Hackathon project: Viewing Datadog metrics in Minecraft

Datadog engineers used a two-day hackathon to display real-time Datadog metrics inside Minecraft. They connected Minecraft’s Python API with Datadog’s metrics API, then built configurable, live-updating graphs and monitor indicators in the game world. The project demonstrated that even an unconventional visualization environment can be practical to prototype with familiar tools.

Controlling Minecraft with Python

• The team used Raspberry Juice and a Minecraft Pi Edition server to expose Minecraft controls.
• They ran the setup on laptops for better performance and faster development.
• The py3minepi library enabled Python code to create, remove, and query blocks.
• Creating a block required only a connection to the server and a call such as mc.setBlock(...).

Retrieving Datadog Metrics

• The Datadog Python library provided access to the Metrics API.
• The prototype authenticated with an API key and application key.
• It queried recent data, such as average system CPU idle time over the previous five minutes.
• The Minecraft and Datadog components were then combined so metric values could be rendered as blocks and structures.
• Monitor status indicators changed between green and red depending on whether an alert was active.

YAML-Based Dashboard Configuration

• The team moved dashboard definitions out of Python code into YAML files.
• Configuration specified:
  • Graph position, size, and orientation
  • Visual properties such as colors, transparency, and borders
  • Datadog queries and time ranges
  • Monitor IDs and display locations
• This allowed complete dashboards containing multiple graphs and monitor indicators to be updated in real time.

Handling Minecraft’s Persistence

• Minecraft blocks remain in the world after being created, while metric graphs change constantly.
• Early experiments left behind random cubes that made the world difficult to navigate.
• The team implemented “vacuum” functions to remove everything generated by the visualization code before redrawing it.

Rendering and Performance Challenges

• Without browser technologies such as JavaScript and CSS, graphs had to be reduced to rows of data and represented with Minecraft blocks.
• Large graphs could overwhelm the data pipeline.
• Caching was added to reduce bandwidth usage and avoid repeatedly requesting the same data.
• The performance concerns mirrored Datadog’s everyday engineering work, where caching and efficient data handling are essential.

Hackathon Experience

• The first four hours focused on configuring the environment and connecting the systems.
• The remaining time was spent experimenting with building, viewing, destroying, and rebuilding metric displays.
• The project’s main value was creative exploration rather than production monitoring.

The prototype shows how quickly APIs can be combined to create unusual monitoring interfaces. While Minecraft is not intended to replace conventional dashboards, the project is a playful demonstration of real-time data visualization and rapid experimentation.