Add chart mlflow 1.9.0
This commit is contained in:
wbsong111
@@ -0,0 +1,510 @@
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# yaml-language-server: $schema=values.schema.json
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# Default values for mlflow.
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# This is a YAML-formatted file.
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# Declare variables to be passed into your templates.
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# -- (int) Numbers of replicas
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replicaCount: 1
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# -- Image of mlflow
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image:
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# -- The docker image repository to use
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repository: paasup/mlflow
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# -- The docker image pull policy
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pullPolicy: IfNotPresent
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# -- The docker image tag to use. Default app version
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tag: "v3.11.1-oidc"
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# -- mlflow init images
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initImages:
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# -- dbchecker init container image configuration
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dbchecker:
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# -- dbchecker init container image repository to use
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repository: busybox
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# -- dbchecker init container image pull policy
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pullPolicy: IfNotPresent
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# -- dbchecker init container image tag to use
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tag: "1.37"
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# -- mlflow-db-migration init container image configuration
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mlflowDbMigration:
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# -- mlflow-db-migration init container image repository to use.
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repository: paasup/mlflow
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# -- mlflow-db-migration init container image pull policy.
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pullPolicy: IfNotPresent
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# -- mlflow-db-migration init container image tag to use. Default app version
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tag: "v3.11.1-oidc"
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# -- ini-file-initializer init container image configuration
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iniFileInitializer:
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# -- ini-file-initializer init container image repository to use
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repository: busybox
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# -- ini-file-initializer init container image pull policy
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pullPolicy: IfNotPresent
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# -- ini-file-initializer init container image tag to use
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tag: "1.37"
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# -- This will set the deployment strategy more information can be found here: https://kubernetes.io/docs/concepts/workloads/controllers/deployment/#strategy
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strategy:
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type: "RollingUpdate"
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rollingUpdate:
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maxSurge: "100%"
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maxUnavailable: 0
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# -- Image pull secrets for private docker registry usages
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imagePullSecrets: []
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# -- String to override the default generated name
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nameOverride: ""
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# -- String to override the default generated fullname
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fullnameOverride: ""
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serviceAccount:
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# -- Specifies whether a ServiceAccount should be created
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create: true
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# -- Automatically mount a ServiceAccount's API credentials?
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automount: true
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# -- Annotations to add to the service account. AWS EKS users can assign role arn from here.
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# Please find more information from here:
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# https://docs.aws.amazon.com/eks/latest/userguide/associate-service-account-role.html
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annotations: {}
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# eks.amazonaws.com/role-arn: ""
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# -- The name of the ServiceAccount to use.
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# If not set and create is true, a name is generated using the fullname template
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name: ""
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# -- Annotations for the pod
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podAnnotations: {}
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# -- Extra labels for the pod
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extraPodLabels: {}
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# -- This is for setting Security Context to a Pod. For more information checkout: https://kubernetes.io/docs/tasks/configure-pod-container/security-context/
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podSecurityContext:
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fsGroup: 1001
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fsGroupChangePolicy: "OnRootMismatch"
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# -- This is for setting Security Context to a Container. For more information checkout: https://kubernetes.io/docs/tasks/configure-pod-container/security-context/
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securityContext:
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allowPrivilegeEscalation: false
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capabilities:
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drop:
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- ALL
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readOnlyRootFilesystem: false
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runAsNonRoot: true
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privileged: false
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runAsUser: 1001
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runAsGroup: 1001
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# -- This is for setting up a service more information can be found here: https://kubernetes.io/docs/concepts/services-networking/service/
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service:
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# -- Specifies if you want to create a service
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enabled: true
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# -- This sets the service type more information can be found here: https://kubernetes.io/docs/concepts/services-networking/service/#publishing-services-service-types
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type: ClusterIP
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# -- This sets the ports more information can be found here: https://kubernetes.io/docs/concepts/services-networking/service/#field-spec-ports
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port: 80
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# -- Default Service name
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name: http
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# -- Default container port
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containerPort: 5000
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# -- Default container port name
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containerPortName: mlflow
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# -- Additional service annotations
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annotations: {}
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# -- Mlflow logging settings
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log:
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# -- Specifies if you want to enable mlflow logging.
