docs-archive/1.10.13/_sources/kubernetes.rst.txt

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Kubernetes
----------

Kubernetes Executor
^^^^^^^^^^^^^^^^^^^

The :doc:`Kubernetes Executor <executor/kubernetes>` allows you to run all the Airflow tasks on
Kubernetes as separate Pods.

KubernetesPodOperator
^^^^^^^^^^^^^^^^^^^^^

The :class:`~airflow.contrib.operators.kubernetes_pod_operator.KubernetesPodOperator` allows you to create Pods on Kubernetes. It works with
any type of executor.

.. code-block:: python

    from airflow.contrib.operators.kubernetes_pod_operator import KubernetesPodOperator
    from airflow.kubernetes.secret import Secret
    from airflow.kubernetes.volume import Volume
    from airflow.kubernetes.volume_mount import VolumeMount
    from airflow.kubernetes.pod import Port


    secret_file = Secret('volume', '/etc/sql_conn', 'airflow-secrets', 'sql_alchemy_conn')
    secret_env  = Secret('env', 'SQL_CONN', 'airflow-secrets', 'sql_alchemy_conn')
    secret_all_keys  = Secret('env', None, 'airflow-secrets-2')
    volume_mount = VolumeMount('test-volume',
                                mount_path='/root/mount_file',
                                sub_path=None,
                                read_only=True)
    port = Port('http', 80)
    configmaps = ['test-configmap-1', 'test-configmap-2']

    volume_config= {
        'persistentVolumeClaim':
          {
            'claimName': 'test-volume'
          }
        }
    volume = Volume(name='test-volume', configs=volume_config)

    affinity = {
        'nodeAffinity': {
          'preferredDuringSchedulingIgnoredDuringExecution': [
            {
              "weight": 1,
              "preference": {
                "matchExpressions": {
                  "key": "disktype",
                  "operator": "In",
                  "values": ["ssd"]
                }
              }
            }
          ]
        },
        "podAffinity": {
          "requiredDuringSchedulingIgnoredDuringExecution": [
            {
              "labelSelector": {
                "matchExpressions": [
                  {
                    "key": "security",
                    "operator": "In",
                    "values": ["S1"]
                  }
                ]
              },
              "topologyKey": "failure-domain.beta.kubernetes.io/zone"
            }
          ]
        },
        "podAntiAffinity": {
          "requiredDuringSchedulingIgnoredDuringExecution": [
            {
              "labelSelector": {
                "matchExpressions": [
                  {
                    "key": "security",
                    "operator": "In",
                    "values": ["S2"]
                  }
                ]
              },
              "topologyKey": "kubernetes.io/hostname"
            }
          ]
        }
    }

    tolerations = [
        {
            'key': "key",
            'operator': 'Equal',
            'value': 'value'
         }
    ]

    k = KubernetesPodOperator(namespace='default',
                              image="ubuntu:16.04",
                              cmds=["bash", "-cx"],
                              arguments=["echo", "10"],
                              labels={"foo": "bar"},
                              secrets=[secret_file, secret_env, secret_all_keys],
                              ports=[port]
                              volumes=[volume],
                              volume_mounts=[volume_mount]
                              name="test",
                              task_id="task",
                              affinity=affinity,
                              is_delete_operator_pod=True,
                              hostnetwork=False,
                              tolerations=tolerations,
                              configmaps=configmaps
                              )



Pod Mutation Hook
^^^^^^^^^^^^^^^^^

The Airflow local settings file (``airflow_local_settings.py``) can define a ``pod_mutation_hook`` function
that has the ability to mutate pod objects before sending them to the Kubernetes client
for scheduling. It receives a single argument as a reference to pod objects, and
is expected to alter its attributes.

This could be used, for instance, to add sidecar or init containers
to every worker pod launched by KubernetesExecutor or KubernetesPodOperator.


.. code-block:: python

    def pod_mutation_hook(pod: Pod):
      pod.annotations['airflow.apache.org/launched-by'] = 'Tests'