### Description

Make resources in KubernetesPodOperator as templated. We need to modify this during several runs and it needs code change for each run.

### Use case/motivation

For running CPU and memory intensive workloads, we want to continuously optimise the "limt_cpu" and "limit_memory" parameters. Hence, we want to provide these parameters as a part of the pipeline definition.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

from pathlib import Path
        path = Path("/var/run/secrets/kubernetes.io/serviceaccount/namespace")
        return path.exists() and path.read_text() or None
    def _render_nested_template_fields(
        self,
        content: Any,
        context: Context,
        jinja_env: jinja2.Environment,
        seen_oids: set,
    ) -> None:
        if id(content) not in seen_oids and isinstance(content, k8s.V1EnvVar):
            seen_oids.add(id(content))
            self._do_render_template_fields(content, ("value", "name"), context, jinja_env, seen_oids)
            return
        super()._render_nested_template_fields(content, context, jinja_env, seen_oids)
    @staticmethod
    def _get_ti_pod_labels(context: Context | None = None, include_try_number: bool = True) -> dict[str, str]:
        """
        Generate labels for the pod to track the pod in case of Operator crash
        :param context: task context provided by airflow DAG
        :return: dict
        """
        if not context:
            return {}