Installing Airflow on EKS fargate using Helm

[tkansara]

Official Helm Chart version

1.6.0 (latest released)

Apache Airflow version

2.4.1

Kubernetes Version

1.22

Helm Chart configuration

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
---
# Default values for airflow.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.

# Provide a name to substitute for the full names of resources
fullnameOverride: ""

# Provide a name to substitute for the name of the chart
nameOverride: ""

# Provide a Kubernetes version (used for API Version selection) to override the auto-detected version
kubeVersionOverride: ""

# Max number of old replicasets to retain. Can be overridden by each deployment's revisionHistoryLimit
#revisionHistoryLimit: ~

# User and group of airflow user
uid: 50000
gid: 0

# Default security context for airflow
securityContext: {}
#  runAsUser: 50000
#  fsGroup: 0
#  runAsGroup: 0

# Airflow home directory
# Used for mount paths
airflowHome: /opt/airflow

# Default airflow repository -- overridden by all the specific images below
defaultAirflowRepository: apache/airflow

# Default airflow tag to deploy
defaultAirflowTag: "2.4.1"

# Airflow version (Used to make some decisions based on Airflow Version being deployed)
airflowVersion: "2.4.1"

# Images
images:
  airflow:
    repository: ~
    tag: ~
    pullPolicy: IfNotPresent
  # To avoid images with user code, you can turn this to 'true' and
  # all the 'run-airflow-migrations' and 'wait-for-airflow-migrations' containers/jobs
  # will use the images from 'defaultAirflowRepository:defaultAirflowTag' values
  # to run and wait for DB migrations .
  useDefaultImageForMigration: false
  # timeout (in seconds) for airflow-migrations to complete
  migrationsWaitTimeout: 60
  pod_template:
    repository: ~
    tag: ~
    pullPolicy: IfNotPresent
  flower:
    repository: ~
    tag: ~
    pullPolicy: IfNotPresent
  statsd:
    repository: quay.io/prometheus/statsd-exporter
    tag: v0.22.8
    pullPolicy: IfNotPresent
  redis:
    repository: redis
    tag: 6-bullseye
    pullPolicy: IfNotPresent
  pgbouncer:
    repository: apache/airflow
    tag: airflow-pgbouncer-2021.04.28-1.14.0
    pullPolicy: IfNotPresent
  pgbouncerExporter:
    repository: apache/airflow
    tag: airflow-pgbouncer-exporter-2021.09.22-0.12.0
    pullPolicy: IfNotPresent
  gitSync:
    repository: k8s.gcr.io/git-sync/git-sync
    tag: v3.4.0
    pullPolicy: IfNotPresent

# Select certain nodes for airflow pods.
nodeSelector: {}
affinity: {}
tolerations: []
topologySpreadConstraints: []

# Add common labels to all objects and pods defined in this chart.
labels: {}

# Ingress configuration
ingress:
  # Enable all ingress resources (deprecated - use ingress.web.enabled and ingress.flower.enabled)
  enabled: ~

  # Configs for the Ingress of the web Service
  web:
    # Enable web ingress resource
    enabled: false

    # Annotations for the web Ingress
    annotations: {}

    # The path for the web Ingress
    path: "/"

    # The pathType for the above path (used only with Kubernetes v1.19 and above)
    pathType: "ImplementationSpecific"

    # The hostname for the web Ingress (Deprecated - renamed to `ingress.web.hosts`)
    host: ""

    # The hostnames or hosts configuration for the web Ingress
    hosts: []
    # - name: ""
    #   # configs for web Ingress TLS
    #   tls:
    #     # Enable TLS termination for the web Ingress
    #     enabled: false
    #     # the name of a pre-created Secret containing a TLS private key and certificate
    #     secretName: ""

    # The Ingress Class for the web Ingress (used only with Kubernetes v1.19 and above)
    ingressClassName: ""

    # configs for web Ingress TLS (Deprecated - renamed to `ingress.web.hosts[*].tls`)
    tls:
      # Enable TLS termination for the web Ingress
      enabled: false
      # the name of a pre-created Secret containing a TLS private key and certificate
      secretName: ""

    # HTTP paths to add to the web Ingress before the default path
    precedingPaths: []

    # Http paths to add to the web Ingress after the default path
    succeedingPaths: []

  # Configs for the Ingress of the flower Service
  flower:
    # Enable web ingress resource
    enabled: false

    # Annotations for the flower Ingress
    annotations: {}

    # The path for the flower Ingress
    path: "/"

    # The pathType for the above path (used only with Kubernetes v1.19 and above)
    pathType: "ImplementationSpecific"

    # The hostname for the flower Ingress (Deprecated - renamed to `ingress.flower.hosts`)
    host: ""

    # The hostnames or hosts configuration for the flower Ingress
    hosts: []
    # - name: ""
    #   tls:
    #     # Enable TLS termination for the flower Ingress
    #     enabled: false
    #     # the name of a pre-created Secret containing a TLS private key and certificate
    #     secretName: ""

    # The Ingress Class for the flower Ingress (used only with Kubernetes v1.19 and above)
    ingressClassName: ""

    # configs for flower Ingress TLS (Deprecated - renamed to `ingress.flower.hosts[*].tls`)
    tls:
      # Enable TLS termination for the flower Ingress
      enabled: false
      # the name of a pre-created Secret containing a TLS private key and certificate
      secretName: ""

# Network policy configuration
networkPolicies:
  # Enabled network policies
  enabled: false

# Extra annotations to apply to all
# Airflow pods
airflowPodAnnotations: {}

# Extra annotations to apply to
# main Airflow configmap
airflowConfigAnnotations: {}

# `airflow_local_settings` file as a string (can be templated).
airflowLocalSettings: |-
  {{- if semverCompare ">=2.2.0" .Values.airflowVersion }}
  {{- if not (or .Values.webserverSecretKey .Values.webserverSecretKeySecretName) }}
  from airflow.www.utils import UIAlert

  DASHBOARD_UIALERTS = [
    UIAlert(
      'Usage of a dynamic webserver secret key detected. We recommend a static webserver secret key instead.'
      ' See the <a href='
      '"https://airflow.apache.org/docs/helm-chart/stable/production-guide.html#webserver-secret-key">'
      'Helm Chart Production Guide</a> for more details.',
      category="warning",
      roles=["Admin"],
      html=True,
    )
  ]
  {{- end }}
  {{- end }}

# Enable RBAC (default on most clusters these days)
rbac:
  # Specifies whether RBAC resources should be created
  create: true
  createSCCRoleBinding: false

# Airflow executor
# One of: LocalExecutor, LocalKubernetesExecutor, CeleryExecutor, KubernetesExecutor, CeleryKubernetesExecutor
executor: "KubernetesExecutor"

# If this is true and using LocalExecutor/KubernetesExecutor/CeleryKubernetesExecutor, the scheduler's
# service account will have access to communicate with the api-server and launch pods.
# If this is true and using CeleryExecutor/KubernetesExecutor/CeleryKubernetesExecutor, the workers
# will be able to launch pods.
allowPodLaunching: true