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enabled: true
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# -- Mlflow logging level.
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level: info
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# -- Mlflow Usage Tracking settings. More information can be found here: https://mlflow.org/docs/latest/community/usage-tracking/
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telemetry:
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# -- Specifies if you want to enable collecting anonymized usage data about how core features of the platform are used.
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enabled: false
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# -- Mlflow database connection settings
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backendStore:
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# -- Specifies if you want to run database migration
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databaseMigration: false
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# -- Add an additional init container, which checks for database availability
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databaseConnectionCheck: false
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# -- Specifies the default sqlite path
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defaultSqlitePath: ":memory:"
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postgres:
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# -- Specifies if you want to use postgres backend storage
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enabled: false
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# -- Postgres host address. e.g. your RDS or Azure Postgres Service endpoint
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host: "" # required
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# -- Postgres service port
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port: 5432 # required
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# -- mlflow database name created before in the postgres instance
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database: "" # required
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# -- postgres database user name which can access to mlflow database
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user: "" # required
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# -- postgres database user password which can access to mlflow database
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password: "" # required
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# -- postgres database connection driver. e.g.: "psycopg2"
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driver: ""
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mysql:
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# -- Specifies if you want to use mysql backend storage
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enabled: false
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# -- MySQL host address. e.g. your Amazon RDS for MySQL
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host: "" # required
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# -- MySQL service port
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port: 3306 # required
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# -- mlflow database name created before in the mysql instance
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database: "" # required
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# -- mysql database user name which can access to mlflow database
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user: "" # required
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# -- mysql database user password which can access to mlflow database
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password: "" # required
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# -- mysql database connection driver. e.g.: "pymysql"
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driver: "pymysql"
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mssql:
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# -- Specifies if you want to use mssql backend storage
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enabled: false
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# -- mssql host address
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host: "" # required
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# -- mssql service port
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port: 1433 # required
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# -- mlflow database name created before in the mssql instance
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database: "" # required
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# -- mssql database user name which can access to mlflow database
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user: "" # required
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# -- mssql database user password which can access to mlflow database
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password: "" # required
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# -- mssql database connection driver. e.g.: "pymssql"
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driver: "pymssql"
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# -- Specifies if you want to use an existing database secret.
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existingDatabaseSecret:
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# -- The name of the existing database secret.
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name: ""
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# -- The key of the username in the existing database secret.
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usernameKey: "username"
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# -- The key of the password in the existing database secret.
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passwordKey: "password"
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# -- Bitnami PostgreSQL configuration. For more information checkout: https://github.com/bitnami/charts/tree/main/bitnami/postgresql
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postgresql:
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# -- Enable postgresql
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enabled: false
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architecture: standalone
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image:
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repository: bitnamilegacy/postgresql
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primary:
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service:
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ports:
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postgresql: 5432
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persistence:
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enabled: true
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existingClaim: ""
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auth:
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username: ""
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password: ""
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# -- The name of the PostgreSQL database.
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database: "mlflow"
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# -- Bitnami MySQL configuration. For more information checkout: https://github.com/bitnami/charts/tree/main/bitnami/mysql
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mysql:
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# -- Enable mysql
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enabled: false
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architecture: standalone
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image:
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repository: bitnamilegacy/mysql
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primary:
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service:
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ports:
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mysql: 3306
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persistence:
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enabled: true
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existingClaim: ""
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auth:
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username: ""
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password: ""
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# -- The name of the MySQL database.
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database: "mlflow"
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# Mlflow blob storage settings
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artifactRoot:
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# -- Specifies if you want to enable proxied artifact storage access
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proxiedArtifactStorage: false
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# -- Specifies the default artifact root.
