Building Multi-Node Django Systems for Time Series Data [Free Course]

If you've ever wanted to run multiple Django nodes—whether on Docker Compose or a fleet of Raspberry Pis—to handle a massive amount of time series data, you're in luck.

Late last year, the good people at CodingEntrepreneurs channel on YouTube put together a fantastic Django Tutorial showing you how to run multi-node Django for Time-Series Data with TimescaleDB, Celery, and more.

We're posting it here to help bump it to the top of your list.

Course Overview

The video provides tons of useful information, but the main points it covers are:

• Setting up Django with a self-hosted or cloud-based TimescaleDB
• Using django-timescaledb to harness TimescaleDB features
• Integrating Celery & Redis for distributed tasks
• Emulating a multi-node production environment with Docker Compose
• Configuring Raspberry Pis (with Ansible) for a real-world IoT cluster
• Visualizing time-series data with Chart.js

The video covers everything from local development to production development to help you collect real-time data from multiple devices, store it effectively using TimescaleDB (a PostgreSQL extension for real-time analytics from time-series data, plus process the data asynchronously with Celery and visualize it using Chart.js.

You'll also pick up some pro tips on how to deploy easily and scale as you add more nodes along the way.

You can also try all of this with Timescale Cloud free for 30 days.

Django Tutorial

🛠️ Resources

• Django IoT with Timescale
• Django + Timescale package
• Create a Sensor Data App Using Django