# Environment variables for all airflow containers
env: []
# - name: ""
#   value: ""

# Secrets for all airflow containers
secret: []
# - envName: ""
#   secretName: ""
#   secretKey: ""

# Enables selected built-in secrets that are set via environment variables by default.
# Those secrets are provided by the Helm Chart secrets by default but in some cases you
# might want to provide some of those variables with _CMD or _SECRET variable, and you should
# in this case disable setting of those variables by setting the relevant configuration to false.
enableBuiltInSecretEnvVars:
  AIRFLOW__CORE__FERNET_KEY: true
  # For Airflow <2.3, backward compatibility; moved to [database] in 2.3
  AIRFLOW__CORE__SQL_ALCHEMY_CONN: true
  AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: true
  AIRFLOW_CONN_AIRFLOW_DB: true
  AIRFLOW__WEBSERVER__SECRET_KEY: true
  AIRFLOW__CELERY__CELERY_RESULT_BACKEND: true
  AIRFLOW__CELERY__RESULT_BACKEND: true
  AIRFLOW__CELERY__BROKER_URL: true
  AIRFLOW__ELASTICSEARCH__HOST: true
  AIRFLOW__ELASTICSEARCH__ELASTICSEARCH_HOST: true

# Extra secrets that will be managed by the chart
# (You can use them with extraEnv or extraEnvFrom or some of the extraVolumes values).
# The format for secret data is "key/value" where
#    * key (can be templated) is the name of the secret that will be created
#    * value: an object with the standard 'data' or 'stringData' key (or both).
#          The value associated with those keys must be a string (can be templated)
extraSecrets: {}
# eg:
# extraSecrets:
#   '{{ .Release.Name }}-airflow-connections':
#     type: 'Opaque'
#     labels:
#       my.custom.label/v1: my_custom_label_value_1
#     data: |
#       AIRFLOW_CONN_GCP: 'base64_encoded_gcp_conn_string'
#       AIRFLOW_CONN_AWS: 'base64_encoded_aws_conn_string'
#     stringData: |
#       AIRFLOW_CONN_OTHER: 'other_conn'
#   '{{ .Release.Name }}-other-secret-name-suffix':
#     data: |
#        ...

# Extra ConfigMaps that will be managed by the chart
# (You can use them with extraEnv or extraEnvFrom or some of the extraVolumes values).
# The format for configmap data is "key/value" where
#    * key (can be templated) is the name of the configmap that will be created
#    * value: an object with the standard 'data' key.
#          The value associated with this keys must be a string (can be templated)
extraConfigMaps: {}
# eg:
# extraConfigMaps:
#   '{{ .Release.Name }}-airflow-variables':
#     labels:
#       my.custom.label/v2: my_custom_label_value_2
#     data: |
#       AIRFLOW_VAR_HELLO_MESSAGE: "Hi!"
#       AIRFLOW_VAR_KUBERNETES_NAMESPACE: "{{ .Release.Namespace }}"

# Extra env 'items' that will be added to the definition of airflow containers
# a string is expected (can be templated).
# TODO: difference from `env`? This is a templated string. Probably should template `env` and remove this.
extraEnv: ~
# eg:
# extraEnv: |
#   - name: AIRFLOW__CORE__LOAD_EXAMPLES
#     value: 'True'

# Extra envFrom 'items' that will be added to the definition of airflow containers
# A string is expected (can be templated).
extraEnvFrom: ~
# eg:
# extraEnvFrom: |
#   - secretRef:
#       name: '{{ .Release.Name }}-airflow-connections'
#   - configMapRef:
#       name: '{{ .Release.Name }}-airflow-variables'

# Airflow database & redis config
data:
  # If secret names are provided, use those secrets
  # These secrets must be created manually, eg:
  #
  # kind: Secret
  # apiVersion: v1
  # metadata:
  #   name: custom-airflow-metadata-secret
  # type: Opaque
  # data:
  #   connection: base64_encoded_connection_string

  metadataSecretName: ~
  # When providing secret names and using the same database for metadata and
  # result backend, for Airflow < 2.4.0 it is necessary to create a separate
  # secret for result backend but with a db+ scheme prefix.
  # For Airflow >= 2.4.0 it is possible to not specify the secret again,
  # as Airflow will use sql_alchemy_conn with a db+ scheme prefix by default.
  resultBackendSecretName: ~
  brokerUrlSecretName: ~

  # Otherwise pass connection values in
  metadataConnection:
    user: postgres
    pass: postgres
    protocol: postgresql
    host: ~
    port: 5432
    db: postgres
    sslmode: disable
  # resultBackendConnection defaults to the same database as metadataConnection
  resultBackendConnection: ~
  # or, you can use a different database
  # resultBackendConnection:
  #   user: postgres
  #   pass: postgres
  #   protocol: postgresql
  #   host: ~
  #   port: 5432
  #   db: postgres
  #   sslmode: disable
  # Note: brokerUrl can only be set during install, not upgrade
  brokerUrl: ~

# Fernet key settings
# Note: fernetKey can only be set during install, not upgrade
fernetKey: ~
fernetKeySecretName: ~

# Flask secret key for Airflow Webserver: `[webserver] secret_key` in airflow.cfg
webserverSecretKey: ~
webserverSecretKeySecretName: ~

# In order to use kerberos you need to create secret containing the keytab file
# The secret name should follow naming convention of the application where resources are
# name {{ .Release-name }}-<POSTFIX>. In case of the keytab file, the postfix is "kerberos-keytab"
# So if your release is named "my-release" the name of the secret should be "my-release-kerberos-keytab"
#
# The Keytab content should be available in the "kerberos.keytab" key of the secret.
#
#  apiVersion: v1
#  kind: Secret
#  data:
#    kerberos.keytab: <base64_encoded keytab file content>
#  type: Opaque
#
#
#  If you have such keytab file you can do it with similar
#
#  kubectl create secret generic {{ .Release.name }}-kerberos-keytab --from-file=kerberos.keytab
#
#
#  Alternatively, instead of manually creating the secret, it is possible to specify
#  kerberos.keytabBase64Content parameter. This parameter should contain base64 encoded keytab.
#

kerberos:
  enabled: false
  ccacheMountPath: /var/kerberos-ccache
  ccacheFileName: cache
  configPath: /etc/krb5.conf
  keytabBase64Content: ~
  keytabPath: /etc/airflow.keytab
  principal: airflow@FOO.COM
  reinitFrequency: 3600
  config: |
    # This is an example config showing how you can use templating and how "example" config
    # might look like. It works with the test kerberos server that we are using during integration
    # testing at Apache Airflow (see `scripts/ci/docker-compose/integration-kerberos.yml` but in
    # order to make it production-ready you must replace it with your own configuration that
    # Matches your kerberos deployment. Administrators of your Kerberos instance should
    # provide the right configuration.

