bpleines commented on issue #15670:
URL: https://github.com/apache/airflow/issues/15670#issuecomment-846125695
Thanks for the example @kaxil. Understood if you want to keep the discussion
for `2.0+` only, but wanted to note that I don't think this pod_override
strategy works for `1.10.15`. I can see the scheduler pulling in the
pod_override (logs attached), but it is not realized on the resulting worker
pod's container.
```
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from datetime import timedelta
from kubernetes.client import models as k8s
import os
import time
from dag_utils import utils
def test():
print('Sleeping for 60')
time.sleep(60)
with DAG(
'kubernetes_pod_override_example',
default_args=utils.get_default_args(),
description='Kubernetes pod_override Example',
schedule_interval=timedelta(minutes=2),
max_active_runs=1) as dag:
pod_override = PythonOperator(
task_id='pod_override',
python_callable=test,
executor_config={
"pod_override": k8s.V1PodSpec(
containers=[
k8s.V1Container(
name="base",
resources=k8s.V1ResourceRequirements(
requests={'cpu': '4', 'memory': '8Gi'},
limits={'cpu': '4', 'memory': '8Gi'}
)
)
]
)
}
)
pod_override
```
[scheduler.log](https://github.com/apache/airflow/files/6524193/scheduler.log)
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