devscheffer commented on PR #36882:
URL: https://github.com/apache/airflow/pull/36882#issuecomment-1921445378
I had similar problems and thought about something like that
```
from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import
KubernetesPodOperator
from airflow.utils.decorators import apply_defaults
from datetime import timedelta
import time
class CustomKubernetesPodOperator(KubernetesPodOperator):
@apply_defaults
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def execute(self, context):
# Check if there are enough resources on the cluster
while True:
cpu_available = check_cpu()
memory_available = check_memory()
if cpu_available and memory_available:
break
else:
time.sleep(300) # Wait for 5 minutes
# Send the request to the Kubernetes cluster
super().execute(context)
def check_cpu(self):
# Check if there is enough CPU available on the cluster
# Return True if there is enough CPU available, False otherwise
pass
def check_memory(self):
# Check if there is enough memory available on the cluster
# Return True if there is enough memory available, False otherwise
pass
```
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