    [logging]
    default = "FILE:{{ template "airflow_logs_no_quote" . }}/kerberos_libs.log"
    kdc = "FILE:{{ template "airflow_logs_no_quote" . }}/kerberos_kdc.log"
    admin_server = "FILE:{{ template "airflow_logs_no_quote" . }}/kadmind.log"

    [libdefaults]
    default_realm = FOO.COM
    ticket_lifetime = 10h
    renew_lifetime = 7d
    forwardable = true

    [realms]
    FOO.COM = {
      kdc = kdc-server.foo.com
      admin_server = admin_server.foo.com
    }

# Airflow Worker Config
workers:
  # Number of airflow celery workers in StatefulSet
  replicas: 1
  # Max number of old replicasets to retain
  #revisionHistoryLimit: ~

  # Command to use when running Airflow workers (templated).
  command: ~
  # Args to use when running Airflow workers (templated).
  args:
    - "bash"
    - "-c"
    # The format below is necessary to get `helm lint` happy
    - |-
      exec \
      airflow {{ semverCompare ">=2.0.0" .Values.airflowVersion | ternary "celery worker" "worker" }}

  # If the worker stops responding for 5 minutes (5*60s) kill the
  # worker and let Kubernetes restart it
  #livenessProbe:
  #  enabled: true
  #  initialDelaySeconds: 10
  #  timeoutSeconds: 20
  #  failureThreshold: 5
  #  periodSeconds: 60
  #  command: ~

  # Update Strategy when worker is deployed as a StatefulSet
  updateStrategy: ~
  # Update Strategy when worker is deployed as a Deployment
  strategy:
    rollingUpdate:
      maxSurge: "100%"
      maxUnavailable: "50%"

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  fsGroup: 0
  #  runAsGroup: 0

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to worker kubernetes service account.
    annotations: {}

  # Allow KEDA autoscaling.
  # Persistence.enabled must be set to false to use KEDA.
  keda:
    enabled: false
    namespaceLabels: {}

    # How often KEDA polls the airflow DB to report new scale requests to the HPA
    pollingInterval: 5

    # How many seconds KEDA will wait before scaling to zero.
    # Note that HPA has a separate cooldown period for scale-downs
    cooldownPeriod: 30

    # Minimum number of workers created by keda
    minReplicaCount: 0

    # Maximum number of workers created by keda
    maxReplicaCount: 10

    # Specify HPA related options
    #advanced: {}
    # horizontalPodAutoscalerConfig:
    #   behavior:
    #     scaleDown:
    #       stabilizationWindowSeconds: 300
    #       policies:
    #         - type: Percent
    #           value: 100
    #           periodSeconds: 15

  persistence:
    # Enable persistent volumes
    enabled: true
    # Volume size for worker StatefulSet
    size: 2Gi
    # If using a custom storageClass, pass name ref to all statefulSets here
    storageClassName: "efs-sc-1"
    # Execute init container to chown log directory.
    # This is currently only needed in kind, due to usage
    # of local-path provisioner.
    fixPermissions: false
    # Annotations to add to worker volumes
    annotations: {}

  kerberosSidecar:
    # Enable kerberos sidecar
    enabled: false
    resources: {}
    #  limits:
    #   cpu: 100m
    #   memory: 128Mi
    #  requests:
    #   cpu: 100m
    #   memory: 128Mi

  resources: {}
  #  limits:
  #   cpu: 100m
  #   memory: 128Mi
  #  requests:
  #   cpu: 100m
  #   memory: 128Mi

  # Grace period for tasks to finish after SIGTERM is sent from kubernetes
  terminationGracePeriodSeconds: 600

  # This setting tells kubernetes that its ok to evict
  # when it wants to scale a node down.
  safeToEvict: true

  # Launch additional containers into worker.
  # Note: If used with KubernetesExecutor, you are responsible for signaling sidecars to exit when the main
  # container finishes so Airflow can continue the worker shutdown process!
  extraContainers: []
  # Add additional init containers into workers.
  extraInitContainers: []

  # Mount additional volumes into worker.
  extraVolumes: []
  extraVolumeMounts: []

  # Select certain nodes for airflow worker pods.
  nodeSelector: {}
  priorityClassName: ~
  affinity: {}
  # default worker affinity is:
  #  podAntiAffinity:
  #    preferredDuringSchedulingIgnoredDuringExecution:
  #    - podAffinityTerm:
  #        labelSelector:
  #          matchLabels:
  #            component: worker
  #        topologyKey: kubernetes.io/hostname
  #      weight: 100
  tolerations: []
  topologySpreadConstraints: []
  # hostAliases to use in worker pods.
  # See:
  # https://kubernetes.io/docs/concepts/services-networking/add-entries-to-pod-etc-hosts-with-host-aliases/
  hostAliases: []
  # - ip: "127.0.0.2"
  #   hostnames:
  #   - "test.hostname.one"
  # - ip: "127.0.0.3"
  #   hostnames:
  #   - "test.hostname.two"

  podAnnotations: {}

  # Labels specific to workers objects and pods
  #labels: {}

  logGroomerSidecar:
    # Command to use when running the Airflow worker log groomer sidecar (templated).
    command: ~
    # Args to use when running the Airflow worker log groomer sidecar (templated).
    args: ["bash", "/clean-logs"]
    # Number of days to retain logs
    retentionDays: 15
    resources: {}
    #  limits:
    #   cpu: 100m
    #   memory: 128Mi
    #  requests:
    #   cpu: 100m
    #   memory: 128Mi

  #waitForMigrations:
  #  env: []

  #env: []

# Airflow scheduler settings
scheduler:
  # If the scheduler stops heartbeating for 5 minutes (5*60s) kill the
  # scheduler and let Kubernetes restart it
  livenessProbe:
    initialDelaySeconds: 10
    timeoutSeconds: 20
    failureThreshold: 5
    periodSeconds: 60
    command: ~
  # Airflow 2.0 allows users to run multiple schedulers,
  # However this feature is only recommended for MySQL 8+ and Postgres
  replicas: 1
  # Max number of old replicasets to retain
  #revisionHistoryLimit: ~

  # Command to use when running the Airflow scheduler (templated).
  command: ~
  # Args to use when running the Airflow scheduler (templated).
  args: ["bash", "-c", "exec airflow scheduler"]

  # Update Strategy when scheduler is deployed as a StatefulSet
  # (when using LocalExecutor and workers.persistence)
  updateStrategy: ~
  # Update Strategy when scheduler is deployed as a Deployment
  # (when not using LocalExecutor and workers.persistence)
  strategy: ~

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  fsGroup: 0
  #  runAsGroup: 0

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to scheduler kubernetes service account.
    annotations: {}

  # Scheduler pod disruption budget
  podDisruptionBudget:
    enabled: false

    # PDB configuration
    config:
      maxUnavailable: 1

  resources: {}
  #  limits:
  #   cpu: 100m
  #   memory: 128Mi
  #  requests:
  #   cpu: 100m
  #   memory: 128Mi

