AI/ML Platforms on EKS

Running AI/ML platforms on Kubernetes can greatly simplify and automate the deployment, scaling, and management of these complex applications. There are a number of popular tools and technologies that have emerged to support this use case, including TensorFlow, PyTorch, Ray, MLFlow, etc.

These tools make it easy to deploy AI/ML models in a containerized environment, and provide features such as automatic scaling, rolling updates, and self-healing capabilities to ensure high availability and reliability. By leveraging the power of Kubernetes, organizations can focus on building and training their AI/ML models, rather than worrying about the underlying infrastructure. With its robust ecosystem of tools and support for a wide range of use cases, Kubernetes is becoming an increasingly popular choice for running AI/ML platforms in production.

The following Terraform templates are available to deploy.

• Ray on EKS: This template deploys RayCluster on EKS.

• EMR NVIDIA Spark-RAPIDS: This template deploys the EMR NVIDIA Spark-RAPIDS blueprint with NVIDIA GPU Operator.