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
:param volume_mounts: volumeMounts for launched pod.
    :type volume_mounts: list[k8s.V1VolumeMount]
    :param volumes: volumes for launched pod. Includes ConfigMaps and PersistentVolumes.
    :type volumes: list[k8s.V1Volume]
    :param env_vars: Environment variables initialized in the container. (templated)
    :type env_vars: list[k8s.V1EnvVar]
    :param secrets: Kubernetes secrets to inject in the container.
        They can be exposed as environment vars or files in a volume.
    :type secrets: list[airflow.kubernetes.secret.Secret]
    :param in_cluster: run kubernetes client with in_cluster configuration.
    :type in_cluster: bool
    :param cluster_context: context that points to kubernetes cluster.
        Ignored when in_cluster is True. If None, current-context is used.
    :type cluster_context: str
    :param reattach_on_restart: if the scheduler dies while the pod is running, reattach and monitor
    :type reattach_on_restart: bool
    :param labels: labels to apply to the Pod. (templated)
    :type labels: dict
    :param startup_timeout_seconds: timeout in seconds to startup the pod.
    :type startup_timeout_seconds: int
    :param get_logs: get the stdout of the container as logs of the tasks.
    :type get_logs: bool
    :param image_pull_policy: Specify a policy to cache or always pull an image.
    :type image_pull_policy: str
    :param annotations: non-identifying metadata you can attach to the Pod.
        Can be a large range of data, and can include characters
        that are not permitted by labels.
    :type annotations: dict
    :param resources: A dict containing resources requests and limits.
        Possible keys are request_memory, request_cpu, limit_memory, limit_cpu,