  # This setting tells kubernetes that its ok to evict
  # when it wants to scale a node down.
  safeToEvict: true

  # Launch additional containers into scheduler.
  extraContainers: []
  # Add additional init containers into scheduler.
  extraInitContainers: []

  # Mount additional volumes into scheduler.
  extraVolumes: []
  extraVolumeMounts: []

  # Select certain nodes for airflow scheduler pods.
  nodeSelector: {}
  affinity: {}
  # default scheduler affinity is:
  #  podAntiAffinity:
  #    preferredDuringSchedulingIgnoredDuringExecution:
  #    - podAffinityTerm:
  #        labelSelector:
  #          matchLabels:
  #            component: scheduler
  #        topologyKey: kubernetes.io/hostname
  #      weight: 100
  tolerations: []
  topologySpreadConstraints: []

  priorityClassName: ~

  podAnnotations: {}

  # Labels specific to scheduler objects and pods
  #labels: {}

  logGroomerSidecar:
    # Whether to deploy the Airflow scheduler log groomer sidecar.
    enabled: true
    # Command to use when running the Airflow scheduler log groomer sidecar (templated).
    command: ~
    # Args to use when running the Airflow scheduler log groomer sidecar (templated).
    args: ["bash", "/clean-logs"]
    # Number of days to retain logs
    retentionDays: 15
    resources: {}
    #  limits:
    #   cpu: 100m
    #   memory: 128Mi
    #  requests:
    #   cpu: 100m
    #   memory: 128Mi

  waitForMigrations:
    # Whether to create init container to wait for db migrations
    enabled: true
    #env: []

  #env: []

# Airflow create user job settings
createUserJob:
  # Command to use when running the create user job (templated).
  command: ~
  # Args to use when running the create user job (templated).
  args:
    - "bash"
    - "-c"
    # The format below is necessary to get `helm lint` happy
    - |-
      exec \
      airflow {{ semverCompare ">=2.0.0" .Values.airflowVersion | ternary "users create" "create_user" }} "$@"
    - --
    - "-r"
    - "{{ .Values.webserver.defaultUser.role }}"
    - "-u"
    - "{{ .Values.webserver.defaultUser.username }}"
    - "-e"
    - "{{ .Values.webserver.defaultUser.email }}"
    - "-f"
    - "{{ .Values.webserver.defaultUser.firstName }}"
    - "-l"
    - "{{ .Values.webserver.defaultUser.lastName }}"
    - "-p"
    - "{{ .Values.webserver.defaultUser.password }}"

  # Annotations on the create user job pod
  annotations: {}
  # jobAnnotations are annotations on the create user job
  jobAnnotations: {}

  # Labels specific to createUserJob objects and pods
  #labels: {}

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  fsGroup: 0
  #  runAsGroup: 0

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to create user kubernetes service account.
    annotations: {}

  # Launch additional containers into user creation job
  extraContainers: []

  # Mount additional volumes into user creation job
  extraVolumes: []
  extraVolumeMounts: []

  nodeSelector: {}
  affinity: {}
  tolerations: []
  topologySpreadConstraints: []
  # In case you need to disable the helm hooks that create the jobs after install.
  # Disable this if you are using ArgoCD for example
  useHelmHooks: true
  #env: []

  resources: {}
  #  limits:
  #   cpu: 100m
  #   memory: 128Mi
  #  requests:
  #   cpu: 100m
  #   memory: 128Mi

# Airflow database migration job settings
migrateDatabaseJob:
  enabled: true
  # Command to use when running the migrate database job (templated).
  command: ~
  # Args to use when running the migrate database job (templated).
  args:
    - "bash"
    - "-c"
    # The format below is necessary to get `helm lint` happy
    - |-
      exec \
      airflow {{ semverCompare ">=2.0.0" .Values.airflowVersion | ternary "db upgrade" "upgradedb" }}

  # Annotations on the database migration pod
  annotations: {}
  # jobAnnotations are annotations on the database migration job
  jobAnnotations: {}

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  fsGroup: 0
  #  runAsGroup: 0

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to migrate database job kubernetes service account.
    annotations: {}

  resources: {}
  #  limits:
  #   cpu: 100m
  #   memory: 128Mi
  #  requests:
  #   cpu: 100m
  #   memory: 128Mi

  # Launch additional containers into database migration job
  extraContainers: []

  # Mount additional volumes into database migration job
  extraVolumes: []
  extraVolumeMounts: []

  nodeSelector: {}
  affinity: {}
  tolerations: []
  topologySpreadConstraints: []
  # In case you need to disable the helm hooks that create the jobs after install.
  # Disable this if you are using ArgoCD for example
  useHelmHooks: true

# Airflow webserver settings
webserver:
  allowPodLogReading: true
  livenessProbe:
    #path: /health
    #port: 8080
    initialDelaySeconds: 15
    timeoutSeconds: 30
    failureThreshold: 20
    periodSeconds: 5
    #scheme: HTTP

  readinessProbe:
    #httpGet: 
    #  path: /health
    #  port: 8080
    initialDelaySeconds: 15
    #timeoutSeconds: 30
    #failureThreshold: 20
    #periodSeconds: 5
    #scheme: HTTP

  # Number of webservers
  replicas: 1
  # Max number of old replicasets to retain
  #revisionHistoryLimit: ~

  # Command to use when running the Airflow webserver (templated).
  command: ~
  # Args to use when running the Airflow webserver (templated).
  args: ["bash", "-c", "exec airflow webserver"]

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to webserver kubernetes service account.
    annotations: {}

  # Webserver pod disruption budget
  podDisruptionBudget:
    enabled: false

    # PDB configuration
    config:
      maxUnavailable: 1

  # Allow overriding Update Strategy for Webserver
  strategy: ~

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  fsGroup: 0
  #  runAsGroup: 0

  # Additional network policies as needed (Deprecated - renamed to `webserver.networkPolicy.ingress.from`)
  extraNetworkPolicies: []
  networkPolicy:
    ingress:
      # Peers for webserver NetworkPolicy ingress
      from: []
      # Ports for webserver NetworkPolicy ingress (if `from` is set)
      ports:
        - port: "{{ .Values.ports.airflowUI }}"

  resources: {}
  #   limits:
  #     cpu: 100m
  #     memory: 128Mi
  #   requests:
  #     cpu: 100m
  #     memory: 128Mi

  # Create initial user.
  defaultUser:
    enabled: true
    role: Admin
    username: admin
    email: admin@example.com
    firstName: admin
    lastName: user
    password: admin

  # Launch additional containers into webserver.
  extraContainers: []
  # Add additional init containers into webserver.
  extraInitContainers: []

  # Mount additional volumes into webserver.
  extraVolumes: []
  extraVolumeMounts: []

  # This string (can be templated) will be mounted into the Airflow Webserver as a custom
  # webserver_config.py. You can bake a webserver_config.py in to your image instead.
  webserverConfig: ~
  # webserverConfig: |
  #   from airflow import configuration as conf

