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Installing on Kubernetes



Running Superset on Kubernetes is supported with the provided Helm chart found in the official Superset helm repository.

Prerequisites​

  • A Kubernetes cluster
  • Helm installed
note

For simpler, single host environments, we recommend using minikube which is easy to setup on many platforms and works fantastically well with the Helm chart referenced here.

Running​

  1. Add the Superset helm repository
helm repo add superset https://apache.github.io/superset
"superset" has been added to your repositories
  1. View charts in repo
helm search repo superset
NAME                    CHART VERSION   APP VERSION     DESCRIPTION
superset/superset       0.1.1           1.0             Apache Superset is a modern, enterprise-ready b...
  1. Configure your setting overrides

Just like any typical Helm chart, you'll need to craft a values.yaml file that would define/override any of the values exposed into the default values.yaml, or from any of the dependent charts it depends on:

More info down below on some important overrides you might need.

  1. Install and run
helm upgrade --install --values my-values.yaml superset superset/superset

You should see various pods popping up, such as:

kubectl get pods
NAME                                    READY   STATUS      RESTARTS   AGE
superset-celerybeat-7cdcc9575f-k6xmc    1/1     Running     0          119s
superset-f5c9c667-dw9lp                 1/1     Running     0          4m7s
superset-f5c9c667-fk8bk                 1/1     Running     0          4m11s
superset-init-db-zlm9z                  0/1     Completed   0          111s
superset-postgresql-0                   1/1     Running     0          6d20h
superset-redis-master-0                 1/1     Running     0          6d20h
superset-worker-75b48bbcc-jmmjr         1/1     Running     0          4m8s
superset-worker-75b48bbcc-qrq49         1/1     Running     0          4m12s

The exact list will depend on some of your specific configuration overrides but you should generally expect:

  • N superset-xxxx-yyyy and superset-worker-xxxx-yyyy pods (depending on your supersetNode.replicaCount and supersetWorker.replicaCount values)
  • 1 superset-postgresql-0 depending on your postgres settings
  • 1 superset-redis-master-0 depending on your redis settings
  • 1 superset-celerybeat-xxxx-yyyy pod if you have supersetCeleryBeat.enabled = true in your values overrides
  1. Access it

The chart will publish appropriate services to expose the Superset UI internally within your k8s cluster. To access it externally you will have to either:

  • Configure the Service as a LoadBalancer or NodePort
  • Set up an Ingress for it - the chart includes a definition, but will need to be tuned to your needs (hostname, tls, annotations etc...)
  • Run kubectl port-forward superset-xxxx-yyyy :8088 to directly tunnel one pod's port into your localhost

Depending how you configured external access, the URL will vary. Once you've identified the appropriate URL you can log in with:

  • user: admin
  • password: admin

Important settings​

Security settings​

Default security settings and passwords are included but you MUST update them to run prod instances, in particular:

postgresql:
  postgresqlPassword: superset

Make sure, you set a unique strong complex alphanumeric string for your SECRET_KEY and use a tool to help you generate a sufficiently random sequence.

  • To generate a good key you can run, openssl rand -base64 42
configOverrides:
  secret: |
    SECRET_KEY = 'YOUR_OWN_RANDOM_GENERATED_SECRET_KEY'

If you want to change the previous secret key then you should rotate the keys. Default secret key for kubernetes deployment is thisISaSECRET_1234

configOverrides:
  my_override: |
    PREVIOUS_SECRET_KEY = 'YOUR_PREVIOUS_SECRET_KEY'
    SECRET_KEY = 'YOUR_OWN_RANDOM_GENERATED_SECRET_KEY'
init:
  command:
    - /bin/sh
    - -c
    - |
      . {{ .Values.configMountPath }}/superset_bootstrap.sh
      superset re-encrypt-secrets
      . {{ .Values.configMountPath }}/superset_init.sh
note

Superset uses Scarf Gateway to collect telemetry data. Knowing the installation counts for different Superset versions informs the project's decisions about patching and long-term support. Scarf purges personally identifiable information (PII) and provides only aggregated statistics.

To opt-out of this data collection in your Helm-based installation, edit the repository: line in your helm/superset/values.yaml file, replacing apachesuperset.docker.scarf.sh/apache/superset with apache/superset to pull the image directly from Docker Hub.

Dependencies​

Install additional packages and do any other bootstrap configuration in the bootstrap script. For production clusters it's recommended to build own image with this step done in CI.

note

Superset requires a Python DB-API database driver and a SQLAlchemy dialect to be installed for each datastore you want to connect to.

See Install Database Drivers for more information.

