DataCenterCDC-DS/deploy/kubernetes/dolphinscheduler/values.yaml

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# Default values for dolphinscheduler-chart.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.

timezone: "Asia/Shanghai"

# Used to detect whether dolphinscheduler dependent services such as database are ready
initImage:
  pullPolicy: "IfNotPresent"
  busybox: "busybox:1.30.1"

image:
  registry: "dolphinscheduler.docker.scarf.sh/apache"
  tag: "dev-SNAPSHOT"
  pullPolicy: "IfNotPresent"
  pullSecret: ""
  master: dolphinscheduler-master
  worker: dolphinscheduler-worker
  api: dolphinscheduler-api
  alert: dolphinscheduler-alert-server
  tools: dolphinscheduler-tools

## If not exists external database, by default, Dolphinscheduler's database will use it.
postgresql:
  enabled: true
  postgresqlUsername: "root"
  postgresqlPassword: "root"
  postgresqlDatabase: "dolphinscheduler"
  params: "characterEncoding=utf8"
  persistence:
    enabled: false
    size: "20Gi"
    storageClass: "-"

mysql:
  enabled: false
  auth:
    username: "ds"
    password: "ds"
    database: "dolphinscheduler"
    params: "characterEncoding=utf8"
  primary:
    persistence:
      enabled: false
      size: "20Gi"
      storageClass: "-"

minio:
  enabled: true
  auth:
    rootUser: minioadmin
    rootPassword: minioadmin
  persistence:
    enabled: false
  defaultBuckets: "dolphinscheduler"

## If exists external database, and set postgresql.enable value to false.
## external database will be used, otherwise Dolphinscheduler's database will be used.
externalDatabase:
  enabled: false
  type: "postgresql"
  host: "localhost"
  port: "5432"
  username: "root"
  password: "root"
  database: "dolphinscheduler"
  params: "characterEncoding=utf8"

## If not exists external registry, the zookeeper registry will be used by default.
zookeeper:
  enabled: true
  service:
    port: 2181
  fourlwCommandsWhitelist: "srvr,ruok,wchs,cons"
  persistence:
    enabled: false
    size: "20Gi"
    storageClass: "-"

etcd:
  enabled: false
  endpoints: ""
  namespace: "dolphinscheduler"
  user: ""
  passWord: ""
  authority: ""
  # Please create a new folder: deploy/kubernetes/dolphinscheduler/etcd-certs
  ssl:
    enabled: false
    certFile: "etcd-certs/ca.crt"
    keyCertChainFile: "etcd-certs/client.crt"
    keyFile: "etcd-certs/client.pem"

## If exists external registry and set zookeeper.enable value to false, the external registry will be used.
externalRegistry:
  registryPluginName: "zookeeper"
  registryServers: "127.0.0.1:2181"

security:
  authentication:
    type: PASSWORD
    ldap:
      urls: ldap://ldap.forumsys.com:389/
      basedn: dc=example,dc=com
      username: cn=read-only-admin,dc=example,dc=com
      password: password
      user:
        admin: read-only-admin
        identityattribute: uid
        emailattribute: mail
        notexistaction: CREATE
      ssl:
        enable: false
        # do not change this value
        truststore: "/opt/ldapkeystore.jks"
        # if you use macOS, please run `base64 -b 0 -i /path/to/your.jks`
        # if you use Linux, please run `base64 -w 0 /path/to/your.jks`
        # if you use Windows, please run `certutil -f -encode /path/to/your.jks`
        # Then copy the base64 content to below field in one line
        jksbase64content: ""
        truststorepassword: ""

conf:
  common:
    # user data local directory path, please make sure the directory exists and have read write permissions
    data.basedir.path: /tmp/dolphinscheduler

    # resource storage type: HDFS, S3, OSS, GCS, ABS, NONE
    resource.storage.type: S3

    # resource store on HDFS/S3 path, resource file will store to this base path, self configuration, please make sure the directory exists on hdfs and have read write permissions. "/dolphinscheduler" is recommended
    resource.storage.upload.base.path: /dolphinscheduler

    # The AWS access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
    resource.aws.access.key.id: minioadmin

    # The AWS secret access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
    resource.aws.secret.access.key: minioadmin

    # The AWS Region to use. if resource.storage.type=S3 or use EMR-Task, This configuration is required
    resource.aws.region: ca-central-1

    # The name of the bucket. You need to create them by yourself. Otherwise, the system cannot start. All buckets in Amazon S3 share a single namespace; ensure the bucket is given a unique name.
    resource.aws.s3.bucket.name: dolphinscheduler

