Sagemaker endpoint with regularly updated models

I want to create a Sagemaker endpoint where the model will be regularly retrained and updated.

resource "aws_sagemaker_endpoint_configuration" "endpoint_configuration" {
  name = "sagemaker-endpoint-configuration"

  production_variants {
    initial_instance_count = 1
    instance_type = "ml.t2.medium"
    model_name = "classification_model_name"
    variant_name = "AllTraffic"

resource "aws_sagemaker_endpoint" "sagemaker_endpoint" {
  name = "sagemaker-endpoint"
  endpoint_config_name =

I want to update the model using the below python script, where container_list references the newly trained model_package_arn:

    ModelName = "classification_model_name"

    ModelName = "classification_model_name",
    ExecutionRoleArn = sagemaker_role,
    Containers = container_list

When I recreate the model as per above, does that new model get automatically cascaded to the sagemaker-endpoint-configuration and sagemaker-endpoint? Does recreating the model as per above result in any downtime of the endpoint?