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Configure Azure WebApp for FastAPI

Configure Azure WebApp for FastAPI

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Ankur
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Table of contents

In this tutorial, we will see how FastAPI can be deployed with Azure Webapps, what are some of the commonly faced issues, and their workarounds. For the example, we will be utilizing a simple fast API, that returns "Hello User" upon calling with the get method. But the conclusion of this blog will be discussing some tips if API is complex, or system requirement is huge.

System Architecture

The user Calls the API i.e. makes a web request to Azure WebApp, this request is received by gunicorn WGSI server, which spawns FastAPI running with help of the Asyncronus Uvicorn Worker class. Each Uvicorn worker class runs a FastAPI application on a randomly selected process id (pid), while the Gunicorn handles request delegation on a process id that can be set to run on a certain port.

GitHub Actions act as a CI/CD tool to handle the automatic deployment. It can fetch changes made into a particular deployed branch, and automatically re-deploy. Learn more about CI/CD tools in this article. In simpler terms, and for this particular tutorial, GitHub action with Azure web app YAML, helps in automated deployments. And what's YAML now?

YAML or yet another markup language (YAML ain't markup Language) is a human-readable data serialization language for all programming languages, basically, it will be used for configuring our web app for deployment (As you dig deeper into deployments, automation, cloud or DevOps, YAML will be your best friend!)

A few requirements before starting:

  • A GitHub repository, with a branch you want to deploy (simply, git checkout -b <>), I will be deploying branch called "demo"

  • Installed Python, with Fast API library

  • What else..., an IDE maybe

Let's get started

Code & Localhost...

Step 1: Configuring venv & Libraries

  • Configure Venv using python3 -m venv venv

  • Activate venv using source <path>/venv/bin/activate

  • Install Necessary Libraries pip install fastapi, uvicorn, gunicorn

Step 2: Basic Code & Test

This file in this example is called main.py


import fastapi
from fastapi.middleware.cors import CORSMiddleware
import uvicorn

app = fastapi.FastAPI(
    title="My API",
    description="This is a very fancy project",
    version="0.1.0",
    openapi_url="/api/v0.1.1/openapi.json",
)

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

@app.get("/")
def read_root():
    return {"Hello": "User"}

# This is to run in localhost, comment out while pushing to deploy on Azure
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port = 8000, log_level='info')

A very simple FastAPI, Please note: Comment out last lines as mentioned below, before pushing changes onto GitHub or proceeding for deployment

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port = 8000, log_level='info')

Verifying Output on Localhost:8000

  • To run main.py script use uvicorn main:app --reload rest parameters are coded into the script...

Push changes on GitHub, please don't push any private info/ keys/ client secrets, use them in os.environor fetch from Azure Key Vault

Step 3: Deployment

  • Save changes, and freeze requirements pip freeze >requirements.txt

  • Commit changes, and push to the desired branch with an innovative commit message like "committing"

  • For this example, I have a demo repository, where I pushed code in the main branch

  • Moving onto deployments...

Configuring Azure

  • Set up a WebApp and WebApp service plan from Azure. From Create a resource > Create WebApp

  • Configure the primary properties of the service plan and Web App, like location, OS (Linux in this case), Stack (Python 3.10 in this case), Subscription, pricing plan etc.

  • The second step is to Add CI/CD details and disable them at this point in time

  • Enable Public Access under networking, click i icon to know more

  • Click Review + Create, and wait for the deployment to get successful. Refer common Problem 1 to know about a common problem at this step with its possible resolution

  • Go to resource > Configuration under Settings Tab> Application settings > Add WEBSITES_PORT : <> port which you want to expose, in this example its 8000 (its generally 8000/ 3000). Read more about Websites_port and why we do it in common problem 2

  • Add any environment variable (Key & Value) at this stage, for multiple values use ["val1","val2",...]

