Installing Superset with containers, PyPI or behind proxies and on restricted networks, and managing configuration and dashboards as code.
Extending an official Superset image with your database drivers, Playwright Chromium for reports and translations: lean versus default images, uv installs, pinning versions and scanning the result.
Where Docker Compose fits for Superset and where it does not: the project's own guidance, external metadata database and backups, custom images, TLS and when to move to Kubernetes.
Installing Superset with pip on a VM: OS packages for the cryptography library, Python version, virtual environments, Gunicorn, and adding Redis and Celery yourself for full features.
Putting NGINX, Traefik or a cloud load balancer in front of Superset: TLS termination, ENABLE_PROXY_FIX, health checks, HSTS, WebSocket routing for async queries and internal HTTP for report workers.
Running Superset at a path such as /analytics behind a shared domain: the application root settings, Docker environment variable, Swagger UI behavior and limits of the beta feature.
Running Superset without internet access: prebuilt images with all drivers, map tiles and fonts served internally, telemetry opt-out, no external OAuth dependencies and offline upgrade steps.
Keeping Superset configuration consistent and secret-free: environment variables for secrets, per-environment overrides, feature flags, mounting config in containers and reviewing changes on upgrade.
Versioning dashboards, charts and datasets as exported YAML in Git and promoting them with the CLI or API: review workflows, database connection handling and conflicts with UI edits.
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