How to use Nginx with FastAPI for reverse proxy and load balancing

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Release: 2023-08-01 09:44:00
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How to use Nginx in FastAPI for reverse proxy and load balancing

Introduction:
FastAPI and Nginx are two very popular web development tools. FastAPI is a high-performance Python framework, and Nginx is a powerful reverse proxy server. Using these two tools together can improve the performance and reliability of your web applications. In this article, we will learn how to use Nginx with FastAPI for reverse proxy and load balancing.

  1. What are reverse proxy and load balancing?
    A reverse proxy is a network service used to forward client requests to internal network resources. Unlike the forward proxy, the reverse proxy server hides the details of the back-end server and the client cannot directly access the back-end server. The reverse proxy server forwards client requests to the backend server according to certain rules, thereby providing security and load balancing.

Load balancing is a technology that distributes requests to multiple servers to improve system performance and reliability. When one server cannot handle all requests, load balancing distributes the requests to other available servers, thereby balancing the load between servers.

  1. Configuring Nginx reverse proxy and load balancing
    First, we need to install and configure the Nginx server. On Ubuntu, you can use the following command to install:
sudo apt update sudo apt install nginx
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After the installation is complete, we need to modify the Nginx configuration file. Open the Nginx configuration file using the following command:

sudo nano /etc/nginx/sites-available/default
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In the configuration file, we need to add the following configuration:

upstream backend { server 127.0.0.1:8000; server 127.0.0.1:8001; } server { listen 80; location / { proxy_pass http://backend; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; } }
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In the above configuration, we define an upstream named "backend" Server cluster. There are two servers in the cluster, listening on ports 8000 and 8001 respectively. We then defined a server block that listens on port 80 and forwards requests to servers in the "backend" cluster. Finally, we set some headers for the proxy request.

After saving and exiting the configuration file, restart the Nginx server:

sudo systemctl restart nginx
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  1. Create a backend application using FastAPI
    Next, we will use FastAPI to create a simple backend application end application. First, make sure FastAPI and uvicorn are installed. You can install it using the following command:
pip install fastapi uvicorn
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Then, create a file named "main.py" and add the following code:

from fastapi import FastAPI app = FastAPI() @app.get("/") def read_root(): return {"Hello": "World"}
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After saving the file, use the following command Start the FastAPI application:

uvicorn main:app --reload
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Now, our FastAPI application is listening on the local port 8000.

  1. Test reverse proxy and load balancing
    By accessing "http://localhost", we can see that Nginx forwards the request to the FastAPI application and returns the response of "Hello World" .

To test load balancing, we can copy the "main.py" file and start the FastAPI application on a different port. For example, copy "main.py" as "main2.py" and start the application on port 8001.

Then, use the following command to start the second FastAPI application:

uvicorn main2:app --port 8001 --reload
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At this point, Nginx has set up load balancing, and requests will be balanced to the two FastAPI applications.

Conclusion:
By combining FastAPI and Nginx, we can implement reverse proxy and load balancing functions, thereby improving the performance and reliability of web applications. Using Nginx's reverse proxy feature, we can hide the details of the backend server and provide security. Through the load balancing function, we can balance the load across multiple servers to improve system performance and reliability. I hope this article can help you learn how to use Nginx for reverse proxy and load balancing in FastAPI.

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