    # You need to set this parameter when private cloud s3. If S3 uses public cloud, you only need to set resource.aws.region or set to the endpoint of a public cloud such as S3.cn-north-1.amazonaws.com.cn
    resource.aws.s3.endpoint: http://minio:9000

    # alibaba cloud access key id, required if you set resource.storage.type=OSS
    resource.alibaba.cloud.access.key.id: <your-access-key-id>

    # alibaba cloud access key secret, required if you set resource.storage.type=OSS
    resource.alibaba.cloud.access.key.secret: <your-access-key-secret>

    # alibaba cloud region, required if you set resource.storage.type=OSS
    resource.alibaba.cloud.region: cn-hangzhou

    # oss bucket name, required if you set resource.storage.type=OSS
    resource.alibaba.cloud.oss.bucket.name: dolphinscheduler

    # oss bucket endpoint, required if you set resource.storage.type=OSS
    resource.alibaba.cloud.oss.endpoint: https://oss-cn-hangzhou.aliyuncs.com

    # if resource.storage.type=HDFS, the user must have the permission to create directories under the HDFS root path
    resource.hdfs.root.user: hdfs

    # if resource.storage.type=S3, the value like: s3a://dolphinscheduler; if resource.storage.type=HDFS and namenode HA is enabled, you need to copy core-site.xml and hdfs-site.xml to conf dir
    resource.hdfs.fs.defaultFS: hdfs://mycluster:8020

    # whether to startup kerberos
    hadoop.security.authentication.startup.state: false

    # java.security.krb5.conf path
    java.security.krb5.conf.path: /opt/krb5.conf

    # login user from keytab username
    login.user.keytab.username: hdfs-mycluster@ESZ.COM

    # login user from keytab path
    login.user.keytab.path: /opt/hdfs.headless.keytab

    # kerberos expire time, the unit is hour
    kerberos.expire.time: 2

    # resourcemanager port, the default value is 8088 if not specified
    resource.manager.httpaddress.port: 8088

    # if resourcemanager HA is enabled, please set the HA IPs; if resourcemanager is single, keep this value empty
    yarn.resourcemanager.ha.rm.ids: 192.168.xx.xx,192.168.xx.xx

    # if resourcemanager HA is enabled or not use resourcemanager, please keep the default value; If resourcemanager is single, you only need to replace ds1 to actual resourcemanager hostname
    yarn.application.status.address: http://ds1:%s/ws/v1/cluster/apps/%s

    # job history status url when application number threshold is reached(default 10000, maybe it was set to 1000)
    yarn.job.history.status.address: http://ds1:19888/ws/v1/history/mapreduce/jobs/%s

    # datasource encryption enable
    datasource.encryption.enable: false

    # datasource encryption salt
    datasource.encryption.salt: '!@#$%^&*'

    # data quality option
    data-quality.jar.name: dolphinscheduler-data-quality-dev-SNAPSHOT.jar

    # Whether hive SQL is executed in the same session
    support.hive.oneSession: false

    # use sudo or not, if set true, executing user is tenant user and deploy user needs sudo permissions; if set false, executing user is the deploy user and doesn't need sudo permissions
    sudo.enable: true

    # development state
    development.state: false

    # rpc port
    alert.rpc.port: 50052

    # set path of conda.sh
    conda.path: /opt/anaconda3/etc/profile.d/conda.sh

    # Task resource limit state
    task.resource.limit.state: false

    # mlflow task plugin preset repository
    ml.mlflow.preset_repository: https://github.com/apache/dolphinscheduler-mlflow

    # mlflow task plugin preset repository version
    ml.mlflow.preset_repository_version: "main"

    # way to collect applicationId: log, aop
    appId.collect: log

common:
  ## Configmap
  configmap:
    DOLPHINSCHEDULER_OPTS: ""
    DATA_BASEDIR_PATH: "/tmp/dolphinscheduler"
    RESOURCE_UPLOAD_PATH: "/dolphinscheduler"

