins.

If you need provider-specific settings not shown here, keep them in a reviewed stack YAML template and pass them through extra: / --extra.

Use YAML for repeatable setup

name: prod-sagemaker
type: sagemaker
artifact_store: s3://my-bucket/kitaru
container_registry: 123456789012.dkr.ecr.eu-west-1.amazonaws.com/kitaru
region: eu-west-1
execution_role: arn:aws:iam::123456789012:role/SageMakerExecutionRole
extra:
  orchestrator:
    synchronous: false

Create it with:

kitaru stack create -f stack.yaml

CLI flags override YAML values, and --extra values merge on top of the YAML extra: block.

Inspect and use it

kitaru stack show prod-sagemaker
kitaru stack use prod-sagemaker
kitaru stack current

kitaru stack show reports the translated Kitaru view: runner, storage, image registry, region, execution role, active status, and whether the stack was created by Kitaru.

Once active, normal flow runs use the SageMaker stack unless a flow-level or run-level stack override is present.

Delete it

kitaru stack delete prod-sagemaker

Use --recursive if you want Kitaru to remove Kitaru-managed component records too. Kitaru does not delete your cloud bucket, registry repository, IAM role, or other AWS resources.

Related

Stacks

The shared stack model, precedence rules, YAML, --extra, and --async

Containerization

How Kitaru builds and configures remote execution images