  #   # The SQLAlchemy connection string.
  #   SQLALCHEMY_DATABASE_URI = conf.get('database', 'SQL_ALCHEMY_CONN')

  #   # Flask-WTF flag for CSRF
  #   CSRF_ENABLED = True

  service:
    type: ClusterIP
    ## service annotations
    annotations: {}
    ports:
      - name: airflow-ui
        port: "{{ .Values.ports.airflowUI }}"
    # To change the port used to access the webserver:
    # ports:
    #   - name: airflow-ui
    #     port: 80
    #     targetPort: airflow-ui
    # To only expose a sidecar, not the webserver directly:
    # ports:
    #   - name: only_sidecar
    #     port: 80
    #     targetPort: 8888
    loadBalancerIP: ~
    ## Limit load balancer source ips to list of CIDRs
    # loadBalancerSourceRanges:
    #   - "10.123.0.0/16"
    loadBalancerSourceRanges: []

  # Select certain nodes for airflow webserver pods.
  nodeSelector: {}
  priorityClassName: ~
  affinity: {}
  # default webserver affinity is:
  #  podAntiAffinity:
  #    preferredDuringSchedulingIgnoredDuringExecution:
  #    - podAffinityTerm:
  #        labelSelector:
  #          matchLabels:
  #            component: webserver
  #        topologyKey: kubernetes.io/hostname
  #      weight: 100
  tolerations: []
  topologySpreadConstraints: []

  podAnnotations: {}

  # Labels specific webserver app
  #labels: {}

  waitForMigrations:
    # Whether to create init container to wait for db migrations
    enabled: true
    #env: []

  #env: []

# Airflow Triggerer Config
triggerer:
  enabled: true
  # Number of airflow triggerers in the deployment
  replicas: 1
  # Max number of old replicasets to retain
  #revisionHistoryLimit: ~

  # Command to use when running Airflow triggerers (templated).
  command: ~
  # Args to use when running Airflow triggerer (templated).
  args: ["bash", "-c", "exec airflow triggerer"]

  # Update Strategy for triggerers
  strategy:
    rollingUpdate:
      maxSurge: "100%"
      maxUnavailable: "50%"

  # If the triggerer stops heartbeating for 5 minutes (5*60s) kill the
  # triggerer and let Kubernetes restart it
  livenessProbe:
    initialDelaySeconds: 10
    timeoutSeconds: 20
    failureThreshold: 5
    periodSeconds: 60
    command: ~

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to triggerer kubernetes service account.
    annotations: {}

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  fsGroup: 0
  #  runAsGroup: 0

  resources: {}
  #  limits:
  #   cpu: 100m
  #   memory: 128Mi
  #  requests:
  #   cpu: 100m
  #   memory: 128Mi

  # Grace period for triggerer to finish after SIGTERM is sent from kubernetes
  terminationGracePeriodSeconds: 60

  # This setting tells kubernetes that its ok to evict
  # when it wants to scale a node down.
  safeToEvict: true

  # Launch additional containers into triggerer.
  extraContainers: []
  # Add additional init containers into triggerers.
  extraInitContainers: []

  # Mount additional volumes into triggerer.
  extraVolumes: []
  extraVolumeMounts: []

  # Select certain nodes for airflow triggerer pods.
  nodeSelector: {}
  affinity: {}
  # default triggerer affinity is:
  #  podAntiAffinity:
  #    preferredDuringSchedulingIgnoredDuringExecution:
  #    - podAffinityTerm:
  #        labelSelector:
  #          matchLabels:
  #            component: triggerer
  #        topologyKey: kubernetes.io/hostname
  #      weight: 100
  tolerations: []
  topologySpreadConstraints: []

  priorityClassName: ~

  podAnnotations: {}

  # Labels specific to triggerer objects and pods
  #labels: {}

  #waitForMigrations:
    # Whether to create init container to wait for db migrations
  #  enabled: true
  #  env: []

  #env: []

# Airflow Dag Processor Config
dagProcessor:
  enabled: false
  # Number of airflow dag processors in the deployment
  replicas: 1
  # Max number of old replicasets to retain
  revisionHistoryLimit: ~

  # Command to use when running Airflow dag processors (templated).
  command: ~
  # Args to use when running Airflow dag processor (templated).
  args: ["bash", "-c", "exec airflow dag-processor"]

  # Update Strategy for dag processors
  strategy:
    rollingUpdate:
      maxSurge: "100%"
      maxUnavailable: "50%"

  # If the dag processor stops heartbeating for 5 minutes (5*60s) kill the
  # dag processor and let Kubernetes restart it
  livenessProbe:
    initialDelaySeconds: 10
    timeoutSeconds: 20
    failureThreshold: 5
    periodSeconds: 60
    command: ~

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to dag processor kubernetes service account.
    annotations: {}

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  fsGroup: 0
  #  runAsGroup: 0

  resources: {}
  #  limits:
  #   cpu: 100m
  #   memory: 128Mi
  #  requests:
  #   cpu: 100m
  #   memory: 128Mi

  # Grace period for dag processor to finish after SIGTERM is sent from kubernetes
  terminationGracePeriodSeconds: 60

  # This setting tells kubernetes that its ok to evict
  # when it wants to scale a node down.
  safeToEvict: true

  # Launch additional containers into dag processor.
  extraContainers: []
  # Add additional init containers into dag processors.
  extraInitContainers: []

  # Mount additional volumes into dag processor.
  extraVolumes: []
  extraVolumeMounts: []

  # Select certain nodes for airflow dag processor pods.
  nodeSelector: {}
  affinity: {}
  # default dag processor affinity is:
  #  podAntiAffinity:
  #    preferredDuringSchedulingIgnoredDuringExecution:
  #    - podAffinityTerm:
  #        labelSelector:
  #          matchLabels:
  #            component: dag-processor
  #        topologyKey: kubernetes.io/hostname
  #      weight: 100
  tolerations: []
  topologySpreadConstraints: []

  priorityClassName: ~

  podAnnotations: {}

  waitForMigrations:
    # Whether to create init container to wait for db migrations
    enabled: true
    env: []

  env: []

# Flower settings
flower:
  # Enable flower.
  # If True, and using CeleryExecutor/CeleryKubernetesExecutor, will deploy flower app.
  enabled: false
  # Max number of old replicasets to retain
  #revisionHistoryLimit: ~

  # Command to use when running flower (templated).
  command: ~
  # Args to use when running flower (templated).
  args:
    - "bash"
    - "-c"
    # The format below is necessary to get `helm lint` happy
    - |-
      exec \
      airflow {{ semverCompare ">=2.0.0" .Values.airflowVersion | ternary "celery flower" "flower" }}

