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Add MWAA module and example #585

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1 change: 1 addition & 0 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -220,6 +220,7 @@ If you are interested in contributing to EKS Blueprints, see the [Contribution g
| <a name="output_cluster_security_group_arn"></a> [cluster\_security\_group\_arn](#output\_cluster\_security\_group\_arn) | Amazon Resource Name (ARN) of the cluster security group |
| <a name="output_cluster_security_group_id"></a> [cluster\_security\_group\_id](#output\_cluster\_security\_group\_id) | EKS Control Plane Security Group ID |
| <a name="output_configure_kubectl"></a> [configure\_kubectl](#output\_configure\_kubectl) | Configure kubectl: make sure you're logged in with the correct AWS profile and run the following command to update your kubeconfig |
| <a name="output_eks_cluster_arn"></a> [eks\_cluster\_arn](#output\_eks\_cluster\_arn) | Amazon EKS Cluster Name |
| <a name="output_eks_cluster_certificate_authority_data"></a> [eks\_cluster\_certificate\_authority\_data](#output\_eks\_cluster\_certificate\_authority\_data) | Base64 encoded certificate data required to communicate with the cluster |
| <a name="output_eks_cluster_endpoint"></a> [eks\_cluster\_endpoint](#output\_eks\_cluster\_endpoint) | Endpoint for your Kubernetes API server |
| <a name="output_eks_cluster_id"></a> [eks\_cluster\_id](#output\_eks\_cluster\_id) | Amazon EKS Cluster Name |
Expand Down
88 changes: 88 additions & 0 deletions examples/managed-workflow-apache-airflow/README.md
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## EKS Cluster w/ Amazon Manged Workflows for Apache Airflopw (MWAA)

The example demonstrates how to use Amazon Managed Workflows for Apache Airflow (MWAA) with Amazon EKS.

This example was originated from the steps provided on MWAA documentation on the link below:
[mwaa-eks-example](https://docs.aws.amazon.com/mwaa/latest/userguide/mwaa-eks-example.html)

### Considerations

1. Ideally we recommend adding the steps to sync requirements/sync dags to the MWAA S3 Bucket as part of a CI/CD pipeline. Generally Dags development have a different lifecycle than the Terraform code to provision infrastructure.
However for simplicity we are providing steps for that using Terraform running AWS CLI commands on null_resource.

## Prerequisites:

Ensure that you have the following tools installed locally:

1. [aws cli](https://docs.aws.amazon.com/cli/latest/userguide/install-cliv2.html)
2. [kubectl](https://Kubernetes.io/docs/tasks/tools/)
3. [terraform](https://learn.hashicorp.com/tutorials/terraform/install-cli)

## Deploy

To provision this example:

```sh
terraform init
terraform apply
```

Enter `yes` at command prompt to apply


## Validate

The following command will update the `kubeconfig` on your local machine and allow you to interact with your EKS Cluster using `kubectl` to validate the deployment.

1. Run `update-kubeconfig` command:

```sh
aws eks --region <REGION> update-kubeconfig --name <CLUSTER_NAME>
```

2. List the nodes running currently

```sh
kubectl get nodes

# Output should look like below
NAME STATUS ROLES AGE VERSION
ip-10-0-30-125.us-west-2.compute.internal Ready <none> 2m19s v1.22.9-eks-810597c
```

3. Log into Apache Airflow UI

- Open the Environments page on the Amazon MWAA console
- Choose an environment
- Under the `Details` section, click the link for the Airflow UI

4. Triger the DAG workflow to execute

In the Airflow UI, enable the example and then trigger it.

![Enable the DAG kubernetes_pod_example ](images/kubernetes_pod_example_dag.png)

![Trigger the DAG kubernetes_pod_example ](images/dag_tree.png)

5. Verify that the pod was executed successfully

After it runs and completes successfully, use the following command to verify the pod:

```sh
kubectl get pods -n mwaa
```

You should see output similar to the following:

```sh
NAME READY STATUS RESTARTS AGE
mwaa-pod-test.4bed823d645844bc8e6899fd858f119d 0/1 Completed 0 25s
```

## Destroy

To teardown and remove the resources created in this example:

```sh
terraform destroy -auto-approve
```
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from airflow import DAG
from datetime import datetime
from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import (
KubernetesPodOperator,
)

default_args = {
"owner": "aws",
"depends_on_past": False,
"start_date": datetime(2019, 2, 20),
"provide_context": True,
}

dag = DAG("kubernetes_pod_example", default_args=default_args, schedule_interval=None)

# use a kube_config stored in s3 dags folder for now
kube_config_path = "/usr/local/airflow/dags/kube_config.yaml"

podRun = KubernetesPodOperator(
namespace="mwaa",
image="ubuntu:18.04",
cmds=["bash"],
arguments=["-c", "ls"],
labels={"foo": "bar"},
name="mwaa-pod-test",
task_id="pod-task",
get_logs=True,
dag=dag,
is_delete_operator_pod=False,
config_file=kube_config_path,
in_cluster=False,
cluster_context="mwaa", # Must match kubeconfig context
)
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kubernetes==11.0.0
apache-airflow-providers-cncf-kubernetes==2.0.2
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