    # dolphinscheduler env
    HADOOP_HOME: "/opt/soft/hadoop"
    HADOOP_CONF_DIR: "/opt/soft/hadoop/etc/hadoop"
    SPARK_HOME: "/opt/soft/spark"
    PYTHON_HOME: "/usr/bin/python"
    JAVA_HOME: "/opt/java/openjdk"
    HIVE_HOME: "/opt/soft/hive"
    FLINK_HOME: "/opt/soft/flink"
    DATAX_HOME: "/opt/soft/datax"
  ## Shared storage persistence mounted into api, master and worker, such as Hadoop, Spark, Flink and DataX binary package
  sharedStoragePersistence:
    enabled: false
    mountPath: "/opt/soft"
    accessModes:
    - "ReadWriteMany"
    ## storageClassName must support the access mode: ReadWriteMany
    storageClassName: "-"
    storage: "20Gi"
  ## If RESOURCE_STORAGE_TYPE is HDFS and FS_DEFAULT_FS is file:///, fsFileResourcePersistence should be enabled for resource storage
  fsFileResourcePersistence:
    enabled: false
    accessModes:
    - "ReadWriteMany"
    ## storageClassName must support the access mode: ReadWriteMany
    storageClassName: "-"
    storage: "20Gi"

master:
  ## PodManagementPolicy controls how pods are created during initial scale up, when replacing pods on nodes, or when scaling down.
  podManagementPolicy: "Parallel"
  ## Replicas is the desired number of replicas of the given Template.
  replicas: "3"
  ## You can use annotations to attach arbitrary non-identifying metadata to objects.
  ## Clients such as tools and libraries can retrieve this metadata.
  annotations: {}
  ## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
  ## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
  affinity: {}
  ## NodeSelector is a selector which must be true for the pod to fit on a node.
  ## Selector which must match a node's labels for the pod to be scheduled on that node.
  ## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
  nodeSelector: {}
  ## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
  ## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
  tolerations: []
  ## Compute Resources required by this container. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
  resources: {}
  # resources:
  #   limits:
  #     memory: "8Gi"
  #     cpu: "4"
  #   requests:
  #     memory: "2Gi"
  #     cpu: "500m"
  ## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  livenessProbe:
    enabled: true
    initialDelaySeconds: "30"
    periodSeconds: "30"
    timeoutSeconds: "5"
    failureThreshold: "3"
    successThreshold: "1"
  ## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  readinessProbe:
    enabled: true
    initialDelaySeconds: "30"
    periodSeconds: "30"
    timeoutSeconds: "5"
    failureThreshold: "3"
    successThreshold: "1"
  ## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
  ## The StatefulSet controller is responsible for mapping network identities to claims in a way that maintains the identity of a pod.
  ## Every claim in this list must have at least one matching (by name) volumeMount in one container in the template.
  ## A claim in this list takes precedence over any volumes in the template, with the same name.
  persistentVolumeClaim:
    enabled: false
    accessModes:
    - "ReadWriteOnce"
    storageClassName: "-"
    storage: "20Gi"
  env:
    JAVA_OPTS: "-Xms1g -Xmx1g -Xmn512m"
    MASTER_EXEC_THREADS: "100"
    MASTER_EXEC_TASK_NUM: "20"
    MASTER_DISPATCH_TASK_NUM: "3"
    MASTER_HOST_SELECTOR: "LowerWeight"
    MASTER_HEARTBEAT_INTERVAL: "10s"
    MASTER_HEARTBEAT_ERROR_THRESHOLD: "5"
    MASTER_TASK_COMMIT_RETRYTIMES: "5"
    MASTER_TASK_COMMIT_INTERVAL: "1s"
    MASTER_STATE_WHEEL_INTERVAL: "5s"
    MASTER_MAX_CPU_LOAD_AVG: "1"
    MASTER_RESERVED_MEMORY: "0.3"
    MASTER_FAILOVER_INTERVAL: "10m"
    MASTER_KILL_APPLICATION_WHEN_HANDLE_FAILOVER: "true"
  service:
    # annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
    annotations: {}
    # serviceMonitor for prometheus operator
    serviceMonitor:
      # -- Enable or disable master serviceMonitor
      enabled: false
      # -- @param serviceMonitor.interval interval at which metrics should be scraped
      interval: 15s
      # -- @param serviceMonitor.path path of the metrics endpoint
      path: /actuator/prometheus
      # -- @param serviceMonitor.labels ServiceMonitor extra labels
      labels: {}
      # -- @param serviceMonitor.annotations ServiceMonitor annotations
      annotations: {}