  # Additional network policies as needed (Deprecated - renamed to `flower.networkPolicy.ingress.from`)
  extraNetworkPolicies: []
  networkPolicy:
    ingress:
      # Peers for flower NetworkPolicy ingress
      from: []
      # Ports for flower NetworkPolicy ingress (if ingressPeers is set)
      ports:
        - port: "{{ .Values.ports.flowerUI }}"

  resources: {}
  #   limits:
  #     cpu: 100m
  #     memory: 128Mi
  #   requests:
  #     cpu: 100m
  #     memory: 128Mi

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  fsGroup: 0
  #  runAsGroup: 0

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to worker kubernetes service account.
    annotations: {}

  # A secret containing the connection
  secretName: ~

  # Else, if username and password are set, create secret from username and password
  username: ~
  password: ~

  service:
    type: ClusterIP
    ## service annotations
    annotations: {}
    ports:
      - name: flower-ui
        port: "{{ .Values.ports.flowerUI }}"
    # To change the port used to access flower:
    # ports:
    #   - name: flower-ui
    #     port: 8080
    #     targetPort: flower-ui
    loadBalancerIP: ~
    ## Limit load balancer source ips to list of CIDRs
    # loadBalancerSourceRanges:
    #   - "10.123.0.0/16"
    loadBalancerSourceRanges: []

  # Launch additional containers into the flower pods.
  extraContainers: []
  # Mount additional volumes into the flower pods.
  extraVolumes: []
  extraVolumeMounts: []

  # Select certain nodes for airflow flower pods.
  nodeSelector: {}
  affinity: {}
  tolerations: []
  topologySpreadConstraints: []

  priorityClassName: ~

  podAnnotations: {}

  # Labels specific to flower objects and pods
  #labels: {}
  #env: []

# StatsD settings
statsd:
  enabled: true
  # Max number of old replicasets to retain
  #revisionHistoryLimit: ~

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to worker kubernetes service account.
    annotations: {}

  uid: 65534
  # When not set, `statsd.uid` will be used
  securityContext: {}
  #  runAsUser: 65534
  #  fsGroup: 0
  #  runAsGroup: 0

  # Additional network policies as needed
  extraNetworkPolicies: []
  resources: {}
  #   limits:
  #     cpu: 100m
  #     memory: 128Mi
  #   requests:
  #     cpu: 100m
  #     memory: 128Mi

  service:
    extraAnnotations: {}

  # Select certain nodes for StatsD pods.
  nodeSelector: {}
  affinity: {}
  tolerations: []
  topologySpreadConstraints: []

  priorityClassName: ~

  # Additional mappings for StatsD exporter.
  # If set, will merge default mapping and extra mappings, default mapping has higher priority.
  # So, if you want to change some default mapping, please use `overrideMappings`
  extraMappings: []

  # Override mappings for StatsD exporter.
  # If set, will ignore setting item in default and `extraMappings`.
  # So, If you use it, ensure all mapping item contains in it.
  #overrideMappings: []

  #podAnnotations: {}

# PgBouncer settings
pgbouncer:
  # Enable PgBouncer
  enabled: false
  # Max number of old replicasets to retain
  #revisionHistoryLimit: ~
  # Command to use for PgBouncer(templated).
  command: ["pgbouncer", "-u", "nobody", "/etc/pgbouncer/pgbouncer.ini"]
  # Args to use for PgBouncer(templated).
  args: ~
  auth_type: md5
  auth_file: /etc/pgbouncer/users.txt

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to worker kubernetes service account.
    annotations: {}

  # Additional network policies as needed
  extraNetworkPolicies: []

  # Pool sizes
  metadataPoolSize: 10
  resultBackendPoolSize: 5

  # Maximum clients that can connect to PgBouncer (higher = more file descriptors)
  maxClientConn: 100

  # supply the name of existing secret with pgbouncer.ini and users.txt defined
  # you can load them to a k8s secret like the one below
  #  apiVersion: v1
  #  kind: Secret
  #  metadata:
  #    name: pgbouncer-config-secret
  #  data:
  #     pgbouncer.ini: <base64_encoded pgbouncer.ini file content>
  #     users.txt: <base64_encoded users.txt file content>
  #  type: Opaque
  #
  #  configSecretName: pgbouncer-config-secret
  #
  configSecretName: ~

  # PgBouncer pod disruption budget
  podDisruptionBudget:
    enabled: false

    # PDB configuration
    config:
      maxUnavailable: 1

  # Limit the resources to PgBouncer.
  # When you specify the resource request the k8s scheduler uses this information to decide which node to
  # place the Pod on. When you specify a resource limit for a Container, the kubelet enforces those limits so
  # that the running container is not allowed to use more of that resource than the limit you set.
  # See: https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/
  # Example:
  #
  # resource:
  #   limits:
  #     cpu: 100m
  #     memory: 128Mi
  #   requests:
  #     cpu: 100m
  #     memory: 128Mi
  resources: {}

  service:
    extraAnnotations: {}

  # https://www.pgbouncer.org/config.html
  verbose: 0
  logDisconnections: 0
  logConnections: 0

  sslmode: "prefer"
  ciphers: "normal"

  ssl:
    ca: ~
    cert: ~
    key: ~

  # Add extra PgBouncer ini configuration in the databases section:
  # https://www.pgbouncer.org/config.html#section-databases
  extraIniMetadata: ~
  extraIniResultBackend: ~
  # Add extra general PgBouncer ini configuration: https://www.pgbouncer.org/config.html
  extraIni: ~

  # Mount additional volumes into pgbouncer.
  extraVolumes: []
  extraVolumeMounts: []

  # Select certain nodes for PgBouncer pods.
  nodeSelector: {}
  affinity: {}
  tolerations: []
  topologySpreadConstraints: []

  priorityClassName: ~

  uid: 65534

  metricsExporterSidecar:
    resources: {}
    #  limits:
    #   cpu: 100m
    #   memory: 128Mi
    #  requests:
    #   cpu: 100m
    #   memory: 128Mi
    sslmode: "disable"

# Configuration for the redis provisioned by the chart
redis:
  enabled: true
  terminationGracePeriodSeconds: 600

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to worker kubernetes service account.
    annotations: {}

  persistence:
    # Enable persistent volumes
    enabled: true
    # Volume size for worker StatefulSet
    size: 1Gi
    # If using a custom storageClass, pass name ref to all statefulSets here
    storageClassName: "efs-sc-1"
    # Annotations to add to redis volumes
    annotations: {}

  resources: {}
  #  limits:
  #   cpu: 100m
  #   memory: 128Mi
  #  requests:
  #   cpu: 100m
  #   memory: 128Mi

  # If set use as redis secret. Make sure to also set data.brokerUrlSecretName value.
  passwordSecretName: ~

  # Else, if password is set, create secret with it,
  # Otherwise a new password will be generated on install
  # Note: password can only be set during install, not upgrade.
  password: ~

  # This setting tells kubernetes that its ok to evict
  # when it wants to scale a node down.
  safeToEvict: true

  # Select certain nodes for redis pods.
  nodeSelector: {}
  affinity: {}
  tolerations: []
  topologySpreadConstraints: []

