Before we start, please complete the following checks:
This project uses AWS CDK library version 1.102.0, hence the same version or higher is required.
Now we can clone the Amazon MWAA Examples repository and navigate to project directory:
git clone email@example.com:aws-samples/amazon-mwaa-examples.git cd amazon-mwaa-examples/usecases/mwaa-with-codeartifact
This is the project structure that you should be seeing:
. ├── infra/ // AWS CDK infrastructure ├── mwaa-ca-bucket-content/ // DAGs and requirements.txt ├── lambda/ // Lambda handler ├── .env // Environment variables ├── Makefile // Make rules for automation
We will now set environment variables and create a Python virtual environment. Let’s start by setting environment variables in the
AWS_REGION=eu-west-1 BUCKET_NAME=REPLACE_WITH_YOUR_BUCKET_NAME AIRFLOW_VERSION=2.0.2
You will set AWS Region for the deployment, name of an S3 bucket that will be created (must be unique), and the version of Apache Airflow (
We can now create Python virtual environment. Run the following
# from the root directory $ make venv
This rule will create a virtual environment in
infra/venv and install all the necessary dependencies.
We are now ready to deploy! Please run the
deploy rule to provision the infrastructure:
# from the root directory $ make deploy
AWS CDK CLI will ask for your permissions to deploy specific IAM Roles and IAM Polices resources. When asked, please acknowledge with
y and press Enter.
It can take a few minutes to provision a new MWAA environment, so when it’s done head over to next section!