How to Deploy Flask Applications to DigitalOcean
DigitalOcean is a popular choice for hosting Flask apps because it’s simple, affordable, and flexible. You can deploy using:
Droplets (virtual servers)
App Platform (managed PaaS — easiest)
Docker containers
Kubernetes
Below you'll find instructions for the two most common methods:
1️⃣ Droplet Deployment (Manual Server Setup)
2️⃣ App Platform Deployment (Fully Managed)
🌐 Option 1: Deploy Flask on a DigitalOcean Droplet (Manual, More Control)
This method gives you full control of the server and environment.
🧱 Step 1: Create a Droplet
Go to DigitalOcean Dashboard → Droplets
Choose Ubuntu 22.04 LTS (recommended)
Select plan (Basic / Shared CPU is fine)
Add SSH key or create a root password
Create Droplet
SSH into the Droplet:
ssh root@YOUR_DROPLET_IP
🛠️ Step 2: Install System Requirements
Update system:
apt update && apt upgrade -y
Install Python + tools:
apt install python3 python3-pip python3-venv -y
Install Git if needed:
apt install git -y
📁 Step 3: Clone Your Flask App
Example:
git clone https://github.com/your-username/your-flask-app.git
cd your-flask-app
Create a virtual environment:
python3 -m venv venv
source venv/bin/activate
Install dependencies:
pip install -r requirements.txt
🔥 Step 4: Use Gunicorn to Run Flask in Production
Install Gunicorn:
pip install gunicorn
Run test server:
gunicorn --bind 0.0.0.0:5000 app:app
💡 Replace app:app with your Python file and Flask variable name.
Stop with CTRL+C.
🧱 Step 5: Create a Gunicorn Systemd Service
Create file:
nano /etc/systemd/system/flaskapp.service
Paste:
[Unit]
Description=Gunicorn instance for Flask
After=network.target
[Service]
User=root
WorkingDirectory=/root/your-flask-app
Environment="PATH=/root/your-flask-app/venv/bin"
ExecStart=/root/your-flask-app/venv/bin/gunicorn --workers 3 --bind unix:flaskapp.sock -m 007 app:app
[Install]
WantedBy=multi-user.target
Save and exit.
Start service:
systemctl start flaskapp
systemctl enable flaskapp
🌐 Step 6: Install and Configure Nginx
Install Nginx:
apt install nginx -y
Create a site config:
nano /etc/nginx/sites-available/flaskapp
Paste:
server {
listen 80;
server_name YOUR_DOMAIN_OR_IP;
location / {
include proxy_params;
proxy_pass http://unix:/root/your-flask-app/flaskapp.sock;
}
}
Enable config:
ln -s /etc/nginx/sites-available/flaskapp /etc/nginx/sites-enabled
nginx -t
systemctl restart nginx
Your Flask app is now live!
🔐 Step 7: (Optional) Enable HTTPS with Let’s Encrypt
Install certbot:
apt install certbot python3-certbot-nginx -y
Run:
certbot --nginx -d yourdomain.com -d www.yourdomain.com
Now your site is fully secured.
🎉 Your Flask app is now deployed with Nginx + Gunicorn on DigitalOcean!
☁️ Option 2: Deploy Flask Using DigitalOcean App Platform (Easiest)
This is a fully managed platform like Heroku.
🧱 Step 1: Push Code to GitHub
Your Flask app should include:
requirements.txt
Procfile (or Dockerfile)
A sample Procfile:
web: gunicorn app:app
🚀 Step 2: Create an App in App Platform
Go to DigitalOcean → Apps
Click Create App
Connect your GitHub repo
Select region, instance size
App Platform detects Python automatically
Set build & run commands if needed:
Build: pip install -r requirements.txt
Run: gunicorn app:app
🌐 Step 3: Configure Environment Variables
In the App Platform UI:
Add secrets (API keys, DB URLs)
Add environment variables
🔐 Step 4: HTTPS Enabled Automatically
App Platform gives:
Free HTTPS
Autoscaling
Log viewing
Automatic deployments
🎉 Your Flask App Is Live on App Platform!
This is the simplest and most beginner-friendly method.
🧩 Which Deployment Method Should You Choose?
Method Pros Cons
Droplet Full control, customizable, cheaper Requires server management
App Platform Easiest, auto HTTPS, auto deploy Slightly more expensive
Docker Portable, consistent Requires Docker knowledge
Kubernetes Scalable Overkill for small apps
🏁 Conclusion
Deploying a Flask application to DigitalOcean is flexible and straightforward.
You can choose a fully managed option (App Platform) or manually configure a production-grade environment with Nginx and Gunicorn on a Droplet.
Both approaches work well — it just depends on how much control you want.
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