  # Set to 0 for backwards-compatiblity
  uid: 0
  # If not set, `redis.uid` will be used
  securityContext: {}
  #  runAsUser: 999
  #  runAsGroup: 0

  #podAnnotations: {}
# Auth secret for a private registry
# This is used if pulling airflow images from a private registry
registry:
  secretName: ~

  # Example:
  # connection:
  #   user: ~
  #   pass: ~
  #   host: ~
  #   email: ~
  connection: {}

# Elasticsearch logging configuration
elasticsearch:
  # Enable elasticsearch task logging
  enabled: false
  # A secret containing the connection
  secretName: ~
  # Or an object representing the connection
  # Example:
  # connection:
  #   user: ~
  #   pass: ~
  #   host: ~
  #   port: ~
  connection: {}

# All ports used by chart
ports:
  flowerUI: 5555
  airflowUI: 8080
  workerLogs: 8793
  redisDB: 6379
  statsdIngest: 9125
  statsdScrape: 9102
  pgbouncer: 6543
  pgbouncerScrape: 9127

# Define any ResourceQuotas for namespace
quotas: {}

# Define default/max/min values for pods and containers in namespace
limits: []

# This runs as a CronJob to cleanup old pods.
cleanup:
  enabled: false
  # Run every 15 minutes
  schedule: "*/15 * * * *"
  # Command to use when running the cleanup cronjob (templated).
  command: ~
  # Args to use when running the cleanup cronjob (templated).
  args: ["bash", "-c", "exec airflow kubernetes cleanup-pods --namespace={{ .Release.Namespace }}"]


  # Select certain nodes for airflow cleanup pods.
  nodeSelector: {}
  affinity: {}
  tolerations: []
  topologySpreadConstraints: []

  podAnnotations: {}

  # Labels specific to cleanup objects and pods
  #labels: {}

  resources: {}
  #  limits:
  #   cpu: 100m
  #   memory: 128Mi
  #  requests:
  #   cpu: 100m
  #   memory: 128Mi

  # Create ServiceAccount
  serviceAccount:
    # Specifies whether a ServiceAccount should be created
    create: true
    # The name of the ServiceAccount to use.
    # If not set and create is true, a name is generated using the release name
    name: ~

    # Annotations to add to cleanup cronjob kubernetes service account.
    annotations: {}

  # When not set, the values defined in the global securityContext will be used
  securityContext: {}
  #  runAsUser: 50000
  #  runAsGroup: 0
  #env: []

  # Specify history limit
  # When set, overwrite the default k8s number of successful and failed CronJob executions that are saved.
  #failedJobsHistoryLimit: ~
  #successfulJobsHistoryLimit: ~

# Configuration for postgresql subchart
# Not recommended for production
postgresql:
  enabled: true
  postgresqlPassword: postgres
  postgresqlUsername: postgres

  persistence:
    enabled: true
    storageClass: "efs-sc-1"
    existingClaim: "af-efs-fargate-1"
    accessModes:
    - ReadWriteMany
    size: 2Gi
  volumePermissions:
    enabled: true

# Config settings to go into the mounted airflow.cfg
#
# Please note that these values are passed through the `tpl` function, so are
# all subject to being rendered as go templates. If you need to include a
# literal `{{` in a value, it must be expressed like this:
#
#    a: '{{ "{{ not a template }}" }}'
#
# Do not set config containing secrets via plain text values, use Env Var or k8s secret object
# yamllint disable rule:line-length
config:
  core:
    dags_folder: '{{ include "airflow_dags" . }}'
    # This is ignored when used with the official Docker image
    load_examples: 'False'
    executor: '{{ .Values.executor }}'
    # For Airflow 1.10, backward compatibility; moved to [logging] in 2.0
    colored_console_log: 'False'
    remote_logging: '{{- ternary "True" "False" .Values.elasticsearch.enabled }}'
  logging:
    remote_logging: '{{- ternary "True" "False" .Values.elasticsearch.enabled }}'
    colored_console_log: 'False'
  metrics:
    statsd_on: '{{ ternary "True" "False" .Values.statsd.enabled }}'
    statsd_port: 9125
    statsd_prefix: airflow
    statsd_host: '{{ printf "%s-statsd" .Release.Name }}'
  webserver:
    enable_proxy_fix: 'True'
    # For Airflow 1.10
    rbac: 'True'
  celery:
    flower_url_prefix: '{{ .Values.ingress.flower.path }}'
    worker_concurrency: 16
  scheduler:
    standalone_dag_processor: '{{ ternary "True" "False" .Values.dagProcessor.enabled }}'
    # statsd params included for Airflow 1.10 backward compatibility; moved to [metrics] in 2.0
    statsd_on: '{{ ternary "True" "False" .Values.statsd.enabled }}'
    statsd_port: 9125
    statsd_prefix: airflow
    statsd_host: '{{ printf "%s-statsd" .Release.Name }}'
    # `run_duration` included for Airflow 1.10 backward compatibility; removed in 2.0.
    run_duration: 41460
  elasticsearch:
    json_format: 'True'
    log_id_template: "{dag_id}_{task_id}_{execution_date}_{try_number}"
  elasticsearch_configs:
    max_retries: 3
    timeout: 30
    retry_timeout: 'True'
  kerberos:
    keytab: '{{ .Values.kerberos.keytabPath }}'
    reinit_frequency: '{{ .Values.kerberos.reinitFrequency }}'
    principal: '{{ .Values.kerberos.principal }}'
    ccache: '{{ .Values.kerberos.ccacheMountPath }}/{{ .Values.kerberos.ccacheFileName }}'
  celery_kubernetes_executor:
    kubernetes_queue: 'kubernetes'
  kubernetes:
    namespace: '{{ .Release.Namespace }}'
    airflow_configmap: '{{ include "airflow_config" . }}'
    airflow_local_settings_configmap: '{{ include "airflow_config" . }}'
    pod_template_file: '{{ include "airflow_pod_template_file" . }}/pod_template_file.yaml'
    worker_container_repository: '{{ .Values.images.airflow.repository | default .Values.defaultAirflowRepository }}'
    worker_container_tag: '{{ .Values.images.airflow.tag | default .Values.defaultAirflowTag }}'
    multi_namespace_mode: '{{ ternary "True" "False" .Values.multiNamespaceMode }}'
# yamllint enable rule:line-length

# Whether Airflow can launch workers and/or pods in multiple namespaces
# If true, it creates ClusterRole/ClusterRolebinding (with access to entire cluster)
multiNamespaceMode: false

# `podTemplate` is a templated string containing the contents of `pod_template_file.yaml` used for
# KubernetesExecutor workers. The default `podTemplate` will use normal `workers` configuration parameters
# (e.g. `workers.resources`). As such, you normally won't need to override this directly, however,
# you can still provide a completely custom `pod_template_file.yaml` if desired.
# If not set, a default one is created using `files/pod-template-file.kubernetes-helm-yaml`.
podTemplate: ~
# The following example is NOT functional, but meant to be illustrative of how you can provide a custom
# `pod_template_file`. You're better off starting with the default in
# `files/pod-template-file.kubernetes-helm-yaml` and modifying from there.
# We will set `priorityClassName` in this example:
# podTemplate: |
#   apiVersion: v1
#   kind: Pod
#   metadata:
#     name: dummy-name
#     labels:
#       tier: airflow
#       component: worker
#       release: {{ .Release.Name }}
#   spec:
#     priorityClassName: high-priority
#     containers:
#       - name: base
#         ...

