Apache Superset: From Zero to Hero with Docker and AWS

Docker packages an application with code, libraries, and settings into a container that runs identically anywhere. This eliminates the works on my machine problem by ensuring consistent behavior.

Bundle code, libraries, binaries, and configuration into immutable Docker images built in layers, a portable blueprint that can be shared and deployed anywhere.

Explore docker networking with two BusyBox containers to see IP-based communication. Create a user defined network to enable name based resolution and container discovery.

Follow the chapter roadmap for installing Apache Superset with Docker, explore the UI and dashboards, and learn how datasets connect to data.

Discover essential resources for Apache Superset, including official docs, preset documentation, GitHub releases, and Docker Hub tags, to install, configure, and troubleshoot with confidence.

Install Apache Superset with Docker Compose by building a custom image, configuring settings, creating an admin user, and loading sample dashboards to explore the interface.

Create a simple yet realistic Covid dashboard in Apache Superset by exploring the dataset, spinning up PostgreSQL in Docker, configuring Superset, and building charts into a dashboard.

Outline the project structure for a three-container Apache Superset setup, with a Covid dataset database, a separate metadata database, and a main app, using env files for portability.

Create a COVID dashboard in Apache Superset by dragging visualizations into a layout with headers and markdown, maps, pies, and bars with country and deaths filters on a horizontal bar.

Explore the roadmap from version 4 to 6, including ui changes, sql lab updates, toml, custom head tag injections, ant design theming, and jinja capabilities.

Learn how uv, a fast, all-in-one Python package manager written in Rust, replaces pip, and handles virtual environments, dependencies, and Python versions, while understanding TOML-based pyproject configurations.

Set up a two-container docker environment for the superset project, including metadata database and custom logos and favicon, then iterate by updating the superset config to observe UI changes.

Customize the Apache Superset logo in a docker setup by adjusting the logo target path, image, width, and tooltip, then add right-side text and restart the container to apply changes.

Modify the browser tab layout in Superset by updating the favicon and tab text, using Visual Studio Code to edit the config and restart the container.

Snowflake, a fully managed cloud data platform, separates storage and compute for elastic scalability and cost efficiency, with a three-layer architecture and easy superset integration for analytics.

Prepare a Snowflake dataset for Apache Superset by creating warehouses, setting role permissions, building a superset database and denormalized views, and loading sample data for dashboards.

Register a dataset in Superset by adding a Snowflake connection, selecting the public schema and view, and creating the dataset from the widget menu.

Create a world map chart to visualize revenue by country, fix the country field to full name, save as country level revenue, and scale Snowflake warehouse to medium.

Explore building a calendar heatmap in apache superset to visualize daily revenue intensity, configure time ranges, adjust visuals, and optimize for dashboard clarity.

Build a tree map to visualize net revenue by market segment with rectangles showing parts of a whole and hierarchies; note Superset lacks interactive drill down and labels/colors affect readability.

Configure filters in superset, including value and time range types, with region and nation pre-filters to shape a dashboard across all visuals.

Explore how to customize dashboards in Apache Superset, from coloring and CSS customization to dynamic SQL with Jinja, and set up static and dynamic row-level security with roles and permissions.

Embed a branding image in a Superset dashboard with CSS, loading an AWS S3 image, resolving content security policy issues, and positioning via an after pseudo-element.

Explore static row level security in Superset, where hardcoded policies use regular or base filters to modify where clauses, and configure rules in settings attached to roles.

Demonstrate creating a static dataset and treemap, then configure two regular row level security policies with group keys to show how or and and combinations constrain regions and market segments.

Configure static row level security with a base type in Apache Superset by creating roles, assigning users, and applying a not in region filter.

Learn how to retrieve and filter user roles in Superset 6 using the built-in current user roles macro, with a live SQL Lab example and where-in filter.

Explore alerts and reports in Superset, automated notifications triggered by data conditions and scheduled dashboard snapshots delivered via email or Slack, with Gmail examples.

Understand caching basics, including cache hit and miss, and how Redis provides fast in-memory caching and as a message broker with producers, consumers, and queues.

Explore Celery, an open source task system for asynchronous execution and scheduling with workers and Celery Beat. Use Redis as broker and result backend to queue, distribute, and track tasks.

Explore the project setup for a dockerized Apache Superset deployment, including a dedicated config, sql directory for alerts, centralized envs, and dual docker compose files for one-time init.

Use shell scripts to initialize and upgrade the superset metadata database, create an admin user and credentials, and run superset with gunicorn and event workers for scalable docker deployment.

Set up an alert in Apache Superset by supplying a numeric query and threshold, trigger when discounts exceed 50%, and receive hourly email notifications with a chart image.

Clean up the dockerized superset setup by bringing down services with docker compose down, removing containers and images, and preserving volumes to keep the metadata database intact for future use.