Deployment options overview

To run artificial intelligence (AI), machine learning (ML), or high performance computing (HPC) workloads, you can deploy AI-optimized VMs and clusters of A4X, A4, and A3 Ultra machines. For more information about the features of these machines that enable you to run large-scale AI/ML clusters, see Cluster management overview.

Note: This guide only applies to the A4X, A4, and A3 Ultra machine types. Guidance for other machine types is out of scope for this documentation. We recommend that you consult the relevant documentation for your choice of machine type. To identify the VM and cluster creation guide for other machine types, see Choose a deployment strategy.

You can create A4X, A4, and A3 Ultra VMs directly from Compute Engine, or through other services that run on Compute Engine instances like Cluster Toolkit or Google Kubernetes Engine.

For the most appropriate option to create your VMs or clusters for your use case, choose one of the following:

Option	Use case
Cluster Toolkit	You want to use open-source software that simplifies the process for you to deploy both Slurm and GKE clusters. Cluster Toolkit is designed to be highly customizable and extensible. To learn more, see the following: Create an AI-optimized Slurm cluster Create an AI-optimized Google Kubernetes Engine cluster with default configuration
GKE	You want maximum flexibility in configuring your Google Kubernetes Engine cluster based on the needs of your workload. To learn more, see Create a custom AI-optimized Google Kubernetes Engine cluster.
Use Compute Engine	You want full control of the infrastructure layer so that you can set up your own orchestrator. To learn more, see the following: Create an AI-optimized instance Create A4X Create A4 or A3 Ultra Create AI-optimized instances in bulk Create A4X Create A4 or A3 Ultra Create an AI-optimized MIG Create A4X Create A4 or A3 Ultra