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defaultArtifactRoot: "./mlruns"
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# -- Specifies the default artifacts destination
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defaultArtifactsDestination: "./mlartifacts"
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# -- Specifies if you want to use Azure Blob Storage Mlflow Artifact Root
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azureBlob:
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# -- Specifies if you want to use Azure Blob Storage Mlflow Artifact Root
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enabled: false
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# -- Azure blob container name
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container: "" # required
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# -- Azure storage account name
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storageAccount: "" # required
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# -- Azure blob container folder. If you want to use root level, please don't set anything.
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path: "" # optional
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# -- Azure Cloud Connection String for the container. Only connectionString or accessKey required
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connectionString: "" # connectionString or accessKey required
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# -- Azure Cloud Storage Account Access Key for the container
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accessKey: "" # connectionString or accessKey required. Only connectionString or accessKey required
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# -- Specifies if you want to use AWS S3 Mlflow Artifact Root
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s3:
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# -- Specifies if you want to use AWS S3 Mlflow Artifact Root
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enabled: false
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# -- S3 bucket name
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bucket: "" # required
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# -- S3 bucket folder. If you want to use root level, please don't set anything.
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path: "" # optional
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# -- AWS IAM user AWS_ACCESS_KEY_ID which has attached policy for access to the S3 bucket
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awsAccessKeyId: "" # (awsAccessKeyId and awsSecretAccessKey) or roleArn serviceaccount annotation required
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# -- AWS IAM user AWS_SECRET_ACCESS_KEY which has attached policy for access to the S3 bucket
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awsSecretAccessKey: "" # (awsAccessKeyId and awsSecretAccessKey) or roleArn serviceaccount annotation required
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# -- Existing secret for AWS IAM user AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY secrets.
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existingSecret:
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# -- This is for setting up the AWS IAM user secrets existing secret name.
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name: ""
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# -- This is for setting up the key for AWS_ACCESS_KEY_ID secret. If it's set, awsAccessKeyId will be ignored.
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keyOfAccessKeyId: ""
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# -- This is for setting up the key for AWS_SECRET_ACCESS_KEY secret. If it's set, awsSecretAccessKey will be ignored.
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keyOfSecretAccessKey: ""
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# -- Specifies if you want to use Google Cloud Storage Mlflow Artifact Root
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gcs:
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# -- Specifies if you want to use Google Cloud Storage Mlflow Artifact Root
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enabled: false
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# -- Google Cloud Storage bucket name
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bucket: "" # required
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# -- Google Cloud Storage bucket folder. If you want to use root level, please don't set anything.
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path: "" # optional
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# -- Mlflow Flask Server Secret Key. Default: Will be auto generated.
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flaskServerSecretKey: ""
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# -- Mlflow authentication settings
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auth:
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# -- Specifies if you want to enable mlflow authentication. auth and ldapAuth can't be enabled at same time.
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enabled: false
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# -- Mlflow admin user username
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adminUsername: ""
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# -- Mlflow admin user password
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adminPassword: ""
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# -- Specifies if you want to use an existing admin credentials secret for auth. If it's set, adminUsername and adminPassword will be ignored.
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existingAdminSecret:
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# -- The name of the existing admin credentials secret.
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name: ""
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# -- The key of the admin username in the existing admin credentials secret.
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usernameKey: "username"
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# -- The key of the admin password in the existing admin credentials secret.
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passwordKey: "password"
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# -- Default permission for all users. More details: https://mlflow.org/docs/latest/auth/index.html#permissions
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defaultPermission: READ
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# -- Default registered authentication app name. If you want to use your custom authentication function, please look at: https://mlflow.org/docs/latest/auth/index.html#custom-authentication
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appName: "basic-auth"
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# -- Default authentication function
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authorizationFunction: "mlflow.server.auth:authenticate_request_basic_auth"
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# -- SQLite database file
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sqliteFile: "basic_auth.db"
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# -- SQLite database folder. Default is user home directory.