The following example installs the drivers for BigQuery and Elasticsearch, allowing you to connect to these data sources within your Superset setup:

bootstrapScript: |
  #!/bin/bash
  pip install psycopg2==2.9.6 \
    sqlalchemy-bigquery==1.6.1 \
    elasticsearch-dbapi==0.2.5 &&\
  if [ ! -f ~/bootstrap ]; then echo "Running Superset with uid {{ .Values.runAsUser }}" > ~/bootstrap; fi

superset_config.py​

The default superset_config.py is fairly minimal and you will very likely need to extend it. This is done by specifying one or more key/value entries in configOverrides, e.g.:

configOverrides:
  my_override: |
    # This will make sure the redirect_uri is properly computed, even with SSL offloading
    ENABLE_PROXY_FIX = True
    FEATURE_FLAGS = {
        "DYNAMIC_PLUGINS": True
    }

Those will be evaluated as Helm templates and therefore will be able to reference other values.yaml variables e.g. {{ .Values.ingress.hosts[0] }} will resolve to your ingress external domain.

The entire superset_config.py will be installed as a secret, so it is safe to pass sensitive parameters directly... however it might be more readable to use secret env variables for that.

Full python files can be provided by running helm upgrade --install --values my-values.yaml --set-file configOverrides.oauth=set_oauth.py

Environment Variables​

Those can be passed as key/values either with extraEnv or extraSecretEnv if they're sensitive. They can then be referenced from superset_config.py using e.g. os.environ.get("VAR").

extraEnv:
  SMTP_HOST: smtp.gmail.com
  SMTP_USER: user@gmail.com
  SMTP_PORT: "587"
  SMTP_MAIL_FROM: user@gmail.com

extraSecretEnv:
  SMTP_PASSWORD: xxxx

configOverrides:
  smtp: |
    import ast
    SMTP_HOST = os.getenv("SMTP_HOST","localhost")
    SMTP_STARTTLS = ast.literal_eval(os.getenv("SMTP_STARTTLS", "True"))
    SMTP_SSL = ast.literal_eval(os.getenv("SMTP_SSL", "False"))
    SMTP_USER = os.getenv("SMTP_USER","superset")
    SMTP_PORT = os.getenv("SMTP_PORT",25)
    SMTP_PASSWORD = os.getenv("SMTP_PASSWORD","superset")

System packages​

If new system packages are required, they can be installed before application startup by overriding the container's command, e.g.:

supersetWorker:
  command:
    - /bin/sh
    - -c
    - |
      apt update
      apt install -y somepackage
      apt autoremove -yqq --purge
      apt clean

      # Run celery worker
      . {{ .Values.configMountPath }}/superset_bootstrap.sh; celery --app=superset.tasks.celery_app:app worker

Data sources​

Data source definitions can be automatically declared by providing key/value yaml definitions in extraConfigs:

extraConfigs:
  import_datasources.yaml: |
    databases:
    - allow_file_upload: true
      allow_ctas: true
      allow_cvas: true
      database_name: example-db
      extra: "{\r\n    \"metadata_params\": {},\r\n    \"engine_params\": {},\r\n    \"\
        metadata_cache_timeout\": {},\r\n    \"schemas_allowed_for_file_upload\": []\r\n\
        }"
      sqlalchemy_uri: example://example-db.local
      tables: []

Those will also be mounted as secrets and can include sensitive parameters.

Configuration Examples​

Setting up OAuth​

note

OAuth setup requires that the authlib Python library is installed. This can be done using pip by updating the bootstrapScript. See the Dependencies section for more information.

extraEnv:
  AUTH_DOMAIN: example.com

extraSecretEnv:
  GOOGLE_KEY: xxxxxxxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx.apps.googleusercontent.com
  GOOGLE_SECRET: xxxxxxxxxxxxxxxxxxxxxxxx

configOverrides:
  enable_oauth: |
    # This will make sure the redirect_uri is properly computed, even with SSL offloading
    ENABLE_PROXY_FIX = True

    from flask_appbuilder.security.manager import AUTH_OAUTH
    AUTH_TYPE = AUTH_OAUTH
    OAUTH_PROVIDERS = [
        {
            "name": "google",
            "icon": "fa-google",
            "token_key": "access_token",
            "remote_app": {
                "client_id": os.getenv("GOOGLE_KEY"),
                "client_secret": os.getenv("GOOGLE_SECRET"),
                "api_base_url": "https://www.googleapis.com/oauth2/v2/",
                "client_kwargs": {"scope": "email profile"},
                "request_token_url": None,
                "access_token_url": "https://accounts.google.com/o/oauth2/token",
                "authorize_url": "https://accounts.google.com/o/oauth2/auth",
                "authorize_params": {"hd": os.getenv("AUTH_DOMAIN", "")}
            },
        }
    ]

    # Map Authlib roles to superset roles
    AUTH_ROLE_ADMIN = 'Admin'
    AUTH_ROLE_PUBLIC = 'Public'

    # Will allow user self registration, allowing to create Flask users from Authorized User
    AUTH_USER_REGISTRATION = True