  • Save after adding Application Settings, and click General settings

  • Edit General settings to mention startup script gunicorn -w 4 -k uvicorn.workers.UvicornWorker main:app to use gunicorn with 4 uvicorn workers

  • Alternatively in the root folder of your repository, where main.py is situated make another file named gunicorn.py , with the following content (Benchmarking reference)

      import multiprocessing
  import os

  name = "Gunicorn config for FastAPI"

  accesslog = "/home/user/fastapi/gunicorn-access.log"
  errorlog = "/home/user/fastapi/gunicorn-error.log"

  bind = "0.0.0.0:8000"

  worker_class = "uvicorn.workers.UvicornWorker"
  workers = multiprocessing.cpu_count () * 2 + 1

    -> To use gunicorn.py, put this in the startup script gunicorn --configgunicorn.pymain:app this script calculates the number of workers required.

    -> Reference - https://stackoverflow.com/questions/66251679/deploy-fastapi-and-uvicorn-on-azure-app-service

  • Or simply use uvicorn main:app --workers 4 or equivalent like in localhost

  • Add Source as GitHub and Builder is GitHub Actions for this example

  • Add details of Organization, Repository & Branch

  • As soon as save is pressed, deployment starts & a yml file is generated in .github/workflows sub-repository, we will have a bit of a look on this file later.

  • Wait for deployment to complete, and your app will be online and reachable.

  • Enable CORS access by ticking the box, or by adding custom-allowed origins. Read more about CORS here

  • Voila, if everything is fine and good, App should be up.

  • Check logs to understand the working of Gunicorn and your application, this tool when configured well also helps to

  • YAML file.

      # Docs for the Azure Web Apps Deploy action: https://github.com/Azure/webapps-deploy
  # More GitHub Actions for Azure: https://github.com/Azure/actions
  # More info on Python, GitHub Actions, and Azure App Service: https://aka.ms/python-webapps-actions

  name: Build and deploy Python app to Azure Web App - fastapi-testing

  on:
    push:
      branches:
        - main
    workflow_dispatch:

  jobs:
    build:
      runs-on: ubuntu-latest

      steps:
        - uses: actions/checkout@v2

        - name: Set up Python version
          uses: actions/setup-python@v1
          with:
            python-version: '3.10'

        - name: Create and start virtual environment
          run: |
            python -m venv venv
            source venv/bin/activate

        - name: Install dependencies
          run: pip install -r requirements.txt

        # Optional: Add step to run tests here (PyTest, Django test suites, etc.)

        - name: Upload artifact for deployment jobs
          uses: actions/upload-artifact@v2
          with:
            name: python-app
            path: |
              . 
              !venv/
    deploy:
      runs-on: ubuntu-latest
      needs: build
      environment:
        name: 'Production'
        url: ${{ steps.deploy-to-webapp.outputs.webapp-url }}

      steps:
        - name: Download artifact from build job
          uses: actions/download-artifact@v2
          with:
            name: python-app
            path: .

        - name: 'Deploy to Azure Web App'
          uses: azure/webapps-deploy@v2
          id: deploy-to-webapp
          with:
            app-name: 'fastapi-testing'
            slot-name: 'Production'
            publish-profile: ${{ secrets.AZUREAPPSERVICE_PUBLISHPROFILE_4FBD8EBBEC0840999671265D0DCB23AE }}
    • As observable in the YAML file, we can check parameters like requirements.txt, venv params, app name, target branch, deployment triggering action etc.

Common Errors & Issues

  • Deployment issue with Azure in final step - Error

    azure web app deployment failed message": "Cannot find User with name ...

    or

    "ErrorEntity": { "Code": "NotFound", "Message": "Cannot find user.", "ExtendedCode": "09004", "MessageTemplate": "Cannot find user.", "Parameters": [], "InnerErrors": null

Resolution - Try the following

-> Create a New App service plan

-> Wait for some time before redeploying

-> Related Stackoverflow conversation

  • Port Related Issue post-deployment during startup (Observable in stream logs)

    Azure Web App on Linux: "Error: Container didn't respond to HTTP pings on port: 8080

Resolution - Try the following (StackOverflow)

-> Expose Port in Dockerfile, if you are using Dockerfile

-> Create a key WEBSITES_PORT in the application setting, along with needed value like 8000 or 3000

-> A final workaround is to remove venv from yml file ( Entire field where venv is created and activated)

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