#Managed Apache Airflow on AWS
Deployment on MWAA
Bucket for Plugins/DAGs/Requirments
- You need to specify a bucket that must start with airlow in the name.
- Specify different paths for Dags, Plugins and Requirements.
- Create a new VPC and select the type of deployment (public or private).
- Select the environment class, to start I suggest mw1.small.
- For monitoring in production environment it is better to enable form INFO logs for tasks, webserver, scheduler, worker and DAGs.
- Create a custom role and give the role permissions over the S3 bucket. (Remember give permissions to the rone in the Bucket policy).
- Store all the DAGs in the dags folder.
- The DAGs should finish with .py extension.
- Take into account that the latest version is 1.10.12 and you will have all the default packages that come with the version.
- In the requirements file you need to specify additional packages in this way: apache-airflow[slack, package2, package3].
- If you need to use custom operators you need to call them from the dag file: from airflow.contrib.operators.slack_webhook_operator import SlackWebhookOperator