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Overview

This template provides a production‑ready Apache Superset instance as a Monk runnable. You can:
  • Run it directly to get a managed business intelligence and data visualization platform
  • Inherit it in your own data infrastructure to add BI and analytics capabilities
Apache Superset is a modern, enterprise-ready business intelligence web application. It’s fast, lightweight, intuitive, and loaded with options that make it easy for users to explore and visualize their data, from simple line charts to highly detailed geospatial charts.

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What this template manages

  • Superset web server and workers
  • PostgreSQL or MySQL metadata database
  • Redis for caching and async queries
  • Web UI on port 8088
  • SQL Lab for data exploration
  • Dashboard and chart management

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Quick start (run directly)

  1. Load templates
monk load MANIFEST
  1. Run Superset stack
monk run superset/stack
  1. Customize credentials (recommended via inheritance)
Running directly uses the defaults defined in this template’s variables. Secrets added with monk secrets add will not affect this runnable unless you inherit it and reference those secrets.
  • Preferred: inherit and replace variables with secret("...") as shown below.
  • Alternative: fork/clone and edit the variables in the template files, then monk load MANIFEST and run.
Once started, access Superset at http://localhost:8088 using the configured credentials (default: admin / admin).

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Configuration

Key variables you can customize in this template: 
variables:
  # Superset
  superset-image-tag: "latest"        # container image tag
  superset-port: "8088"               # web UI port (env: SUPERSET_PORT)
  superset-admin-username: "admin"    # admin username (env: ADMIN_USERNAME)
  superset-admin-password: "..."      # admin password (env: ADMIN_PASSWORD)
  superset-secret-key: "..."          # Flask secret key (env: SECRET_KEY)
  
  # Database
  postgres-password: "..."            # PostgreSQL password (env: POSTGRES_PASSWORD)
  postgres-user: "superset"           # database user (env: POSTGRES_USER)
  postgres-db: "superset"             # database name (env: POSTGRES_DB)
  
  # Redis
  redis-password: "..."               # Redis password, optional (env: REDIS_PASSWORD)
Data is persisted under ${monk-volume-path}/superset, ${monk-volume-path}/postgres, and ${monk-volume-path}/redis on the host. Inherit the Superset stack in your application and declare a connection. Example: 
namespace: myapp
analytics:
  defines: runnable
  inherits: superset/stack
  variables:
    superset-admin-password: <- secret("superset-password")
    superset-secret-key: <- secret("superset-secret")
    postgres-password: <- secret("postgres-password")
datawarehouse:
  defines: runnable
  containers:
    dw:
      image: myorg/datawarehouse
  connections:
    bi:
      runnable: analytics
      service: superset
  variables:
    superset-url:
      value: <- connection-hostname("bi")
Then set the secrets once and run your app group: 
monk secrets add -g superset-password="STRONG_PASSWORD"
monk secrets add -g superset-secret="<random-secret-key>"
monk secrets add -g postgres-password="STRONG_DB_PASSWORD"
monk run myapp/analytics

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Ports and connectivity

  • Service: superset on TCP port 8088
  • From other runnables in the same process group, use connection-hostname("\<connection-name>") to resolve the Superset host.
  • From data sources, Superset connects via database drivers (configure in UI)

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Persistence and configuration

  • Superset home path: ${monk-volume-path}/superset:/app/superset_home
  • PostgreSQL data path: ${monk-volume-path}/postgres:/var/lib/postgresql/data
  • Redis data path: ${monk-volume-path}/redis:/data
  • You can customize Superset configuration by mounting additional config files into the superset_home directory.

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Features

  • Rich Visualizations: 40+ chart types (line, bar, pie, maps, etc.)
  • SQL Lab: Interactive SQL editor with query history
  • No-Code Viz Builder: Create charts without writing code
  • Dashboards: Combine multiple charts into interactive dashboards
  • Database Support: PostgreSQL, MySQL, SQLite, Redshift, BigQuery, Snowflake, etc.
  • Caching: Redis-based caching for fast query results
  • Security: Row-level security, LDAP/OAuth integration
  • Async Queries: Long-running queries with Celery
  • Alerting: Schedule reports and alerts

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Connecting Data Sources

Superset supports many databases:
  • SQL: PostgreSQL, MySQL, SQLite, Oracle
  • Big Data: Presto, Hive, Spark SQL, Druid
  • Cloud: BigQuery, Redshift, Snowflake, Athena
  • Time-Series: InfluxDB, Prometheus
  • And 30+ more via SQLAlchemy drivers
Add database in UI: Data → Databases → + Database

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SQL Lab

Interactive SQL editor with:
  • Auto-completion
  • Query history
  • Multiple tabs
  • Query results export
  • Visualization from queries

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Use cases

Superset excels at:
  • Business intelligence dashboards
  • Data exploration and discovery
  • Ad-hoc data analysis
  • Scheduled reporting
  • Self-service analytics
  • Data democratization

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Production Considerations

For production deployments:
  • Use external PostgreSQL or MySQL for metadata
  • Configure Redis for caching and Celery
  • Enable SSL/TLS
  • Set up authentication (OAuth, LDAP)
  • Configure row-level security
  • Set up monitoring and logging
  • Use pgadmin/ for web-based database administration
  • Combine with grafana/ for time-series visualization
  • Integrate with telegraf/ for metrics collection

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Troubleshooting

  • Access Superset UI at http://localhost:8088
  • If you changed superset-admin-password but the container has existing data, you may need to recreate the admin user inside Superset.
  • Ensure the host volumes are writable by the container user.
  • Check logs:
monk logs -l 500 -f superset/superset
  • For connection issues to data sources, verify database drivers are installed in the Superset container
  • For slow queries, check Redis cache configuration
  • For large datasets, configure async query execution with Celery workers
  • Monitor PostgreSQL for metadata database performance
  • Initialize database manually (if needed):
superset db upgrade
superset init