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Definitely this.

Our teams have many 1 or 2 step DAGs that are idempotent. They could have been lambdas and they're already pulling from SQS already. It could be just my misfortune, but in AWS, MWAA is kind of janky. It's difficult to track down problems in the logs (task failures look fine there) and the Airflow UI is randomly unavailable ("document returns empty", "connection reset" kind of things).

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Lambdas have resource constraints that Airflow DAGs don't. Most notably, Airflow DAGs can run for any arbitrary length of time. And the local storage attached to the Airflow cluster is actual disk space, and not just a fake in-memory disk, making it possible process files larger than the amount of memory allocated to the DAG.

There's certainly some functionality overlap, but I don't see Lambda and Airflow as competitors. Each has capabilities that the other doesn't.

I remember reading that you can attach EFS to lambdas. That would solve some of the storage issues.

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