This architecture is for deploying and managing Apache Airflow environments using Terraform on Amazon Web Services (AWS) through Amazon Managed Workflows for Apache Airflow (MWAA).
To implement the architecture mentioned in the document, you would need the following Terraform resources:
- aws_vpc
: For creating the VPCs (Customer VPC and MWAA Service VPC)
- aws_subnet
: For defining the subnets (Public and Private)
- aws_internet_gateway
: For setting up the Internet Gateway
- aws_lb
: For creating the Application Load Balancer
- aws_vpc_endpoint
: For configuring the VPC Endpoints
- aws_iam_role
and aws_iam_policy
: For managing AWS Identity and Access Management (IAM) Roles and Policies
- aws_s3_bucket
: For setting up the AWS Simple Storage Service (S3)
- aws_sqs_queue
: For configuring the AWS Simple Queue Service (SQS)
- aws_ecr_repository
: For creating the AWS Elastic Container Registry (ECR)
- aws_kms_key
: For managing the AWS Key Management Service (KMS)
- aws_cloudwatch_log_group
: For configuring the AWS CloudWatch log group
Please note that this is not an exhaustive list, and there may be additional resources required depending on your specific implementation and requirements.

I can give you a high-level breakdown of what the Terraform structure might look like and provide an example of what some of the code could be for a piece of the architecture.
The architecture shown in the image involves several AWS services:
- VPCs (Customer VPC and MWAA Service VPC)
- Subnets (Public and Private)
- Internet Gateway
- Application Load Balancer
- AWS PrivateLink
- EC2 Instances (Airflow Schedulers and Workers)
- RDS Instances (Database)
- VPC Endpoints
- AWS Identity and Access Management (IAM) Roles and Policies
- AWS Simple Storage Service (S3)
- AWS Simple Queue Service (SQS)
- AWS Elastic Container Registry (ECR)
- AWS Key Management Service (KMS)
- AWS CloudWatch
Here's an example of how you might start writing Terraform code for part of this setup, particularly the VPCs and subnets:
provider "aws" {
region = "us-west-2" # Example region
}
resource "aws_vpc" "customer_vpc" {
cidr_block = "10.0.0.0/16"
enable_dns_support = true
enable_dns_hostnames = true
tags = {
Name = "customer-vpc"
}
}
resource "aws_subnet" "customer_public_subnet" {
vpc_id = aws_vpc.customer_vpc.id
cidr_block = "10.0.1.0/24"
availability_zone = "us-west-2a"
map_public_ip_on_launch = true
tags = {
Name = "customer-public-subnet"
}
}
resource "aws_subnet" "customer_private_subnet" {
vpc_id = aws_vpc.customer_vpc.id
cidr_block = "10.0.2.0/24"
availability_zone = "us-west-2b"
map_public_ip_on_launch = false
tags = {
Name = "customer-private-subnet"
}
}
resource "aws_internet_gateway" "customer_igw" {
vpc_id = aws_vpc.customer_vpc.id
tags = {
Name = "customer-igw"
}
}
# ... Repeat similar resources for MWAA Service VPC, subnets, and other components.
# Application Load Balancer and Listeners would also need to be defined.
This is just a basic example to get you started. Each resource (like EC2 instances, RDS instances, IAM roles, etc.) would need to be defined in a similar way, each with their own set of configurations and dependencies.
For a complete and functional setup, you would need to:
- Organize your code into modules for reusability.
- Use data sources to fetch information about the AWS environment.
- Create security groups and network ACLs to control access.
- Set up IAM roles and policies for permissions.
- Define the resources for the various AWS services mentioned in the architecture.
- Use outputs to fetch important information like IPs and ARNs.
- Possibly use remote backends for state management.