worker:
  ## PodManagementPolicy controls how pods are created during initial scale up, when replacing pods on nodes, or when scaling down.
  podManagementPolicy: "Parallel"
  ## Replicas is the desired number of replicas of the given Template.
  replicas: "3"
  ## You can use annotations to attach arbitrary non-identifying metadata to objects.
  ## Clients such as tools and libraries can retrieve this metadata.
  annotations: {}
  ## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
  ## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
  affinity: {}
  ## NodeSelector is a selector which must be true for the pod to fit on a node.
  ## Selector which must match a node's labels for the pod to be scheduled on that node.
  ## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
  nodeSelector: {}
  ## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
  ## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
  tolerations: []
  ## Compute Resources required by this container. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
  resources: {}
  # resources:
  #   limits:
  #     memory: "8Gi"
  #     cpu: "4"
  #   requests:
  #     memory: "2Gi"
  #     cpu: "500m"
  ## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  livenessProbe:
    enabled: true
    initialDelaySeconds: "30"
    periodSeconds: "30"
    timeoutSeconds: "5"
    failureThreshold: "3"
    successThreshold: "1"
  ## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  readinessProbe:
    enabled: true
    initialDelaySeconds: "30"
    periodSeconds: "30"
    timeoutSeconds: "5"
    failureThreshold: "3"
    successThreshold: "1"
  ## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
  ## The StatefulSet controller is responsible for mapping network identities to claims in a way that maintains the identity of a pod.
  ## Every claim in this list must have at least one matching (by name) volumeMount in one container in the template.
  ## A claim in this list takes precedence over any volumes in the template, with the same name.
  persistentVolumeClaim:
    enabled: false
    ## dolphinscheduler data volume
    dataPersistentVolume:
      enabled: false
      accessModes:
      - "ReadWriteOnce"
      storageClassName: "-"
      storage: "20Gi"
    ## dolphinscheduler logs volume
    logsPersistentVolume:
      enabled: false
      accessModes:
      - "ReadWriteOnce"
      storageClassName: "-"
      storage: "20Gi"
  env:
    WORKER_MAX_CPU_LOAD_AVG: "1"
    WORKER_RESERVED_MEMORY: "0.3"
    WORKER_EXEC_THREADS: "100"
    WORKER_HEARTBEAT_INTERVAL: "10s"
    WORKER_HEART_ERROR_THRESHOLD: "5"
    WORKER_HOST_WEIGHT: "100"
  keda:
    enabled: false
    namespaceLabels: { }

    # How often KEDA polls the DolphinScheduler 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: 3

    # Specify HPA related options
    advanced: { }
    # horizontalPodAutoscalerConfig:
    #   behavior:
    #     scaleDown:
    #       stabilizationWindowSeconds: 300
    #       policies:
    #         - type: Percent
    #           value: 100
    #           periodSeconds: 15
  service:
    # annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
    annotations: {}
    # serviceMonitor for prometheus operator
    serviceMonitor:
      # -- Enable or disable worker serviceMonitor
      enabled: false
      # -- @param serviceMonitor.interval interval at which metrics should be scraped
      interval: 15s
      # -- @param serviceMonitor.path path of the metrics endpoint
      path: /actuator/prometheus
      # -- @param serviceMonitor.labels ServiceMonitor extra labels
      labels: {}
      # -- @param serviceMonitor.annotations ServiceMonitor annotations
      annotations: {}


alert:
  ## Number of desired pods. This is a pointer to distinguish between explicit zero and not specified. Defaults to 1.
  replicas: 1
  ## The deployment strategy to use to replace existing pods with new ones.
  strategy:
    type: "RollingUpdate"
    rollingUpdate:
      maxSurge: "25%"
      maxUnavailable: "25%"
  ## You can use annotations to attach arbitrary non-identifying metadata to objects.
  ## Clients such as tools and libraries can retrieve this metadata.
  annotations: {}
  ## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
  ## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
  affinity: {}
  ## NodeSelector is a selector which must be true for the pod to fit on a node.
  ## Selector which must match a node's labels for the pod to be scheduled on that node.
  ## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
  nodeSelector: {}
  ## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
  ## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
  tolerations: []
  ## Compute Resources required by this container. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
  resources: {}
  # resources:
  #   limits:
  #     memory: "2Gi"
  #     cpu: "1"
  #   requests:
  #     memory: "1Gi"
  #     cpu: "500m"
  ## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  livenessProbe:
    enabled: true
    initialDelaySeconds: "30"
    periodSeconds: "30"
    timeoutSeconds: "5"
    failureThreshold: "3"
    successThreshold: "1"
  ## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  readinessProbe:
    enabled: true
    initialDelaySeconds: "30"
    periodSeconds: "30"
    timeoutSeconds: "5"
    failureThreshold: "3"
    successThreshold: "1"
  ## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
  ## More info: https://kubernetes.io/docs/concepts/storage/persistent-volumes#persistentvolumeclaims
  persistentVolumeClaim:
    enabled: false
    accessModes:
    - "ReadWriteOnce"
    storageClassName: "-"
    storage: "20Gi"
  env:
    JAVA_OPTS: "-Xms512m -Xmx512m -Xmn256m"
  service:
    # annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
    annotations: {}
    # serviceMonitor for prometheus operator
    serviceMonitor:
      # -- Enable or disable alert-server serviceMonitor
      enabled: false
      # -- @param serviceMonitor.interval interval at which metrics should be scraped
      interval: 15s
      # -- @param serviceMonitor.path path of the metrics endpoint
      path: /actuator/prometheus
      # -- @param serviceMonitor.labels ServiceMonitor extra labels
      labels: {}
      # -- @param serviceMonitor.annotations ServiceMonitor annotations
      annotations: {}


