What Should Happen Instead

Oct 13, 2025 by recoveryshake.com 46 views

Introduction

Apache Airflow is a powerful workflow management platform that enables users to create, schedule, and monitor complex workflows. One of the key features of Airflow is its ability to integrate with various executors, including the Kubernetes executor. However, when using the Kubernetes executor, the executor_config dictionary is used to configure worker pods. Unfortunately, the current implementation of Airflow does not raise an error if any keys besides "pod_override" or "pod_template_file" are used in executor_config. This can lead to unexpected behavior and make it difficult for users to identify and fix issues.

The Problem

When using the Kubernetes executor, the executor_config dictionary is used to configure worker pods. However, if any keys besides "pod_override" or "pod_template_file" are used in executor_config, Airflow will simply disregard the invalid keys and run the DAG as expected. This can lead to unexpected behavior and make it difficult for users to identify and fix issues.

What Should Happen Instead

If any keys besides "pod_override" or "pod_template_file" are used in executor_config, an error should be raised. This will give the user feedback that their executor_config keys are invalid and need to be removed or changed. This is a critical issue that needs to be addressed to ensure the reliability and stability of Airflow.

How to Reproduce the Issue

To reproduce the issue, follow these steps:

Create an Airflow instance that uses the Kubernetes Executor.
Create a DAG with the following code including an invalid key in executor_config.

import datetime

from airflow.decorators import dag
from airflow.decorators import task

executor_config = {
    "key": "value"
}

@dag(start_date=datetime.datetime(2024, 10, 1), schedule="@daily", catchup=False)
def dag_1():

    @task(executor_config=executor_config)
    def task_1():
        print("task 1")

    task_1()

dag_1()

Observe that the DAG will be imported and run on the Airflow instance without any issues.

Expected Behavior

Code Changes

To fix this issue, the following code changes can be made:

from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import KubernetesPodOperator
from airflow.providers.cncf.kubernetes.utils import KubernetesExecutorConfig

class KubernetesExecutorConfigValidator(KubernetesExecutorConfig):
    def validate(self, executor_config):
        if "pod_override" not in executor_config and "pod_template_file" not in executor_config:
            raise ValueError("Invalid executor_config. Only 'pod_override' and 'pod_template_file' are allowed.")
        return super().validate(executor_config)

Conclusion

In conclusion, the current implementation of Airflow does not raise an error if any keys besides "pod_override" or "pod_template_file" are used in executor_config. This can lead to unexpected behavior and make it difficult for users to identify and fix issues. To fix this issue, an error should be raised if any keys besides "pod_override" or "pod_template_file" are used in executor_config. This will give the user feedback that their executor_config keys are invalid and need to be removed or changed.

Recommendations

Based on the analysis, the following recommendations are made:

Raise an error if any keys besides "pod_override" or "pod_template_file" are used in executor_config.
Provide feedback to the user that their executor_config keys are invalid and need to be removed or changed.
Update the Airflow documentation to reflect the changes.

Are You Willing to Submit a PR?

Yes, I am willing to submit a PR to fix this issue.

Code of Conduct

Q: What is the current behavior of Airflow when using the Kubernetes executor?

A: Currently, Airflow does not raise an error if any keys besides "pod_override" or "pod_template_file" are used in executor_config. Instead, it simply disregards the invalid keys and runs the DAG as expected.

Q: Why is this a problem?

A: This can lead to unexpected behavior and make it difficult for users to identify and fix issues. It can also lead to security vulnerabilities if invalid keys are used to configure worker pods.

Q: What should happen instead?

A: If any keys besides "pod_override" or "pod_template_file" are used in executor_config, an error should be raised. This will give the user feedback that their executor_config keys are invalid and need to be removed or changed.

Q: How can I reproduce the issue?

A: To reproduce the issue, follow these steps:

Create an Airflow instance that uses the Kubernetes Executor.
Create a DAG with the following code including an invalid key in executor_config.

import datetime

from airflow.decorators import dag
from airflow.decorators import task

executor_config = {
    "key": "value"
}

@dag(start_date=datetime.datetime(2024, 10, 1), schedule="@daily", catchup=False)
def dag_1():

    @task(executor_config=executor_config)
    def task_1():
        print("task 1")

    task_1()

dag_1()

Observe that the DAG will be imported and run on the Airflow instance without any issues.

Q: What are the expected changes to the Airflow code?

A: To fix this issue, the following code changes can be made:

from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import KubernetesPodOperator
from airflow.providers.cncf.kubernetes.utils import KubernetesExecutorConfig

class KubernetesExecutorConfigValidator(KubernetesExecutorConfig):
    def validate(self, executor_config):
        if "pod_override" not in executor_config and "pod_template_file" not in executor_config:
            raise ValueError("Invalid executor_config. Only 'pod_override' and 'pod_template_file' are allowed.")
        return super().validate(executor_config)

Q: How can I contribute to fixing this issue?

A: If you are interested in contributing to fixing this issue, you can submit a pull request to the Airflow repository. Make sure to follow the Airflow code of conduct and contribute to the project in a responsible and respectful manner.

Q: What are the benefits of fixing this issue?

A: Fixing this issue will improve the reliability and stability of Airflow. It will also provide users with more feedback and help them identify and fix issues more easily.

Q: How can I stay up-to-date with the latest developments on this issue?

A: You can stay up-to-date with the latest developments on this issue by following the Airflow repository and participating in the Airflow community. You can also subscribe to the Airflow newsletter to receive updates on new features and bug fixes.