A company has trained an ML model that is packaged in a container.

Option C is correct because the company needs Kubernetes hosting, does not want to manage the control plane, wants repeatable infrastructure provisioning, and requires that provisioning be done by using Python. Amazon EKS is AWS’s managed Kubernetes service, so it satisfies the requirement to avoid managing the Kubernetes control plane directly. The AWS CDK documentation also confirms that Python is a fully supported client language for defining infrastructure as code.

AWS CDK is the best fit because it lets engineers define cloud infrastructure programmatically in Python and deploy it in a repeatable way. The AWS CDK EKS construct library specifically supports defining Amazon EKS clusters and related Kubernetes resources. This makes it a strong match for infrastructure that must be reproducible and expressed in code rather than provisioned manually. Since the model is already packaged in a container, storing the image in Amazon ECR and then deploying it to Amazon EKS follows the normal AWS container workflow.

The other options are less suitable. Option A requires setting up and managing a Kubernetes cluster on EC2, which violates the requirement to avoid control-plane management. Option B uses the AWS CLI, but the question specifically requires infrastructure provisioning by using Python, not command-line provisioning. Option D uses CloudFormation, which is repeatable infrastructure as code, but the question explicitly says the infrastructure must be provisioned by using Python. AWS CDK uniquely satisfies both the IaC and Python requirements while using managed Kubernetes with EKS.

Therefore, the best verified AWS-docs answer is C.