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sqliteFullPath: ""
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# -- Mlflow authentication INI configuration file path.
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configPath: "/etc/mlflow/auth/"
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# -- Mlflow authentication INI file
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configFile: "basic_auth.ini"
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# -- PostgreSQL based centrilised authentication database
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postgres:
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# -- Specifies if you want to use postgres auth backend storage
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enabled: false
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# -- Postgres host address. e.g. your RDS or Azure Postgres Service endpoint
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host: "" # required
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# -- Postgres service port
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port: 5432 # required
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# -- mlflow authorization database name created before in the postgres instance
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database: "" # required
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# -- postgres database user name which can access to mlflow authorization database
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user: "" # required
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# -- postgres database user password which can access to mlflow authorization database
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password: "" # required
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# -- postgres database connection driver. e.g.: "psycopg2"
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driver: ""
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# -- Specifies if you want to use an existing database secret for auth. If it's set, user and password will be ignored.
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existingSecret:
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# -- The name of the existing database secret.
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name: ""
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# -- The key of the username in the existing database secret.
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usernameKey: "username"
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# -- The key of the password in the existing database secret.
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passwordKey: "password"
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# -- Basic Authentication with LDAP backend
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ldapAuth:
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# -- Specifies if you want to enable mlflow LDAP authentication. auth and ldapAuth can't be enabled at same time.
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enabled: false
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# -- LDAP URI. e.g.: "ldap://lldap:3890/dc=mlflow,dc=test"
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uri: ""
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# -- TLS verification mode. Options: required, optional, none
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tlsVerification: required
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# -- LDAP Loopup Bind. e.g.: "uid=%s,ou=people,dc=mlflow,dc=test"
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lookupBind: ""
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# -- LDAP group attribute.
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groupAttribute: "dn"
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# -- Optional group attribute key for Active Directory users. e.g.: "attributes"
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groupAttributeKey: ""
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# -- LDAP base DN for the search. e.g.: "ou=groups,dc=mlflow,dc=test"
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searchBaseDistinguishedName: ""
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# -- LDAP query filter for search
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searchFilter: "(&(objectclass=groupOfUniqueNames)(uniquemember=%s))"
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# -- LDAP DN for the admin group. e.g.: "cn=test-admin,ou=groups,dc=mlflow,dc=test"
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adminGroupDistinguishedName: ""
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# -- LDAP DN for the user group. e.g.: "cn=test-user,ou=groups,dc=mlflow,dc=test"
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userGroupDistinguishedName: ""
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# -- Base64 encoded trusted CA certificate for LDAP server connection.
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encodedTrustedCACertificate: ""
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# -- External secret name for trusted CA certificate for LDAP server connection.
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externalSecretForTrustedCACertificate: ""
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# -- Autoscaling settings. Can be enabled only when backendStore is not sqlite and artifactRoot is one of blob storage systems.
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autoscaling:
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# -- If true, the number of replicas will be automatically scaled based on default metrics. On default, it will scale based on CPU and memory. For more information can be found here: https://kubernetes.io/docs/concepts/workloads/autoscaling/"
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enabled: false
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# -- The minimum number of replicas.
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minReplicas: 1
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# -- The maximum number of replicas.
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||||
maxReplicas: 5
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||||
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# -- The metrics to use for autoscaling.
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metrics:
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- type: Resource
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resource:
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name: memory
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target:
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type: Utilization
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||||
averageUtilization: 80
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||||
- type: Resource
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resource:
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name: cpu
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||||
target:
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||||
type: Utilization
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||||
averageUtilization: 80
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||||
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||||
# -- The behavior of the autoscaler. Only supported on K8s 1.18.0 or later.
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behavior: {}
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||||
# -- A map of arguments and values to pass to the `mlflow server` command. Keys must be camelcase. Helm will turn them to kebabcase style.
|
||||
extraArgs: {}
|
||||
# workers: TEXT
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||||
# staticPrefix: TEXT
|
||||
# gunicornOpts: TEXT
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||||
# waitressOpts: TEXT
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||||
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||||
# -- A list of flags to pass to `mlflow server` command. Items must be camelcase. Helm will turn them to kebabcase style.
