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 v2.1.2
To download Terraform
, visit https://releases.hashicorp.com/terraform/
From terraform
folder:
- Copy
terraform_backend.tf.template
toterraform_backend.tf
and 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.template
toterraform.tfvars
and 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 tfplan
terraform 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.