# Validating runtime before running production workloads on a HyperPod Slurm cluster
<a name="sagemaker-hyperpod-lifecycle-best-practices-slurm-slurm-validate-runtime"></a>

To check the runtime before running any production workloads on a Slurm cluster on HyperPod, use the runtime validation script [https://github.com/aws-samples/awsome-distributed-training/blob/main/1.architectures/5.sagemaker-hyperpod/hyperpod-precheck.py](https://github.com/aws-samples/awsome-distributed-training/blob/main/1.architectures/5.sagemaker-hyperpod/hyperpod-precheck.py). This script checks if the Slurm cluster has all packages installed for running Docker, if the cluster has a properly mounted FSx for Lustre file system and a user directory sharing the file system, and if the Slurm deamon is running on all compute nodes.

To run the script on multiple nodes at once, use `srun` as shown in the following example command of running the script on a Slurm cluster of 8 nodes.

```
# The following command runs on 8 nodes
srun -N 8 python3 hyperpod-precheck.py
```

**Note**  
To learn more about the validation script such as what runtime validation functions the script provides and guidelines to resolve issues that don't pass the validations, see [Runtime validation before running workloads](https://github.com/aws-samples/awsome-distributed-training/tree/main/1.architectures/5.sagemaker-hyperpod#35-runtime-validation-before-running-workloads) in the *Awsome Distributed Training GitHub repository*.