{"id":15111,"date":"2025-12-13T00:27:35","date_gmt":"2025-12-12T16:27:35","guid":{"rendered":"https:\/\/www.quantsnote.com\/?p=15111"},"modified":"2026-04-30T19:54:08","modified_gmt":"2026-04-30T11:54:08","slug":"deploy-jupyter-notebook-xcloud-docker","status":"publish","type":"post","link":"https:\/\/www.quantsnote.com\/en\/deploy-jupyter-notebook-xcloud-docker\/","title":{"rendered":"xCloud Deployment in Action: Jupyter Notebook with Docker, Cloudflare, and Nginx Reverse Proxy"},"content":{"rendered":"

In the previous article \"Python \u2013 Building a Jupyter Notebook Cloud Development Environment\" (Part 1)<\/a>, we completed the basic setup of a DigitalOcean Droplet. Following the traditional path, one would typically need to log in via SSH to manually handle Python environment variables, Virtualenv, and the tedious installation of Jupyter and firewall settings.<\/p>\n\n\n\n

For quantitative traders or data scientists, having a Jupyter Notebook environment that is accessible anytime, anywhere, and has independent computing resources is a dream configuration. Especially when you need to conduct long-term options historical backtesting<\/strong>, or simply don't want heavy calculations to occupy your laptop's resources, a cloud environment is the best solution.<\/p>\n\n\n\n

This is also why in our newly upgraded \"Python Options Quantitative Trading in Action\"<\/a> course, we specifically recommend this solution for students to deploy their Strategy Lab<\/strong>.<\/p>\n\n\n\n

However, the traditional SSH deployment method is tedious and full of pitfalls. This article will demonstrate how to use the xCloud panel combined with Docker technology to complete the setup of a Jupyter Notebook cloud environment on a DigitalOcean host in just 20 minutes, integrating Cloudflare SSL and Nginx reverse proxy to build an efficient and secure quantitative development platform.<\/p>\n\n\n\n

Environment Preparation and Architecture Overview<\/h2>\n\n\n\n

Before starting, please confirm that you have an xCloud account and a DigitalOcean (or Vultr, Hetzner) account.<\/p>\n\n\n\n

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xCloud<\/a> Free Plan \u2192 Self-hosted 1 server, 10 sites\/apps
DigitalOcean<\/a> Free Credit \u2192 30 days, $300 USD
Vultr<\/a> Free Credit \u2192 2 months, $200 USD<\/p><\/p>\n<\/blockquote>\n\n\n\n

This deployment uses a Docker containerization<\/strong> solution rather than installing directly on the Host OS. The reason is that xCloud is essentially a management tool optimized for WordPress and PHP applications, taking over the host's Nginx, PHP-FPM, and database settings. Installing a Python environment directly at the OS level might conflict with packages used by xCloud or even be overwritten during panel updates. Docker isolates the Jupyter environment, allowing us to enjoy the convenience of xCloud without interference.<\/p>\n\n\n\n

Architecture Diagram<\/h3>\n\n\n\n

External Request (HTTPS:443) \u2192 Cloudflare (SSL) \u2192 Nginx managed by xCloud (Reverse Proxy) \u2192 Docker Container (Localhost:8888) \u2192 Jupyter Notebook<\/p>\n\n\n\n

\"xCloud<\/a><\/figure>\n\n\n\n

Step 1: Install Docker Environment via xCloud Commands<\/h2>\n\n\n\n

First, connect your DigitalOcean account in the xCloud backend and create a new Droplet via Create Server.<\/p>\n\n\n\n

\"Connect<\/a><\/figure>\n\n\n\n

It is recommended to choose Ubuntu 22.04 LTS or 24.04 LTS version, with at least 2GB RAM to ensure smooth Python computation.<\/p>\n\n\n\n

\n
\"Create<\/a>
Create NGINX Server<\/figcaption><\/figure>\n\n\n\n
\"Server<\/a>
Server is being configured<\/figcaption><\/figure>\n<\/figure>\n\n\n\n

After the server is created, a reboot is required for security updates. Then, enter the server management interface. We no longer need to open Putty or Terminal; simply click Management \u2192 Commands<\/strong> in the left menu.<\/p>\n\n\n\n

\"xCloud<\/a><\/figure>\n\n\n\n

Execute Installation Command<\/h3>\n\n\n\n

Clicking + Run Custom Command<\/strong> will open the window below. Enter the following command in the Command content box, and the system will automatically download and install Docker:<\/p>\n\n\n\n

\"Run<\/a><\/figure>\n\n\n\n\n\n
# Install Docker\ncurl -fsSL https:\/\/get.docker.com | sh\n\n# Start and enable on boot\nsystemctl start docker\nsystemctl enable docker<\/code><\/pre>\n\n\n\n
Click Run Command<\/strong>, and xCloud will send the instruction to the server. When the Status shows Completed<\/code> and the Action column's View result shows no error messages, Docker is ready.<\/p>\n\n\n\n
\"Run<\/a><\/figure>\n\n\n\n
Step 2: Deploy Jupyter Notebook Container<\/h2>\n\n\n\n
After Docker installation is complete, proceed to configure the network and storage space.<\/p>\n\n\n\n
Configure Firewall Rules<\/h3>\n\n\n\n
From the left menu Security \u2192 Firewall Management<\/strong>, click Add New Rule to open Port 8888<\/code>. This is to ensure the system can correctly identify the communication port inside the Docker container.<\/p>\n\n\n\n
\"add<\/a><\/figure>\n\n\n\n
Set Up Data Persistence (Volume)<\/h3>\n\n\n\n
Data resets after a container restart, so code files must be stored in the host's physical directory. Use Commands<\/strong> again to create the directory:<\/p>\n\n\n\n
mkdir -p \/home\/master\/jupyter_data\nchmod 777 \/home\/master\/jupyter_data<\/code><\/pre>\n\n\n\n
(Note: To avoid permission issues, loose permissions are granted here temporarily. In practice, configure this based on User ID.)<\/em><\/em><\/p>\n\n\n\n
Execute Docker Run Command<\/h3>\n\n\n\n
Next, create a new Command to start Jupyter. We use the official jupyter\/scipy-notebook<\/code> (which includes more scientific computing packages).<\/p>\n\n\n\n
docker run -d -p 8888:8888 --name my-jupyter -v \/home\/master\/jupyter_data:\/home\/jovyan\/work --restart unless-stopped -e JUPYTER_ENABLE_LAB=yes quay.io\/jupyter\/scipy-notebook<\/code><\/pre>\n\n\n\n
Command Parameter Analysis:<\/strong><\/strong><\/p>\n\n\n\n\n\n
    \n
  1. docker run<\/code>
    The basic command, meaning “Create and start a new Container from an Image<\/strong>“.<\/li>\n\n\n\n
  2. -d<\/code>\n