brata96 opened a new issue #20101:
URL: https://github.com/apache/airflow/issues/20101


   ### Official Helm Chart version
   
   1.3.0 (latest released)
   
   ### Apache Airflow version
   
   2.0.2
   
   ### Kubernetes Version
   
   Client Version: version.Info{Major:"1", Minor:"15", GitVersion:"v1.15.3", 
GitCommit:"2d3c76f9091b6bec110a5e63777c332469e0cba2", GitTreeState:"clean", 
BuildDate:"2019-08-19T11:13:54Z", GoVersion:"go1.12.9", Compiler:"gc", 
Platform:"linux/amd64"} Server Version: version.Info{Major:"1", Minor:"18+", 
GitVersion:"v1.18.20-gke.900", 
GitCommit:"1facb91642e16cb4f5be4e4a632c488aa4700382", GitTreeState:"clean", 
BuildDate:"2021-06-28T09:19:58Z", GoVersion:"go1.13.15b4", Compiler:"gc", 
Platform:"linux/amd64"}
   
   ### Helm Chart configuration
   
   `ingress:
     enabled: true
     
     web:
       annotations: {
         'kubernetes.io/ingress.class': 'nginx'
       }
       host: "airflow{{ url_suffix }}.{{ GCP_GKE_CLUSTER }}.{{ dns_domain }}"
   
     flower:
       annotations: {
         'kubernetes.io/ingress.class': 'nginx'
       }
       host: "airflow-flower{{ url_suffix }}.{{ GCP_GKE_CLUSTER }}.{{ 
dns_domain }}"
   
   web:
     authenticate: false
     webserverConfig:
       stringOverride: |-
          AUTH_ROLE_PUBLIC = "Admin"
   
     resources:
       requests:
         cpu: "1000m"
         memory: "4Gi"
       limits:
         cpu: "1000m"
         memory: "4Gi"
   web:
     extraPipPackages:
       ## the following configs require Flask-AppBuilder 3.2.0 (or later)
       - "Flask-AppBuilder~=3.2.0"
       ## the following configs require Authlib
       - "Authlib~=0.15.3"
    
   webserver:
     service:
       type: NodePort
     authenticate: false
   
   
   flower:
     service:
       type: NodePort
   
     resources:
       requests:
         cpu: "500m"
         memory: "1Gi"
       limits:
         cpu: "500m"
         memory: "1Gi"
   
   airflow:
     users: []
     connections:
       
     executor: KubernetesExecutor
   
     image:
       repository: "{{ DOCKER_REGISTRY 
}}/************/**********/airflow-cluster"
       tag: "{{ version }}"
    
     config:
   
       AIRFLOW__WEBSERVER__EXPOSE_CONFIG: "True"
   
       AIRFLOW__SCHEDULER__DAG_DIR_LIST_INTERVAL: "30"
   
       AIRFLOW__CORE__REMOTE_LOGGING: "True"
       AIRFLOW__CORE__REMOTE_BASE_LOG_FOLDER: "gs://{{ 
GCP_WORKLOAD_IDENTITY_PROJECT }}-airflow-cluster/airflow/logs"
       AIRFLOW__CORE__REMOTE_LOG_CONN_ID: "google_cloud_airflow"
   
       AIRFLOW__CORE__LOAD_EXAMPLES: "False"
       AIRFLOW__CORE__LAZY_LOAD_PLUGINS: "False"
       AIRFLOW__CORE__PLUGINS_FOLDER: "/opt/airflow/plugins"
       AIRFLOW__WEBSERVER__RELOAD_ON_PLUGIN_CHANGE: "True"
       # kubernetesexecutor config start
       AIRFLOW__KUBERNETES__DAGS_IN_IMAGE: "False"
       AIRFLOW__KUBERNETES__DAGS_VOLUME_HOST: 
"/opt/airflow/dags/repo/airflow-dags"
       AIRFLOW__KUBERNETES__WORKER_CONTAINER_REPOSITORY: "{{ DOCKER_REGISTRY 
}}/**********/*********/airflow-cluster"
       AIRFLOW__KUBERNETES__WORKER_CONTAINER_TAG: "{{ version }}"
       AIRFLOW__KUBERNETES__DELETE_WORKER_PODS: "False"
       # kubernetesexecutor config end
       AIRFLOW__API__ENABLE_EXPERIMENTAL_API: "True"
       AIRFLOW__API__AUTH_BACKEND: "airflow.api.auth.backend.default"
       AIRFLOW__WEBSERVER__ENABLE_PROXY_FIX: "{{ enable_proxy_fix }}"
   
       AUTH_ROLE_PUBLIC: "Admin"
       
       AIRFLOW__METRICS__STATSD_ON: "True"
        
     extraPipPackages:
        - "apache-airflow-providers-google==3.0.0"
   scheduler:
     resources:
       requests:
         cpu: "2000m"
         memory: "2Gi"
       limits:
         cpu: "2000m"
         memory: "2Gi"
   
     connections:
       - id: google_cloud_airflow
         type: google_cloud_platform
         extra: '{ "extra__google_cloud_platform__project": "{{ GCP_PROJECT 
}}", "extra__google_cloud_platform__scope": 
"https://www.googleapis.com/auth/cloud-platform";, 
"extra__google_cloud_platform__key_path": "", 
"extra__google_cloud_platform__keyfile_dict": ""}'
   
     pools: |
       {
         "example": {
           "description": "This is an example pool with 2 slots.",
           "slots": 4
         }
       }
     variables: |
       {
         "dags_folder": "/opt/airflow/dags/airflow-dags",
         "*********": "{{ ********* }}"
       }
   
   workers:
     extraVolumes:
     
     replicas: 4
   resources:
       requests:
         cpu: "1000m"
         memory: "4Gi"
       limits:
         cpu: "1000m"
         memory: "4Gi"
   
     podDisruptionBudget:
       enabled: true
       maxUnavailable: "20%"
   
     autoscaling:
       enabled: true
       maxReplicas: 20 
       metrics:
       - type: Resource
         resource:
           name: memory
           target:
             type: Utilization
             averageUtilization: 80
   
     celery:
       instances: 6 
       gracefullTermination: true
       gracefullTerminationPeriod: 540
     terminationPeriod: 60
   
   dags:
     persistence:
       enabled: true
       storageClassName: "csi-gcs-test-sc"
       accessMode: ReadOnlyMany
       existingClaim: "airflow-gcs-pvc2"
       size: 5Gi
   rbac:
     create: false
   
   redis:
     enabled: false
   
   workers:
     enabled: false`
   flower:
     enabled: false
   
   ### Docker Image customisations
   
   _No response_
   
   ### What happened
   
   trying to replace celeryexecutor with kubernetesExecutor after replacing 
kubernetes pods are crashing .we have disable the flower , worker and redis as 
each task in kubernetes executor create a new pods.
   `rbac:
     create: false
   
   redis:
     enabled: false
   
   workers:
     enabled: false
   
   flower:
     enabled: false`
   
   ### What you expected to happen
   
   successful implementation kubernetesExecutor 
   
   ### How to reproduce
   
   _No response_
   
   ### Anything else
   
   _No response_
   
   ### Are you willing to submit PR?
   
   - [ ] 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)
   


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