# Preparing and uploading lifecycle scripts
<a name="sagemaker-hyperpod-multihead-slurm-scripts"></a>

After creating all the required resources, you'll need to set up [lifecycle scripts](https://github.com/aws-samples/awsome-distributed-training/tree/main/1.architectures/5.sagemaker-hyperpod/LifecycleScripts) for your SageMaker HyperPod cluster. These [lifecycle scripts](https://github.com/aws-samples/awsome-distributed-training/tree/main/1.architectures/5.sagemaker-hyperpod/LifecycleScripts) provide a [base configuration](https://github.com/aws-samples/awsome-distributed-training/tree/main/1.architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config) you can use to create a basic HyperPod Slurm cluster.

## Prepare the lifecycle scripts
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Follow these steps to get the lifecycle scripts.

1. Download the [lifecycle scripts](https://github.com/aws-samples/awsome-distributed-training/tree/main/1.architectures/5.sagemaker-hyperpod/LifecycleScripts) from the GitHub repository to your machine.

1. Upload the [lifecycle scripts](https://github.com/aws-samples/awsome-distributed-training/tree/main/1.architectures/5.sagemaker-hyperpod/LifecycleScripts) to the Amazon S3 bucket you created in [Provision basic resources](sagemaker-hyperpod-multihead-slurm-cfn.md#sagemaker-hyperpod-multihead-slurm-cfn-basic), using the [cp](https://docs.aws.amazon.com//cli/latest/reference/s3/cp.html) CLI command.

   ```
   aws s3 cp --recursive LifeCycleScripts/base-config s3://${ROOT_BUCKET_NAME}/LifeCycleScripts/base-config
   ```

## Create configuration file
<a name="sagemaker-hyperpod-multihead-slurm-update-config-file"></a>

Follow these steps to create the configuration file and upload it to the same Amazon S3 bucket where you store the lifecycle scripts.

1. Create a configuration file named `provisioning_parameters.json` with the following configuration. Note that `slurm_sns_arn` is optional. If not provided, HyperPod will not set up the Amazon SNS notifications.

   ```
   cat <<EOF > /tmp/provisioning_parameters.json
   {
     "version": "1.0.0",
     "workload_manager": "slurm",
     "controller_group": "$CONTOLLER_IG_NAME",
     "login_group": "my-login-group",
     "worker_groups": [
       {
         "instance_group_name": "$COMPUTE_IG_NAME",
         "partition_name": "dev"
       }
     ],
     "fsx_dns_name": "$SLURM_FSX_DNS_NAME",
     "fsx_mountname": "$SLURM_FSX_MOUNT_NAME",
     "slurm_configurations": {
       "slurm_database_secret_arn": "$SLURM_DB_SECRET_ARN",
       "slurm_database_endpoint": "$SLURM_DB_ENDPOINT_ADDRESS",
       "slurm_shared_directory": "/fsx",
       "slurm_database_user": "$DB_USER_NAME",
       "slurm_sns_arn": "$SLURM_SNS_FAILOVER_TOPIC_ARN"
     }
   }
   EOF
   ```

1. Upload the `provisioning_parameters.json` file to the same Amazon S3 bucket where you store the lifecycle scripts.

   ```
   aws s3 cp /tmp/provisioning_parameters.json s3://${ROOT_BUCKET_NAME}/LifeCycleScripts/base-config/provisioning_parameters.json
   ```
**Note**  
If you are using API-driven configuration, the `provisioning_parameters.json` file is not required. With API-driven configuration, you define Slurm node types, partitions, and FSx mounting directly in the CreateCluster API payload. For details, see [Getting started with SageMaker HyperPod using the AWS CLI](smcluster-getting-started-slurm-cli.md).

## Verify files in Amazon S3 bucket
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After you upload all the lifecycle scripts and the `provisioning_parameters.json` file, your Amazon S3 bucket should look like the following.

![\[Image showing all the lifecycle scripts uploaded to the Amazon S3 bucket in the Amazon Simple Storage Service console.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/hyperpod/hyperpod-lifecycle-scripts-s3.png)


For more information, see [Start with base lifecycle scripts provided by HyperPod](https://docs.aws.amazon.com//sagemaker/latest/dg/sagemaker-hyperpod-lifecycle-best-practices-slurm-slurm-base-config.html).