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||||
extraFlags: []
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# serveArtifacts
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# artifactsOnly
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||||
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||||
# -- Extra environment variables
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||||
extraEnvVars: {}
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||||
# MLFLOW_S3_IGNORE_TLS: true
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||||
# MLFLOW_S3_ENDPOINT_URL: http://1.2.3.4:9000
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||||
# AWS_DEFAULT_REGION: my_region
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||||
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||||
# -- Extra secrets for environment variables
|
||||
extraSecretNamesForEnvFrom: []
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||||
|
||||
ingress:
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||||
# -- Specifies if you want to create an ingress access
|
||||
enabled: false
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||||
# -- New style ingress class name. Only possible if you use K8s 1.18.0 or later version
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||||
className: ""
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||||
# -- Additional ingress annotations
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||||
annotations: {}
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||||
hosts:
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||||
- host: chart-example.local
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||||
paths:
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||||
- path: /
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||||
# -- Ingress path type
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||||
pathType: ImplementationSpecific
|
||||
# -- Ingress tls configuration for https access
|
||||
tls: []
|
||||
|
||||
# -- This block is for setting up the resource management for the pod more information can be found here: https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/
|
||||
resources: {}
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||||
|
||||
serviceMonitor:
|
||||
# -- When set true then use a ServiceMonitor to configure scraping
|
||||
enabled: false
|
||||
# -- When set true then use a service port. On default use a pod port.
|
||||
useServicePort: false
|
||||
# -- Set the namespace the ServiceMonitor should be deployed
|
||||
namespace: monitoring
|
||||
# -- Set how frequently Prometheus should scrape
|
||||
interval: 30s
|
||||
# -- Set path to mlflow telemetry-path
|
||||
telemetryPath: /metrics
|
||||
# -- Set labels for the ServiceMonitor, use this to define your scrape label for Prometheus Operator
|
||||
labels:
|
||||
release: prometheus
|
||||
# -- Set timeout for scrape
|
||||
timeout: 10s
|
||||
# -- Set of labels to transfer on the Kubernetes Service onto the target.
|
||||
targetLabels: []
|
||||
# -- Set of rules to relabel your exist metric labels
|
||||
metricRelabelings: []
|
||||
|
||||
# -- For more information checkout: https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/#nodeselector
|
||||
nodeSelector: {}
|
||||
|
||||
# -- For more information checkout: https://kubernetes.io/docs/concepts/scheduling-eviction/taint-and-toleration/
|
||||
tolerations: []
|
||||
|
||||
# -- For more information checkout: https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/#affinity-and-anti-affinity
|
||||
affinity: {}
|
||||
|
||||
# -- Init Containers for Mlflow Pod
|
||||
initContainers: []
|
||||
|
||||
# -- Extra containers for the mlflow pod
|
||||
extraContainers: []
|
||||
|
||||
# -- Extra Volumes for the pod
|
||||
extraVolumes: []
|
||||
|
||||
# -- Extra Volume Mounts for the mlflow container
|
||||
extraVolumeMounts: []
|
||||
|
||||
# -- Liveness probe configurations. Please look to [here](https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/#configure-probes).
|
||||
livenessProbe:
|
||||
initialDelaySeconds: 10
|
||||
periodSeconds: 30
|
||||
timeoutSeconds: 3
|
||||
failureThreshold: 5
|
||||
|
||||
# -- Readiness probe configurations. Please look to [here](https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-startup-probes/#configure-probes).
|
||||
readinessProbe:
|
||||
initialDelaySeconds: 10
|
||||
periodSeconds: 30
|
||||
timeoutSeconds: 3
|
||||
failureThreshold: 5
|
||||
Reference in New Issue
Block a user