# Git sync
dags:
  persistence:
    # Enable persistent volume for storing dags
    enabled: false
    # Volume size for dags
    size: 1Gi
    # If using a custom storageClass, pass name here
    storageClassName: "efs-sc-1"
    # access mode of the persistent volume
    accessMode: ReadWriteOnce
    ## the name of an existing PVC to use
    existingClaim: "af-efs-fargate-1"
    ## optional subpath for dag volume mount
    subPath: ~
  gitSync:
    enabled: True

    # git repo clone url
    # ssh examples ssh://git@github.com/apache/airflow.git
    # git@github.com:apache/airflow.git
    # https example: https://github.com/apache/airflow.git
    repo: https://github.com/apache/airflow.git
    branch: v2-2-stable
    rev: HEAD
    depth: 1
    # the number of consecutive failures allowed before aborting
    maxFailures: 0
    # subpath within the repo where dags are located
    # should be "" if dags are at repo root
    subPath: "tests/dags"
    # if your repo needs a user name password
    # you can load them to a k8s secret like the one below
    #   ---
    #   apiVersion: v1
    #   kind: Secret
    #   metadata:
    #     name: git-credentials
    #   data:
    #     GIT_SYNC_USERNAME: <base64_encoded_git_username>
    #     GIT_SYNC_PASSWORD: <base64_encoded_git_password>
    # and specify the name of the secret below
    #
    # credentialsSecret: git-credentials
    #
    #
    # If you are using an ssh clone url, you can load
    # the ssh private key to a k8s secret like the one below
    #   ---
    #   apiVersion: v1
    #   kind: Secret
    #   metadata:
    #     name: airflow-ssh-secret
    #   data:
    #     # key needs to be gitSshKey
    #     gitSshKey: <base64_encoded_data>
    # and specify the name of the secret below
    # sshKeySecret: airflow-ssh-secret
    #
    # If you are using an ssh private key, you can additionally
    # specify the content of your known_hosts file, example:
    #
    # knownHosts: |
    #    <host1>,<ip1> <key1>
    #    <host2>,<ip2> <key2>
    # interval between git sync attempts in seconds
    wait: 60
    containerName: git-sync
    uid: 65533

    # When not set, the values defined in the global securityContext will be used
    securityContext: {}
    #  runAsUser: 65533
    #  runAsGroup: 0

    extraVolumeMounts: []
    env: []
    resources: {}
    #  limits:
    #   cpu: 100m
    #   memory: 128Mi
    #  requests:
    #   cpu: 100m
    #   memory: 128Mi

logs:
  persistence:
    # Enable persistent volume for storing logs
    enabled: true
    # Volume size for logs
    size: 3Gi
    # If using a custom storageClass, pass name here
    storageClassName: "efs-sc-1"
    ## the name of an existing PVC to use
    existingClaim: "af-efs-fargate-1"

Docker Image customisations

N/A

What happened

When running C:\Kore\git_repo\airflow-eks-config>kubectl get pods -n dev
NAME READY STATUS RESTARTS AGE
airflow-postgresql-0 1/1 Running 0 38m
airflow-scheduler-77fbff86f5-q6cpm 2/3 CrashLoopBackOff 11 (94s ago) 38m
airflow-statsd-77bd4f95df-p28fr 0/1 CrashLoopBackOff 12 (74s ago) 38m
airflow-triggerer-59545ffc87-dlz8d 2/2 Running 7 (2m56s ago) 38m
airflow-webserver-7cfcd66964-2m847 0/1 Running 11 (73s ago) 38m

The Webserver/scheduler etc. remain in CrashLoopBackOff state. I do have the Sc/PV/PCV already configured.

What you think should happen instead

AIrflow should install

How to reproduce

The Values.yaml file is the one posted in "Helm Chart Configuration" section.

helm upgrade --install airflow apache-airflow/airflow -n dev --values values.yaml --set volumePermissions.enabled=true --debug

I am installing airflow using the above command and the pods remain in crashbackoff state:
airflow-webserver-69b9554c56-r4d9n 0/1 CrashLoopBackOff 9 (2m58s ago) 33m

kubectl describe output

Events:
Type Reason Age From Message

---

Warning LoggingDisabled 36m fargate-scheduler Disabled logging because aws-logging configmap was not found. configmap "aws-logging" not found
Normal Scheduled 35m fargate-scheduler Successfully assigned dev/airflow-webserver-69b9554c56-r4d9n to fargate-ip-192-168-128-124.us-west-2.compute.internal
Normal Pulling 35m kubelet Pulling image "apache/airflow:2.4.1"
Normal Pulled 33m kubelet Successfully pulled image "apache/airflow:2.4.1" in 1m56.248482482s
Normal Created 33m kubelet Created container wait-for-airflow-migrations
Normal Started 33m kubelet Started container wait-for-airflow-migrations
Normal Pulled 32m kubelet Container image "apache/airflow:2.4.1" already present on machine
Normal Created 32m kubelet Created container webserver
Normal Started 32m kubelet Started container webserver
Warning Unhealthy 20m (x132 over 32m) kubelet Liveness probe failed: Get "http://192.168.128.124:8080/health": dial tcp 192.168.128.124:8080: connect: connection refused
Warning BackOff 5m22s (x44 over 19m) kubelet Back-off restarting failed container
Warning Unhealthy 26s (x230 over 32m) kubelet Readiness probe failed: Get "http://192.168.128.124:8080/health": dial tcp 192.168.128.124:8080: connect: connection refused

Anything else

No response

Are you willing to submit PR?

• Yes I am willing to submit a PR!

Code of Conduct

• I agree to follow this project's Code of Conduct

[boring-cyborg[bot]]

Thanks for opening your first issue here! Be sure to follow the issue template!

[potiuk]

I am afraid It is impossible to analyse your configuration and figure out anything that could help to solve your problem. My wild guess is that you have some resource problem, but only looking at the logs of the crashed pods will make it possible you can help yourself to investigate it. You just need to find out why the pods are crashing - and if you cannot find any logs in airflow logs showing the reason, there must be somewhere in k8s logs.

This is something you need to learn how to do it anyway - managing deplioyment is not something that airlfow maintainers or users can help you with. I always recommend k9s as a tool to look at the logs, but you might alse need to look at the EKS logs to find out what is the reason for the crashes.