    # The default user self registration role
    AUTH_USER_REGISTRATION_ROLE = "Admin"

Enable Alerts and Reports​

For this, as per the Alerts and Reports doc, you will need to:

Install a supported webdriver in the Celery worker​

This is done either by using a custom image that has the webdriver pre-installed, or installing at startup time by overriding the command. Here's a working example for chromedriver:

supersetWorker:
  command:
    - /bin/sh
    - -c
    - |
      # Install chrome webdriver
      # See https://github.com/apache/superset/blob/4fa3b6c7185629b87c27fc2c0e5435d458f7b73d/docs/src/pages/docs/installation/email_reports.mdx
      apt-get update
      apt-get install -y wget
      wget https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb
      apt-get install -y --no-install-recommends ./google-chrome-stable_current_amd64.deb
      wget https://chromedriver.storage.googleapis.com/88.0.4324.96/chromedriver_linux64.zip
      apt-get install -y zip
      unzip chromedriver_linux64.zip
      chmod +x chromedriver
      mv chromedriver /usr/bin
      apt-get autoremove -yqq --purge
      apt-get clean
      rm -f google-chrome-stable_current_amd64.deb chromedriver_linux64.zip

      # Run
      . {{ .Values.configMountPath }}/superset_bootstrap.sh; celery --app=superset.tasks.celery_app:app worker

Run the Celery beat​

This pod will trigger the scheduled tasks configured in the alerts and reports UI section:

supersetCeleryBeat:
  enabled: true

Configure the appropriate Celery jobs and SMTP/Slack settings​

extraEnv:
  SMTP_HOST: smtp.gmail.com
  SMTP_USER: user@gmail.com
  SMTP_PORT: "587"
  SMTP_MAIL_FROM: user@gmail.com

extraSecretEnv:
  SLACK_API_TOKEN: xoxb-xxxx-yyyy
  SMTP_PASSWORD: xxxx-yyyy

configOverrides:
  feature_flags: |
    import ast

    FEATURE_FLAGS = {
        "ALERT_REPORTS": True
    }

    SMTP_HOST = os.getenv("SMTP_HOST","localhost")
    SMTP_STARTTLS = ast.literal_eval(os.getenv("SMTP_STARTTLS", "True"))
    SMTP_SSL = ast.literal_eval(os.getenv("SMTP_SSL", "False"))
    SMTP_USER = os.getenv("SMTP_USER","superset")
    SMTP_PORT = os.getenv("SMTP_PORT",25)
    SMTP_PASSWORD = os.getenv("SMTP_PASSWORD","superset")
    SMTP_MAIL_FROM = os.getenv("SMTP_MAIL_FROM","superset@superset.com")

    SLACK_API_TOKEN = os.getenv("SLACK_API_TOKEN",None)
  celery_conf: |
    from celery.schedules import crontab

    class CeleryConfig:
      broker_url = f"redis://{env('REDIS_HOST')}:{env('REDIS_PORT')}/0"
      imports = (
          "superset.sql_lab",
          "superset.tasks.cache",
          "superset.tasks.scheduler",
      )
      result_backend = f"redis://{env('REDIS_HOST')}:{env('REDIS_PORT')}/0"
      task_annotations = {
          "sql_lab.get_sql_results": {
              "rate_limit": "100/s",
          },
      }
      beat_schedule = {
          "reports.scheduler": {
              "task": "reports.scheduler",
              "schedule": crontab(minute="*", hour="*"),
          },
          "reports.prune_log": {
              "task": "reports.prune_log",
              'schedule': crontab(minute=0, hour=0),
          },
          'cache-warmup-hourly': {
              "task": "cache-warmup",
              "schedule": crontab(minute="*/30", hour="*"),
              "kwargs": {
                  "strategy_name": "top_n_dashboards",
                  "top_n": 10,
                  "since": "7 days ago",
              },
          }
      }

    CELERY_CONFIG = CeleryConfig
  reports: |
    EMAIL_PAGE_RENDER_WAIT = 60
    WEBDRIVER_BASEURL = "http://{{ template "superset.fullname" . }}:{{ .Values.service.port }}/"
    WEBDRIVER_BASEURL_USER_FRIENDLY = "https://www.example.com/"
    WEBDRIVER_TYPE= "chrome"
    WEBDRIVER_OPTION_ARGS = [
        "--force-device-scale-factor=2.0",
        "--high-dpi-support=2.0",
        "--headless",
        "--disable-gpu",
        "--disable-dev-shm-usage",
        # This is required because our process runs as root (in order to install pip packages)
        "--no-sandbox",
        "--disable-setuid-sandbox",
        "--disable-extensions",
    ]

Load the Examples data and dashboards​

If you are trying Superset out and want some data and dashboards to explore, you can load some examples by creating a my_values.yaml and deploying it as described above in the Configure your setting overrides step of the Running section. To load the examples, add the following to the my_values.yaml file:

init:
  loadExamples: true