It's a really tough balancing act.
On the one hand I agree that ideally we don't want to force people to user
k8s's (ridiculously) verbose model. On the other hand the other solution is
to hand-craft requests like this
I think it's going to be an antipattern to write Python configuration in
Airflow to configure a Kubernetes deployment since even a "simple"
deployment would likely be more classes/objects than the DAG itself. I do
like the idea of having a more featured operator than the PodOperator, but
if I were
An example of creating a deployment using the k8s model architecture can be
found here:
https://github.com/kubernetes-client/python/blob/master/examples/deployment_examples.py
def create_deployment_object():
# Configureate Pod template container
container = client.V1Container(
Hi all,
Enclosed is a proposal for a kubernetes deployment management operator. I
think this would be a good addition to current k8s offerings s.t. users can
actually launch persistent applications from airflow DAGs.
* What?*
Add an operator that monitors a k8s deployment, declaring the task
