The "template_ext" mechanism is useful for automatically loading and jinja-processing files which are specified in parameters of Operators. However this might lead to certain problems for example (from slack conversation):

```
The templated_fields in  KubernetesPodOperator seems cause the error airflow jinja2.exceptions.TemplateNotFound when some character in the column, e.g / in env_vars.
The code got error.
env_vars=[
            k8s.V1EnvVar(
                name="GOOGLE_APPLICATION_CREDENTIALS",
                value="/var/secrets/google/service-account.json",
            ),
```

I believe the behaviour changed comparing to not-so-long-past. Some of the changes with processing parameters with jinja recursively caused this template behaviour to be applied also nested parameters like above.

There were also several discussions and user confusion with this behaviour: #15942, #16922

There are two ways we could improve the situation:
1) limit the "template_extension" resolution to only direct string kwargs passed to the operator (I think this is no brainer and we should do it)

2) propose some "escaping" mechanism, where you could either disable template_extension processing entirely or somehow mark the parameters that should not be treated as templates.

Here I have several proposals:

a) we could add "skip_template_ext_processing" or similar parameter in BaseOperator <- I do not like it as many operators rely on this behaviour for a good reason
b) we could add "template_ext" parameter in the operator that could override the original class-level-field <- I like this one a lot
c) we could add "disable_template_ext_pattern"  (str) parameter where we could specify list of regexp's where we could filter out only specific values <- this one will allow to disable template_ext much more "selectively" - only for certain parameters.


UPDATE: It only affects Kubenernetes Pod Operator due to it's recursive behaviour and should be fixed there.

airflow/providers/cncf/kubernetes/operators/kubernetes_pod.py
self, labels: dict, try_numbers_match: bool, launcher: Any, pod: k8s.V1Pod
    ) -> Tuple[State, k8s.V1Pod, Optional[str]]:
        """
        In cases where the Scheduler restarts while a KubernetesPodOperator task is running,
        this function will either continue to monitor the existing pod or launch a new pod
        based on the `reattach_on_restart` parameter.
        :param labels: labels used to determine if a pod is repeated
        :type labels: dict
        :param try_numbers_match: do the try numbers match? Only needed for logging purposes
        :type try_numbers_match: bool
        :param launcher: PodLauncher
        :param pod: Pod found with matching labels
        """
        if try_numbers_match:
            log_line = f"found a running pod with labels {labels} and the same try_number."
        else:
            log_line = f"found a running pod with labels {labels} but a different try_number."
        
        
        if self.reattach_on_restart and not pod.metadata.labels.get("already_checked"):
            log_line += " Will attach to this pod and monitor instead of starting new one"
            self.log.info(log_line)
            self.pod = pod
            final_state, remote_pod, result = self.monitor_launched_pod(launcher, pod)
        else: