# Creating SageMaker HyperPod clusters using CloudFormation templates
<a name="smcluster-getting-started-slurm-console-create-cluster-cfn"></a>

You can create SageMaker HyperPod clusters using the CloudFormation templates for HyperPod. You must install AWS CLI to proceed.

**Topics**
+ [Configure resources in the console and deploy using CloudFormation](#smcluster-getting-started-slurm-console-create-cluster-deploy-console)
+ [Configure resources and deploy using CloudFormation](#smcluster-getting-started-slurm-console-create-cluster-deploy-cfn)

## Configure resources in the console and deploy using CloudFormation
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You can configure resources using the AWS Management Console and deploy using the CloudFormation templates. 

Follow these steps.

1. *Instead of choosing **Submit***, choose **Download CloudFormation template parameters** at the end of the tutorial in [Getting started with SageMaker HyperPod using the SageMaker AI console](smcluster-getting-started-slurm-console.md). The tutorial contains important configuration information you will need to create your cluster successfully.
**Important**  
If you choose **Submit**, you will not be able to deploy a cluster with the same name until you delete the cluster.

   After you choose **Download CloudFormation template parameters**, the **Using the configuration file to create the cluster using the AWS CLI** window will appear on the right side of the page.

1. On the **Using the configuration file to create the cluster using the AWS CLI** window, choose **Download configuration parameters file**. The file will be downloaded to your machine. You can edit the configuration JSON file based on your needs or leave it as-is, if no change is required.

1. In the terminal, navigate to the location of the parameter file `file://params.json`.

1. Run the [create-stack](https://docs.aws.amazon.com//cli/latest/reference/cloudformation/create-stack.html) AWS CLI command to deploy the CloudFormation stack that will provision the configured resources and create the HyperPod cluster.

   ```
   aws cloudformation create-stack 
       --stack-name my-stack
       --template-url https://aws-sagemaker-hyperpod-cluster-setup.amazonaws.com/templates-slurm/main-stack-slurm-based-template.yaml
       --parameters file://params.json
       --capabilities CAPABILITY_IAM CAPABILITY_NAMED_IAM
   ```

1. To view the status of the resources provisioning, navigate to the [CloudFormation console](https://console.aws.amazon.com/cloudformation).

   After the cluster creation completes, view the new cluster under **Clusters** in the main pane of the SageMaker HyperPod console. You can check the status of it displayed under the **Status** column.

1. After the status of the cluster turns to `InService`, you can start logging into the cluster nodes. To access the cluster nodes and start running ML workloads, see [Jobs on SageMaker HyperPod clusters](sagemaker-hyperpod-run-jobs-slurm.md).

## Configure resources and deploy using CloudFormation
<a name="smcluster-getting-started-slurm-console-create-cluster-deploy-cfn"></a>

You can configure resources and deploy using the CloudFormation templates for SageMaker HyperPod.

Follow these steps.

1. Download a CloudFormation template for SageMaker HyperPod from the [sagemaker-hyperpod-cluster-setup](https://github.com/aws/sagemaker-hyperpod-cluster-setup) GitHub repository.

1. Run the [create-stack](https://docs.aws.amazon.com//cli/latest/reference/cloudformation/create-stack.html) AWS CLI command to deploy the CloudFormation stack that will provision the configured resources and create the HyperPod cluster.

   ```
   aws cloudformation create-stack 
       --stack-name my-stack
       --template-url URL_of_the_file_that_contains_the_template_body
       --parameters file://params.json
       --capabilities CAPABILITY_IAM CAPABILITY_NAMED_IAM
   ```

1. To view the status of the resources provisioning, navigate to the CloudFormation console.

   After the cluster creation completes, view the new cluster under **Clusters** in the main pane of the SageMaker HyperPod console. You can check the status of it displayed under the **Status** column.

1. After the status of the cluster turns to `InService`, you can start logging into the cluster nodes. To access the cluster nodes and start running ML workloads, see [Jobs on SageMaker HyperPod clusters](sagemaker-hyperpod-run-jobs-slurm.md).