update test DAG focal

dags_airflow_ale_kopfocal.py

@@ -35,12 +35,12 @@
         # unique id of the task within the DAG
         task_id="kubeop",
         # the Docker image to launch
-        image="ubuntu:20.04",
-        cmds=["sleep","infinity"],
+        image="ubuntu",
+        cmds=["echo","Hello World"],
         # launch the Pod on the same cluster as Airflow is running on
         in_cluster=True,
         # launch the Pod in the same namespace as Airflow is running in
-        namespace="glitchflow",
+        namespace="default",
         # Pod configuration
         # name the Pod
         name="airflow_op",
@@ -50,7 +50,7 @@
         # reattach to worker instead of creating a new Pod on worker failure
         reattach_on_restart=True,
         # delete Pod after the task is finished
-        is_delete_operator_pod=True,
+        is_delete_operator_pod=False,
         # get log stdout of the container as task logs
         get_logs=True,
         # log events in case of Pod failure