Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker and Terraform.
This repo supports the original article posted on Medium.
Ensure your Terraform version is as follows (some modifications would be required if you run other Terraform versions):
$ terraform --version
Terraform v0.11.14
+ provider.archive v1.2.2
+ provider.aws v2.21.1
+ provider.template v2.1.2To download Terraform, visit https://releases.hashicorp.com/terraform/
From terraform folder:
- Copy
terraform_backend.tf.templatetoterraform_backend.tfand modify values accordingly. You need to manually create an S3 bucket or use an existing one to store the Terraform state file. - Copy
terraform.tfvars.templatetoterraform.tfvarsand modify values accordingly. You don't need to create any buckets specified in here, they're to be created by terraform apply. - Run the followings:
export AWS_PROFILE=<your desired profile>
terraform init
terraform validate
terraform plan -out=tfplan
terraform apply --auto-approve tfplanterraform plan -destroy -out=tfplan
terraform apply tfplan
https://github.com/awslabs/fraud-detection-using-machine-learning
Original CloudFormation script can be found at cloudformation folder (renamed from deployment).
This library is licensed under the Apache 2.0 License.