api:
  ## Number of desired pods. This is a pointer to distinguish between explicit zero and not specified. Defaults to 1.
  replicas: "1"
  ## The deployment strategy to use to replace existing pods with new ones.
  strategy:
    type: "RollingUpdate"
    rollingUpdate:
      maxSurge: "25%"
      maxUnavailable: "25%"
  ## You can use annotations to attach arbitrary non-identifying metadata to objects.
  ## Clients such as tools and libraries can retrieve this metadata.
  annotations: {}
  ## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
  ## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
  affinity: {}
  ## NodeSelector is a selector which must be true for the pod to fit on a node.
  ## Selector which must match a node's labels for the pod to be scheduled on that node.
  ## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
  nodeSelector: {}
  ## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
  ## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
  tolerations: []
  ## Compute Resources required by this container. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
  resources: {}
  # resources:
  #   limits:
  #     memory: "2Gi"
  #     cpu: "1"
  #   requests:
  #     memory: "1Gi"
  #     cpu: "500m"
  ## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  livenessProbe:
    enabled: true
    initialDelaySeconds: "30"
    periodSeconds: "30"
    timeoutSeconds: "5"
    failureThreshold: "3"
    successThreshold: "1"
  ## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
  ## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
  readinessProbe:
    enabled: true
    initialDelaySeconds: "30"
    periodSeconds: "30"
    timeoutSeconds: "5"
    failureThreshold: "3"
    successThreshold: "1"
  ## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
  ## More info: https://kubernetes.io/docs/concepts/storage/persistent-volumes#persistentvolumeclaims
  persistentVolumeClaim:
    enabled: false
    accessModes:
    - "ReadWriteOnce"
    storageClassName: "-"
    storage: "20Gi"
  service:
    ## type determines how the Service is exposed. Defaults to ClusterIP. Valid options are ExternalName, ClusterIP, NodePort, and LoadBalancer
    type: "ClusterIP"
    ## clusterIP is the IP address of the service and is usually assigned randomly by the master
    clusterIP: ""
    ## nodePort is the port on each node on which this api service is exposed when type=NodePort
    nodePort: ""
    ## pythonNodePort is the port on each node on which this python api service is exposed when type=NodePort
    pythonNodePort: ""
    ## externalIPs is a list of IP addresses for which nodes in the cluster will also accept traffic for this service
    externalIPs: []
    ## externalName is the external reference that kubedns or equivalent will return as a CNAME record for this service, requires Type to be ExternalName
    externalName: ""
    ## loadBalancerIP when service.type is LoadBalancer. LoadBalancer will get created with the IP specified in this field
    loadBalancerIP: ""
    ## annotations may need to be set when service.type is LoadBalancer
    ## service.beta.kubernetes.io/aws-load-balancer-ssl-cert: arn:aws:acm:us-east-1:EXAMPLE_CERT
    annotations: {}
    # serviceMonitor for prometheus operator
    serviceMonitor:
      # -- Enable or disable api-server serviceMonitor
      enabled: false
      # -- @param serviceMonitor.interval interval at which metrics should be scraped
      interval: 15s
      # -- @param serviceMonitor.path path of the metrics endpoint
      path: /dolphinscheduler/actuator/prometheus
      # -- @param serviceMonitor.labels ServiceMonitor extra labels
      labels: {}
      # -- @param serviceMonitor.annotations ServiceMonitor annotations
      annotations: {}
  env:
    JAVA_OPTS: "-Xms512m -Xmx512m -Xmn256m"

ingress:
  enabled: false
  host: "dolphinscheduler.org"
  path: "/dolphinscheduler"
  annotations: {}
  tls:
    enabled: false
    secretName: "dolphinscheduler-tls"